Prabhu, Roshan S; Press, Robert H; Boselli, Danielle M; Miller, Katherine R; Lankford, Scott P; McCammon, Robert J; Moeller, Benjamin J; Heinzerling, John H; Fasola, Carolina E; Patel, Kirtesh R; Asher, Anthony L; Sumrall, Ashley L; Curran, Walter J; Shu, Hui-Kuo G; Burri, Stuart H
2018-03-01
Patients treated with stereotactic radiosurgery (SRS) for brain metastases (BM) are at increased risk of distant brain failure (DBF). Two nomograms have been recently published to predict individualized risk of DBF after SRS. The goal of this study was to assess the external validity of these nomograms in an independent patient cohort. The records of consecutive patients with BM treated with SRS at Levine Cancer Institute and Emory University between 2005 and 2013 were reviewed. Three validation cohorts were generated based on the specific nomogram or recursive partitioning analysis (RPA) entry criteria: Wake Forest nomogram (n = 281), Canadian nomogram (n = 282), and Canadian RPA (n = 303) validation cohorts. Freedom from DBF at 1-year in the Wake Forest study was 30% compared with 50% in the validation cohort. The validation c-index for both the 6-month and 9-month freedom from DBF Wake Forest nomograms was 0.55, indicating poor discrimination ability, and the goodness-of-fit test for both nomograms was highly significant (p < 0.001), indicating poor calibration. The 1-year actuarial DBF in the Canadian nomogram study was 43.9% compared with 50.9% in the validation cohort. The validation c-index for the Canadian 1-year DBF nomogram was 0.56, and the goodness-of-fit test was also highly significant (p < 0.001). The validation accuracy and c-index of the Canadian RPA classification was 53% and 0.61, respectively. The Wake Forest and Canadian nomograms for predicting risk of DBF after SRS were found to have limited predictive ability in an independent bi-institutional validation cohort. These results reinforce the importance of validating predictive models in independent patient cohorts.
Brodowska, Katarzyna; Stryjewski, Tomasz P; Papavasileiou, Evangelia; Chee, Yewlin E; Eliott, Dean
2017-05-01
The Retinal Detachment after Open Globe Injury (RD-OGI) Score is a clinical prediction model that was developed at the Massachusetts Eye and Ear Infirmary to predict the risk of retinal detachment (RD) after open globe injury (OGI). This study sought to validate the RD-OGI Score in an independent cohort of patients. Retrospective cohort study. The predictive value of the RD-OGI Score was evaluated by comparing the original RD-OGI Scores of 893 eyes with OGI that presented between 1999 and 2011 (the derivation cohort) with 184 eyes with OGI that presented from January 1, 2012, to January 31, 2014 (the validation cohort). Three risk classes (low, moderate, and high) were created and logistic regression was undertaken to evaluate the optimal predictive value of the RD-OGI Score. A Kaplan-Meier survival analysis evaluated survival experience between the risk classes. Time to RD. At 1 year after OGI, 255 eyes (29%) in the derivation cohort and 66 eyes (36%) in the validation cohort were diagnosed with an RD. At 1 year, the low risk class (RD-OGI Scores 0-2) had a 3% detachment rate in the derivation cohort and a 0% detachment rate in the validation cohort, the moderate risk class (RD-OGI Scores 2.5-4.5) had a 29% detachment rate in the derivation cohort and a 35% detachment rate in the validation cohort, and the high risk class (RD-OGI scores 5-7.5) had a 73% detachment rate in the derivation cohort and an 86% detachment rate in the validation cohort. Regression modeling revealed the RD-OGI to be highly discriminative, especially 30 days after injury, with an area under the receiver operating characteristic curve of 0.939 in the validation cohort. Survival experience was significantly different depending upon the risk class (P < 0.0001, log-rank chi-square). The RD-OGI Score can reliably predict the future risk of developing an RD based on clinical variables that are present at the time of the initial evaluation after OGI. Copyright © 2017 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.
Clinical inquiries. What test is the best for diagnosing infectious mononucleosis?
Bell, Amy Trelease; Fortune, Barbara; Sheeler, Robert
2006-09-01
Tests for antibodies to Epstein-Barr viral capsid antigen or Epstein-Barr nuclear antigen are the most sensitive, are highly specific, and are also the most expensive for diagnosing infectious mononucleosis (strength of recommendation [SOR]: C, based on validating cohort study). Heterophile antibody tests have similar specificity and are cheaper, but are less sensitive in children or in adults during the early days of the illness (SOR: C, based on validating cohort study). The polymerase chain reaction assay for Epstein-Barr virus DNA is more sensitive than the heterophile antibody test in children, is highly specific, but is also expensive (SOR: C, based on validating cohort study). The percentages of atypical lymphocytes and total lymphocytes on a complete blood count provide another specific and moderately sensitive, yet inexpensive, test (SOR: C, based on validating cohort study).
Early Prediction of Intensive Care Unit-Acquired Weakness: A Multicenter External Validation Study.
Witteveen, Esther; Wieske, Luuk; Sommers, Juultje; Spijkstra, Jan-Jaap; de Waard, Monique C; Endeman, Henrik; Rijkenberg, Saskia; de Ruijter, Wouter; Sleeswijk, Mengalvio; Verhamme, Camiel; Schultz, Marcus J; van Schaik, Ivo N; Horn, Janneke
2018-01-01
An early diagnosis of intensive care unit-acquired weakness (ICU-AW) is often not possible due to impaired consciousness. To avoid a diagnostic delay, we previously developed a prediction model, based on single-center data from 212 patients (development cohort), to predict ICU-AW at 2 days after ICU admission. The objective of this study was to investigate the external validity of the original prediction model in a new, multicenter cohort and, if necessary, to update the model. Newly admitted ICU patients who were mechanically ventilated at 48 hours after ICU admission were included. Predictors were prospectively recorded, and the outcome ICU-AW was defined by an average Medical Research Council score <4. In the validation cohort, consisting of 349 patients, we analyzed performance of the original prediction model by assessment of calibration and discrimination. Additionally, we updated the model in this validation cohort. Finally, we evaluated a new prediction model based on all patients of the development and validation cohort. Of 349 analyzed patients in the validation cohort, 190 (54%) developed ICU-AW. Both model calibration and discrimination of the original model were poor in the validation cohort. The area under the receiver operating characteristics curve (AUC-ROC) was 0.60 (95% confidence interval [CI]: 0.54-0.66). Model updating methods improved calibration but not discrimination. The new prediction model, based on all patients of the development and validation cohort (total of 536 patients) had a fair discrimination, AUC-ROC: 0.70 (95% CI: 0.66-0.75). The previously developed prediction model for ICU-AW showed poor performance in a new independent multicenter validation cohort. Model updating methods improved calibration but not discrimination. The newly derived prediction model showed fair discrimination. This indicates that early prediction of ICU-AW is still challenging and needs further attention.
Güiza, Fabian; Depreitere, Bart; Piper, Ian; Citerio, Giuseppe; Jorens, Philippe G; Maas, Andrew; Schuhmann, Martin U; Lo, Tsz-Yan Milly; Donald, Rob; Jones, Patricia; Maier, Gottlieb; Van den Berghe, Greet; Meyfroidt, Geert
2017-03-01
A model for early detection of episodes of increased intracranial pressure in traumatic brain injury patients has been previously developed and validated based on retrospective adult patient data from the multicenter Brain-IT database. The purpose of the present study is to validate this early detection model in different cohorts of recently treated adult and pediatric traumatic brain injury patients. Prognostic modeling. Noninterventional, observational, retrospective study. The adult validation cohort comprised recent traumatic brain injury patients from San Gerardo Hospital in Monza (n = 50), Leuven University Hospital (n = 26), Antwerp University Hospital (n = 19), Tübingen University Hospital (n = 18), and Southern General Hospital in Glasgow (n = 8). The pediatric validation cohort comprised patients from neurosurgical and intensive care centers in Edinburgh and Newcastle (n = 79). None. The model's performance was evaluated with respect to discrimination, calibration, overall performance, and clinical usefulness. In the recent adult validation cohort, the model retained excellent performance as in the original study. In the pediatric validation cohort, the model retained good discrimination and a positive net benefit, albeit with a performance drop in the remaining criteria. The obtained external validation results confirm the robustness of the model to predict future increased intracranial pressure events 30 minutes in advance, in adult and pediatric traumatic brain injury patients. These results are a large step toward an early warning system for increased intracranial pressure that can be generally applied. Furthermore, the sparseness of this model that uses only two routinely monitored signals as inputs (intracranial pressure and mean arterial blood pressure) is an additional asset.
ERIC Educational Resources Information Center
Lung, For-Wey; Chiang, Tung-Liang; Lin, Shio-Jean; Feng, Jui-Ying; Chen, Po-Fei; Shu, Bih-Ching
2011-01-01
The parental report instrument is the most efficient developmental detection method and has shown high validity with professional assessment instruments. The reliability and validity of the Taiwan Birth Cohort Study (TBCS) 6-, 18- and 36-month scales have already been established. In this study, the reliability and validity of the 60-month scale…
Prediction of Waitlist Mortality in Adult Heart Transplant Candidates: The Candidate Risk Score.
Jasseron, Carine; Legeai, Camille; Jacquelinet, Christian; Leprince, Pascal; Cantrelle, Christelle; Audry, Benoît; Porcher, Raphael; Bastien, Olivier; Dorent, Richard
2017-09-01
The cardiac allocation system in France is currently based on urgency and geography. Medical urgency is defined by therapies without considering objective patient mortality risk factors. This study aimed to develop a waitlist mortality risk score from commonly available candidate variables. The study included all patients, aged 16 years or older, registered on the national registry CRISTAL for first single-organ heart transplantation between January 2010 and December 2014. This population was randomly divided in a 2:1 ratio into derivation and validation cohorts. The association of variables at listing with 1-year waitlist death or delisting for worsening medical condition was assessed within the derivation cohort. The predictors were used to generate a candidate risk score (CRS). Validation of the CRS was performed in the validation cohort. Concordance probability estimation (CPE) was used to evaluate the discriminative capacity of the models. During the study period, 2333 patients were newly listed. The derivation (n =1 555) and the validation cohorts (n = 778) were similar. Short-term mechanical circulatory support, natriuretic peptide decile, glomerular filtration rate, and total bilirubin level were included in a simplified model and incorporated into the score. The Concordance probability estimation of the CRS was 0.73 in the derivation cohort and 0.71 in the validation cohort. The correlation between observed and expected 1-year waitlist mortality in the validation cohort was 0.87. The candidate risk score provides an accurate objective prediction of waitlist mortality. It is currently being used to develop a modified cardiac allocation system in France.
Rubio-Álvarez, Ana; Molina-Alarcón, Milagros; Arias-Arias, Ángel; Hernández-Martínez, Antonio
2018-03-01
postpartum haemorrhage is one of the leading causes of maternal morbidity and mortality worldwide. Despite the use of uterotonics agents as preventive measure, it remains a challenge to identify those women who are at increased risk of postpartum bleeding. to develop and to validate a predictive model to assess the risk of excessive bleeding in women with vaginal birth. retrospective cohorts study. "Mancha-Centro Hospital" (Spain). the elaboration of the predictive model was based on a derivation cohort consisting of 2336 women between 2009 and 2011. For validation purposes, a prospective cohort of 953 women between 2013 and 2014 were employed. Women with antenatal fetal demise, multiple pregnancies and gestations under 35 weeks were excluded METHODS: we used a multivariate analysis with binary logistic regression, Ridge Regression and areas under the Receiver Operating Characteristic curves to determine the predictive ability of the proposed model. there was 197 (8.43%) women with excessive bleeding in the derivation cohort and 63 (6.61%) women in the validation cohort. Predictive factors in the final model were: maternal age, primiparity, duration of the first and second stages of labour, neonatal birth weight and antepartum haemoglobin levels. Accordingly, the predictive ability of this model in the derivation cohort was 0.90 (95% CI: 0.85-0.93), while it remained 0.83 (95% CI: 0.74-0.92) in the validation cohort. this predictive model is proved to have an excellent predictive ability in the derivation cohort, and its validation in a latter population equally shows a good ability for prediction. This model can be employed to identify women with a higher risk of postpartum haemorrhage. Copyright © 2017 Elsevier Ltd. All rights reserved.
van Soest, Johan; Meldolesi, Elisa; van Stiphout, Ruud; Gatta, Roberto; Damiani, Andrea; Valentini, Vincenzo; Lambin, Philippe; Dekker, Andre
2017-09-01
Multiple models have been developed to predict pathologic complete response (pCR) in locally advanced rectal cancer patients. Unfortunately, validation of these models normally omit the implications of cohort differences on prediction model performance. In this work, we will perform a prospective validation of three pCR models, including information whether this validation will target transferability or reproducibility (cohort differences) of the given models. We applied a novel methodology, the cohort differences model, to predict whether a patient belongs to the training or to the validation cohort. If the cohort differences model performs well, it would suggest a large difference in cohort characteristics meaning we would validate the transferability of the model rather than reproducibility. We tested our method in a prospective validation of three existing models for pCR prediction in 154 patients. Our results showed a large difference between training and validation cohort for one of the three tested models [Area under the Receiver Operating Curve (AUC) cohort differences model: 0.85], signaling the validation leans towards transferability. Two out of three models had a lower AUC for validation (0.66 and 0.58), one model showed a higher AUC in the validation cohort (0.70). We have successfully applied a new methodology in the validation of three prediction models, which allows us to indicate if a validation targeted transferability (large differences between training/validation cohort) or reproducibility (small cohort differences). © 2017 American Association of Physicists in Medicine.
Ahmed, Adil; Vairavan, Srinivasan; Akhoundi, Abbasali; Wilson, Gregory; Chiofolo, Caitlyn; Chbat, Nicolas; Cartin-Ceba, Rodrigo; Li, Guangxi; Kashani, Kianoush
2015-10-01
Timely detection of acute kidney injury (AKI) facilitates prevention of its progress and potentially therapeutic interventions. The study objective is to develop and validate an electronic surveillance tool (AKI sniffer) to detect AKI in 2 independent retrospective cohorts of intensive care unit (ICU) patients. The primary aim is to compare the sensitivity, specificity, and positive and negative predictive values of AKI sniffer performance against a reference standard. This study is conducted in the ICUs of a tertiary care center. The derivation cohort study subjects were Olmsted County, MN, residents admitted to all Mayo Clinic ICUs from July 1, 2010, through December 31, 2010, and the validation cohort study subjects were all patients admitted to a Mayo Clinic, Rochester, campus medical/surgical ICU on January 12, 2010, through March 23, 2010. All included records were reviewed by 2 independent investigators who adjudicated AKI using the Acute Kidney Injury Network criteria; disagreements were resolved by a third reviewer. This constituted the reference standard. An electronic algorithm was developed; its precision and reliability were assessed in comparison with the reference standard in 2 separate cohorts, derivation and validation. Of 1466 screened patients, a total of 944 patients were included in the study: 482 for derivation and 462 for validation. Compared with the reference standard in the validation cohort, the sensitivity and specificity of the AKI sniffer were 88% and 96%, respectively. The Cohen κ (95% confidence interval) agreement between the electronic and the reference standard was 0.84 (0.78-0.89) and 0.85 (0.80-0.90) in the derivation and validation cohorts. Acute kidney injury can reliably and accurately be detected electronically in ICU patients. The presented method is applicable for both clinical (decision support) and research (enrollment for clinical trials) settings. Prospective validation is required. Copyright © 2015 Elsevier Inc. All rights reserved.
George, Steven Z; Beneciuk, Jason M; Lentz, Trevor A; Wu, Samuel S
2017-01-01
Purpose There is an increased need for determining which patients with musculoskeletal pain benefit from additional diagnostic testing or psychologically informed intervention. The Optimal Screening for Prediction of Referral and Outcome (OSPRO) cohort studies were designed to develop and validate standard assessment tools for review of systems and yellow flags. This cohort profile paper provides a description of and future plans for the validation cohort. Participants Patients (n=440) with primary complaint of spine, shoulder or knee pain were recruited into the OSPRO validation cohort via a national Orthopaedic Physical Therapy-Investigative Network. Patients were followed up at 4 weeks, 6 months and 12 months for pain, functional status and quality of life outcomes. Healthcare utilisation outcomes were also collected at 6 and 12 months. Findings to date There are no longitudinal findings reported to date from the ongoing OSPRO validation cohort. The previously completed cross-sectional OSPRO development cohort yielded two assessment tools that were investigated in the validation cohort. Future plans Follow-up data collection was completed in January 2017. Primary analyses will investigate how accurately the OSPRO review of systems and yellow flag tools predict 12-month pain, functional status, quality of life and healthcare utilisation outcomes. Planned secondary analyses include prediction of pain interference and/or development of chronic pain, investigation of treatment expectation on patient outcomes and analysis of patient satisfaction following an episode of physical therapy. Trial registration number The OSPRO validation cohort was not registered. PMID:28600371
Hippisley-Cox, Julia; Coupland, Carol; Brindle, Peter
2014-01-01
Objectives To validate the performance of a set of risk prediction algorithms developed using the QResearch database, in an independent sample from general practices contributing to the Clinical Research Data Link (CPRD). Setting Prospective open cohort study using practices contributing to the CPRD database and practices contributing to the QResearch database. Participants The CPRD validation cohort consisted of 3.3 million patients, aged 25–99 years registered at 357 general practices between 1 Jan 1998 and 31 July 2012. The validation statistics for QResearch were obtained from the original published papers which used a one-third sample of practices separate to those used to derive the score. A cohort from QResearch was used to compare incidence rates and baseline characteristics and consisted of 6.8 million patients from 753 practices registered between 1 Jan 1998 and until 31 July 2013. Outcome measures Incident events relating to seven different risk prediction scores: QRISK2 (cardiovascular disease); QStroke (ischaemic stroke); QDiabetes (type 2 diabetes); QFracture (osteoporotic fracture and hip fracture); QKidney (moderate and severe kidney failure); QThrombosis (venous thromboembolism); QBleed (intracranial bleed and upper gastrointestinal haemorrhage). Measures of discrimination and calibration were calculated. Results Overall, the baseline characteristics of the CPRD and QResearch cohorts were similar though QResearch had higher recording levels for ethnicity and family history. The validation statistics for each of the risk prediction scores were very similar in the CPRD cohort compared with the published results from QResearch validation cohorts. For example, in women, the QDiabetes algorithm explained 50% of the variation within CPRD compared with 51% on QResearch and the receiver operator curve value was 0.85 on both databases. The scores were well calibrated in CPRD. Conclusions Each of the algorithms performed practically as well in the external independent CPRD validation cohorts as they had in the original published QResearch validation cohorts. PMID:25168040
Kelsen, Judith; Bittinger, Kyle; Pauly-Hubbard, Helen; Posivak, Leah; Grunberg, Stephanie; Baldassano, Robert; Lewis, James D; Wu, Gary D; Bushman, Frederic D
2016-01-01
Background Oral manifestations are common in Crohn's disease (CD). Here we characterized the subgingival microbiota in pediatric CD patients initiating therapy and after 8 weeks to identify microbial community features associated with CD and therapy. Methods Pediatric CD patients were recruited from The Children's Hospital of Pennsylvania. Healthy control subjects were recruited from primary care or orthopedics clinic. Subgingival plaque samples were collected at initiation of therapy and after 8 weeks. Treatment exposures included 5-ASAs, immunomodualtors, steroids, and infliximab. The microbiota was characterized by 16S rRNA gene sequencing. The study was repeated in separate discovery (35 CD, 43 healthy) and validation cohorts (43 CD, 31 healthy). Results A majority of subjects in both cohorts demonstrated clinical response after 8 weeks of therapy (discovery cohort 88%, validation cohort 79%). At week 0, both antibiotic exposure and disease state were associated with differences in bacterial community composition. Seventeen genera were identified in the discovery cohort as candidate biomarkers, of which 11 were confirmed in the validation cohort. Capnocytophaga, Rothia, and TM7 were more abundant in CD relative to healthy controls. Other bacteria were reduced in abundance with antibiotic exposure among CD subjects. CD-associated genera were not enriched compared to healthy controls after 8 weeks of therapy. Conclusions Subgingival microbial community structure differed with CD and antibiotic use. Results in the discovery cohort were replicated in a separate validation cohort. Several potentially pathogenic bacterial lineages were associated with CD but were not diminished in abundance by antibiotic treatment, suggesting targets for additional surveillance. PMID:26288001
Kelsen, Judith; Bittinger, Kyle; Pauly-Hubbard, Helen; Posivak, Leah; Grunberg, Stephanie; Baldassano, Robert; Lewis, James D; Wu, Gary D; Bushman, Frederic D
2015-12-01
Oral manifestations are common in Crohn's disease (CD). Here we characterized the subgingival microbiota in pediatric patients with CD initiating therapy and after 8 weeks to identify microbial community features associated with CD and therapy. Pediatric patients with CD were recruited from The Children's Hospital of Pennsylvania. Healthy control subjects were recruited from primary care or orthopedics clinic. Subgingival plaque samples were collected at initiation of therapy and after 8 weeks. Treatment exposures included 5-ASAs, immunomodulators, steroids, and infliximab. The microbiota was characterized by 16S rRNA gene sequencing. The study was repeated in separate discovery (35 CD, 43 healthy) and validation cohorts (43 CD, 31 healthy). Most subjects in both cohorts demonstrated clinical response after 8 weeks of therapy (discovery cohort 88%, validation cohort 79%). At week 0, both antibiotic exposure and disease state were associated with differences in bacterial community composition. Seventeen genera were identified in the discovery cohort as candidate biomarkers, of which 11 were confirmed in the validation cohort. Capnocytophaga, Rothia, and TM7 were more abundant in CD relative to healthy controls. Other bacteria were reduced in abundance with antibiotic exposure among CD subjects. CD-associated genera were not enriched compared with healthy controls after 8 weeks of therapy. Subgingival microbial community structure differed with CD and antibiotic use. Results in the discovery cohort were replicated in a separate validation cohort. Several potentially pathogenic bacterial lineages were associated with CD but were not diminished in abundance by antibiotic treatment, suggesting targets for additional surveillance.
Hang, Junjie; Wu, Lixia; Zhu, Lina; Sun, Zhiqiang; Wang, Ge; Pan, Jingjing; Zheng, Suhua; Xu, Kequn; Du, Jiadi; Jiang, Hua
2018-06-01
It is necessary to develop prognostic tools of metastatic pancreatic cancer (MPC) for optimizing therapeutic strategies. Thus, we tried to develop and validate a prognostic nomogram of MPC. Data from 3 clinical trials (NCT00844649, NCT01124786, and NCT00574275) and 133 Chinese MPC patients were used for analysis. The former 2 trials were taken as the training cohort while NCT00574275 was used as the validation cohort. In addition, 133 MPC patients treated in China were taken as the testing cohort. Cox regression model was used to investigate prognostic factors in the training cohort. With these factors, we established a nomogram and verified it by Harrell's concordance index (C-index) and calibration plots. Furthermore, the nomogram was externally validated in the validation cohort and testing cohort. In the training cohort (n = 445), performance status, liver metastasis, Carbohydrate antigen 19-9 (CA19-9) log-value, absolute neutrophil count (ANC), and albumin were independent prognostic factors for overall survival (OS). A nomogram was established with these factors to predict OS and survival probabilities. The nomogram showed an acceptable discrimination ability (C-index: .683) and good calibration, and was further externally validated in the validation cohort (n = 273, C-index: .699) and testing cohort (n = 133, C-index: .653).The nomogram total points (NTP) had the potential to stratify patients into 3-risk groups with median OS of 11.7, 7.0 and 3.7 months (P < .001), respectively. In conclusion, the prognostic nomogram with NTP can predict OS for patients with MPC with considerable accuracy. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.
Veldhuijzen van Zanten, Sophie E M; Lane, Adam; Heymans, Martijn W; Baugh, Joshua; Chaney, Brooklyn; Hoffman, Lindsey M; Doughman, Renee; Jansen, Marc H A; Sanchez, Esther; Vandertop, William P; Kaspers, Gertjan J L; van Vuurden, Dannis G; Fouladi, Maryam; Jones, Blaise V; Leach, James
2017-08-01
We aimed to perform external validation of the recently developed survival prediction model for diffuse intrinsic pontine glioma (DIPG), and discuss its utility. The DIPG survival prediction model was developed in a cohort of patients from the Netherlands, United Kingdom and Germany, registered in the SIOPE DIPG Registry, and includes age <3 years, longer symptom duration and receipt of chemotherapy as favorable predictors, and presence of ring-enhancement on MRI as unfavorable predictor. Model performance was evaluated by analyzing the discrimination and calibration abilities. External validation was performed using an unselected cohort from the International DIPG Registry, including patients from United States, Canada, Australia and New Zealand. Basic comparison with the results of the original study was performed using descriptive statistics, and univariate- and multivariable regression analyses in the validation cohort. External validation was assessed following a variety of analyses described previously. Baseline patient characteristics and results from the regression analyses were largely comparable. Kaplan-Meier curves of the validation cohort reproduced separated groups of standard (n = 39), intermediate (n = 125), and high-risk (n = 78) patients. This discriminative ability was confirmed by similar values for the hazard ratios across these risk groups. The calibration curve in the validation cohort showed a symmetric underestimation of the predicted survival probabilities. In this external validation study, we demonstrate that the DIPG survival prediction model has acceptable cross-cohort calibration and is able to discriminate patients with short, average, and increased survival. We discuss how this clinico-radiological model may serve a useful role in current clinical practice.
Mahan, Charles E; Liu, Yang; Turpie, A Graham; Vu, Jennifer T; Heddle, Nancy; Cook, Richard J; Dairkee, Undaleeb; Spyropoulos, Alex C
2014-10-01
Venous thromboembolic (VTE) risk assessment remains an important issue in hospitalised, acutely-ill medical patients, and several VTE risk assessment models (RAM) have been proposed. The purpose of this large retrospective cohort study was to externally validate the IMPROVE RAM using a large database of three acute care hospitals. We studied 41,486 hospitalisations (28,744 unique patients) with 1,240 VTE hospitalisations (1,135 unique patients) in the VTE cohort and 40,246 VTE-free hospitalisations (27,609 unique patients) in the control cohort. After chart review, 139 unique VTE patients were identified and 278 randomly-selected matched patients in the control cohort. Seven independent VTE risk factors as part of the RAM in the derivation cohort were identified. In the validation cohort, the incidence of VTE was 0.20%; 95% confidence interval (CI) 0.18-0.22, 1.04%; 95%CI 0.88-1.25, and 4.15%; 95%CI 2.79-8.12 in the low, moderate, and high VTE risk groups, respectively, which compared to rates of 0.45%, 1.3%, and 4.74% in the three risk categories of the derivation cohort. For the derivation and validation cohorts, the total percentage of patients in low, moderate and high VTE risk occurred in 68.6% vs 63.3%, 24.8% vs 31.1%, and 6.5% vs 5.5%, respectively. Overall, the area under the receiver-operator characteristics curve for the validation cohort was 0.7731. In conclusion, the IMPROVE RAM can accurately identify medical patients at low, moderate, and high VTE risk. This will tailor future thromboprophylactic strategies in this population as well as identify particularly high VTE risk patients in whom multimodal or more intensive prophylaxis may be beneficial.
Wang, Dong-Yu; Done, Susan J; Mc Cready, David R; Leong, Wey L
2014-07-04
Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts. An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147). The original training cohort reached a statistically significant difference (p < 0.05) in disease-free survivals between the three CMTC groups after an additional two years of follow-up (median = 55 months). The prognostic value of the triad classification was reproduced in the second independent internal cohort and the new external validation cohort. CMTC achieved even higher prognostic significance when all available patients were analyzed (n = 4,851). Oncogenic pathways Myc, E2F1, Ras and β-catenin were again implicated in the high-risk groups. Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments.
Lek, Sze Min; Ku, Chee Wai; Allen, John C; Malhotra, Rahul; Tan, Nguan Soon; Østbye, Truls; Tan, Thiam Chye
2017-03-06
Our recent paper, based on a pilot cohort of 119 women, showed that serum progesterone <35 nmol/L was prognostic of spontaneous miscarriage by 16 weeks in women with threatened miscarriage in early pregnancy. Using a larger cohort of women from the same setting (validation cohort), we aim to assess the validity of serum progesterone <35 nmol/L with the outcome of spontaneous miscarriage by 16 weeks. In a prospective cohort study, 360 pregnant women presenting with threatened miscarriage between gestation weeks 6-10 at a tertiary hospital emergency unit for women in Singapore were recruited for this study. The main outcome measure measured is spontaneous miscarriage prior to week 16 of gestation. Area under the ROC curve (AUC) and test characteristics (sensitivity, specificity, positive and negative predictive value) at a serum progesterone cutpoint of <35 nmol/L for predicting high and low risk of spontaneous miscarriage by 16 weeks were compared between the Pilot and Validation cohorts. Test characteristics and AUC values using serum progesterone <35 nmol/L in the validation cohort were not significantly different from those in the Pilot cohort, demonstrating excellent accuracy and reproducibility of the proposed serum progesterone cut-off level. The cut-off value for serum progesterone (35 nmol/L) demonstrated clinical relevance and allow clinicians to stratify patients into high and low risk groups for spontaneous miscarriage.
Blood-based protein biomarkers for diagnosis of Alzheimer disease.
Doecke, James D; Laws, Simon M; Faux, Noel G; Wilson, William; Burnham, Samantha C; Lam, Chiou-Peng; Mondal, Alinda; Bedo, Justin; Bush, Ashley I; Brown, Belinda; De Ruyck, Karl; Ellis, Kathryn A; Fowler, Christopher; Gupta, Veer B; Head, Richard; Macaulay, S Lance; Pertile, Kelly; Rowe, Christopher C; Rembach, Alan; Rodrigues, Mark; Rumble, Rebecca; Szoeke, Cassandra; Taddei, Kevin; Taddei, Tania; Trounson, Brett; Ames, David; Masters, Colin L; Martins, Ralph N
2012-10-01
To identify plasma biomarkers for the diagnosis of Alzheimer disease (AD). Baseline plasma screening of 151 multiplexed analytes combined with targeted biomarker and clinical pathology data. General community-based, prospective, longitudinal study of aging. A total of 754 healthy individuals serving as controls and 207 participants with AD from the Australian Imaging Biomarker and Lifestyle study (AIBL) cohort with identified biomarkers that were validated in 58 healthy controls and 112 individuals with AD from the Alzheimer Disease Neuroimaging Initiative (ADNI) cohort. A biomarker panel was identified that included markers significantly increased (cortisol, pancreatic polypeptide, insulinlike growth factor binding protein 2, β(2) microglobulin, vascular cell adhesion molecule 1, carcinoembryonic antigen, matrix metalloprotein 2, CD40, macrophage inflammatory protein 1α, superoxide dismutase, and homocysteine) and decreased (apolipoprotein E, epidermal growth factor receptor, hemoglobin, calcium, zinc, interleukin 17, and albumin) in AD. Cross-validated accuracy measures from the AIBL cohort reached a mean (SD) of 85% (3.0%) for sensitivity and specificity and 93% (3.0) for the area under the receiver operating characteristic curve. A second validation using the ADNI cohort attained accuracy measures of 80% (3.0%) for sensitivity and specificity and 85% (3.0) for area under the receiver operating characteristic curve. This study identified a panel of plasma biomarkers that distinguish individuals with AD from cognitively healthy control subjects with high sensitivity and specificity. Cross-validation within the AIBL cohort and further validation within the ADNI cohort provides strong evidence that the identified biomarkers are important for AD diagnosis.
Reveles, Kelly R; Mortensen, Eric M; Koeller, Jim M; Lawson, Kenneth A; Pugh, Mary Jo V; Rumbellow, Sarah A; Argamany, Jacqueline R; Frei, Christopher R
2018-03-01
Prior studies have identified risk factors for recurrent Clostridium difficile infection (CDI), but few studies have integrated these factors into a clinical prediction rule that can aid clinical decision-making. The objectives of this study were to derive and validate a CDI recurrence prediction rule to identify patients at risk for first recurrence in a national cohort of veterans. Retrospective cohort study. Veterans Affairs Informatics and Computing Infrastructure. A total of 22,615 adult Veterans Health Administration beneficiaries with first-episode CDI between October 1, 2002, and September 30, 2014; of these patients, 7538 were assigned to the derivation cohort and 15,077 to the validation cohort. A 60-day CDI recurrence prediction rule was created in a derivation cohort using backward logistic regression. Those variables significant at p<0.01 were assigned an integer score proportional to the regression coefficient. The model was then validated in the derivation cohort and a separate validation cohort. Patients were then split into three risk categories, and rates of recurrence were described for each category. The CDI recurrence prediction rule included the following predictor variables with their respective point values: prior third- and fourth-generation cephalosporins (1 point), prior proton pump inhibitors (1 point), prior antidiarrheals (1 point), nonsevere CDI (2 points), and community-onset CDI (3 points). In the derivation cohort, the 60-day CDI recurrence risk for each score ranged from 7.5% (0 points) to 57.9% (8 points). The risk score was strongly correlated with recurrence (R 2 = 0.94). Patients were split into low-risk (0-2 points), medium-risk (3-5 points), and high-risk (6-8 points) classes and had the following recurrence rates: 8.9%, 20.2%, and 35.0%, respectively. Findings were similar in the validation cohort. Several CDI and patient-specific factors were independently associated with 60-day CDI recurrence risk. When integrated into a clinical prediction rule, higher risk scores and risk classes were strongly correlated with CDI recurrence. This clinical prediction rule can be used by providers to identify patients at high risk for CDI recurrence and help guide preventive strategy decisions, while accounting for clinical judgment. © 2018 Pharmacotherapy Publications, Inc.
Leveraging biospecimen resources for discovery or validation of markers for early cancer detection.
Schully, Sheri D; Carrick, Danielle M; Mechanic, Leah E; Srivastava, Sudhir; Anderson, Garnet L; Baron, John A; Berg, Christine D; Cullen, Jennifer; Diamandis, Eleftherios P; Doria-Rose, V Paul; Goddard, Katrina A B; Hankinson, Susan E; Kushi, Lawrence H; Larson, Eric B; McShane, Lisa M; Schilsky, Richard L; Shak, Steven; Skates, Steven J; Urban, Nicole; Kramer, Barnett S; Khoury, Muin J; Ransohoff, David F
2015-04-01
Validation of early detection cancer biomarkers has proven to be disappointing when initial promising claims have often not been reproducible in diagnostic samples or did not extend to prediagnostic samples. The previously reported lack of rigorous internal validity (systematic differences between compared groups) and external validity (lack of generalizability beyond compared groups) may be effectively addressed by utilizing blood specimens and data collected within well-conducted cohort studies. Cohort studies with prediagnostic specimens (eg, blood specimens collected prior to development of clinical symptoms) and clinical data have recently been used to assess the validity of some early detection biomarkers. With this background, the Division of Cancer Control and Population Sciences (DCCPS) and the Division of Cancer Prevention (DCP) of the National Cancer Institute (NCI) held a joint workshop in August 2013. The goal was to advance early detection cancer research by considering how the infrastructure of cohort studies that already exist or are being developed might be leveraged to include appropriate blood specimens, including prediagnostic specimens, ideally collected at periodic intervals, along with clinical data about symptom status and cancer diagnosis. Three overarching recommendations emerged from the discussions: 1) facilitate sharing of existing specimens and data, 2) encourage collaboration among scientists developing biomarkers and those conducting observational cohort studies or managing healthcare systems with cohorts followed over time, and 3) conduct pilot projects that identify and address key logistic and feasibility issues regarding how appropriate specimens and clinical data might be collected at reasonable effort and cost within existing or future cohorts. © Published by Oxford University Press 2015.
Leveraging Biospecimen Resources for Discovery or Validation of Markers for Early Cancer Detection
Carrick, Danielle M.; Mechanic, Leah E.; Srivastava, Sudhir; Anderson, Garnet L.; Baron, John A.; Berg, Christine D.; Cullen, Jennifer; Diamandis, Eleftherios P.; Doria-Rose, V. Paul; Goddard, Katrina A. B.; Hankinson, Susan E.; Kushi, Lawrence H.; Larson, Eric B.; McShane, Lisa M.; Schilsky, Richard L.; Shak, Steven; Skates, Steven J.; Urban, Nicole; Kramer, Barnett S.; Khoury, Muin J.; Ransohoff, David F.
2015-01-01
Validation of early detection cancer biomarkers has proven to be disappointing when initial promising claims have often not been reproducible in diagnostic samples or did not extend to prediagnostic samples. The previously reported lack of rigorous internal validity (systematic differences between compared groups) and external validity (lack of generalizability beyond compared groups) may be effectively addressed by utilizing blood specimens and data collected within well-conducted cohort studies. Cohort studies with prediagnostic specimens (eg, blood specimens collected prior to development of clinical symptoms) and clinical data have recently been used to assess the validity of some early detection biomarkers. With this background, the Division of Cancer Control and Population Sciences (DCCPS) and the Division of Cancer Prevention (DCP) of the National Cancer Institute (NCI) held a joint workshop in August 2013. The goal was to advance early detection cancer research by considering how the infrastructure of cohort studies that already exist or are being developed might be leveraged to include appropriate blood specimens, including prediagnostic specimens, ideally collected at periodic intervals, along with clinical data about symptom status and cancer diagnosis. Three overarching recommendations emerged from the discussions: 1) facilitate sharing of existing specimens and data, 2) encourage collaboration among scientists developing biomarkers and those conducting observational cohort studies or managing healthcare systems with cohorts followed over time, and 3) conduct pilot projects that identify and address key logistic and feasibility issues regarding how appropriate specimens and clinical data might be collected at reasonable effort and cost within existing or future cohorts. PMID:25688116
Iida, Masahiro; Ikeda, Fumie; Hata, Jun; Hirakawa, Yoichiro; Ohara, Tomoyuki; Mukai, Naoko; Yoshida, Daigo; Yonemoto, Koji; Esaki, Motohiro; Kitazono, Takanari; Kiyohara, Yutaka; Ninomiya, Toshiharu
2018-05-01
There have been very few reports of risk score models for the development of gastric cancer. The aim of this study was to develop and validate a risk assessment tool for discerning future gastric cancer risk in Japanese. A total of 2444 subjects aged 40 years or over were followed up for 14 years from 1988 (derivation cohort), and 3204 subjects of the same age group were followed up for 5 years from 2002 (validation cohort). The weighting (risk score) of each risk factor for predicting future gastric cancer in the risk assessment tool was determined based on the coefficients of a Cox proportional hazards model in the derivation cohort. The goodness of fit of the established risk assessment tool was assessed using the c-statistic and the Hosmer-Lemeshow test in the validation cohort. During the follow-up, gastric cancer developed in 90 subjects in the derivation cohort and 35 subjects in the validation cohort. In the derivation cohort, the risk prediction model for gastric cancer was established using significant risk factors: age, sex, the combination of Helicobacter pylori antibody and pepsinogen status, hemoglobin A1c level, and smoking status. The incidence of gastric cancer increased significantly as the sum of risk scores increased (P trend < 0.001). The risk assessment tool was validated internally and showed good discrimination (c-statistic = 0.76) and calibration (Hosmer-Lemeshow test P = 0.43) in the validation cohort. We developed a risk assessment tool for gastric cancer that provides a useful guide for stratifying an individual's risk of future gastric cancer.
Development and validation of the Surgical Outcome Risk Tool (SORT)
Protopapa, K L; Simpson, J C; Smith, N C E; Moonesinghe, S R
2014-01-01
Background Existing risk stratification tools have limitations and clinical experience suggests they are not used routinely. The aim of this study was to develop and validate a preoperative risk stratification tool to predict 30-day mortality after non-cardiac surgery in adults by analysis of data from the observational National Confidential Enquiry into Patient Outcome and Death (NCEPOD) Knowing the Risk study. Methods The data set was split into derivation and validation cohorts. Logistic regression was used to construct a model in the derivation cohort to create the Surgical Outcome Risk Tool (SORT), which was tested in the validation cohort. Results Prospective data for 19 097 cases in 326 hospitals were obtained from the NCEPOD study. Following exclusion of 2309, details of 16 788 patients were analysed (derivation cohort 11 219, validation cohort 5569). A model of 45 risk factors was refined on repeated regression analyses to develop a model comprising six variables: American Society of Anesthesiologists Physical Status (ASA-PS) grade, urgency of surgery (expedited, urgent, immediate), high-risk surgical specialty (gastrointestinal, thoracic, vascular), surgical severity (from minor to complex major), cancer and age 65 years or over. In the validation cohort, the SORT was well calibrated and demonstrated better discrimination than the ASA-PS and Surgical Risk Scale; areas under the receiver operating characteristic (ROC) curve were 0·91 (95 per cent c.i. 0·88 to 0·94), 0·87 (0·84 to 0·91) and 0·88 (0·84 to 0·92) respectively (P < 0·001). Conclusion The SORT allows rapid and simple data entry of six preoperative variables, and provides a percentage mortality risk for individuals undergoing surgery. PMID:25388883
Predicting Blunt Cerebrovascular Injury in Pediatric Trauma: Validation of the “Utah Score”
Ravindra, Vijay M.; Bollo, Robert J.; Sivakumar, Walavan; Akbari, Hassan; Naftel, Robert P.; Limbrick, David D.; Jea, Andrew; Gannon, Stephen; Shannon, Chevis; Birkas, Yekaterina; Yang, George L.; Prather, Colin T.; Kestle, John R.
2017-01-01
Abstract Risk factors for blunt cerebrovascular injury (BCVI) may differ between children and adults, suggesting that children at low risk for BCVI after trauma receive unnecessary computed tomography angiography (CTA) and high-dose radiation. We previously developed a score for predicting pediatric BCVI based on retrospective cohort analysis. Our objective is to externally validate this prediction score with a retrospective multi-institutional cohort. We included patients who underwent CTA for traumatic cranial injury at four pediatric Level I trauma centers. Each patient in the validation cohort was scored using the “Utah Score” and classified as high or low risk. Before analysis, we defined a misclassification rate <25% as validating the Utah Score. Six hundred forty-five patients (mean age 8.6 ± 5.4 years; 63.4% males) underwent screening for BCVI via CTA. The validation cohort was 411 patients from three sites compared with the training cohort of 234 patients. Twenty-two BCVIs (5.4%) were identified in the validation cohort. The Utah Score was significantly associated with BCVIs in the validation cohort (odds ratio 8.1 [3.3, 19.8], p < 0.001) and discriminated well in the validation cohort (area under the curve 72%). When the Utah Score was applied to the validation cohort, the sensitivity was 59%, specificity was 85%, positive predictive value was 18%, and negative predictive value was 97%. The Utah Score misclassified 16.6% of patients in the validation cohort. The Utah Score for predicting BCVI in pediatric trauma patients was validated with a low misclassification rate using a large, independent, multicenter cohort. Its implementation in the clinical setting may reduce the use of CTA in low-risk patients. PMID:27297774
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhong, Bin-Yan; He, Shi-Cheng; Zhu, Hai-Dong
PurposeWe aim to determine the predictors of new adjacent vertebral fractures (AVCFs) after percutaneous vertebroplasty (PVP) in patients with osteoporotic vertebral compression fractures (OVCFs) and to construct a risk prediction score to estimate a 2-year new AVCF risk-by-risk factor condition.Materials and MethodsPatients with OVCFs who underwent their first PVP between December 2006 and December 2013 at Hospital A (training cohort) and Hospital B (validation cohort) were included in this study. In training cohort, we assessed the independent risk predictors and developed the probability of new adjacent OVCFs (PNAV) score system using the Cox proportional hazard regression analysis. The accuracy ofmore » this system was then validated in both training and validation cohorts by concordance (c) statistic.Results421 patients (training cohort: n = 256; validation cohort: n = 165) were included in this study. In training cohort, new AVCFs after the first PVP treatment occurred in 33 (12.9%) patients. The independent risk factors were intradiscal cement leakage and preexisting old vertebral compression fracture(s). The estimated 2-year absolute risk of new AVCFs ranged from less than 4% in patients with neither independent risk factors to more than 45% in individuals with both factors.ConclusionsThe PNAV score is an objective and easy approach to predict the risk of new AVCFs.« less
Brunwasser, Steven M; Gebretsadik, Tebeb; Gold, Diane R; Turi, Kedir N; Stone, Cosby A; Datta, Soma; Gern, James E; Hartert, Tina V
2018-01-01
The International Study of Asthma and Allergies in Children (ISAAC) Wheezing Module is commonly used to characterize pediatric asthma in epidemiological studies, including nearly all airway cohorts participating in the Environmental Influences on Child Health Outcomes (ECHO) consortium. However, there is no consensus model for operationalizing wheezing severity with this instrument in explanatory research studies. Severity is typically measured using coarsely-defined categorical variables, reducing power and potentially underestimating etiological associations. More precise measurement approaches could improve testing of etiological theories of wheezing illness. We evaluated a continuous latent variable model of pediatric wheezing severity based on four ISAAC Wheezing Module items. Analyses included subgroups of children from three independent cohorts whose parents reported past wheezing: infants ages 0-2 in the INSPIRE birth cohort study (Cohort 1; n = 657), 6-7-year-old North American children from Phase One of the ISAAC study (Cohort 2; n = 2,765), and 5-6-year-old children in the EHAAS birth cohort study (Cohort 3; n = 102). Models were estimated using structural equation modeling. In all cohorts, covariance patterns implied by the latent variable model were consistent with the observed data, as indicated by non-significant χ2 goodness of fit tests (no evidence of model misspecification). Cohort 1 analyses showed that the latent factor structure was stable across time points and child sexes. In both cohorts 1 and 3, the latent wheezing severity variable was prospectively associated with wheeze-related clinical outcomes, including physician asthma diagnosis, acute corticosteroid use, and wheeze-related outpatient medical visits when adjusting for confounders. We developed an easily applicable continuous latent variable model of pediatric wheezing severity based on items from the well-validated ISAAC Wheezing Module. This model prospectively associates with asthma morbidity, as demonstrated in two ECHO birth cohort studies, and provides a more statistically powerful method of testing etiologic hypotheses of childhood wheezing illness and asthma.
Ochoa-Gondar, O; Vila-Corcoles, A; Rodriguez-Blanco, T; Hospital, I; Salsench, E; Ansa, X; Saun, N
2014-04-01
This study compares the ability of two simpler severity rules (classical CRB65 vs. proposed CORB75) in predicting short-term mortality in elderly patients with community-acquired pneumonia (CAP). A population-based study was undertaken involving 610 patients ≥ 65 years old with radiographically confirmed CAP diagnosed between 2008 and 2011 in Tarragona, Spain (350 cases in the derivation cohort, 260 cases in the validation cohort). Severity rules were calculated at the time of diagnosis, and 30-day mortality was considered as the dependent variable. The area under the receiver operating characteristic curves (AUC) was used to compare the discriminative power of the severity rules. Eighty deaths (46 in the derivation and 34 in the validation cohorts) were observed, which gives a mortality rate of 13.1 % (15.6 % for hospitalized and 3.3 % for outpatient cases). After multivariable analyses, besides CRB (confusion, respiration rate ≥ 30/min, systolic blood pressure <90 mmHg or diastolic ≤ 60 mmHg), peripheral oxygen saturation (≤ 90 %) and age ≥ 75 years appeared to be associated with increasing 30-day mortality in the derivation cohort. The model showed adequate calibration for the derivation and validation cohorts. A modified CORB75 scoring system (similar to the classical CRB65, but adding oxygen saturation and increasing the age to 75 years) was constructed. The AUC statistics for predicting mortality in the derivation and validation cohorts were 0.79 and 0.82, respectively. In the derivation cohort, a CORB75 score ≥ 2 showed 78.3 % sensitivity and 65.5 % specificity for mortality (in the validation cohort, these were 82.4 and 71.7 %, respectively). The proposed CORB75 scoring system has good discriminative power in predicting short-term mortality among elderly people with CAP, which supports its use for severity assessment of these patients in primary care.
Pu, Yonglin; Zhang, James X; Liu, Haiyan; Appelbaum, Daniel; Meng, Jianfeng; Penney, Bill C
2018-06-07
We hypothesized that whole-body metabolic tumor volume (MTVwb) could be used to supplement non-small cell lung cancer (NSCLC) staging due to its independent prognostic value. The goal of this study was to develop and validate a novel MTVwb risk stratification system to supplement NSCLC staging. We performed an IRB-approved retrospective review of 935 patients with NSCLC and FDG-avid tumor divided into modeling and validation cohorts based on the type of PET/CT scanner used for imaging. In addition, sensitivity analysis was conducted by dividing the patient population into two randomized cohorts. Cox regression and Kaplan-Meier survival analyses were performed to determine the prognostic value of the MTVwb risk stratification system. The cut-off values (10.0, 53.4 and 155.0 mL) between the MTVwb quartiles of the modeling cohort were applied to both the modeling and validation cohorts to determine each patient's MTVwb risk stratum. The survival analyses showed that a lower MTVwb risk stratum was associated with better overall survival (all p < 0.01), independent of TNM stage together with other clinical prognostic factors, and the discriminatory power of the MTVwb risk stratification system, as measured by Gönen and Heller's concordance index, was not significantly different from that of TNM stage in both cohorts. Also, the prognostic value of the MTVwb risk stratum was robust in the two randomized cohorts. The discordance rate between the MTVwb risk stratum and TNM stage or substage was 45.1% in the modeling cohort and 50.3% in the validation cohort. This study developed and validated a novel MTVwb risk stratification system, which has prognostic value independent of the TNM stage and other clinical prognostic factors in NSCLC, suggesting that it could be used for further NSCLC pretreatment assessment and for refining treatment decisions in individual patients.
Hay, Ashley; Migliacci, Jocelyn; Zanoni, Daniella Karassawa; Patel, Snehal; Yu, Changhong; Kattan, Michael W; Ganly, Ian
2018-05-01
The purpose of this study was to investigate the performance of the Memorial Sloan Kettering Cancer Center salivary carcinoma nomograms predicting overall survival, cancer-specific survival, and recurrence with an external validation dataset. The validation dataset comprised 123 patients treated between 2010 and 2015 at our institution. They were evaluated by assessing discrimination (concordance index [C-index]) and calibration (plotting predicted vs actual probabilities for quintiles). The validation cohort (n = 123) showed some differences to the original cohort (n = 301). The validation cohort had less high-grade cancers (P = .006), less lymphovascular invasion (LVI; P < .001) and shorter follow-up of 19 months versus 45.6 months. Validation showed a C-index of 0.833 (95% confidence interval [CI] 0.758-0.908), 0.807 (95% CI 0.717-0.898), and 0.844 (95% CI 0.768-0.920) for overall survival, cancer-specific survival, and recurrence, respectively. The 3 salivary gland nomograms performed well using a contemporary validation dataset, despite limitations related to sample size, follow-up, and differences in clinical and pathology characteristics between the original and validation cohorts. © 2018 Wiley Periodicals, Inc.
Nijhuis, Rogier L; Stijnen, Theo; Peeters, Anna; Witteman, Jacqueline C M; Hofman, Albert; Hunink, M G Myriam
2006-01-01
To determine the apparent and internal validity of the Rotterdam Ischemic heart disease & Stroke Computer (RISC) model, a Monte Carlo-Markov model, designed to evaluate the impact of cardiovascular disease (CVD) risk factors and their modification on life expectancy (LE) and cardiovascular disease-free LE (DFLE) in a general population (hereinafter, these will be referred to together as (DF)LE). The model is based on data from the Rotterdam Study, a cohort follow-up study of 6871 subjects aged 55 years and older who visited the research center for risk factor assessment at baseline (1990-1993) and completed a follow-up visit 7 years later (original cohort). The transition probabilities and risk factor trends used in the RISC model were based on data from 3501 subjects (the study cohort). To validate the RISC model, the number of simulated CVD events during 7 years' follow-up were compared with the observed number of events in the study cohort and the original cohort, respectively, and simulated (DF)LEs were compared with the (DF)LEs calculated from multistate life tables. Both in the study cohort and in the original cohort, the simulated distribution of CVD events was consistent with the observed number of events (CVD deaths: 7.1% v. 6.6% and 7.4% v. 7.6%, respectively; non-CVD deaths: 11.2% v. 11.5% and 12.9% v. 13.0%, respectively). The distribution of (DF)LEs estimated with the RISC model consistently encompassed the (DF)LEs calculated with multistate life tables. The simulated events and (DF)LE estimates from the RISC model are consistent with observed data from a cohort follow-up study.
2014-01-01
Introduction Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts. Methods An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147). Results The original training cohort reached a statistically significant difference (p < 0.05) in disease-free survivals between the three CMTC groups after an additional two years of follow-up (median = 55 months). The prognostic value of the triad classification was reproduced in the second independent internal cohort and the new external validation cohort. CMTC achieved even higher prognostic significance when all available patients were analyzed (n = 4,851). Oncogenic pathways Myc, E2F1, Ras and β-catenin were again implicated in the high-risk groups. Conclusions Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments. PMID:24996446
McLernon, David J; Donnan, Peter T; Sullivan, Frank M; Roderick, Paul; Rosenberg, William M; Ryder, Steve D; Dillon, John F
2014-06-02
To derive and validate a clinical prediction model to estimate the risk of liver disease diagnosis following liver function tests (LFTs) and to convert the model to a simplified scoring tool for use in primary care. Population-based observational cohort study of patients in Tayside Scotland identified as having their LFTs performed in primary care and followed for 2 years. Biochemistry data were linked to secondary care, prescriptions and mortality data to ascertain baseline characteristics of the derivation cohort. A separate validation cohort was obtained from 19 general practices across the rest of Scotland to externally validate the final model. Primary care, Tayside, Scotland. Derivation cohort: LFT results from 310 511 patients. After exclusions (including: patients under 16 years, patients having initial LFTs measured in secondary care, bilirubin >35 μmol/L, liver complications within 6 weeks and history of a liver condition), the derivation cohort contained 95 977 patients with no clinically apparent liver condition. Validation cohort: after exclusions, this cohort contained 11 653 patients. Diagnosis of a liver condition within 2 years. From the derivation cohort (n=95 977), 481 (0.5%) were diagnosed with a liver disease. The model showed good discrimination (C-statistic=0.78). Given the low prevalence of liver disease, the negative predictive values were high. Positive predictive values were low but rose to 20-30% for high-risk patients. This study successfully developed and validated a clinical prediction model and subsequent scoring tool, the Algorithm for Liver Function Investigations (ALFI), which can predict liver disease risk in patients with no clinically obvious liver disease who had their initial LFTs taken in primary care. ALFI can help general practitioners focus referral on a small subset of patients with higher predicted risk while continuing to address modifiable liver disease risk factors in those at lower risk. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
External validation of preexisting first trimester preeclampsia prediction models.
Allen, Rebecca E; Zamora, Javier; Arroyo-Manzano, David; Velauthar, Luxmilar; Allotey, John; Thangaratinam, Shakila; Aquilina, Joseph
2017-10-01
To validate the increasing number of prognostic models being developed for preeclampsia using our own prospective study. A systematic review of literature that assessed biomarkers, uterine artery Doppler and maternal characteristics in the first trimester for the prediction of preeclampsia was performed and models selected based on predefined criteria. Validation was performed by applying the regression coefficients that were published in the different derivation studies to our cohort. We assessed the models discrimination ability and calibration. Twenty models were identified for validation. The discrimination ability observed in derivation studies (Area Under the Curves) ranged from 0.70 to 0.96 when these models were validated against the validation cohort, these AUC varied importantly, ranging from 0.504 to 0.833. Comparing Area Under the Curves obtained in the derivation study to those in the validation cohort we found statistically significant differences in several studies. There currently isn't a definitive prediction model with adequate ability to discriminate for preeclampsia, which performs as well when applied to a different population and can differentiate well between the highest and lowest risk groups within the tested population. The pre-existing large number of models limits the value of further model development and future research should be focussed on further attempts to validate existing models and assessing whether implementation of these improves patient care. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.
Risk score to predict gastrointestinal bleeding after acute ischemic stroke.
Ji, Ruijun; Shen, Haipeng; Pan, Yuesong; Wang, Penglian; Liu, Gaifen; Wang, Yilong; Li, Hao; Singhal, Aneesh B; Wang, Yongjun
2014-07-25
Gastrointestinal bleeding (GIB) is a common and often serious complication after stroke. Although several risk factors for post-stroke GIB have been identified, no reliable or validated scoring system is currently available to predict GIB after acute stroke in routine clinical practice or clinical trials. In the present study, we aimed to develop and validate a risk model (acute ischemic stroke associated gastrointestinal bleeding score, the AIS-GIB score) to predict in-hospital GIB after acute ischemic stroke. The AIS-GIB score was developed from data in the China National Stroke Registry (CNSR). Eligible patients in the CNSR were randomly divided into derivation (60%) and internal validation (40%) cohorts. External validation was performed using data from the prospective Chinese Intracranial Atherosclerosis Study (CICAS). Independent predictors of in-hospital GIB were obtained using multivariable logistic regression in the derivation cohort, and β-coefficients were used to generate point scoring system for the AIS-GIB. The area under the receiver operating characteristic curve (AUROC) and the Hosmer-Lemeshow goodness-of-fit test were used to assess model discrimination and calibration, respectively. A total of 8,820, 5,882, and 2,938 patients were enrolled in the derivation, internal validation and external validation cohorts. The overall in-hospital GIB after AIS was 2.6%, 2.3%, and 1.5% in the derivation, internal, and external validation cohort, respectively. An 18-point AIS-GIB score was developed from the set of independent predictors of GIB including age, gender, history of hypertension, hepatic cirrhosis, peptic ulcer or previous GIB, pre-stroke dependence, admission National Institutes of Health stroke scale score, Glasgow Coma Scale score and stroke subtype (Oxfordshire). The AIS-GIB score showed good discrimination in the derivation (0.79; 95% CI, 0.764-0.825), internal (0.78; 95% CI, 0.74-0.82) and external (0.76; 95% CI, 0.71-0.82) validation cohorts. The AIS-GIB score was well calibrated in the derivation (P = 0.42), internal (P = 0.45) and external (P = 0.86) validation cohorts. The AIS-GIB score is a valid clinical grading scale to predict in-hospital GIB after AIS. Further studies on the effect of the AIS-GIB score on reducing GIB and improving outcome after AIS are warranted.
Yu, Jun; Feng, Qiang; Wong, Sunny Hei; Zhang, Dongya; Liang, Qiao Yi; Qin, Youwen; Tang, Longqing; Zhao, Hui; Stenvang, Jan; Li, Yanli; Wang, Xiaokai; Xu, Xiaoqiang; Chen, Ning; Wu, William Ka Kei; Al-Aama, Jumana; Nielsen, Hans Jørgen; Kiilerich, Pia; Jensen, Benjamin Anderschou Holbech; Yau, Tung On; Lan, Zhou; Jia, Huijue; Li, Junhua; Xiao, Liang; Lam, Thomas Yuen Tung; Ng, Siew Chien; Cheng, Alfred Sze-Lok; Wong, Vincent Wai-Sun; Chan, Francis Ka Leung; Xu, Xun; Yang, Huanming; Madsen, Lise; Datz, Christian; Tilg, Herbert; Wang, Jian; Brünner, Nils; Kristiansen, Karsten; Arumugam, Manimozhiyan; Sung, Joseph Jao-Yiu; Wang, Jun
2017-01-01
To evaluate the potential for diagnosing colorectal cancer (CRC) from faecal metagenomes. We performed metagenome-wide association studies on faecal samples from 74 patients with CRC and 54 controls from China, and validated the results in 16 patients and 24 controls from Denmark. We further validated the biomarkers in two published cohorts from France and Austria. Finally, we employed targeted quantitative PCR (qPCR) assays to evaluate diagnostic potential of selected biomarkers in an independent Chinese cohort of 47 patients and 109 controls. Besides confirming known associations of Fusobacterium nucleatum and Peptostreptococcus stomatis with CRC, we found significant associations with several species, including Parvimonas micra and Solobacterium moorei. We identified 20 microbial gene markers that differentiated CRC and control microbiomes, and validated 4 markers in the Danish cohort. In the French and Austrian cohorts, these four genes distinguished CRC metagenomes from controls with areas under the receiver-operating curve (AUC) of 0.72 and 0.77, respectively. qPCR measurements of two of these genes accurately classified patients with CRC in the independent Chinese cohort with AUC=0.84 and OR of 23. These genes were enriched in early-stage (I-II) patient microbiomes, highlighting the potential for using faecal metagenomic biomarkers for early diagnosis of CRC. We present the first metagenomic profiling study of CRC faecal microbiomes to discover and validate microbial biomarkers in ethnically different cohorts, and to independently validate selected biomarkers using an affordable clinically relevant technology. Our study thus takes a step further towards affordable non-invasive early diagnostic biomarkers for CRC from faecal samples. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Zemek, Roger; Barrowman, Nick; Freedman, Stephen B; Gravel, Jocelyn; Gagnon, Isabelle; McGahern, Candice; Aglipay, Mary; Sangha, Gurinder; Boutis, Kathy; Beer, Darcy; Craig, William; Burns, Emma; Farion, Ken J; Mikrogianakis, Angelo; Barlow, Karen; Dubrovsky, Alexander S; Meeuwisse, Willem; Gioia, Gerard; Meehan, William P; Beauchamp, Miriam H; Kamil, Yael; Grool, Anne M; Hoshizaki, Blaine; Anderson, Peter; Brooks, Brian L; Yeates, Keith Owen; Vassilyadi, Michael; Klassen, Terry; Keightley, Michelle; Richer, Lawrence; DeMatteo, Carol; Osmond, Martin H
2016-03-08
Approximately one-third of children experiencing acute concussion experience ongoing somatic, cognitive, and psychological or behavioral symptoms, referred to as persistent postconcussion symptoms (PPCS). However, validated and pragmatic tools enabling clinicians to identify patients at risk for PPCS do not exist. To derive and validate a clinical risk score for PPCS among children presenting to the emergency department. Prospective, multicenter cohort study (Predicting and Preventing Postconcussive Problems in Pediatrics [5P]) enrolled young patients (aged 5-<18 years) who presented within 48 hours of an acute head injury at 1 of 9 pediatric emergency departments within the Pediatric Emergency Research Canada (PERC) network from August 2013 through September 2014 (derivation cohort) and from October 2014 through June 2015 (validation cohort). Participants completed follow-up 28 days after the injury. All eligible patients had concussions consistent with the Zurich consensus diagnostic criteria. The primary outcome was PPCS risk score at 28 days, which was defined as 3 or more new or worsening symptoms using the patient-reported Postconcussion Symptom Inventory compared with recalled state of being prior to the injury. In total, 3063 patients (median age, 12.0 years [interquartile range, 9.2-14.6 years]; 1205 [39.3%] girls) were enrolled (n = 2006 in the derivation cohort; n = 1057 in the validation cohort) and 2584 of whom (n = 1701 [85%] in the derivation cohort; n = 883 [84%] in the validation cohort) completed follow-up at 28 days after the injury. Persistent postconcussion symptoms were present in 801 patients (31.0%) (n = 510 [30.0%] in the derivation cohort and n = 291 [33.0%] in the validation cohort). The 12-point PPCS risk score model for the derivation cohort included the variables of female sex, age of 13 years or older, physician-diagnosed migraine history, prior concussion with symptoms lasting longer than 1 week, headache, sensitivity to noise, fatigue, answering questions slowly, and 4 or more errors on the Balance Error Scoring System tandem stance. The area under the curve was 0.71 (95% CI, 0.69-0.74) for the derivation cohort and 0.68 (95% CI, 0.65-0.72) for the validation cohort. A clinical risk score developed among children presenting to the emergency department with concussion and head injury within the previous 48 hours had modest discrimination to stratify PPCS risk at 28 days. Before this score is adopted in clinical practice, further research is needed for external validation, assessment of accuracy in an office setting, and determination of clinical utility.
Rasmussen, Jacob H; Håkansson, Katrin; Rasmussen, Gregers B; Vogelius, Ivan R; Friborg, Jeppe; Fischer, Barbara M; Bentzen, Søren M; Specht, Lena
2018-06-01
A previously published prognostic model in patients with head and neck squamous cell carcinoma (HNSCC) was validated in both a p16-negative and a p16-positive independent patient cohort and the performance was compared with the newly adopted 8th edition of the UICC staging system. Consecutive patients with HNSCC treated at a single institution from 2005 to 2012 were included. The cohort was divided in three. 1.) Training cohort, patients treated from 2005 to 2009 excluding patients with p16-positive oropharyngeal squamous cell carcinomas (OPSCC); 2.) A p16-negative validation cohort and 3.) A p16-positive validation cohort. A previously published prognostic model (clinical model) with the significant covariates (smoking status, FDG uptake, and tumor volume) was refitted in the training cohort and validated in the two validation cohorts. The clinical model was used to generate four risk groups based on the predicted risk of disease recurrence after 2 years and the performance was compared with UICC staging 8th edition using concordance index. Overall 568 patients were included. Compared to UICC the clinical model had a significantly better concordance index in the p16-negative validation cohort (AUC = 0.63 for UICC and AUC = 0.73 for the clinical model; p = 0.003) and a borderline significantly better concordance index in the p16-positive cohort (AUC = 0.63 for UICC and 0.72 for the clinical model; p = 0.088). The validated clinical model provided a better prognostication of risk of disease recurrence than UICC stage in the p16-negative validation cohort, and similar prognostication as the newly adopted 8th edition of the UICC staging in the p16-positive patient cohort. Copyright © 2018 Elsevier Ltd. All rights reserved.
Coupland, Carol
2015-01-01
Study question Is it possible to develop and externally validate risk prediction equations to estimate the 10 year risk of blindness and lower limb amputation in patients with diabetes aged 25-84 years? Methods This was a prospective cohort study using routinely collected data from general practices in England contributing to the QResearch and Clinical Practice Research Datalink (CPRD) databases during the study period 1998-2014. The equations were developed using 763 QResearch practices (n=454 575 patients with diabetes) and validated in 254 different QResearch practices (n=142 419) and 357 CPRD practices (n=206 050). Cox proportional hazards models were used to derive separate risk equations for blindness and amputation in men and women that could be evaluated at 10 years. Measures of calibration and discrimination were calculated in the two validation cohorts. Study answer and limitations Risk prediction equations to quantify absolute risk of blindness and amputation in men and women with diabetes have been developed and externally validated. In the QResearch derivation cohort, 4822 new cases of lower limb amputation and 8063 new cases of blindness occurred during follow-up. The risk equations were well calibrated in both validation cohorts. Discrimination was good in men in the external CPRD cohort for amputation (D statistic 1.69, Harrell’s C statistic 0.77) and blindness (D statistic 1.40, Harrell’s C statistic 0.73), with similar results in women and in the QResearch validation cohort. The algorithms are based on variables that patients are likely to know or that are routinely recorded in general practice computer systems. They can be used to identify patients at high risk for prevention or further assessment. Limitations include lack of formally adjudicated outcomes, information bias, and missing data. What this study adds Patients with type 1 or type 2 diabetes are at increased risk of blindness and amputation but generally do not have accurate assessments of the magnitude of their individual risks. The new algorithms calculate the absolute risk of developing these complications over a 10 year period in patients with diabetes, taking account of their individual risk factors. Funding, competing interests, data sharing JH-C is co-director of QResearch, a not for profit organisation which is a joint partnership between the University of Nottingham and Egton Medical Information Systems, and is also a paid director of ClinRisk Ltd. CC is a paid consultant statistician for ClinRisk Ltd. PMID:26560308
Development and validation of a prediction model for functional decline in older medical inpatients.
Takada, Toshihiko; Fukuma, Shingo; Yamamoto, Yosuke; Tsugihashi, Yukio; Nagano, Hiroyuki; Hayashi, Michio; Miyashita, Jun; Azuma, Teruhisa; Fukuhara, Shunichi
2018-05-17
To prevent functional decline in older inpatients, identification of high-risk patients is crucial. The aim of this study was to develop and validate a prediction model to assess the risk of functional decline in older medical inpatients. In this retrospective cohort study, patients ≥65 years admitted acutely to medical wards were included. The healthcare database of 246 acute care hospitals (n = 229,913) was used for derivation, and two acute care hospitals (n = 1767 and 5443, respectively) were used for validation. Data were collected using a national administrative claims and discharge database. Functional decline was defined as a decline of the Katz score at discharge compared with on admission. About 6% of patients in the derivation cohort and 9% and 2% in each validation cohort developed functional decline. A model with 7 items, age, body mass index, living in a nursing home, ambulance use, need for assistance in walking, dementia, and bedsore, was developed. On internal validation, it demonstrated a c-statistic of 0.77 (95% confidence interval (CI) = 0.767-0.771) and good fit on the calibration plot. On external validation, the c-statistics were 0.79 (95% CI = 0.77-0.81) and 0.75 (95% CI = 0.73-0.77) for each cohort, respectively. Calibration plots showed good fit in one cohort and overestimation in the other one. A prediction model for functional decline in older medical inpatients was derived and validated. It is expected that use of the model would lead to early identification of high-risk patients and introducing early intervention. Copyright © 2018 Elsevier B.V. All rights reserved.
Tang, Qiuqiong; Holland-Letz, Tim; Slynko, Alla; Cuk, Katarina; Marme, Frederik; Schott, Sarah; Heil, Jörg; Qu, Bin; Golatta, Michael; Bewerunge-Hudler, Melanie; Sutter, Christian; Surowy, Harald; Wappenschmidt, Barbara; Schmutzler, Rita; Hoth, Markus; Bugert, Peter; Bartram, Claus R; Sohn, Christof; Schneeweiss, Andreas; Yang, Rongxi; Burwinkel, Barbara
2016-09-27
DNA methylation changes in peripheral blood DNA have been shown to be associated with solid tumors. We sought to identify methylation alterations in whole blood DNA that are associated with breast cancer (BC). Epigenome-wide DNA methylation profiling on blood DNA from BC cases and healthy controls was performed by applying Infinium HumanMethylation450K BeadChips. Promising CpG sites were selected and validated in three independent larger sample cohorts via MassARRAY EpiTyper assays. CpG sites located in three genes (cg06418238 in RPTOR, cg00736299 in MGRN1 and cg27466532 in RAPSN), which showed significant hypomethylation in BC patients compared to healthy controls in the discovery cohort (p < 1.00 x 10-6) were selected and successfully validated in three independent cohorts (validation I, n =211; validation II, n=378; validation III, n=520). The observed methylation differences are likely not cell-type specific, as the differences were only seen in whole blood, but not in specific sub cell-types of leucocytes. Moreover, we observed in quartile analysis that women in the lower methylation quartiles of these three loci had higher ORs than women in the higher quartiles. The combined AUC of three loci was 0.79 (95%CI 0.73-0.85) in validation cohort I, and was 0.60 (95%CI 0.54-0.66) and 0.62 (95%CI 0.57-0.67) in validation cohort II and III, respectively. Our study suggests that hypomethylation of CpG sites in RPTOR, MGRN1 and RAPSN in blood is associated with BC and might serve as blood-based marker supplements for BC if these could be verified in prospective studies.
Real-time Raman spectroscopy for automatic in vivo skin cancer detection: an independent validation.
Zhao, Jianhua; Lui, Harvey; Kalia, Sunil; Zeng, Haishan
2015-11-01
In a recent study, we have demonstrated that real-time Raman spectroscopy could be used for skin cancer diagnosis. As a translational study, the objective of this study is to validate previous findings through a completely independent clinical test. In total, 645 confirmed cases were included in the analysis, including a cohort of 518 cases from a previous study, and an independent cohort of 127 new cases. Multi-variant statistical data analyses including principal component with general discriminant analysis (PC-GDA) and partial least squares (PLS) were used separately for lesion classification, which generated similar results. When the previous cohort (n = 518) was used as training and the new cohort (n = 127) was used as testing, the area under the receiver operating characteristic curve (ROC AUC) was found to be 0.889 (95 % CI 0.834-0.944; PLS); when the two cohorts were combined, the ROC AUC was 0.894 (95 % CI 0.870-0.918; PLS) with the narrowest confidence intervals. Both analyses were comparable to the previous findings, where the ROC AUC was 0.896 (95 % CI 0.846-0.946; PLS). The independent study validates that real-time Raman spectroscopy could be used for automatic in vivo skin cancer diagnosis with good accuracy.
Subramanyam, Rajeev; Yeramaneni, Samrat; Hossain, Mohamed Monir; Anneken, Amy M; Varughese, Anna M
2016-05-01
Perioperative respiratory adverse events (PRAEs) are the most common cause of serious adverse events in children receiving anesthesia. Our primary aim of this study was to develop and validate a risk prediction tool for the occurrence of PRAE from the onset of anesthesia induction until discharge from the postanesthesia care unit in children younger than 18 years undergoing elective ambulatory anesthesia for surgery and radiology. The incidence of PRAE was studied. We analyzed data from 19,059 patients from our department's quality improvement database. The predictor variables were age, sex, ASA physical status, morbid obesity, preexisting pulmonary disorder, preexisting neurologic disorder, and location of ambulatory anesthesia (surgery or radiology). Composite PRAE was defined as the presence of any 1 of the following events: intraoperative bronchospasm, intraoperative laryngospasm, postoperative apnea, postoperative laryngospasm, postoperative bronchospasm, or postoperative prolonged oxygen requirement. Development and validation of the risk prediction tool for PRAE were performed using a split sampling technique to split the database into 2 independent cohorts based on the year when the patient received ambulatory anesthesia for surgery and radiology using logistic regression. A risk score was developed based on the regression coefficients from the validation tool. The performance of the risk prediction tool was assessed by using tests of discrimination and calibration. The overall incidence of composite PRAE was 2.8%. The derivation cohort included 8904 patients, and the validation cohort included 10,155 patients. The risk of PRAE was 3.9% in the development cohort and 1.8% in the validation cohort. Age ≤ 3 years (versus >3 years), ASA physical status II or III (versus ASA physical status I), morbid obesity, preexisting pulmonary disorder, and surgery (versus radiology) significantly predicted the occurrence of PRAE in a multivariable logistic regression model. A risk score in the range of 0 to 3 was assigned to each significant variable in the logistic regression model, and final score for all risk factors ranged from 0 to 11. A cutoff score of 4 was derived from a receiver operating characteristic curve to determine the high-risk category. The model C-statistic and the corresponding SE for the derivation and validation cohort was 0.64 ± 0.01 and 0.63 ± 0.02, respectively. Sensitivity and SE of the risk prediction tool to identify children at risk for PRAE was 77.6 ± 0.02 in the derivation cohort and 76.2 ± 0.03 in the validation cohort. The risk tool developed and validated from our study cohort identified 5 risk factors: age ≤ 3 years (versus >3 years), ASA physical status II and III (versus ASA physical status I), morbid obesity, preexisting pulmonary disorder, and surgery (versus radiology) for PRAE. This tool can be used to provide an individual risk score for each patient to predict the risk of PRAE in the preoperative period.
Analysis of blood-based gene expression in idiopathic Parkinson disease.
Shamir, Ron; Klein, Christine; Amar, David; Vollstedt, Eva-Juliane; Bonin, Michael; Usenovic, Marija; Wong, Yvette C; Maver, Ales; Poths, Sven; Safer, Hershel; Corvol, Jean-Christophe; Lesage, Suzanne; Lavi, Ofer; Deuschl, Günther; Kuhlenbaeumer, Gregor; Pawlack, Heike; Ulitsky, Igor; Kasten, Meike; Riess, Olaf; Brice, Alexis; Peterlin, Borut; Krainc, Dimitri
2017-10-17
To examine whether gene expression analysis of a large-scale Parkinson disease (PD) patient cohort produces a robust blood-based PD gene signature compared to previous studies that have used relatively small cohorts (≤220 samples). Whole-blood gene expression profiles were collected from a total of 523 individuals. After preprocessing, the data contained 486 gene profiles (n = 205 PD, n = 233 controls, n = 48 other neurodegenerative diseases) that were partitioned into training, validation, and independent test cohorts to identify and validate a gene signature. Batch-effect reduction and cross-validation were performed to ensure signature reliability. Finally, functional and pathway enrichment analyses were applied to the signature to identify PD-associated gene networks. A gene signature of 100 probes that mapped to 87 genes, corresponding to 64 upregulated and 23 downregulated genes differentiating between patients with idiopathic PD and controls, was identified with the training cohort and successfully replicated in both an independent validation cohort (area under the curve [AUC] = 0.79, p = 7.13E-6) and a subsequent independent test cohort (AUC = 0.74, p = 4.2E-4). Network analysis of the signature revealed gene enrichment in pathways, including metabolism, oxidation, and ubiquitination/proteasomal activity, and misregulation of mitochondria-localized genes, including downregulation of COX4I1 , ATP5A1 , and VDAC3 . We present a large-scale study of PD gene expression profiling. This work identifies a reliable blood-based PD signature and highlights the importance of large-scale patient cohorts in developing potential PD biomarkers. © 2017 American Academy of Neurology.
Validation of the pooled cohort risk score in an Asian population - a retrospective cohort study.
Chia, Yook Chin; Lim, Hooi Min; Ching, Siew Mooi
2014-11-20
The Pooled Cohort Risk Equation was introduced by the American College of Cardiology (ACC) and American Heart Association (AHA) 2013 in their Blood Cholesterol Guideline to estimate the 10-year atherosclerotic cardiovascular disease (ASCVD) risk. However, absence of Asian ethnicity in the contemporary cohorts and limited studies to examine the use of the risk score limit the applicability of the equation in an Asian population. This study examines the validity of the pooled cohort risk score in a primary care setting and compares the cardiovascular risk using both the pooled cohort risk score and the Framingham General Cardiovascular Disease (CVD) risk score. This is a 10-year retrospective cohort study of randomly selected patients aged 40-79 years. Baseline demographic data, co-morbidities and cardiovascular (CV) risk parameters were captured from patient records in 1998. Pooled cohort risk score and Framingham General CVD risk score for each patient were computed. All ASCVD events (nonfatal myocardial infarction, coronary heart disease (CHD) death, fatal and nonfatal stroke) occurring from 1998-2007 were recorded. A total of 922 patients were studied. In 1998, mean age was 57.5 ± 8.8 years with 66.7% female. There were 47% diabetic patients and 59.9% patients receiving anti-hypertensive treatment. More than 98% of patients with pooled cohort risk score ≥7.5% had FRS >10%. A total of 45 CVD events occurred, 22 (7.2%) in males and 23 (3.7%) in females. The median pooled cohort risk score for the population was 10.1 (IQR 4.7-20.6) while the actual ASCVD events that occurred was 4.9% (45/922). Our study showed moderate discrimination with AUC of 0.63. There was good calibration with Hosmer-Lemeshow test χ2 = 12.6, P = 0.12. The pooled cohort risk score appears to overestimate CV risk but this apparent over-prediction could be a result of treatment. In the absence of a validated score in an untreated population, the pooled cohort risk score appears to be appropriate for use in a primary care setting.
Walenkamp, Monique M J; Bentohami, Abdelali; Slaar, Annelie; Beerekamp, M S H Suzan; Maas, Mario; Jager, L C Cara; Sosef, Nico L; van Velde, Romuald; Ultee, Jan M; Steyerberg, Ewout W; Goslings, J C Carel; Schep, Niels W L
2016-01-01
Although only 39% of patients with wrist trauma have sustained a fracture, the majority of patients is routinely referred for radiography. The purpose of this study was to derive and externally validate a clinical decision rule that selects patients with acute wrist trauma in the Emergency Department (ED) for radiography. This multicenter prospective study consisted of three components: (1) derivation of a clinical prediction model for detecting wrist fractures in patients following wrist trauma; (2) external validation of this model; and (3) design of a clinical decision rule. The study was conducted in the EDs of five Dutch hospitals: one academic hospital (derivation cohort) and four regional hospitals (external validation cohort). We included all adult patients with acute wrist trauma. The main outcome was fracture of the wrist (distal radius, distal ulna or carpal bones) diagnosed on conventional X-rays. A total of 882 patients were analyzed; 487 in the derivation cohort and 395 in the validation cohort. We derived a clinical prediction model with eight variables: age; sex, swelling of the wrist; swelling of the anatomical snuffbox, visible deformation; distal radius tender to palpation; pain on radial deviation and painful axial compression of the thumb. The Area Under the Curve at external validation of this model was 0.81 (95% CI: 0.77-0.85). The sensitivity and specificity of the Amsterdam Wrist Rules (AWR) in the external validation cohort were 98% (95% CI: 95-99%) and 21% (95% CI: 15%-28). The negative predictive value was 90% (95% CI: 81-99%). The Amsterdam Wrist Rules is a clinical prediction rule with a high sensitivity and negative predictive value for fractures of the wrist. Although external validation showed low specificity and 100 % sensitivity could not be achieved, the Amsterdam Wrist Rules can provide physicians in the Emergency Department with a useful screening tool to select patients with acute wrist trauma for radiography. The upcoming implementation study will further reveal the impact of the Amsterdam Wrist Rules on the anticipated reduction of X-rays requested, missed fractures, Emergency Department waiting times and health care costs.
McHugh, Leo; Seldon, Therese A.; Brandon, Roslyn A.; Kirk, James T.; Rapisarda, Antony; Sutherland, Allison J.; Presneill, Jeffrey J.; Venter, Deon J.; Lipman, Jeffrey; Thomas, Mervyn R.; Klein Klouwenberg, Peter M. C.; van Vught, Lonneke; Scicluna, Brendon; Bonten, Marc; Cremer, Olaf L.; Schultz, Marcus J.; van der Poll, Tom; Yager, Thomas D.; Brandon, Richard B.
2015-01-01
Background Systemic inflammation is a whole body reaction having an infection-positive (i.e., sepsis) or infection-negative origin. It is important to distinguish between these two etiologies early and accurately because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on peripheral blood RNAs could be discovered that would (1) determine which patients with systemic inflammation had sepsis, (2) be robust across independent patient cohorts, (3) be insensitive to disease severity, and (4) provide diagnostic utility. The goal of this study was to identify and validate such a molecular classifier. Methods and Findings We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICUs). Biomarker discovery utilized an Australian cohort (n = 105) consisting of 74 cases (sepsis patients) and 31 controls (post-surgical patients with infection-negative systemic inflammation) recruited at five tertiary care settings in Brisbane, Australia, from June 3, 2008, to December 22, 2011. A four-gene classifier combining CEACAM4, LAMP1, PLA2G7, and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte Lab, was validated using reverse transcription quantitative PCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Patients for validation were selected from the Molecular Diagnosis and Risk Stratification of Sepsis study (ClinicalTrials.gov, NCT01905033), which recruited ICU patients from the Academic Medical Center in Amsterdam and the University Medical Center Utrecht. Patients recruited from November 30, 2012, to August 5, 2013, were eligible for inclusion in the present study. Validation cohort 1 (n = 59) consisted entirely of unambiguous cases and controls; SeptiCyte Lab gave an area under curve (AUC) of 0.95 (95% CI 0.91–1.00) in this cohort. ROC curve analysis of an independent, more heterogeneous group of patients (validation cohorts 2–5; 249 patients after excluding 37 patients with an infection likelihood of “possible”) gave an AUC of 0.89 (95% CI 0.85–0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility of SeptiCyte Lab was evaluated by comparison to various clinical and laboratory parameters available to a clinician within 24 h of ICU admission. SeptiCyte Lab was significantly better at differentiating cases from controls than all tested parameters, both singly and in various logistic combinations, and more than halved the diagnostic error rate compared to procalcitonin in all tested cohorts and cohort combinations. Limitations of this study relate to (1) cohort compositions that do not perfectly reflect the composition of the intended use population, (2) potential biases that could be introduced as a result of the current lack of a gold standard for diagnosing sepsis, and (3) lack of a complete, unbiased comparison to C-reactive protein. Conclusions SeptiCyte Lab is a rapid molecular assay that may be clinically useful in managing ICU patients with systemic inflammation. Further study in population-based cohorts is needed to validate this assay for clinical use. PMID:26645559
Preinjury Psychological Status, Injury Severity and Postdeployment Posttraumatic Stress Disorder
2011-05-01
Millennium Cohort Study Team. Smallpox vaccination : comparison of self-reported and electronic vaccine records in the Millennium Cohort Study. Hum Vaccin ...Smith B, Leard CA, Smith TC, Reed RJ, Ryan MAK; Millennium Cohort Study Team. Anthrax vaccination in the Millennium Cohort: validation and measures of...in Adults With Autism Spectrum Dis- orders” by Suzuki et al, published in the March 2011 is- sue of the Archives (2011;68(3):306-313), some figure
Butts, Ryan J; Savage, Andrew J; Atz, Andrew M; Heal, Elisabeth M; Burnette, Ali L; Kavarana, Minoo M; Bradley, Scott M; Chowdhury, Shahryar M
2015-09-01
This study aimed to develop a reliable and feasible score to assess the risk of rejection in pediatric heart transplantation recipients during the first post-transplant year. The first post-transplant year is the most likely time for rejection to occur in pediatric heart transplantation. Rejection during this period is associated with worse outcomes. The United Network for Organ Sharing database was queried for pediatric patients (age <18 years) who underwent isolated orthotopic heart transplantation from January 1, 2000 to December 31, 2012. Transplantations were divided into a derivation cohort (n = 2,686) and a validation (n = 509) cohort. The validation cohort was randomly selected from 20% of transplantations from 2005 to 2012. Covariates found to be associated with rejection (p < 0.2) were included in the initial multivariable logistic regression model. The final model was derived by including only variables independently associated with rejection. A risk score was then developed using relative magnitudes of the covariates' odds ratio. The score was then tested in the validation cohort. A 9-point risk score using 3 variables (age, cardiac diagnosis, and panel reactive antibody) was developed. Mean score in the derivation and validation cohorts were 4.5 ± 2.6 and 4.8 ± 2.7, respectively. A higher score was associated with an increased rate of rejection (score = 0, 10.6% in the validation cohort vs. score = 9, 40%; p < 0.01). In weighted regression analysis, the model-predicted risk of rejection correlated closely with the actual rates of rejection in the validation cohort (R(2) = 0.86; p < 0.01). The rejection score is accurate in determining the risk of early rejection in pediatric heart transplantation recipients. The score has the potential to be used in clinical practice to aid in determining the immunosuppressant regimen and the frequency of rejection surveillance in the first post-transplant year. Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Hirsch, Jan D; Metz, Kelli R; Hosokawa, Patrick W; Libby, Anne M
2014-08-01
The Medication Regimen Complexity Index (MRCI) is a 65-item instrument that can be used to quantify medication regimen complexity at the patient level, capturing all prescribed and over-the-counter medications. Although the MRCI has been used in several studies, the narrow scope of the initial validation limits application at a population or clinical practice level. To conduct a MRCI validation pertinent to the desired clinical use to identify patients for medication therapy management interventions. An expert panel of clinical pharmacists ranked medication regimen complexity for two samples of cases: a single-disease cohort (diabetes mellitus) and a multiple-disease cohort (diabetes mellitus, hypertension, human immunodeficiency virus infection, geriatric depression). Cases for expert panel review were selected from 400 ambulatory clinic patients, and each case description included data that were available via claims or electronic medical records (EMRs). Construct validity was assessed using patient-level MRCI scores, medication count, and additional patient data. Concordance was evaluated using weighted κ agreement statistic, and correlations were determined using Spearman rank-order correlation coefficient (ρ) or Kendall τ. Moderate to good concordance between patient-level MRCI scores and expert medication regimen complexity ranking was observed (claims data, consensus ranking: single-disease cohort 0.55, multiple disease cohort 0.63). In contrast, only fair to moderate concordance was observed for medication count (single-disease cohort 0.33, multiple-disease cohort 0.48). Adding more-detailed administration directions from EMR data did not improve concordance. MRCI convergent validity was supported by strong correlations with medication count (all cohorts 0.90) and moderate correlations with morbidity measures (e.g., all cohorts; number of comorbidities 0.46, Chronic Disease Score 0.46). Nonsignificant correlation of MRCI scores with age and gender (all cohorts 0.08 and 0.06, respectively) supported MRCI divergent validity. This study used cross-sectional, retrospective patient data for a small number of patients and clinical pharmacists from only two universities; therefore, results may have limited generalizability. The patient-level MRCI is a valid tool for assessing medication regimen complexity that can be applied by using data commonly found in claims and EMR databases and could be useful to identify patients who may benefit from medication therapy management. © 2014 The Authors Pharmacotherapy published by Wiley Periodicals, Inc. on behalf of Pharmacotherapy Publications, Inc.
A Severe Sepsis Mortality Prediction Model and Score for Use with Administrative Data
Ford, Dee W.; Goodwin, Andrew J.; Simpson, Annie N.; Johnson, Emily; Nadig, Nandita; Simpson, Kit N.
2016-01-01
Objective Administrative data is used for research, quality improvement, and health policy in severe sepsis. However, there is not a sepsis-specific tool applicable to administrative data with which to adjust for illness severity. Our objective was to develop, internally validate, and externally validate a severe sepsis mortality prediction model and associated mortality prediction score. Design Retrospective cohort study using 2012 administrative data from five US states. Three cohorts of patients with severe sepsis were created: 1) ICD-9-CM codes for severe sepsis/septic shock, 2) ‘Martin’ approach, and 3) ‘Angus’ approach. The model was developed and internally validated in ICD-9-CM cohort and externally validated in other cohorts. Integer point values for each predictor variable were generated to create a sepsis severity score. Setting Acute care, non-federal hospitals in NY, MD, FL, MI, and WA Subjects Patients in one of three severe sepsis cohorts: 1) explicitly coded (n=108,448), 2) Martin cohort (n=139,094), and 3) Angus cohort (n=523,637) Interventions None Measurements and Main Results Maximum likelihood estimation logistic regression to develop a predictive model for in-hospital mortality. Model calibration and discrimination assessed via Hosmer-Lemeshow goodness-of-fit (GOF) and C-statistics respectively. Primary cohort subset into risk deciles and observed versus predicted mortality plotted. GOF demonstrated p>0.05 for each cohort demonstrating sound calibration. C-statistic ranged from low of 0.709 (sepsis severity score) to high of 0.838 (Angus cohort) suggesting good to excellent model discrimination. Comparison of observed versus expected mortality was robust although accuracy decreased in highest risk decile. Conclusions Our sepsis severity model and score is a tool that provides reliable risk adjustment for administrative data. PMID:26496452
Lionte, Catalina; Sorodoc, Victorita; Jaba, Elisabeta; Botezat, Alina
2017-01-01
Abstract Acute poisoning with drugs and nonpharmaceutical agents represents an important challenge in the emergency department (ED). The objective is to create and validate a risk-prediction nomogram for use in the ED to predict the risk of in-hospital mortality in adults from acute poisoning with drugs and nonpharmaceutical agents. This was a prospective cohort study involving adults with acute poisoning from drugs and nonpharmaceutical agents admitted to a tertiary referral center for toxicology between January and December 2015 (derivation cohort) and between January and June 2016 (validation cohort). We used a program to generate nomograms based on binary logistic regression predictive models. We included variables that had significant associations with death. Using regression coefficients, we calculated scores for each variable, and estimated the event probability. Model validation was performed using bootstrap to quantify our modeling strategy and using receiver operator characteristic (ROC) analysis. The nomogram was tested on a separate validation cohort using ROC analysis and goodness-of-fit tests. Data from 315 patients aged 18 to 91 years were analyzed (n = 180 in the derivation cohort; n = 135 in the validation cohort). In the final model, the following variables were significantly associated with mortality: age, laboratory test results (lactate, potassium, MB isoenzyme of creatine kinase), electrocardiogram parameters (QTc interval), and echocardiography findings (E wave velocity deceleration time). Sex was also included to use the same model for men and women. The resulting nomogram showed excellent survival/mortality discrimination (area under the curve [AUC] 0.976, 95% confidence interval [CI] 0.954–0.998, P < 0.0001 for the derivation cohort; AUC 0.957, 95% CI 0.892–1, P < 0.0001 for the validation cohort). This nomogram provides more precise, rapid, and simple risk-analysis information for individual patients acutely exposed to drugs and nonpharmaceutical agents, and accurately estimates the probability of in-hospital death, exclusively using the results of objective tests available in the ED. PMID:28328838
Susceptibility to corticosteroid-induced adrenal suppression: a genome-wide association study.
Hawcutt, Daniel B; Francis, Ben; Carr, Daniel F; Jorgensen, Andrea L; Yin, Peng; Wallin, Naomi; O'Hara, Natalie; Zhang, Eunice J; Bloch, Katarzyna M; Ganguli, Amitava; Thompson, Ben; McEvoy, Laurence; Peak, Matthew; Crawford, Andrew A; Walker, Brian R; Blair, Joanne C; Couriel, Jonathan; Smyth, Rosalind L; Pirmohamed, Munir
2018-06-01
A serious adverse effect of corticosteroid therapy is adrenal suppression. Our aim was to identify genetic variants affecting susceptibility to corticosteroid-induced adrenal suppression. We enrolled children with asthma who used inhaled corticosteroids as part of their treatment from 25 sites across the UK (discovery cohort), as part of the Pharmacogenetics of Adrenal Suppression with Inhaled Steroids (PASS) study. We included two validation cohorts, one comprising children with asthma (PASS study) and the other consisting of adults with chronic obstructive pulmonary disorder (COPD) who were recruited from two UK centres for the Pharmacogenomics of Adrenal Suppression in COPD (PASIC) study. Participants underwent a low-dose short synacthen test. Adrenal suppression was defined as peak cortisol less than 350 nmol/L (in children) and less than 500 nmol/L (in adults). A case-control genome-wide association study was done with the control subset augmented by Wellcome Trust Case Control Consortium 2 (WTCCC2) participants. Single nucleotide polymorphisms (SNPs) that fulfilled criteria to be advanced to replication were tested by a random-effects inverse variance meta-analysis. This report presents the primary analysis. The PASS study is registered in the European Genome-phenome Archive (EGA). The PASS study is complete whereas the PASIC study is ongoing. Between November, 2008, and September, 2011, 499 children were enrolled to the discovery cohort. Between October, 2011, and December, 2012, 81 children were enrolled to the paediatric validation cohort, and from February, 2010, to June, 2015, 78 adults were enrolled to the adult validation cohort. Adrenal suppression was present in 35 (7%) children in the discovery cohort and six (7%) children and 17 (22%) adults in the validation cohorts. In the discovery cohort, 40 SNPs were found to be associated with adrenal suppression (genome-wide significance p<1 × 10 -6 ), including an intronic SNP within the PDGFD gene locus (rs591118; odds ratio [OR] 7·32, 95% CI 3·15-16·99; p=5·8 × 10 -8 ). This finding for rs591118 was validated successfully in both the paediatric asthma (OR 3·86, 95% CI 1·19-12·50; p=0·02) and adult COPD (2·41, 1·10-5·28; p=0·03) cohorts. The proportions of patients with adrenal suppression by rs591118 genotype were six (3%) of 214 patients with the GG genotype, 15 (6%) of 244 with the AG genotype, and 22 (25%) of 87 with the AA genotype. Meta-analysis of the paediatric cohorts (discovery and validation) and all three cohorts showed genome-wide significance of rs591118 (respectively, OR 5·89, 95% CI 2·97-11·68; p=4·3 × 10 -9 ; and 4·05, 2·00-8·21; p=3·5 × 10 -10 ). Our findings suggest that genetic variation in the PDGFD gene locus increases the risk of adrenal suppression in children and adults who use corticosteroids to treat asthma and COPD, respectively. Department of Health Chair in Pharmacogenetics. Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.
Lim, So Yeon; Koh, Shin Ok; Jeon, Kyeongman; Na, Sungwon; Lim, Chae-Man; Choi, Won-Il; Lee, Young-Joo; Kim, Seok Chan; Chon, Gyu Rak; Kim, Je Hyeong; Kim, Jae Yeol; Lim, Jaemin; Rhee, Chin Kook; Park, Sunghoon; Kim, Ho Cheol; Lee, Jin Hwa; Lee, Ji Hyun; Park, Jisook; Koh, Younsuck; Suh, Gee Young
2013-08-01
To externally validate the simplified acute physiology score 3 (SAPS3) and to customize it for use in Korean intensive care unit (ICU) patients. This is a prospective multicentre cohort study involving 22 ICUs from 15 centres throughout Korea. The study population comprised patients who were consecutively admitted to participating ICUs from 1 July 2010 to 31 January 2011. A total of 4617 patients were enrolled. ICU mortality was 14.3%, and hospital mortality was 20.6%. The patients were randomly assigned into one of two cohorts: a development (n = 2309) or validation (n = 2308) cohort. In the development cohort, the general SAPS3 had good discrimination (area under the receiver operating characteristics curve = 0.829), but poor calibration (Hosmer-Lemeshow goodness-of-fit test H = 123.06, P < 0.001, C = 118.45, P < 0.001). The Australasia SAPS3 did not improve calibration (H = 73.53, P < 0.001, C = 70.52, P < 0.001). Customization was achieved by altering the logit of the original SAPS3 equation. The new equation for Korean ICU patients was validated in the validation cohort, and demonstrated both good discrimination (area under the receiver operating characteristics curve = 0.835) and good calibration (H = 4.61, P = 0.799, C = 5.67, P = 0.684). General and regional Australasia SAPS3 admission scores showed poor calibration for use in Korean ICU patients, but the prognostic power of the SAPS3 was significantly improved by customization. Prediction models should be customized before being used to predict mortality in different regions of the world. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.
Konda, Sanjit R; Seymour, Rachel; Manoli, Arthur; Gales, Jordan; Karunakar, Madhav A
2016-11-01
This study aimed to develop a tool to quantify risk of inpatient mortality among geriatric and middleaged trauma patients. This study sought to demonstrate the ability of the novel risk score in the early identification of high risk trauma patients for resource-sparing interventions, including referral to palliative medicine. This retrospective cohort study utilized data from a single level 1 trauma center. Regression analysis was used to create a novel risk of inpatient mortality score. A total of 2,387 low energy and 1,201 high-energy middle-aged (range: 55 to 64 years of age) and geriatric (65 years of age or odler) trauma patients comprised the study cohort. Model validation was performed using 37,474 lowenergy and 97,034 high-energy patients from the National Trauma Databank (NTDB). Potential hospital cost reduction was calculated for early referral of high risk trauma patients to palliative medicine services in comparison to no palliative medicine referral. Factors predictive of inpatient mortality among the study and validation patient cohorts included; age, Glasgow Coma Scale, and Abbreviated Injury Scale for the head and neck and chest. Within the validation cohort, the novel mortality risk score demonstrated greater predictive capacity than existing trauma scores [STTGMALE-AUROC: 0.83 vs. TRISS 0.80, (p < 0.01), STTGMAHE-AUROC: 0.86 vs. TRISS 0.85, (p < 0.01)]. Our model demonstrated early palliative medicine evaluation could produce $1,083,082 in net hospital savings per year. This novel risk score for older trauma patients has shown fidelity in prediction of inpatient mortality; in the study and validation cohorts. This tool may be used for early intervention in the care of patients at high risk of mortality and resource expenditure.
Walenkamp, Monique M J; Bentohami, Abdelali; Slaar, Annelie; Beerekamp, M Suzan H; Maas, Mario; Jager, L Cara; Sosef, Nico L; van Velde, Romuald; Ultee, Jan M; Steyerberg, Ewout W; Goslings, J Carel; Schep, Niels W L
2015-12-18
Although only 39 % of patients with wrist trauma have sustained a fracture, the majority of patients is routinely referred for radiography. The purpose of this study was to derive and externally validate a clinical decision rule that selects patients with acute wrist trauma in the Emergency Department (ED) for radiography. This multicenter prospective study consisted of three components: (1) derivation of a clinical prediction model for detecting wrist fractures in patients following wrist trauma; (2) external validation of this model; and (3) design of a clinical decision rule. The study was conducted in the EDs of five Dutch hospitals: one academic hospital (derivation cohort) and four regional hospitals (external validation cohort). We included all adult patients with acute wrist trauma. The main outcome was fracture of the wrist (distal radius, distal ulna or carpal bones) diagnosed on conventional X-rays. A total of 882 patients were analyzed; 487 in the derivation cohort and 395 in the validation cohort. We derived a clinical prediction model with eight variables: age; sex, swelling of the wrist; swelling of the anatomical snuffbox, visible deformation; distal radius tender to palpation; pain on radial deviation and painful axial compression of the thumb. The Area Under the Curve at external validation of this model was 0.81 (95 % CI: 0.77-0.85). The sensitivity and specificity of the Amsterdam Wrist Rules (AWR) in the external validation cohort were 98 % (95 % CI: 95-99 %) and 21 % (95 % CI: 15 %-28). The negative predictive value was 90 % (95 % CI: 81-99 %). The Amsterdam Wrist Rules is a clinical prediction rule with a high sensitivity and negative predictive value for fractures of the wrist. Although external validation showed low specificity and 100 % sensitivity could not be achieved, the Amsterdam Wrist Rules can provide physicians in the Emergency Department with a useful screening tool to select patients with acute wrist trauma for radiography. The upcoming implementation study will further reveal the impact of the Amsterdam Wrist Rules on the anticipated reduction of X-rays requested, missed fractures, Emergency Department waiting times and health care costs. This study was registered in the Dutch Trial Registry, reference number NTR2544 on October 1(st), 2010.
Hill, Jonathan C; Kang, Sujin; Benedetto, Elena; Myers, Helen; Blackburn, Steven; Smith, Stephanie; Hay, Elaine; Rees, Jonathan; Beard, David; Glyn-Jones, Sion; Barker, Karen; Ellis, Benjamin; Fitzpatrick, Ray; Price, Andrew
2016-01-01
Objectives Current musculoskeletal outcome tools are fragmented across different healthcare settings and conditions. Our objectives were to develop and validate a single musculoskeletal outcome measure for use throughout the pathway and patients with different musculoskeletal conditions: the Arthritis Research UK Musculoskeletal Health Questionnaire (MSK-HQ). Setting A consensus workshop with stakeholders from across the musculoskeletal community, workshops and individual interviews with a broad mix of musculoskeletal patients identified and prioritised outcomes for MSK-HQ inclusion. Initial psychometric validation was conducted in four cohorts from community physiotherapy, and secondary care orthopaedic hip, knee and shoulder clinics. Participants Stakeholders (n=29) included primary care, physiotherapy, orthopaedic and rheumatology patients (n=8); general practitioners, physiotherapists, orthopaedists, rheumatologists and pain specialists (n=7), patient and professional national body representatives (n=10), and researchers (n=4). The four validation cohorts included 570 participants (n=210 physiotherapy, n=150 hip, n=150 knee, n=60 shoulder patients). Outcome measures Outcomes included the MSK-HQ's acceptability, feasibility, comprehension, readability and responder burden. The validation cohort outcomes were the MSK-HQ's completion rate, test–retest reliability and convergent validity with reference standards (EQ-5D-5L, Oxford Hip, Knee, Shoulder Scores, and the Keele MSK-PROM). Results Musculoskeletal domains prioritised were pain severity, physical function, work interference, social interference, sleep, fatigue, emotional health, physical activity, independence, understanding, confidence to self-manage and overall impact. Patients reported MSK-HQ items to be ‘highly relevant’ and ‘easy to understand’. Completion rates were high (94.2%), with scores normally distributed, and no floor/ceiling effects. Test–retest reliability was excellent, and convergent validity was strong (correlations 0.81–0.88). Conclusions A new musculoskeletal outcome measure has been developed through a coproduction process with patients to capture prioritised outcomes for use throughout the pathway and with different musculoskeletal conditions. Four validation cohorts found that the MSK-HQ had high completion rates, excellent test–retest reliability and strong convergent validity with reference standards. Further validation studies are ongoing, including a cohort with rheumatoid/inflammatory arthritis. PMID:27496243
Yadav, Dawesh Prakash; Madhusudhan, Kumble Seetharama; Kedia, Saurabh; Sharma, Raju; Pratap Mouli, Venigalla; Bopanna, Sawan; Dhingra, Rajan; Pradhan, Rajesh; Goyal, Sandeep; Sreenivas, Vishnubhatla; Vikram, Naval K; Makharia, Govind; Ahuja, Vineet
2017-02-01
Crohn's disease (CD) and intestinal tuberculosis (ITB) have close phenotypic resemblance. Mesenteric fat (a component of visceral fat [VF]) hypertrophy and fat wrapping, which is visible radiologically as fibrofatty proliferation, is seen more commonly in CD than in ITB. The present study was conducted to study the role of VF in differentiating CD and ITB. Visceral fat area and subcutaneous (SC) fat area were measured on computed tomography in two cohorts (development and validation). VF/SC ratio was also calculated for all patients. In the development cohort, retrospective data collection was carried out for 75 patients with CD and ITB who were on follow-up from January 2012 to November 2014. In the validation cohort, 82 patients were recruited prospectively from December 2014 to December 2015 and were diagnosed as CD or ITB according to standard diagnostic criteria. Visceral fat area and VF/SC ratio were significantly higher in CD patients (n = 42: development, n = 46: validation) than in ITB patients (n = 33: development, n = 36: validation) in both the development (106.2 ± 63.5 vs 37.3 ± 22, P = <0.001; 1.1 ± 0.57 vs 0.43 ± 0.24, P = <0.001) and validation cohorts (102.2 ± 69.8 vs 55.8 ± 44.9, P = 0.01; 1.2 ± 0.68 vs 0.56 ± 0.33, P = <0.001). A cut-off of 0.63 for VF/SC ratio in the development cohort had a high sensitivity (82%) and specificity (81%) in differentiating CD and ITB. Similar sensitivity (81%) and specificity (78%) were seen when this cut-off was applied in the validation cohort. The VF/SC ratio is a simple, cost-effective, non-invasive and single objective parameter with a good sensitivity and specificity to differentiate CD and ITB. © 2016 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.
Niyazi, Maximilian; Adeberg, Sebastian; Kaul, David; Boulesteix, Anne-Laure; Bougatf, Nina; Fleischmann, Daniel F; Grün, Arne; Krämer, Anna; Rödel, Claus; Eckert, Franziska; Paulsen, Frank; Kessel, Kerstin A; Combs, Stephanie E; Oehlke, Oliver; Grosu, Anca-Ligia; Seidlitz, Annekatrin; Lattermann, Annika; Krause, Mechthild; Baumann, Michael; Guberina, Maja; Stuschke, Martin; Budach, Volker; Belka, Claus; Debus, Jürgen
2018-04-01
Reirradiation (reRT) is a valid option with considerable efficacy in patients with recurrent high-grade glioma, but it is still not known which patients might be optimal candidates for a second course of irradiation. This study validated a newly developed prognostic score independently in an external patient cohort. The reRT risk score (RRRS) is based on a linear combination of initial histology, clinical performance status, and age derived from a multivariable model of 353 patients. This score can predict post-recurrence survival (PRS) after reRT. The validation dataset consisted of 212 patients. The RRRS differentiates three prognostic groups. Discrimination and calibration were maintained in the validation group. Median PRS times in the development cohort for the good/intermediate/poor risk categories were 14.2, 9.1, and 5.3 months, respectively. The respective groups within the validation cohort displayed median PRS times of 13.8, 8.8, and 3.8 months, respectively. Uno's C for development data was 0.64 (CI: 0.60-0.69) and for validation data 0.63 (CI: 0.58-0.68). The RRRS has been successfully validated in an independent patient cohort. This linear combination of three easily determined clinicopathological factors allows for a reliable classification of patients and may be used as stratification factor for future trials. Copyright © 2018 Elsevier B.V. All rights reserved.
Scicluna, Brendon P; van Vught, Lonneke A; Zwinderman, Aeilko H; Wiewel, Maryse A; Davenport, Emma E; Burnham, Katie L; Nürnberg, Peter; Schultz, Marcus J; Horn, Janneke; Cremer, Olaf L; Bonten, Marc J; Hinds, Charles J; Wong, Hector R; Knight, Julian C; van der Poll, Tom
2017-10-01
Host responses during sepsis are highly heterogeneous, which hampers the identification of patients at high risk of mortality and their selection for targeted therapies. In this study, we aimed to identify biologically relevant molecular endotypes in patients with sepsis. This was a prospective observational cohort study that included consecutive patients admitted for sepsis to two intensive care units (ICUs) in the Netherlands between Jan 1, 2011, and July 20, 2012 (discovery and first validation cohorts) and patients admitted with sepsis due to community-acquired pneumonia to 29 ICUs in the UK (second validation cohort). We generated genome-wide blood gene expression profiles from admission samples and analysed them by unsupervised consensus clustering and machine learning. The primary objective of this study was to establish endotypes for patients with sepsis, and assess the association of these endotypes with clinical traits and survival outcomes. We also established candidate biomarkers for the endotypes to allow identification of patient endotypes in clinical practice. The discovery cohort had 306 patients, the first validation cohort had 216, and the second validation cohort had 265 patients. Four molecular endotypes for sepsis, designated Mars1-4, were identified in the discovery cohort, and were associated with 28-day mortality (log-rank p=0·022). In the discovery cohort, the worst outcome was found for patients classified as having a Mars1 endotype, and at 28 days, 35 (39%) of 90 people with a Mars1 endotype had died (hazard ratio [HR] vs all other endotypes 1·86 [95% CI 1·21-2·86]; p=0·0045), compared with 23 (22%) of 105 people with a Mars2 endotype (HR 0·64 [0·40-1·04]; p=0·061), 16 (23%) of 71 people with a Mars3 endotype (HR 0·71 [0·41-1·22]; p=0·19), and 13 (33%) of 40 patients with a Mars4 endotype (HR 1·13 [0·63-2·04]; p=0·69). Analysis of the net reclassification improvement using a combined clinical and endotype model significantly improved risk prediction to 0·33 (0·09-0·58; p=0·008). A 140-gene expression signature reliably stratified patients with sepsis to the four endotypes in both the first and second validation cohorts. Only Mars1 was consistently significantly associated with 28-day mortality across the cohorts. To facilitate possible clinical use, a biomarker was derived for each endotype; BPGM and TAP2 reliably identified patients with a Mars1 endotype. This study provides a method for the molecular classification of patients with sepsis to four different endotypes upon ICU admission. Detection of sepsis endotypes might assist in providing personalised patient management and in selection for trials. Center for Translational Molecular Medicine, Netherlands. Copyright © 2017 Elsevier Ltd. All rights reserved.
Hippisley-Cox, Julia; Coupland, Carol
2015-11-11
Is it possible to develop and externally validate risk prediction equations to estimate the 10 year risk of blindness and lower limb amputation in patients with diabetes aged 25-84 years? This was a prospective cohort study using routinely collected data from general practices in England contributing to the QResearch and Clinical Practice Research Datalink (CPRD) databases during the study period 1998-2014. The equations were developed using 763 QResearch practices (n=454,575 patients with diabetes) and validated in 254 different QResearch practices (n=142,419) and 357 CPRD practices (n=206,050). Cox proportional hazards models were used to derive separate risk equations for blindness and amputation in men and women that could be evaluated at 10 years. Measures of calibration and discrimination were calculated in the two validation cohorts. Risk prediction equations to quantify absolute risk of blindness and amputation in men and women with diabetes have been developed and externally validated. In the QResearch derivation cohort, 4822 new cases of lower limb amputation and 8063 new cases of blindness occurred during follow-up. The risk equations were well calibrated in both validation cohorts. Discrimination was good in men in the external CPRD cohort for amputation (D statistic 1.69, Harrell's C statistic 0.77) and blindness (D statistic 1.40, Harrell's C statistic 0.73), with similar results in women and in the QResearch validation cohort. The algorithms are based on variables that patients are likely to know or that are routinely recorded in general practice computer systems. They can be used to identify patients at high risk for prevention or further assessment. Limitations include lack of formally adjudicated outcomes, information bias, and missing data. Patients with type 1 or type 2 diabetes are at increased risk of blindness and amputation but generally do not have accurate assessments of the magnitude of their individual risks. The new algorithms calculate the absolute risk of developing these complications over a 10 year period in patients with diabetes, taking account of their individual risk factors. JH-C is co-director of QResearch, a not for profit organisation which is a joint partnership between the University of Nottingham and Egton Medical Information Systems, and is also a paid director of ClinRisk Ltd. CC is a paid consultant statistician for ClinRisk Ltd. © Hippisley-Cox et al 2015.
Pulmonary artery enlargement and cystic fibrosis pulmonary exacerbations: a cohort study
Wells, J. Michael; Farris, Roopan F.; Gosdin, Taylor A.; Dransfield, Mark T.; Wood, Michelle E.; Bell, Scott C.; Rowe, Steven M.
2017-01-01
Background Acute pulmonary exacerbations are associated with progressive lung function decline and increased mortality in cystic fibrosis (CF). The role of pulmonary vascular disease in pulmonary exacerbations is unknown. We investigated the association between pulmonary artery enlargement (PA:A>1), a marker of pulmonary vascular disease, and exacerbations. Methods We analyzed clinical, computed tomography (CT), and prospective exacerbation data in a derivation cohort of 74 adult CF patients, measuring the PA:A at the level of the PA bifurcation. We then replicated our findings in a validation cohort of 190 adult CF patients. Patients were separated into groups based on the presence or absence of a PA:A>1 and were followed for 1-year in the derivation cohort and 2-years in the validation cohort. The primary endpoint was developing ≥1 acute pulmonary exacerbation during follow-up. Linear and logistic regression models were used to determine associations between clinical factors, the PA:A ratio, and pulmonary exacerbations. We used Cox regression to determine time to first exacerbation in the validation cohort. Findings We found that PA:A>1 was present in n=37/74 (50%) of the derivation and n=89/190 (47%) of the validation cohort. In the derivation cohort, n=50/74 (68%) had ≥1 exacerbation at 1 year and n=133/190 (70%) in the validation cohort had ≥1 exacerbation after 2 years. PA:A>1 was associated with younger age in both cohorts and with elevated sweat chloride (100.5±10.9 versus 90.4±19.9mmol/L, difference between groups 10.1mmol/L [95%CI 2.5–17.7], P=0.017) in the derivation group. PA:A>1 was associated with exacerbations in the derivation (OR 3.49, 95%CI 1.18–10.3, P=0.023) and validation (OR 2.41, 95%CI 1.06–5.52, P=0.037) cohorts when adjusted for confounders. Time to first exacerbation was shorter in PA:A>1 versus PA:A<1 [HR 1.66 (95%CI 1.18–2.34), P=0.004] in unadjusted analysis, but not when adjusted for sex, BMI, prior exacerbation, positive Pseudomonas status, and FEV1/FVC [HR 1.14 (95%CI 0.80–1.62), P=0.82]). Interpretation PA enlargement is prevalent in adult CF patients and is associated with acute pulmonary exacerbation risk in two well-characterized cohorts. PA:A may be a predictive marker in CF. PMID:27298019
Wada, Tomoki; Yasunaga, Hideo; Yamana, Hayato; Matsui, Hiroki; Fushimi, Kiyohide; Morimura, Naoto
2018-03-01
There was no established disability predictive measurement for patients with trauma that could be used in administrative claims databases. The aim of the present study was to develop and validate a diagnosis-based disability predictive index for severe physical disability at discharge using the International Classification of Diseases, 10th revision (ICD-10) coding. This retrospective observational study used the Diagnosis Procedure Combination database in Japan. Patients who were admitted to hospitals with trauma and discharged alive from 01 April 2010 to 31 March 2015 were included. Pediatric patients under 15 years old were excluded. Data for patients admitted to hospitals from 01 April 2010 to 31 March 2013 was used for development of a disability predictive index (derivation cohort), while data for patients admitted to hospitals from 01 April 2013 to 31 March 2015 was used for the internal validation (validation cohort). The outcome of interest was severe physical disability defined as the Barthel Index score of <60 at discharge. Trauma-related ICD-10 codes were categorized into 36 injury groups with reference to the categorization used in the Global Burden of Diseases study 2013. A multivariable logistic regression analysis was performed for the outcome using the injury groups and patient baseline characteristics including patient age, sex, and Charlson Comorbidity Index (CCI) score in the derivation cohort. A score corresponding to a regression coefficient was assigned to each injury group. The disability predictive index for each patient was defined as the sum of the scores. The predictive performance of the index was validated using the receiver operating characteristic curve analysis in the validation cohort. The derivation cohort included 1,475,158 patients, while the validation cohort included 939,659 patients. Of the 939,659 patients, 235,382 (25.0%) were discharged with severe physical disability. The c-statistics of the disability predictive index was 0.795 (95% confidence interval [CI] 0.794-0.795), while that of a model using the disability predictive index and patient baseline characteristics was 0.856 (95% CI 0.855-0.857). Severe physical disability at discharge may be well predicted with patient age, sex, CCI score, and the diagnosis-based disability predictive index in patients admitted to hospitals with trauma. Copyright © 2018 Elsevier Ltd. All rights reserved.
Evaluation of community-acquired sepsis by PIRO system in the emergency department.
Chen, Yun-Xia; Li, Chun-Sheng
2013-09-01
The predisposition, infection/insult, response, and organ dysfunction (PIRO) staging system for septic patients allows grouping of heterogeneous patients into homogeneous subgroups. The purposes of this single-center, prospective, observational cohort study were to create a PIRO system for patients with community-acquired sepsis (CAS) presenting to the emergency department (ED) and assess its prognostic and stratification capabilities. Septic patients were enrolled and allocated to derivation (n = 831) or validation (n = 860) cohorts according to their enrollment dates. The derivation cohort was used to identify independent predictors of mortality and create a PIRO system by binary logistic regression analysis, and the prognostic performance of PIRO was investigated in the validation cohort by receiver operator characteristic (ROC) curve. Ten independent predictors of 28-day mortality were identified. The PIRO system combined the components of predisposition (age, chronic obstructive pulmonary disease, hypoalbuminemia), infection (central nervous system infection), response (temperature, procalcitonin), and organ dysfunction (brain natriuretic peptide, troponin I, mean arterial pressure, Glasgow coma scale score). The area under the ROC of PIRO was 0.833 for the derivation cohort and 0.813 for the validation cohort. There was a stepwise increase in 28-day mortality with increasing PIRO score and the differences between the low- (PIRO 0-10), intermediate- (11-20), and high- (>20) risk groups were very significant in both cohorts (p < 0.01). The present study demonstrates that this PIRO system is valuable for prognosis and risk stratification in patients with CAS in the ED.
Ovsyannikova, Inna G.; Jacobson, Robert M.; Vierkant, Robert A.; O’Byrne, Megan M.; Poland, Gregory A.
2009-01-01
Purported genetic associations found in population studies require validation for confirmation. We previously reported rubella vaccine-induced immune responses and HLA associations in 346 adolescents, age 12–18 years (1st cohort), following two doses of a rubella-containing vaccine. We sought to replicate the associations discovered in that work by verifying these associations in a new cohort of 396 subjects, age 11–19 years (2nd cohort), all having had two doses of a rubella-containing vaccine. We found that B*2705 (median 1st cohort 20.9 IU/ml, p=0.028; 2nd cohort 20.5 IU/ml, p=0.001) and DPA1*0201 (median 1st cohort 32.5 IU/ml, p=0.048; 2nd cohort 25.8 IU/ml, p=0.025) alleles were consistently associated with lower rubella-induced antibodies. Further, DPB1*0401 (median 1st cohort 43.5 IU/ml, p=0.021; 2nd cohort 36.2 IU/ml, p=0.002) alleles were associated with higher antibody levels in both populations. The association of DRB1*04-DQB1*03-DPB1*03 (mean 1st cohort 25.2 IU/ml, p=0.011; 2nd cohort 21.4 IU/ml, p=0.032) and DRB1*15/16-DQB1*06-DPB1*03 (1st cohort 16.3 IU/ml, p=0.043; 2nd cohort 19.1 IU/ml, p=0.023) haplotypes with lower rubella-specific antibodies were observed in both studies. This study provides confirmatory evidence for an association between specific class I and II HLA markers and haplotypes with rubella vaccine-induced humoral responses and lends further weight to their influence on rubella immune responses. PMID:19761839
Reproducibility and validity of a semi-quantitative FFQ for trace elements.
Lee, Yujin; Park, Kyong
2016-09-01
The aim of this study was to test the reproducibility and validity of a self-administered FFQ for the Trace Element Study of Korean Adults in the Yeungnam area (SELEN). Study subjects were recruited from the SELEN cohort selected from rural and urban areas in Yeungnam, Korea. A semi-quantitative FFQ with 146 items was developed considering the dietary characteristics of cohorts in the study area. In a validation study, seventeen men and forty-eight women aged 38-62 years completed 3-d dietary records (DR) and two FFQ over a 3-month period. The validity was examined with the FFQ and DR, and the reproducibility was estimated using partial correlation coefficients, the Bland-Altman method and cross-classification. There were no significant differences between the mean intakes of selected nutrients as estimated from FFQ1, FFQ2 and DR. The median correlation coefficients for all nutrients were 0·47 and 0·56 in the reproducibility and validity tests, respectively. Bland-Altman's index and cross-classification showed acceptable agreement between FFQ1 and FFQ2 and between FFQ2 and DR. Ultimately, 78 % of the subjects were classified into the same and adjacent quartiles for most nutrients. In addition, the weighted κ value indicated that the two methods agreed fairly. In conclusion, this newly developed FFQ was a suitable dietary assessment method for the SELEN cohort study.
Potential serum biomarkers from a metabolomics study of autism
Wang, Han; Liang, Shuang; Wang, Maoqing; Gao, Jingquan; Sun, Caihong; Wang, Jia; Xia, Wei; Wu, Shiying; Sumner, Susan J.; Zhang, Fengyu; Sun, Changhao; Wu, Lijie
2016-01-01
Background Early detection and diagnosis are very important for autism. Current diagnosis of autism relies mainly on some observational questionnaires and interview tools that may involve a great variability. We performed a metabolomics analysis of serum to identify potential biomarkers for the early diagnosis and clinical evaluation of autism. Methods We analyzed a discovery cohort of patients with autism and participants without autism in the Chinese Han population using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF MS/MS) to detect metabolic changes in serum associated with autism. The potential metabolite candidates for biomarkers were individually validated in an additional independent cohort of cases and controls. We built a multiple logistic regression model to evaluate the validated biomarkers. Results We included 73 patients and 63 controls in the discovery cohort and 100 cases and 100 controls in the validation cohort. Metabolomic analysis of serum in the discovery stage identified 17 metabolites, 11 of which were validated in an independent cohort. A multiple logistic regression model built on the 11 validated metabolites fit well in both cohorts. The model consistently showed that autism was associated with 2 particular metabolites: sphingosine 1-phosphate and docosahexaenoic acid. Limitations While autism is diagnosed predominantly in boys, we were unable to perform the analysis by sex owing to difficulty recruiting enough female patients. Other limitations include the need to perform test–retest assessment within the same individual and the relatively small sample size. Conclusion Two metabolites have potential as biomarkers for the clinical diagnosis and evaluation of autism. PMID:26395811
Austin, Peter C; Mamdani, Muhammad M; Juurlink, David N; Hux, Janet E
2006-09-01
To illustrate how multiple hypotheses testing can produce associations with no clinical plausibility. We conducted a study of all 10,674,945 residents of Ontario aged between 18 and 100 years in 2000. Residents were randomly assigned to equally sized derivation and validation cohorts and classified according to their astrological sign. Using the derivation cohort, we searched through 223 of the most common diagnoses for hospitalization until we identified two for which subjects born under one astrological sign had a significantly higher probability of hospitalization compared to subjects born under the remaining signs combined (P<0.05). We tested these 24 associations in the independent validation cohort. Residents born under Leo had a higher probability of gastrointestinal hemorrhage (P=0.0447), while Sagittarians had a higher probability of humerus fracture (P=0.0123) compared to all other signs combined. After adjusting the significance level to account for multiple comparisons, none of the identified associations remained significant in either the derivation or validation cohort. Our analyses illustrate how the testing of multiple, non-prespecified hypotheses increases the likelihood of detecting implausible associations. Our findings have important implications for the analysis and interpretation of clinical studies.
Rochefort, Christian M; Buckeridge, David L; Tanguay, Andréanne; Biron, Alain; D'Aragon, Frédérick; Wang, Shengrui; Gallix, Benoit; Valiquette, Louis; Audet, Li-Anne; Lee, Todd C; Jayaraman, Dev; Petrucci, Bruno; Lefebvre, Patricia
2017-02-16
Adverse events (AEs) in acute care hospitals are frequent and associated with significant morbidity, mortality, and costs. Measuring AEs is necessary for quality improvement and benchmarking purposes, but current detection methods lack in accuracy, efficiency, and generalizability. The growing availability of electronic health records (EHR) and the development of natural language processing techniques for encoding narrative data offer an opportunity to develop potentially better methods. The purpose of this study is to determine the accuracy and generalizability of using automated methods for detecting three high-incidence and high-impact AEs from EHR data: a) hospital-acquired pneumonia, b) ventilator-associated event and, c) central line-associated bloodstream infection. This validation study will be conducted among medical, surgical and ICU patients admitted between 2013 and 2016 to the Centre hospitalier universitaire de Sherbrooke (CHUS) and the McGill University Health Centre (MUHC), which has both French and English sites. A random 60% sample of CHUS patients will be used for model development purposes (cohort 1, development set). Using a random sample of these patients, a reference standard assessment of their medical chart will be performed. Multivariate logistic regression and the area under the curve (AUC) will be employed to iteratively develop and optimize three automated AE detection models (i.e., one per AE of interest) using EHR data from the CHUS. These models will then be validated on a random sample of the remaining 40% of CHUS patients (cohort 1, internal validation set) using chart review to assess accuracy. The most accurate models developed and validated at the CHUS will then be applied to EHR data from a random sample of patients admitted to the MUHC French site (cohort 2) and English site (cohort 3)-a critical requirement given the use of narrative data -, and accuracy will be assessed using chart review. Generalizability will be determined by comparing AUCs from cohorts 2 and 3 to those from cohort 1. This study will likely produce more accurate and efficient measures of AEs. These measures could be used to assess the incidence rates of AEs, evaluate the success of preventive interventions, or benchmark performance across hospitals.
Siddique, Juned; Ruhnke, Gregory W.; Flores, Andrea; Prochaska, Micah T.; Paesch, Elizabeth; Meltzer, David O.; Whelan, Chad T.
2015-01-01
Background Lower gastrointestinal bleeding (LGIB) is a common cause of acute hospitalization. Currently, there is no accepted standard for identifying patients with LGIB in hospital administrative data. The objective of this study was to develop and validate a set of classification algorithms that use hospital administrative data to identify LGIB. Methods Our sample consists of patients admitted between July 1, 2001 and June 30, 2003 (derivation cohort) and July 1, 2003 and June 30, 2005 (validation cohort) to the general medicine inpatient service of the University of Chicago Hospital, a large urban academic medical center. Confirmed cases of LGIB in both cohorts were determined by reviewing the charts of those patients who had at least 1 of 36 principal or secondary International Classification of Diseases, Ninth revision, Clinical Modification (ICD-9-CM) diagnosis codes associated with LGIB. Classification trees were used on the data of the derivation cohort to develop a set of decision rules for identifying patients with LGIB. These rules were then applied to the validation cohort to assess their performance. Results Three classification algorithms were identified and validated: a high specificity rule with 80.1% sensitivity and 95.8% specificity, a rule that balances sensitivity and specificity (87.8% sensitivity, 90.9% specificity), and a high sensitivity rule with 100% sensitivity and 91.0% specificity. Conclusion These classification algorithms can be used in future studies to evaluate resource utilization and assess outcomes associated with LGIB without the use of chart review. PMID:26406318
Predictive Mortality Index for Community-Dwelling Elderly Koreans
Kim, Nan H.; Cho, Hyun J.; Kim, Soriul; Seo, Ji H.; Lee, Hyun J.; Yu, Ji H.; Chung, Hye S.; Yoo, Hye J.; Seo, Ji A.; Kim, Sin Gon; Baik, Sei Hyun; Choi, Dong Seop; Shin, Chol; Choi, Kyung Mook
2016-01-01
Abstract There are very few predictive indexes for long-term mortality among community-dwelling elderly Asian individuals, despite its importance, given the rapid and continuous increase in this population. We aimed to develop 10-year predictive mortality indexes for community-dwelling elderly Korean men and women based on routinely collected clinical data. We used data from 2244 elderly individuals (older than 60 years of age) from the southwest Seoul Study, a prospective cohort study, for the development of a prognostic index. An independent longitudinal cohort of 679 elderly participants was selected from the Korean Genome Epidemiology Study in Ansan City for validation. During a 10-year follow-up, 393 participants (17.5%) from the development cohort died. Nine risk factors were identified and weighed in the Cox proportional regression model to create a point scoring system: age, male sex, smoking, diabetes, systolic blood pressure, triglyceride, total cholesterol, white blood cell count, and hemoglobin. In the development cohort, the 10-year mortality risk was 6.6%, 14.8%, 18.2%, and 38.4% among subjects with 1 to 4, 5 to 7, 8 to 9, and ≥10 points, respectively. In the validation cohort, the 10-year mortality risk was 5.2%, 12.0%, 16.0%, and 16.0% according to these categories. The C-statistic for the point system was 0.73 and 0.67 in the development and validation cohorts, respectively. The present study provides valuable information for prognosis among elderly Koreans and may guide individualized approaches for appropriate care in a rapidly aging society. PMID:26844511
Lamain-de Ruiter, Marije; Kwee, Anneke; Naaktgeboren, Christiana A; de Groot, Inge; Evers, Inge M; Groenendaal, Floris; Hering, Yolanda R; Huisjes, Anjoke J M; Kirpestein, Cornel; Monincx, Wilma M; Siljee, Jacqueline E; Van 't Zelfde, Annewil; van Oirschot, Charlotte M; Vankan-Buitelaar, Simone A; Vonk, Mariska A A W; Wiegers, Therese A; Zwart, Joost J; Franx, Arie; Moons, Karel G M; Koster, Maria P H
2016-08-30
To perform an external validation and direct comparison of published prognostic models for early prediction of the risk of gestational diabetes mellitus, including predictors applicable in the first trimester of pregnancy. External validation of all published prognostic models in large scale, prospective, multicentre cohort study. 31 independent midwifery practices and six hospitals in the Netherlands. Women recruited in their first trimester (<14 weeks) of pregnancy between December 2012 and January 2014, at their initial prenatal visit. Women with pre-existing diabetes mellitus of any type were excluded. Discrimination of the prognostic models was assessed by the C statistic, and calibration assessed by calibration plots. 3723 women were included for analysis, of whom 181 (4.9%) developed gestational diabetes mellitus in pregnancy. 12 prognostic models for the disorder could be validated in the cohort. C statistics ranged from 0.67 to 0.78. Calibration plots showed that eight of the 12 models were well calibrated. The four models with the highest C statistics included almost all of the following predictors: maternal age, maternal body mass index, history of gestational diabetes mellitus, ethnicity, and family history of diabetes. Prognostic models had a similar performance in a subgroup of nulliparous women only. Decision curve analysis showed that the use of these four models always had a positive net benefit. In this external validation study, most of the published prognostic models for gestational diabetes mellitus show acceptable discrimination and calibration. The four models with the highest discriminative abilities in this study cohort, which also perform well in a subgroup of nulliparous women, are easy models to apply in clinical practice and therefore deserve further evaluation regarding their clinical impact. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Time-saving impact of an algorithm to identify potential surgical site infections.
Knepper, B C; Young, H; Jenkins, T C; Price, C S
2013-10-01
To develop and validate a partially automated algorithm to identify surgical site infections (SSIs) using commonly available electronic data to reduce manual chart review. Retrospective cohort study of patients undergoing specific surgical procedures over a 4-year period from 2007 through 2010 (algorithm development cohort) or over a 3-month period from January 2011 through March 2011 (algorithm validation cohort). A single academic safety-net hospital in a major metropolitan area. Patients undergoing at least 1 included surgical procedure during the study period. Procedures were identified in the National Healthcare Safety Network; SSIs were identified by manual chart review. Commonly available electronic data, including microbiologic, laboratory, and administrative data, were identified via a clinical data warehouse. Algorithms using combinations of these electronic variables were constructed and assessed for their ability to identify SSIs and reduce chart review. The most efficient algorithm identified in the development cohort combined microbiologic data with postoperative procedure and diagnosis codes. This algorithm resulted in 100% sensitivity and 85% specificity. Time savings from the algorithm was almost 600 person-hours of chart review. The algorithm demonstrated similar sensitivity on application to the validation cohort. A partially automated algorithm to identify potential SSIs was highly sensitive and dramatically reduced the amount of manual chart review required of infection control personnel during SSI surveillance.
Soo, Danielle H E; Pendharkar, Sayali A; Jivanji, Chirag J; Gillies, Nicola A; Windsor, John A; Petrov, Maxim S
2017-10-01
Approximately 40% of patients develop abnormal glucose metabolism after a single episode of acute pancreatitis. This study aimed to develop and validate a prediabetes self-assessment screening score for patients after acute pancreatitis. Data from non-overlapping training (n=82) and validation (n=80) cohorts were analysed. Univariate logistic and linear regression identified variables associated with prediabetes after acute pancreatitis. Multivariate logistic regression developed the score, ranging from 0 to 215. The area under the receiver-operating characteristic curve (AUROC), Hosmer-Lemeshow χ 2 statistic, and calibration plots were used to assess model discrimination and calibration. The developed score was validated using data from the validation cohort. The score had an AUROC of 0.88 (95% CI, 0.80-0.97) and Hosmer-Lemeshow χ 2 statistic of 5.75 (p=0.676). Patients with a score of ≥75 had a 94.1% probability of having prediabetes, and were 29 times more likely to have prediabetes than those with a score of <75. The AUROC in the validation cohort was 0.81 (95% CI, 0.70-0.92) and the Hosmer-Lemeshow χ 2 statistic was 5.50 (p=0.599). Model calibration of the score showed good calibration in both cohorts. The developed and validated score, called PERSEUS, is the first instrument to identify individuals who are at high risk of developing abnormal glucose metabolism following an episode of acute pancreatitis. Copyright © 2017 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.
Brasil, Pedro Emmanuel Alvarenga Americano do; Xavier, Sergio Salles; Holanda, Marcelo Teixeira; Hasslocher-Moreno, Alejandro Marcel; Braga, José Ueleres
2016-01-01
With the globalization of Chagas disease, unexperienced health care providers may have difficulties in identifying which patients should be examined for this condition. This study aimed to develop and validate a diagnostic clinical prediction model for chronic Chagas disease. This diagnostic cohort study included consecutive volunteers suspected to have chronic Chagas disease. The clinical information was blindly compared to serological tests results, and a logistic regression model was fit and validated. The development cohort included 602 patients, and the validation cohort included 138 patients. The Chagas disease prevalence was 19.9%. Sex, age, referral from blood bank, history of living in a rural area, recognizing the kissing bug, systemic hypertension, number of siblings with Chagas disease, number of relatives with a history of stroke, ECG with low voltage, anterosuperior divisional block, pathologic Q wave, right bundle branch block, and any kind of extrasystole were included in the final model. Calibration and discrimination in the development and validation cohorts (ROC AUC 0.904 and 0.912, respectively) were good. Sensitivity and specificity analyses showed that specificity reaches at least 95% above the predicted 43% risk, while sensitivity is at least 95% below the predicted 7% risk. Net benefit decision curves favor the model across all thresholds. A nomogram and an online calculator (available at http://shiny.ipec.fiocruz.br:3838/pedrobrasil/chronic_chagas_disease_prediction/) were developed to aid in individual risk estimation.
Analysis of model development strategies: predicting ventral hernia recurrence.
Holihan, Julie L; Li, Linda T; Askenasy, Erik P; Greenberg, Jacob A; Keith, Jerrod N; Martindale, Robert G; Roth, J Scott; Liang, Mike K
2016-11-01
There have been many attempts to identify variables associated with ventral hernia recurrence; however, it is unclear which statistical modeling approach results in models with greatest internal and external validity. We aim to assess the predictive accuracy of models developed using five common variable selection strategies to determine variables associated with hernia recurrence. Two multicenter ventral hernia databases were used. Database 1 was randomly split into "development" and "internal validation" cohorts. Database 2 was designated "external validation". The dependent variable for model development was hernia recurrence. Five variable selection strategies were used: (1) "clinical"-variables considered clinically relevant, (2) "selective stepwise"-all variables with a P value <0.20 were assessed in a step-backward model, (3) "liberal stepwise"-all variables were included and step-backward regression was performed, (4) "restrictive internal resampling," and (5) "liberal internal resampling." Variables were included with P < 0.05 for the Restrictive model and P < 0.10 for the Liberal model. A time-to-event analysis using Cox regression was performed using these strategies. The predictive accuracy of the developed models was tested on the internal and external validation cohorts using Harrell's C-statistic where C > 0.70 was considered "reasonable". The recurrence rate was 32.9% (n = 173/526; median/range follow-up, 20/1-58 mo) for the development cohort, 36.0% (n = 95/264, median/range follow-up 20/1-61 mo) for the internal validation cohort, and 12.7% (n = 155/1224, median/range follow-up 9/1-50 mo) for the external validation cohort. Internal validation demonstrated reasonable predictive accuracy (C-statistics = 0.772, 0.760, 0.767, 0.757, 0.763), while on external validation, predictive accuracy dipped precipitously (C-statistic = 0.561, 0.557, 0.562, 0.553, 0.560). Predictive accuracy was equally adequate on internal validation among models; however, on external validation, all five models failed to demonstrate utility. Future studies should report multiple variable selection techniques and demonstrate predictive accuracy on external data sets for model validation. Copyright © 2016 Elsevier Inc. All rights reserved.
A Risk Prediction Score for Kidney Failure or Mortality in Rhabdomyolysis
McMahon, Gearoid M.; Zeng, Xiaoxi; Waikar, Sushrut S.
2016-01-01
IMPORTANCE Rhabdomyolysis ranges in severity from asymptomatic elevations in creatine phosphokinase levels to a life-threatening disorder characterized by severe acute kidney injury requiring hemodialysis or continuous renal replacement therapy (RRT). OBJECTIVE To develop a risk prediction tool to identify patients at greatest risk of RRT or in-hospital mortality. DESIGN, SETTING, AND PARTICIPANTS Retrospective cohort study of 2371 patients admitted between January 1, 2000, and March 31, 2011, to 2 large teaching hospitals in Boston, Massachusetts, with creatine phosphokinase levels in excess of 5000 U/L within 3 days of admission. The derivation cohort consisted of 1397 patients from Massachusetts General Hospital, and the validation cohort comprised 974 patients from Brigham and Women’s Hospital. MAIN OUTCOMES AND MEASURES The composite of RRT or in-hospital mortality. RESULTS The causes and outcomes of rhabdomyolysis were similar between the derivation and validation cohorts. In total, the composite outcome occurred in 19.0% of patients (8.0% required RRT and 14.1% died during hospitalization). The highest rates of the composite outcome were from compartment syndrome (41.2%), sepsis (39.3%), and following cardiac arrest (58.5%). The lowest rates were from myositis (1.7%), exercise (3.2%), and seizures (6.0%). The independent predictors of the composite outcome were age, female sex, cause of rhabdomyolysis, and values of initial creatinine, creatine phosphokinase, phosphate, calcium, and bicarbonate. We developed a risk-prediction score from these variables in the derivation cohort and subsequently applied it in the validation cohort. The C statistic for the prediction model was 0.82 (95% CI, 0.80–0.85) in the derivation cohort and 0.83 (0.80–0.86) in the validation cohort. The Hosmer-Lemeshow P values were .14 and .28, respectively. In the validation cohort, among the patients with the lowest risk score (<5), 2.3% died or needed RRT. Among the patients with the highest risk score (>10), 61.2% died or needed RRT. CONCLUSIONS AND RELEVANCE Outcomes from rhabdomyolysis vary widely depending on the clinical context. The risk of RRT or in-hospital mortality in patients with rhabdomyolysis can be estimated using commonly available demographic, clinical, and laboratory variables on admission. PMID:24000014
Hill, Jonathan C; Kang, Sujin; Benedetto, Elena; Myers, Helen; Blackburn, Steven; Smith, Stephanie; Dunn, Kate M; Hay, Elaine; Rees, Jonathan; Beard, David; Glyn-Jones, Sion; Barker, Karen; Ellis, Benjamin; Fitzpatrick, Ray; Price, Andrew
2016-08-05
Current musculoskeletal outcome tools are fragmented across different healthcare settings and conditions. Our objectives were to develop and validate a single musculoskeletal outcome measure for use throughout the pathway and patients with different musculoskeletal conditions: the Arthritis Research UK Musculoskeletal Health Questionnaire (MSK-HQ). A consensus workshop with stakeholders from across the musculoskeletal community, workshops and individual interviews with a broad mix of musculoskeletal patients identified and prioritised outcomes for MSK-HQ inclusion. Initial psychometric validation was conducted in four cohorts from community physiotherapy, and secondary care orthopaedic hip, knee and shoulder clinics. Stakeholders (n=29) included primary care, physiotherapy, orthopaedic and rheumatology patients (n=8); general practitioners, physiotherapists, orthopaedists, rheumatologists and pain specialists (n=7), patient and professional national body representatives (n=10), and researchers (n=4). The four validation cohorts included 570 participants (n=210 physiotherapy, n=150 hip, n=150 knee, n=60 shoulder patients). Outcomes included the MSK-HQ's acceptability, feasibility, comprehension, readability and responder burden. The validation cohort outcomes were the MSK-HQ's completion rate, test-retest reliability and convergent validity with reference standards (EQ-5D-5L, Oxford Hip, Knee, Shoulder Scores, and the Keele MSK-PROM). Musculoskeletal domains prioritised were pain severity, physical function, work interference, social interference, sleep, fatigue, emotional health, physical activity, independence, understanding, confidence to self-manage and overall impact. Patients reported MSK-HQ items to be 'highly relevant' and 'easy to understand'. Completion rates were high (94.2%), with scores normally distributed, and no floor/ceiling effects. Test-retest reliability was excellent, and convergent validity was strong (correlations 0.81-0.88). A new musculoskeletal outcome measure has been developed through a coproduction process with patients to capture prioritised outcomes for use throughout the pathway and with different musculoskeletal conditions. Four validation cohorts found that the MSK-HQ had high completion rates, excellent test-retest reliability and strong convergent validity with reference standards. Further validation studies are ongoing, including a cohort with rheumatoid/inflammatory arthritis. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Zhao, Hui; Hua, Ye; Dai, Tu; He, Jian; Tang, Min; Fu, Xu; Mao, Liang; Jin, Huihan; Qiu, Yudong
2017-03-01
Microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) cannot be accurately predicted preoperatively. This study aimed to establish a predictive scoring model of MVI in solitary HCC patients without macroscopic vascular invasion. A total of 309 consecutive HCC patients who underwent curative hepatectomy were divided into the derivation (n=206) and validation cohort (n=103). A predictive scoring model of MVI was established according to the valuable predictors in the derivation cohort based on multivariate logistic regression analysis. The performance of the predictive model was evaluated in the derivation and validation cohorts. Preoperative imaging features on CECT, such as intratumoral arteries, non-nodular type of HCC and absence of radiological tumor capsule were independent predictors for MVI. The predictive scoring model was established according to the β coefficients of the 3 predictors. Area under receiver operating characteristic (AUROC) of the predictive scoring model was 0.872 (95% CI, 0.817-0.928) and 0.856 (95% CI, 0.771-0.940) in the derivation and validation cohorts. The positive and negative predictive values were 76.5% and 88.0% in the derivation cohort and 74.4% and 88.3% in the validation cohort. The performance of the model was similar between the patients with tumor size ≤5cm and >5cm in AUROC (P=0.910). The predictive scoring model based on intratumoral arteries, non-nodular type of HCC, and absence of the radiological tumor capsule on preoperative CECT is of great value in the prediction of MVI regardless of tumor size. Copyright © 2017 Elsevier B.V. All rights reserved.
Lean body mass: the development and validation of prediction equations in healthy adults
2013-01-01
Background There is a loss of lean body mass (LBM) with increasing age. A low LBM has been associated with increased adverse effects from prescribed medications such as chemotherapy. Accurate assessment of LBM may allow for more accurate drug prescribing. The aims of this study were to develop new prediction equations (PEs) for LBM with anthropometric and biochemical variables from a development cohort and then validate the best performing PEs in validation cohorts. Methods PEs were developed in a cohort of 188 healthy subjects and then validated in a convenience cohort of 52 healthy subjects. The best performing anthropometric PE was then compared to published anthropometric PEs in an older (age ≥ 50 years) cohort of 2287 people. Best subset regression analysis was used to derive PEs. Correlation, Bland-Altman and Sheiner & Beal methods were used to validate and compare the PEs against dual X-ray absorptiometry (DXA)-derived LBM. Results The PE which included biochemistry variables performed only marginally better than the anthropometric PE. The anthropometric PE on average over-estimated LBM by 0.74 kg in the combined cohort. Across gender (male vs. female), body mass index (< 22, 22- < 27, 27- < 30 and ≥30 kg/m2) and age groups (50–64, 65–79 and ≥80 years), the maximum mean over-estimation of the anthropometric PE was 1.36 kg. Conclusions A new anthropometric PE has been developed that offers an alternative for clinicians when access to DXA is limited. Further research is required to determine the clinical utility and if it will improve the safety of medication use. PMID:24499708
Pusceddu, Sara; Barretta, Francesco; Trama, Annalisa; Botta, Laura; Milione, Massimo; Buzzoni, Roberto; De Braud, Filippo; Mazzaferro, Vincenzo; Pastorino, Ugo; Seregni, Ettore; Mariani, Luigi; Gatta, Gemma; Di Bartolomeo, Maria; Femia, Daniela; Prinzi, Natalie; Coppa, Jorgelina; Panzuto, Francesco; Antonuzzo, Lorenzo; Bajetta, Emilio; Brizzi, Maria Pia; Campana, Davide; Catena, Laura; Comber, Harry; Dwane, Fiona; Fazio, Nicola; Faggiano, Antongiulio; Giuffrida, Dario; Henau, Kris; Ibrahim, Toni; Marconcini, Riccardo; Massironi, Sara; Žakelj, Maja Primic; Spada, Francesca; Tafuto, Salvatore; Van Eycken, Elizabeth; Van der Zwan, Jan Maaten; Žagar, Tina; Giacomelli, Luca; Miceli, Rosalba; Aroldi, Francesca; Bongiovanni, Alberto; Berardi, Rossana; Brighi, Nicole; Cingarlini, Sara; Cauchi, Carolina; Cavalcoli, Federica; Carnaghi, Carlo; Corti, Francesca; Duro, Marilina; Davì, Maria Vittoria; De Divitiis, Chiara; Ermacora, Paola; La Salvia, Anna; Luppi, Gabriele; Lo Russo, Giuseppe; Nichetti, Federico; Raimondi, Alessandra; Perfetti, Vittorio; Razzore, Paola; Rinzivillo, Maria; Siesling, Sabine; Torchio, Martina; Van Dijk, Boukje; Visser, Otto; Vernieri, Claudio
2018-01-01
No validated prognostic tool is available for predicting overall survival (OS) of patients with well-differentiated neuroendocrine tumors (WDNETs). This study, conducted in three independent cohorts of patients from five different European countries, aimed to develop and validate a classification prognostic score for OS in patients with stage IV WDNETs. We retrospectively collected data on 1387 patients: (i) patients treated at the Istituto Nazionale Tumori (Milan, Italy; n = 515); (ii) European cohort of rare NET patients included in the European RARECAREnet database (n = 457); (iii) Italian multicentric cohort of pancreatic NET (pNETs) patients treated at 24 Italian institutions (n = 415). The score was developed using data from patients included in cohort (i) (training set); external validation was performed by applying the score to the data of the two independent cohorts (ii) and (iii) evaluating both calibration and discriminative ability (Harrell C statistic). We used data on age, primary tumor site, metastasis (synchronous vs metachronous), Ki-67, functional status and primary surgery to build the score, which was developed for classifying patients into three groups with differential 10-year OS: (I) favorable risk group: 10-year OS ≥70%; (II) intermediate risk group: 30% ≤ 10-year OS < 70%; (III) poor risk group: 10-year OS <30%. The Harrell C statistic was 0.661 in the training set, and 0.626 and 0.601 in the RARECAREnet and Italian multicentric validation sets, respectively. In conclusion, based on the analysis of three ‘field-practice’ cohorts collected in different settings, we defined and validated a prognostic score to classify patients into three groups with different long-term prognoses. PMID:29559553
Vos-Kerkhof, Evelien de; Gomez, Borja; Milcent, Karen; Steyerberg, Ewout W; Nijman, Ruud Gerard; Smit, Frank J; Mintegi, Santiago; Moll, Henriette A; Gajdos, Vincent; Oostenbrink, Rianne
2018-05-24
To assess the diagnostic value of existing clinical prediction models (CPM; ie, statistically derived) in febrile young infants at risk for serious bacterial infections. A systematic literature review identified eight CPMs for predicting serious bacterial infections in febrile children. We validated these CPMs on four validation cohorts of febrile children in Spain (age <3 months), France (age <3 months) and two cohorts in the Netherlands (age 1-3 months and >3-12 months). We evaluated the performance of the CPMs by sensitivity/specificity, area under the receiver operating characteristic curve (AUC) and calibration studies. The original cohorts in which the prediction rules were developed (derivation cohorts) ranged from 381 to 15 781 children, with a prevalence of serious bacterial infections varying from 0.8% to 27% and spanned an age range of 0-16 years. All CPMs originally performed moderately to very well (AUC 0.60-0.93). The four validation cohorts included 159-2204 febrile children, with a median age range of 1.8 (1.2-2.4) months for the three cohorts <3 months and 8.4 (6.0-9.6) months for the cohort >3-12 months of age. The prevalence of serious bacterial infections varied between 15.1% and 17.2% in the three cohorts <3 months and was 9.8% for the cohort >3-12 months of age. Although discriminative values varied greatly, best performance was observed for four CPMs including clinical signs and symptoms, urine dipstick analyses and laboratory markers with AUC ranging from 0.68 to 0.94 in the three cohorts <3 months (ranges sensitivity: 0.48-0.94 and specificity: 0.71-0.97). For the >3-12 months' cohort AUC ranges from 0.80 to 0.89 (ranges sensitivity: 0.70-0.82 and specificity: 0.78-0.90). In general, the specificities exceeded sensitivities in our cohorts, in contrast to derivation cohorts with high sensitivities, although this effect was stronger in infants <3 months than in infants >3-12 months. We identified four CPMs, including clinical signs and symptoms, urine dipstick analysis and laboratory markers, which can aid clinicians in identifying serious bacterial infections. We suggest clinicians should use CPMs as an adjunctive clinical tool when assessing the risk of serious bacterial infections in febrile young infants. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Ali, Mohammad; You, Young Ae; Sur, Dipika; Kanungo, Suman; Kim, Deok Ryun; Deen, Jacqueline; Lopez, Anna Lena; Wierzba, Thomas F; Bhattacharya, Sujit K; Clemens, John D
2016-01-20
The test-negative design (TND) has emerged as a simple method for evaluating vaccine effectiveness (VE). Its utility for evaluating oral cholera vaccine (OCV) effectiveness is unknown. We examined this method's validity in assessing OCV effectiveness by comparing the results of TND analyses with those of conventional cohort analyses. Randomized controlled trials of OCV were conducted in Matlab (Bangladesh) and Kolkata (India), and an observational cohort design was used in Zanzibar (Tanzania). For all three studies, VE using the TND was estimated from the odds ratio (OR) relating vaccination status to fecal test status (Vibrio cholerae O1 positive or negative) among diarrheal patients enrolled during surveillance (VE= (1-OR)×100%). In cohort analyses of these studies, we employed the Cox proportional hazard model for estimating VE (=1-hazard ratio)×100%). OCV effectiveness estimates obtained using the TND (Matlab: 51%, 95% CI:37-62%; Kolkata: 67%, 95% CI:57-75%) were similar to the cohort analyses of these RCTs (Matlab: 52%, 95% CI:43-60% and Kolkata: 66%, 95% CI:55-74%). The TND VE estimate for the Zanzibar data was 94% (95% CI:84-98%) compared with 82% (95% CI:58-93%) in the cohort analysis. After adjusting for residual confounding in the cohort analysis of the Zanzibar study, using a bias indicator condition, we observed almost no difference in the two estimates. Our findings suggest that the TND is a valid approach for evaluating OCV effectiveness in routine vaccination programs. Copyright © 2015 Elsevier Ltd. All rights reserved.
Ware, Lorraine B; Zhao, Zhiguo; Koyama, Tatsuki; Brown, Ryan M; Semler, Matthew W; Janz, David R; May, Addison K; Fremont, Richard D; Matthay, Michael A; Cohen, Mitchell J; Calfee, Carolyn S
2017-01-01
Background Acute respiratory distress syndrome (ARDS) is common after severe traumatic injuries but is underdiagnosed and undertreated. We hypothesized that a panel of plasma biomarkers could be used to diagnose ARDS in severe trauma. To test this hypothesis, we derived and validated a biomarker panel in three independent cohorts and compared the diagnostic performance to clinician recognition of ARDS. Methods Eleven plasma biomarkers of inflammation, lung epithelial and endothelial injury were measured in a derivation cohort of 439 severe trauma patients. ARDS status was analyzed by two-investigator consensus, and cases were required to meet Berlin criteria on intensive care unit (ICU) day 1. Controls were subjects without ARDS during the first 4 days of study enrollment. A multivariable logistic regression model was used to generate probabilities for ARDS. A reduced model with the top two performing markers was then tested in two independent validation cohorts. To assess clinical diagnosis of ARDS, medical records in the derivation cohort were systematically searched for documentation of ARDS diagnosis made by a clinical provider. Results Among 11 biomarkers, the combination of the endothelial injury marker angiopoietin-2 (Ang-2) and the lung epithelial injury marker receptor for advanced glycation endproducts (RAGE) provided good discrimination for ARDS in the derivation cohort (area under the curve (AUC)=0.74 (95% CI 0.67 to 0.80). In the validation cohorts, the AUCs for this model were 0.70 (0.61 to 0.77) and 0.78 (0.71 to 0.84). In contrast, provider assessment demonstrated poor diagnostic accuracy for ARDS, with AUC of 0.55 (0.51 to 0.60). Discussion A two-biomarker panel consisting of Ang-2 and RAGE performed well across multiple patient cohorts and outperformed clinical providers for diagnosing ARDS in severe trauma. Clinical application of this model could improve both diagnosis and treatment of ARDS in patients with severe trauma. Level of evidence Diagnostic study, level II. PMID:29766112
Ware, Lorraine B; Zhao, Zhiguo; Koyama, Tatsuki; Brown, Ryan M; Semler, Matthew W; Janz, David R; May, Addison K; Fremont, Richard D; Matthay, Michael A; Cohen, Mitchell J; Calfee, Carolyn S
2017-01-01
Acute respiratory distress syndrome (ARDS) is common after severe traumatic injuries but is underdiagnosed and undertreated. We hypothesized that a panel of plasma biomarkers could be used to diagnose ARDS in severe trauma. To test this hypothesis, we derived and validated a biomarker panel in three independent cohorts and compared the diagnostic performance to clinician recognition of ARDS. Eleven plasma biomarkers of inflammation, lung epithelial and endothelial injury were measured in a derivation cohort of 439 severe trauma patients. ARDS status was analyzed by two-investigator consensus, and cases were required to meet Berlin criteria on intensive care unit (ICU) day 1. Controls were subjects without ARDS during the first 4 days of study enrollment. A multivariable logistic regression model was used to generate probabilities for ARDS. A reduced model with the top two performing markers was then tested in two independent validation cohorts. To assess clinical diagnosis of ARDS, medical records in the derivation cohort were systematically searched for documentation of ARDS diagnosis made by a clinical provider. Among 11 biomarkers, the combination of the endothelial injury marker angiopoietin-2 (Ang-2) and the lung epithelial injury marker receptor for advanced glycation endproducts (RAGE) provided good discrimination for ARDS in the derivation cohort (area under the curve (AUC)=0.74 (95% CI 0.67 to 0.80). In the validation cohorts, the AUCs for this model were 0.70 (0.61 to 0.77) and 0.78 (0.71 to 0.84). In contrast, provider assessment demonstrated poor diagnostic accuracy for ARDS, with AUC of 0.55 (0.51 to 0.60). A two-biomarker panel consisting of Ang-2 and RAGE performed well across multiple patient cohorts and outperformed clinical providers for diagnosing ARDS in severe trauma. Clinical application of this model could improve both diagnosis and treatment of ARDS in patients with severe trauma. Diagnostic study, level II.
Hamada, Sophie Rym; Rosa, Anne; Gauss, Tobias; Desclefs, Jean-Philippe; Raux, Mathieu; Harrois, Anatole; Follin, Arnaud; Cook, Fabrice; Boutonnet, Mathieu; Attias, Arie; Ausset, Sylvain; Boutonnet, Mathieu; Dhonneur, Gilles; Duranteau, Jacques; Langeron, Olivier; Paugam-Burtz, Catherine; Pirracchio, Romain; de St Maurice, Guillaume; Vigué, Bernard; Rouquette, Alexandra; Duranteau, Jacques
2018-05-05
Haemorrhagic shock is the leading cause of early preventable death in severe trauma. Delayed treatment is a recognized prognostic factor that can be prevented by efficient organization of care. This study aimed to develop and validate Red Flag, a binary alert identifying blunt trauma patients with high risk of severe haemorrhage (SH), to be used by the pre-hospital trauma team in order to trigger an adequate intra-hospital standardized haemorrhage control response: massive transfusion protocol and/or immediate haemostatic procedures. A multicentre retrospective study of prospectively collected data from a trauma registry (Traumabase®) was performed. SH was defined as: packed red blood cell (RBC) transfusion in the trauma room, or transfusion ≥ 4 RBC in the first 6 h, or lactate ≥ 5 mmol/L, or immediate haemostatic surgery, or interventional radiology and/or death of haemorrhagic shock. Pre-hospital characteristics were selected using a multiple logistic regression model in a derivation cohort to develop a Red Flag binary alert whose performances were confirmed in a validation cohort. Among the 3675 patients of the derivation cohort, 672 (18%) had SH. The final prediction model included five pre-hospital variables: Shock Index ≥ 1, mean arterial blood pressure ≤ 70 mmHg, point of care haemoglobin ≤ 13 g/dl, unstable pelvis and pre-hospital intubation. The Red Flag alert was triggered by the presence of any combination of at least two criteria. Its predictive performances were sensitivity 75% (72-79%), specificity 79% (77-80%) and area under the receiver operating characteristic curve 0.83 (0.81-0.84) in the derivation cohort, and were not significantly different in the independent validation cohort of 2999 patients. The Red Flag alert developed and validated in this study has high performance to accurately predict or exclude SH.
Bos, L D; Schouten, L R; van Vught, L A; Wiewel, M A; Ong, D S Y; Cremer, O; Artigas, A; Martin-Loeches, I; Hoogendijk, A J; van der Poll, T; Horn, J; Juffermans, N; Calfee, C S; Schultz, M J
2017-10-01
We hypothesised that patients with acute respiratory distress syndrome (ARDS) can be clustered based on concentrations of plasma biomarkers and that the thereby identified biological phenotypes are associated with mortality. Consecutive patients with ARDS were included in this prospective observational cohort study. Cluster analysis of 20 biomarkers of inflammation, coagulation and endothelial activation provided the phenotypes in a training cohort, not taking any outcome data into account. Logistic regression with backward selection was used to select the most predictive biomarkers, and these predicted phenotypes were validated in a separate cohort. Multivariable logistic regression was used to quantify the independent association with mortality. Two phenotypes were identified in 454 patients, which we named 'uninflamed' (N=218) and 'reactive' (N=236). A selection of four biomarkers (interleukin-6, interferon gamma, angiopoietin 1/2 and plasminogen activator inhibitor-1) could be used to accurately predict the phenotype in the training cohort (area under the receiver operating characteristics curve: 0.98, 95% CI 0.97 to 0.99). Mortality rates were 15.6% and 36.4% (p<0.001) in the training cohort and 13.6% and 37.5% (p<0.001) in the validation cohort (N=207). The 'reactive phenotype' was independent from confounders associated with intensive care unit mortality (training cohort: OR 1.13, 95% CI 1.04 to 1.23; validation cohort: OR 1.18, 95% CI 1.06 to 1.31). Patients with ARDS can be clustered into two biological phenotypes, with different mortality rates. Four biomarkers can be used to predict the phenotype with high accuracy. The phenotypes were very similar to those found in cohorts derived from randomised controlled trials, and these results may improve patient selection for future clinical trials targeting host response in patients with ARDS. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Cubiella, Joaquín; Digby, Jayne; Rodríguez-Alonso, Lorena; Vega, Pablo; Salve, María; Díaz-Ondina, Marta; Strachan, Judith A; Mowat, Craig; McDonald, Paula J; Carey, Francis A; Godber, Ian M; Younes, Hakim Ben; Rodriguez-Moranta, Francisco; Quintero, Enrique; Álvarez-Sánchez, Victoria; Fernández-Bañares, Fernando; Boadas, Jaume; Campo, Rafel; Bujanda, Luis; Garayoa, Ana; Ferrandez, Ángel; Piñol, Virginia; Rodríguez-Alcalde, Daniel; Guardiola, Jordi; Steele, Robert J C; Fraser, Callum G
2017-05-15
Prediction models for colorectal cancer (CRC) detection in symptomatic patients, based on easily obtainable variables such as fecal haemoglobin concentration (f-Hb), age and sex, may simplify CRC diagnosis. We developed, and then externally validated, a multivariable prediction model, the FAST Score, with data from five diagnostic test accuracy studies that evaluated quantitative fecal immunochemical tests in symptomatic patients referred for colonoscopy. The diagnostic accuracy of the Score in derivation and validation cohorts was compared statistically with the area under the curve (AUC) and the Chi-square test. 1,572 and 3,976 patients were examined in these cohorts, respectively. For CRC, the odds ratio (OR) of the variables included in the Score were: age (years): 1.03 (95% confidence intervals (CI): 1.02-1.05), male sex: 1.6 (95% CI: 1.1-2.3) and f-Hb (0-<20 µg Hb/g feces): 2.0 (95% CI: 0.7-5.5), (20-<200 µg Hb/g): 16.8 (95% CI: 6.6-42.0), ≥200 µg Hb/g: 65.7 (95% CI: 26.3-164.1). The AUC for CRC detection was 0.88 (95% CI: 0.85-0.90) in the derivation and 0.91 (95% CI: 0.90-093; p = 0.005) in the validation cohort. At the two Score thresholds with 90% (4.50) and 99% (2.12) sensitivity for CRC, the Score had equivalent sensitivity, although the specificity was higher in the validation cohort (p < 0.001). Accordingly, the validation cohort was divided into three groups: high (21.4% of the cohort, positive predictive value-PPV: 21.7%), intermediate (59.8%, PPV: 0.9%) and low (18.8%, PPV: 0.0%) risk for CRC. The FAST Score is an easy to calculate prediction tool, highly accurate for CRC detection in symptomatic patients. © 2017 UICC.
Bozcuk, H; Yıldız, M; Artaç, M; Kocer, M; Kaya, Ç; Ulukal, E; Ay, S; Kılıç, M P; Şimşek, E H; Kılıçkaya, P; Uçar, S; Coskun, H S; Savas, B
2015-06-01
There is clinical need to predict risk of febrile neutropenia before a specific cycle of chemotherapy in cancer patients. Data on 3882 chemotherapy cycles in 1089 consecutive patients with lung, breast, and colon cancer from four teaching hospitals were used to construct a predictive model for febrile neutropenia. A final nomogram derived from the multivariate predictive model was prospectively confirmed in a second cohort of 960 consecutive cases and 1444 cycles. The following factors were used to construct the nomogram: previous history of febrile neutropenia, pre-cycle lymphocyte count, type of cancer, cycle of current chemotherapy, and patient age. The predictive model had a concordance index of 0.95 (95 % confidence interval (CI) = 0.91-0.99) in the derivation cohort and 0.85 (95 % CI = 0.80-0.91) in the external validation cohort. A threshold of 15 % for the risk of febrile neutropenia in the derivation cohort was associated with a sensitivity of 0.76 and specificity of 0.98. These figures were 1.00 and 0.49 in the validation cohort if a risk threshold of 50 % was chosen. This nomogram is helpful in the prediction of febrile neutropenia after chemotherapy in patients with lung, breast, and colon cancer. Usage of this nomogram may help decrease the morbidity and mortality associated with febrile neutropenia and deserves further validation.
ERIC Educational Resources Information Center
Lee, Ming; Wimmers, Paul F.
2016-01-01
Although problem-based learning (PBL) has been widely used in medical schools, few studies have attended to the assessment of PBL processes using validated instruments. This study examined reliability and validity for an instrument assessing PBL performance in four domains: Problem Solving, Use of Information, Group Process, and Professionalism.…
Wang, Na-Na; Yang, Zheng-Jun; Wang, Xue; Chen, Li-Xuan; Zhao, Hong-Meng; Cao, Wen-Feng; Zhang, Bin
2018-04-25
Molecular subtype of breast cancer is associated with sentinel lymph node status. We sought to establish a mathematical prediction model that included breast cancer molecular subtype for risk of positive non-sentinel lymph nodes in breast cancer patients with sentinel lymph node metastasis and further validate the model in a separate validation cohort. We reviewed the clinicopathologic data of breast cancer patients with sentinel lymph node metastasis who underwent axillary lymph node dissection between June 16, 2014 and November 16, 2017 at our hospital. Sentinel lymph node biopsy was performed and patients with pathologically proven sentinel lymph node metastasis underwent axillary lymph node dissection. Independent risks for non-sentinel lymph node metastasis were assessed in a training cohort by multivariate analysis and incorporated into a mathematical prediction model. The model was further validated in a separate validation cohort, and a nomogram was developed and evaluated for diagnostic performance in predicting the risk of non-sentinel lymph node metastasis. Moreover, we assessed the performance of five different models in predicting non-sentinel lymph node metastasis in training cohort. Totally, 495 cases were eligible for the study, including 291 patients in the training cohort and 204 in the validation cohort. Non-sentinel lymph node metastasis was observed in 33.3% (97/291) patients in the training cohort. The AUC of MSKCC, Tenon, MDA, Ljubljana, and Louisville models in training cohort were 0.7613, 0.7142, 0.7076, 0.7483, and 0.671, respectively. Multivariate regression analysis indicated that tumor size (OR = 1.439; 95% CI 1.025-2.021; P = 0.036), sentinel lymph node macro-metastasis versus micro-metastasis (OR = 5.063; 95% CI 1.111-23.074; P = 0.036), the number of positive sentinel lymph nodes (OR = 2.583, 95% CI 1.714-3.892; P < 0.001), and the number of negative sentinel lymph nodes (OR = 0.686, 95% CI 0.575-0.817; P < 0.001) were independent statistically significant predictors of non-sentinel lymph node metastasis. Furthermore, luminal B (OR = 3.311, 95% CI 1.593-6.884; P = 0.001) and HER2 overexpression (OR = 4.308, 95% CI 1.097-16.912; P = 0.036) were independent and statistically significant predictor of non-sentinel lymph node metastasis versus luminal A. A regression model based on the results of multivariate analysis was established to predict the risk of non-sentinel lymph node metastasis, which had an AUC of 0.8188. The model was validated in the validation cohort and showed excellent diagnostic performance. The mathematical prediction model that incorporates five variables including breast cancer molecular subtype demonstrates excellent diagnostic performance in assessing the risk of non-sentinel lymph node metastasis in sentinel lymph node-positive patients. The prediction model could be of help surgeons in evaluating the risk of non-sentinel lymph node involvement for breast cancer patients; however, the model requires further validation in prospective studies.
Sailer, Verena; Holmes, Emily Eva; Gevensleben, Heidrun; Goltz, Diane; Dröge, Freya; Franzen, Alina; Dietrich, Jörn; Kristiansen, Glen; Bootz, Friedrich; Schröck, Andreas; Dietrich, Dimo
2017-01-01
Molecular biomarkers assisting risk-group assignment and subsequent treatment stratification are urgently needed for patients with squamous cell cancer of the head and neck region (HNSCC). Aberrant methylation is a frequent event in cancer and, therefore, a promising source for potential biomarkers. Here, the methylation status of the paired-like homeodomain transcription factor 3 ( PITX3 ) was evaluated in HNSCC. Using a quantitative real-time PCR, PITX3 methylation was assessed in a cohort of 326 HNSCC patients treated for localized or locally advanced disease (training cohort). The results were validated with Infinium HumanMethylation450 BeadChip data from a 528 HNSCC patient cohort (validation cohort) generated by The Cancer Genome Atlas (TCGA) Research Network. PITX3 methylation was significantly higher methylated in tumor compared to normal adjacent tissue (NAT; training cohort: median methylation NAT 32.3%, tumor 71.8%, p < 0.001; validation cohort: median methylation NAT 16.9%, tumor 35.9%, p < 0.001). PITX3 methylation was also significantly correlated with lymph node status both in the training ( p = 0.006) and validation ( p < 0.001) cohort. PITX3 methylation was significantly higher in HPV-associated (p16-positive) tumors compared to p16-negative tumors (training cohort: 73.7 vs. 66.2%, p = 0.013; validation cohort: 40.0 vs. 33.1%, p = 0.015). Hypermethylation was significantly associated with the risk of death (training cohort: hazard ratio (HR) = 1.80, [95% confidence interval (CI) 1.20-2.69], p = 0.005; validation cohort: HR = 1.43, [95% CI 1.05-1.95], p = 0.022). In multivariate Cox analyses, PITX3 added independent prognostic information. Messenger RNA (mRNA) expression analysis revealed an inverse correlation with PITX3 methylation in the TCGA cohort. PITX3 DNA methylation is an independent prognostic biomarker for overall survival in patients with HNSCC and might aid in the process of risk stratification for individualized treatment.
AXIN2 expression predicts prostate cancer recurrence and regulates invasion and tumor growth.
Hu, Brian R; Fairey, Adrian S; Madhav, Anisha; Yang, Dongyun; Li, Meng; Groshen, Susan; Stephens, Craig; Kim, Philip H; Virk, Navneet; Wang, Lina; Martin, Sue Ellen; Erho, Nicholas; Davicioni, Elai; Jenkins, Robert B; Den, Robert B; Xu, Tong; Xu, Yucheng; Gill, Inderbir S; Quinn, David I; Goldkorn, Amir
2016-05-01
Treatment of prostate cancer (PCa) may be improved by identifying biological mechanisms of tumor growth that directly impact clinical disease progression. We investigated whether genes associated with a highly tumorigenic, drug resistant, progenitor phenotype impact PCa biology and recurrence. Radical prostatectomy (RP) specimens (±disease recurrence, N = 276) were analyzed by qRT-PCR to quantify expression of genes associated with self-renewal, drug resistance, and tumorigenicity in prior studies. Associations between gene expression and PCa recurrence were confirmed by bootstrap internal validation and by external validation in independent cohorts (total N = 675) and in silico. siRNA knockdown and lentiviral overexpression were used to determine the effect of gene expression on PCa invasion, proliferation, and tumor growth. Four candidate genes were differentially expressed in PCa recurrence. Of these, low AXIN2 expression was internally validated in the discovery cohort. Validation in external cohorts and in silico demonstrated that low AXIN2 was independently associated with more aggressive PCa, biochemical recurrence, and metastasis-free survival after RP. Functionally, siRNA-mediated depletion of AXIN2 significantly increased invasiveness, proliferation, and tumor growth. Conversely, ectopic overexpression of AXIN2 significantly reduced invasiveness, proliferation, and tumor growth. Low AXIN2 expression was associated with PCa recurrence after RP in our test population as well as in external validation cohorts, and its expression levels in PCa cells significantly impacted invasiveness, proliferation, and tumor growth. Given these novel roles, further study of AXIN2 in PCa may yield promising new predictive and therapeutic strategies. © 2016 Wiley Periodicals, Inc.
Diagnosing gestational diabetes mellitus in the Danish National Birth Cohort.
Olsen, Sjurdur F; Houshmand-Oeregaard, Azedeh; Granström, Charlotta; Langhoff-Roos, Jens; Damm, Peter; Bech, Bodil H; Vaag, Allan A; Zhang, Cuilin
2017-05-01
The Danish National Birth Cohort (DNBC) contains comprehensive information on diet, lifestyle, constitutional and other major characteristics of women during pregnancy. It provides a unique source for studies on health consequences of gestational diabetes mellitus. Our aim was to identify and validate the gestational diabetes mellitus cases in the cohort. We extracted clinical information from hospital records for 1609 pregnancies included in the Danish National Birth Cohort with a diagnosis of diabetes during or before pregnancy registered in the Danish National Patient Register and/or from a Danish National Birth Cohort interview during pregnancy. We further validated the diagnosis of gestational diabetes mellitus in 2126 randomly selected pregnancies from the entire Danish National Birth Cohort. From the individual hospital records, an expert panel evaluated gestational diabetes mellitus status based on results from oral glucose tolerance tests, fasting blood glucose and Hb1c values, as well as diagnoses made by local obstetricians. The audit categorized 783 pregnancies as gestational diabetes mellitus, corresponding to 0.89% of the 87 792 pregnancies for which a pregnancy interview for self-reported diabetes in pregnancy was available. From the randomly selected group the combined information from register and interviews could correctly identify 96% (95% CI 80-99.9%) of all cases in the entire Danish National Birth Cohort population. Positive predictive value, however, was only 59% (56-61%). The combined use of data from register and interview provided a high sensitivity for gestational diabetes mellitus diagnosis. The low positive predictive value, however, suggests that systematic validation by hospital record review is essential not to underestimate the health consequences of gestational diabetes mellitus in future studies. © 2016 Nordic Federation of Societies of Obstetrics and Gynecology.
Maret-Ouda, John; Tao, Wenjing; Wahlin, Karl; Lagergren, Jesper
2017-07-01
All five Nordic countries (Denmark, Finland, Iceland, Norway and Sweden) have nationwide registries with similar data structure and validity, as well as personal identity numbers enabling linkage between registries. These resources provide opportunities for medical research that is based on large registry-based cohort studies with long and complete follow-up. This review describes practical aspects, opportunities and challenges encountered when setting up all-Nordic registry-based cohort studies. Relevant articles describing registries often used for medical research in the Nordic countries were retrieved. Further, our experiences of conducting this type of study, including planning, acquiring permissions, data retrieval and data cleaning and handling, and the possibilities and challenges we have encountered are described. Combining data from the Nordic countries makes it possible to create large and powerful cohorts. The main challenges include obtaining all permissions within each country, usually in the local language, and retrieving the data. These challenges emphasise the importance of having experienced collaborators within each country. Following the acquisition of data, data management requires the understanding of the differences between the variables to be used in the various countries. A concern is the long time required between initiation and completion. Nationwide Nordic registries can be combined into cohorts with high validity and statistical power, but the considerable expertise, workload and time required to complete such cohorts should not be underestimated.
PRRT genomic signature in blood for prediction of 177Lu-octreotate efficacy.
Bodei, Lisa; Kidd, Mark S; Singh, Aviral; van der Zwan, Wouter A; Severi, Stefano; Drozdov, Ignat A; Cwikla, Jaroslaw; Baum, Richard P; Kwekkeboom, Dik J; Paganelli, Giovanni; Krenning, Eric P; Modlin, Irvin M
2018-07-01
Peptide receptor radionuclide therapy (PRRT) utilizes somatostatin receptor (SSR) overexpression on neuroendocrine tumors (NET) to deliver targeted radiotherapy. Intensity of uptake at imaging is considered related to efficacy but has low sensitivity. A pretreatment strategy to determine individual PRRT response remains a key unmet need. NET transcript expression in blood integrated with tumor grade provides a PRRT predictive quotient (PPQ) which stratifies PRRT "responders" from "non-responders". This study clinically validates the utility of the PPQ in NETs. The development and validation of the PPQ was undertaken in three independent 177 Lu-PRRT treated cohorts. Specificity was tested in two separate somatostatin analog-treated cohorts. Prognostic value of the marker was defined in a cohort of untreated patients. The developmental cohort included lung and gastroenteropancreatic [GEP] NETs (n = 72) from IRST Meldola, Italy. The majority were GEP (71%) and low grade (86% G1-G2). Prospective validation cohorts were from Zentralklinik Bad Berka, Germany (n = 44), and Erasmus Medical Center, Rotterdam, Netherlands (n = 42). Each cohort included predominantly well differentiated, low grade (86-95%) lung and GEP-NETs. The non-PRRT comparator cohorts included SSA cohort I, n = 28 (100% low grade, 100% GEP-NET); SSA cohort II, n = 51 (98% low grade; 76% GEP-NET); and an untreated cohort, n = 44 (64% low grade; 91% GEP-NET). Baseline evaluations included clinical information (disease status, grade, SSR) and biomarker (CgA). NET blood gene transcripts (n = 8: growth factor signaling and metabolism) were measured pre-therapy and integrated with tumor Ki67 using a logistic regression model. This provided a binary output: "predicted responder" (PPQ+); "predicted non-responder" (PPQ-). Treatment response was evaluated using RECIST criteria [Responder (stable, partial and complete response) vs Non-Responder)]. Sample measurement and analyses were blinded to study outcome. Statistical evaluation included Kaplan-Meier survival and standard test evaluation analyses. In the developmental cohort, 56% responded to PRRT. The PPQ predicted 100% of responders and 84% of non-responders (accuracy: 93%). In the two validation cohorts (response: 64-79%), the PPQ was 95% accurate (Bad Berka: PPQ + =97%, PPQ- = 93%; Rotterdam: PPQ + =94%, PPQ- = 100%). Overall, the median PFS was not reached in PPQ+ vs PPQ- (10-14 months; HR: 18-77, p < 0.0001). In the comparator cohorts, the predictor (PPQ) was 47-50% accurate for SSA-treatment and 50% as a prognostic. No differences in PFS were respectively noted (PPQ+: 10-12 months vs. PPQ-: 9-15 months). The PPQ derived from circulating NET specific genes and tumor grade prior to the initiation of therapy is a highly specific predictor of the efficacy of PRRT with an accuracy of 95%.
An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.
Nemati, Shamim; Holder, Andre; Razmi, Fereshteh; Stanley, Matthew D; Clifford, Gari D; Buchman, Timothy G
2018-04-01
Sepsis is among the leading causes of morbidity, mortality, and cost overruns in critically ill patients. Early intervention with antibiotics improves survival in septic patients. However, no clinically validated system exists for real-time prediction of sepsis onset. We aimed to develop and validate an Artificial Intelligence Sepsis Expert algorithm for early prediction of sepsis. Observational cohort study. Academic medical center from January 2013 to December 2015. Over 31,000 admissions to the ICUs at two Emory University hospitals (development cohort), in addition to over 52,000 ICU patients from the publicly available Medical Information Mart for Intensive Care-III ICU database (validation cohort). Patients who met the Third International Consensus Definitions for Sepsis (Sepsis-3) prior to or within 4 hours of their ICU admission were excluded, resulting in roughly 27,000 and 42,000 patients within our development and validation cohorts, respectively. None. High-resolution vital signs time series and electronic medical record data were extracted. A set of 65 features (variables) were calculated on hourly basis and passed to the Artificial Intelligence Sepsis Expert algorithm to predict onset of sepsis in the proceeding T hours (where T = 12, 8, 6, or 4). Artificial Intelligence Sepsis Expert was used to predict onset of sepsis in the proceeding T hours and to produce a list of the most significant contributing factors. For the 12-, 8-, 6-, and 4-hour ahead prediction of sepsis, Artificial Intelligence Sepsis Expert achieved area under the receiver operating characteristic in the range of 0.83-0.85. Performance of the Artificial Intelligence Sepsis Expert on the development and validation cohorts was indistinguishable. Using data available in the ICU in real-time, Artificial Intelligence Sepsis Expert can accurately predict the onset of sepsis in an ICU patient 4-12 hours prior to clinical recognition. A prospective study is necessary to determine the clinical utility of the proposed sepsis prediction model.
Bösner, Stefan; Haasenritter, Jörg; Becker, Annette; Karatolios, Konstantinos; Vaucher, Paul; Gencer, Baris; Herzig, Lilli; Heinzel-Gutenbrunner, Monika; Schaefer, Juergen R; Abu Hani, Maren; Keller, Heidi; Sönnichsen, Andreas C; Baum, Erika; Donner-Banzhoff, Norbert
2010-09-07
Chest pain can be caused by various conditions, with life-threatening cardiac disease being of greatest concern. Prediction scores to rule out coronary artery disease have been developed for use in emergency settings. We developed and validated a simple prediction rule for use in primary care. We conducted a cross-sectional diagnostic study in 74 primary care practices in Germany. Primary care physicians recruited all consecutive patients who presented with chest pain (n = 1249) and recorded symptoms and findings for each patient (derivation cohort). An independent expert panel reviewed follow-up data obtained at six weeks and six months on symptoms, investigations, hospital admissions and medications to determine the presence or absence of coronary artery disease. Adjusted odds ratios of relevant variables were used to develop a prediction rule. We calculated measures of diagnostic accuracy for different cut-off values for the prediction scores using data derived from another prospective primary care study (validation cohort). The prediction rule contained five determinants (age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation), with the score ranging from 0 to 5 points. The area under the curve (receiver operating characteristic curve) was 0.87 (95% confidence interval [CI] 0.83-0.91) for the derivation cohort and 0.90 (95% CI 0.87-0.93) for the validation cohort. The best overall discrimination was with a cut-off value of 3 (positive result 3-5 points; negative result
Hippisley-Cox, Julia; Coupland, Carol
2015-01-01
Objective To derive and validate a set of clinical risk prediction algorithm to estimate the 10-year risk of 11 common cancers. Design Prospective open cohort study using routinely collected data from 753 QResearch general practices in England. We used 565 practices to develop the scores and 188 for validation. Subjects 4.96 million patients aged 25–84 years in the derivation cohort; 1.64 million in the validation cohort. Patients were free of the relevant cancer at baseline. Methods Cox proportional hazards models in the derivation cohort to derive 10-year risk algorithms. Risk factors considered included age, ethnicity, deprivation, body mass index, smoking, alcohol, previous cancer diagnoses, family history of cancer, relevant comorbidities and medication. Measures of calibration and discrimination in the validation cohort. Outcomes Incident cases of blood, breast, bowel, gastro-oesophageal, lung, oral, ovarian, pancreas, prostate, renal tract and uterine cancers. Cancers were recorded on any one of four linked data sources (general practitioner (GP), mortality, hospital or cancer records). Results We identified 228 241 incident cases during follow-up of the 11 types of cancer. Of these 25 444 were blood; 41 315 breast; 32 626 bowel, 12 808 gastro-oesophageal; 32 187 lung; 4811 oral; 6635 ovarian; 7119 pancreatic; 35 256 prostate; 23 091 renal tract; 6949 uterine cancers. The lung cancer algorithm had the best performance with an R2 of 64.2%; D statistic of 2.74; receiver operating characteristic curve statistic of 0.91 in women. The sensitivity for the top 10% of women at highest risk of lung cancer was 67%. Performance of the algorithms in men was very similar to that for women. Conclusions We have developed and validated a prediction models to quantify absolute risk of 11 common cancers. They can be used to identify patients at high risk of cancers for prevention or further assessment. The algorithms could be integrated into clinical computer systems and used to identify high-risk patients. Web calculator: There is a simple web calculator to implement the Qcancer 10 year risk algorithm together with the open source software for download (available at http://qcancer.org/10yr/). PMID:25783428
Holden, Libby; Lee, Christina; Hockey, Richard; Ware, Robert S; Dobson, Annette J
2014-12-01
This study aimed to validate a 6-item 1-factor global measure of social support developed from the Medical Outcomes Study Social Support Survey (MOS-SSS) for use in large epidemiological studies. Data were obtained from two large population-based samples of participants in the Australian Longitudinal Study on Women's Health. The two cohorts were aged 53-58 and 28-33 years at data collection (N = 10,616 and 8,977, respectively). Items selected for the 6-item 1-factor measure were derived from the factor structure obtained from unpublished work using an earlier wave of data from one of these cohorts. Descriptive statistics, including polychoric correlations, were used to describe the abbreviated scale. Cronbach's alpha was used to assess internal consistency and confirmatory factor analysis to assess scale validity. Concurrent validity was assessed using correlations between the new 6-item version and established 19-item version, and other concurrent variables. In both cohorts, the new 6-item 1-factor measure showed strong internal consistency and scale reliability. It had excellent goodness-of-fit indices, similar to those of the established 19-item measure. Both versions correlated similarly with concurrent measures. The 6-item 1-factor MOS-SSS measures global functional social support with fewer items than the established 19-item measure.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mbah, Chamberlain, E-mail: chamberlain.mbah@ugent.be; Department of Mathematical Modeling, Statistics, and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent; Thierens, Hubert
Purpose: To identify the main causes underlying the failure of prediction models for radiation therapy toxicity to replicate. Methods and Materials: Data were used from two German cohorts, Individual Radiation Sensitivity (ISE) (n=418) and Mammary Carcinoma Risk Factor Investigation (MARIE) (n=409), of breast cancer patients with similar characteristics and radiation therapy treatments. The toxicity endpoint chosen was telangiectasia. The LASSO (least absolute shrinkage and selection operator) logistic regression method was used to build a predictive model for a dichotomized endpoint (Radiation Therapy Oncology Group/European Organization for the Research and Treatment of Cancer score 0, 1, or ≥2). Internal areas undermore » the receiver operating characteristic curve (inAUCs) were calculated by a naïve approach whereby the training data (ISE) were also used for calculating the AUC. Cross-validation was also applied to calculate the AUC within the same cohort, a second type of inAUC. Internal AUCs from cross-validation were calculated within ISE and MARIE separately. Models trained on one dataset (ISE) were applied to a test dataset (MARIE) and AUCs calculated (exAUCs). Results: Internal AUCs from the naïve approach were generally larger than inAUCs from cross-validation owing to overfitting the training data. Internal AUCs from cross-validation were also generally larger than the exAUCs, reflecting heterogeneity in the predictors between cohorts. The best models with largest inAUCs from cross-validation within both cohorts had a number of common predictors: hypertension, normalized total boost, and presence of estrogen receptors. Surprisingly, the effect (coefficient in the prediction model) of hypertension on telangiectasia incidence was positive in ISE and negative in MARIE. Other predictors were also not common between the 2 cohorts, illustrating that overcoming overfitting does not solve the problem of replication failure of prediction models completely. Conclusions: Overfitting and cohort heterogeneity are the 2 main causes of replication failure of prediction models across cohorts. Cross-validation and similar techniques (eg, bootstrapping) cope with overfitting, but the development of validated predictive models for radiation therapy toxicity requires strategies that deal with cohort heterogeneity.« less
Ma, Hon Ming; Ip, Margaret; Woo, Jean; Hui, David S C
2014-05-01
Health care-associated pneumonia (HCAP) and drug-resistant bacterial pneumonia may not share identical risk factors. We have shown that bronchiectasis, recent hospitalization and severe pneumonia (confusion, blood urea level, respiratory rate, low blood pressure and 65 year old (CURB-65) score ≥ 3) were independent predictors of pneumonia caused by potentially drug-resistant (PDR) pathogens. This study aimed to develop and validate a clinical risk score for predicting drug-resistant bacterial pneumonia in older patients. We derived a risk score by assigning a weighting to each of these risk factors as follows: 14, bronchiectasis; 5, recent hospitalization; 2, severe pneumonia. A 0.5 point was defined for the presence of other risk factors for HCAP. We compared the areas under the receiver-operating characteristics curve (AUROC) of our risk score and the HCAP definition in predicting PDR pathogens in two cohorts of older patients hospitalized with non-nosocomial pneumonia. The derivation and validation cohorts consisted of 354 and 96 patients with bacterial pneumonia, respectively. PDR pathogens were isolated in 48 and 21 patients in the derivation and validation cohorts, respectively. The AUROCs of our risk score and the HCAP definition were 0.751 and 0.650, respectively, in the derivation cohort, and were 0.782 and 0.671, respectively, in the validation cohort. The differences between our risk score and the HCAP definition reached statistical significance. A score ≥ 2.5 had the best balance between sensitivity and specificity. Our risk score outperformed the HCAP definition to predict pneumonia caused by PDR pathogens. A history of bronchiectasis or recent hospitalization is the major indication of starting empirical broad-spectrum antibiotics. © 2014 Asian Pacific Society of Respirology.
Antic, Darko; Milic, Natasa; Nikolovski, Srdjan; Todorovic, Milena; Bila, Jelena; Djurdjevic, Predrag; Andjelic, Bosko; Djurasinovic, Vladislava; Sretenovic, Aleksandra; Vukovic, Vojin; Jelicic, Jelena; Hayman, Suzanne; Mihaljevic, Biljana
2016-10-01
Lymphoma patients are at increased risk of thromboembolic events but thromboprophylaxis in these patients is largely underused. We sought to develop and validate a simple model, based on individual clinical and laboratory patient characteristics that would designate lymphoma patients at risk for thromboembolic event. The study population included 1,820 lymphoma patients who were treated in the Lymphoma Departments at the Clinics of Hematology, Clinical Center of Serbia and Clinical Center Kragujevac. The model was developed using data from a derivation cohort (n = 1,236), and further assessed in the validation cohort (n = 584). Sixty-five patients (5.3%) in the derivation cohort and 34 (5.8%) patients in the validation cohort developed thromboembolic events. The variables independently associated with risk for thromboembolism were: previous venous and/or arterial events, mediastinal involvement, BMI>30 kg/m(2) , reduced mobility, extranodal localization, development of neutropenia and hemoglobin level < 100g/L. Based on the risk model score, the population was divided into the following risk categories: low (score 0-1), intermediate (score 2-3), and high (score >3). For patients classified at risk (intermediate and high-risk scores), the model produced negative predictive value of 98.5%, positive predictive value of 25.1%, sensitivity of 75.4%, and specificity of 87.5%. A high-risk score had positive predictive value of 65.2%. The diagnostic performance measures retained similar values in the validation cohort. Developed prognostic Thrombosis Lymphoma - ThroLy score is more specific for lymphoma patients than any other available score targeting thrombosis in cancer patients. Am. J. Hematol. 91:1014-1019, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Novel risk score of contrast-induced nephropathy after percutaneous coronary intervention.
Ji, Ling; Su, XiaoFeng; Qin, Wei; Mi, XuHua; Liu, Fei; Tang, XiaoHong; Li, Zi; Yang, LiChuan
2015-08-01
Contrast-induced nephropathy (CIN) post-percutaneous coronary intervention (PCI) is a major cause of acute kidney injury. In this study, we established a comprehensive risk score model to assess risk of CIN after PCI procedure, which could be easily used in a clinical environment. A total of 805 PCI patients, divided into analysis cohort (70%) and validation cohort (30%), were enrolled retrospectively in this study. Risk factors for CIN were identified using univariate analysis and multivariate logistic regression in the analysis cohort. Risk score model was developed based on multiple regression coefficients. Sensitivity and specificity of the new risk score system was validated in the validation cohort. Comparisons between the new risk score model and previous reported models were applied. The incidence of post-PCI CIN in the analysis cohort (n = 565) was 12%. Considerably high CIN incidence (50%) was observed in patients with chronic kidney disease (CKD). Age >75, body mass index (BMI) >25, myoglobin level, cardiac function level, hypoalbuminaemia, history of chronic kidney disease (CKD), Intra-aortic balloon pump (IABP) and peripheral vascular disease (PVD) were identified as independent risk factors of post-PCI CIN. A novel risk score model was established using multivariate regression coefficients, which showed highest sensitivity and specificity (0.917, 95%CI 0.877-0.957) compared with previous models. A new post-PCI CIN risk score model was developed based on a retrospective study of 805 patients. Application of this model might be helpful to predict CIN in patients undergoing PCI procedure. © 2015 Asian Pacific Society of Nephrology.
Esplen, Mary Jane; Cappelli, Mario; Wong, Jiahui; Bottorff, Joan L; Hunter, Jon; Carroll, June; Dorval, Michel; Wilson, Brenda; Allanson, Judith; Semotiuk, Kara; Aronson, Melyssa; Bordeleau, Louise; Charlemagne, Nicole; Meschino, Wendy
2013-01-01
Objectives To develop a brief, reliable and valid instrument to screen psychosocial risk among those who are undergoing genetic testing for Adult-Onset Hereditary Disease (AOHD). Design A prospective two-phase cohort study. Setting 5 genetic testing centres for AOHD, such as cancer, Huntington's disease or haemochromatosis, in ambulatory clinics of tertiary hospitals across Canada. Participants 141 individuals undergoing genetic testing were approached and consented to the instrument development phase of the study (Phase I). The Genetic Psychosocial Risk Instrument (GPRI) developed in Phase I was tested in Phase II for item refinement and validation. A separate cohort of 722 individuals consented to the study, 712 completed the baseline package and 463 completed all follow-up assessments. Most participants were female, at the mid-life stage. Individuals in advanced stages of the illness or with cognitive impairment or a language barrier were excluded. Interventions Phase I: GPRI items were generated from (1) a review of the literature, (2) input from genetic counsellors and (3) phase I participants. Phase II: further item refinement and validation were conducted with a second cohort of participants who completed the GPRI at baseline and were followed for psychological distress 1-month postgenetic testing results. Primary and secondary outcome measures GPRI, Hamilton Depression Rating Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A), Brief Symptom Inventory (BSI) and Impact of Event Scale (IES). Results The final 20-item GPRI had a high reliability—Cronbach's α at 0.81. The construct validity was supported by high correlations between GPRI and BSI and IES. The predictive value was demonstrated by a receiver operating characteristic curve of 0.78 plotting GPRI against follow-up assessments using HAM-D and HAM-A. Conclusions With a cut-off score of 50, GPRI identified 84% of participants who displayed distress postgenetic testing results, supporting its potential usefulness in a clinical setting. PMID:23485718
Kim, Hyun-Duck; Sukhbaatar, Munkhzaya; Shin, Myungseop; Ahn, Yoo-Been; Yoo, Wook-Sung
2014-12-01
This study aims to evaluate and validate a periodontitis screening model that includes sociodemographic, metabolic syndrome (MetS), and molecular information, including gingival crevicular fluid (GCF), matrix metalloproteinase (MMP), and blood cytokines. The authors selected 506 participants from the Shiwha-Banwol cohort: 322 participants from the 2005 cohort for deriving the screening model and 184 participants from the 2007 cohort for its validation. Periodontitis was assessed by dentists using the community periodontal index. Interleukin (IL)-6, IL-8, and tumor necrosis factor-α in blood and MMP-8, -9, and -13 in GCF were assayed using enzyme-linked immunosorbent assay. MetS was assessed by physicians using physical examination and blood laboratory data. Information about age, sex, income, smoking, and drinking was obtained by interview. Logistic regression analysis was applied to finalize the best-fitting model and validate the model using sensitivity, specificity, and c-statistics. The derived model for periodontitis screening had a sensitivity of 0.73, specificity of 0.85, and c-statistic of 0.86 (P <0.001); those of the validated model were 0.64, 0.91, and 0.83 (P <0.001), respectively. The model that included age, sex, income, smoking, drinking, and blood and GCF biomarkers could be useful in screening for periodontitis. A future prospective study is indicated for evaluating this model's ability to predict the occurrence of periodontitis.
Stoll, C; Kapfhammer, H P; Rothenhäusler, H B; Haller, M; Briegel, J; Schmidt, M; Krauseneck, T; Durst, K; Schelling, G
1999-07-01
Many survivors of critical illness and intensive care unit (ICU) treatment have traumatic memories such as nightmares, panic or pain which can be associated with the development of posttraumatic stress disorder (PTSD). In order to simplify the rapid and early detection of PTSD in such patients, we modified an existing questionnaire for diagnosis of PTSD and validated the instrument in a cohort of ARDS patients after long-term ICU therapy. Follow-up cohort study. The 20-bed ICU of a university teaching hospital. A cohort of 52 long-term survivors of the acute respiratory distress syndrome (ARDS). The questionnaire was administered to the study cohort at two time points 2 years apart. At the second evaluation, the patients underwent a structured interview with two trained psychiatrists to diagnose PTSD according to Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) criteria. The reliability and validity of the questionnaire was then estimated and its specificity, sensitivity and optimal decision threshold determined using receiver operating characteristic (ROC) curve analyses. The questionnaire showed a high internal consistency (Crohnbach's alpha = 0.93) and a high test-retest reliability (intraclass correlation coefficient alpha = 0.89). There was evidence of construct validity by a linear relationship between scores and the number of traumatic memories from the ICU the patients described (Spearman's rho = 0.48, p < 0.01). Criterion validity was demonstrated by ROC curve analyses resulting in a sensitivity of 77.0% and a specificity of 97.5% for the diagnosis of PTSD. The questionnaire was found to be a responsive, valid and reliable instrument to screen survivors of intensive care for PTSD.
Forzley, Brian; Er, Lee; Chiu, Helen Hl; Djurdjev, Ognjenka; Martinusen, Dan; Carson, Rachel C; Hargrove, Gaylene; Levin, Adeera; Karim, Mohamud
2018-02-01
End-stage kidney disease is associated with poor prognosis. Health care professionals must be prepared to address end-of-life issues and identify those at high risk for dying. A 6-month mortality prediction model for patients on dialysis derived in the United States is used but has not been externally validated. We aimed to assess the external validity and clinical utility in an independent cohort in Canada. We examined the performance of the published 6-month mortality prediction model, using discrimination, calibration, and decision curve analyses. Data were derived from a cohort of 374 prevalent dialysis patients in two regions of British Columbia, Canada, which included serum albumin, age, peripheral vascular disease, dementia, and answers to the "the surprise question" ("Would I be surprised if this patient died within the next year?"). The observed mortality in the validation cohort was 11.5% at 6 months. The prediction model had reasonable discrimination (c-stat = 0.70) but poor calibration (calibration-in-the-large = -0.53 (95% confidence interval: -0.88, -0.18); calibration slope = 0.57 (95% confidence interval: 0.31, 0.83)) in our data. Decision curve analysis showed the model only has added value in guiding clinical decision in a small range of threshold probabilities: 8%-20%. Despite reasonable discrimination, the prediction model has poor calibration in this external study cohort; thus, it may have limited clinical utility in settings outside of where it was derived. Decision curve analysis clarifies limitations in clinical utility not apparent by receiver operating characteristic curve analysis. This study highlights the importance of external validation of prediction models prior to routine use in clinical practice.
Chromatin organisation and cancer prognosis: a pan-cancer study.
Kleppe, Andreas; Albregtsen, Fritz; Vlatkovic, Ljiljana; Pradhan, Manohar; Nielsen, Birgitte; Hveem, Tarjei S; Askautrud, Hanne A; Kristensen, Gunnar B; Nesbakken, Arild; Trovik, Jone; Wæhre, Håkon; Tomlinson, Ian; Shepherd, Neil A; Novelli, Marco; Kerr, David J; Danielsen, Håvard E
2018-03-01
Chromatin organisation affects gene expression and regional mutation frequencies and contributes to carcinogenesis. Aberrant organisation of DNA has been correlated with cancer prognosis in analyses of the chromatin component of tumour cell nuclei using image texture analysis. As yet, the methodology has not been sufficiently validated to permit its clinical application. We aimed to define and validate a novel prognostic biomarker for the automatic detection of heterogeneous chromatin organisation. Machine learning algorithms analysed the chromatin organisation in 461 000 images of tumour cell nuclei stained for DNA from 390 patients (discovery cohort) treated for stage I or II colorectal cancer at the Aker University Hospital (Oslo, Norway). The resulting marker of chromatin heterogeneity, termed Nucleotyping, was subsequently independently validated in six patient cohorts: 442 patients with stage I or II colorectal cancer in the Gloucester Colorectal Cancer Study (UK); 391 patients with stage II colorectal cancer in the QUASAR 2 trial; 246 patients with stage I ovarian carcinoma; 354 patients with uterine sarcoma; 307 patients with prostate carcinoma; and 791 patients with endometrial carcinoma. The primary outcome was cancer-specific survival. In all patient cohorts, patients with chromatin heterogeneous tumours had worse cancer-specific survival than patients with chromatin homogeneous tumours (univariable analysis hazard ratio [HR] 1·7, 95% CI 1·2-2·5, in the discovery cohort; 1·8, 1·0-3·0, in the Gloucester validation cohort; 2·2, 1·1-4·5, in the QUASAR 2 validation cohort; 3·1, 1·9-5·0, in the ovarian carcinoma cohort; 2·5, 1·8-3·4, in the uterine sarcoma cohort; 2·3, 1·2-4·6, in the prostate carcinoma cohort; and 4·3, 2·8-6·8, in the endometrial carcinoma cohort). After adjusting for established prognostic patient characteristics in multivariable analyses, Nucleotyping was prognostic in all cohorts except for the prostate carcinoma cohort (HR 1·7, 95% CI 1·1-2·5, in the discovery cohort; 1·9, 1·1-3·2, in the Gloucester validation cohort; 2·6, 1·2-5·6, in the QUASAR 2 cohort; 1·8, 1·1-3·0, for ovarian carcinoma; 1·6, 1·0-2·4, for uterine sarcoma; 1·43, 0·68-2·99, for prostate carcinoma; and 1·9, 1·1-3·1, for endometrial carcinoma). Chromatin heterogeneity was a significant predictor of cancer-specific survival in microsatellite unstable (HR 2·9, 95% CI 1·0-8·4) and microsatellite stable (1·8, 1·2-2·7) stage II colorectal cancer, but microsatellite instability was not a significant predictor of outcome in chromatin homogeneous (1·3, 0·7-2·4) or chromatin heterogeneous (0·8, 0·3-2·0) stage II colorectal cancer. The consistent prognostic prediction of Nucleotyping in different biological and technical circumstances suggests that the marker of chromatin heterogeneity can be reliably assessed in routine clinical practice and could be used to objectively assist decision making in a range of clinical settings. An immediate application would be to identify high-risk patients with stage II colorectal cancer who might have greater absolute benefit from adjuvant chemotherapy. Clinical trials are warranted to evaluate the survival benefit and cost-effectiveness of using Nucleotyping to guide treatment decisions in multiple clinical settings. The Research Council of Norway, the South-Eastern Norway Regional Health Authority, the National Institute for Health Research, and the Wellcome Trust. Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC-BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.
Citrin, Rebecca; Horowitz, Joseph P; Reilly, Anne F; Li, Yimei; Huang, Yuan-Shung; Getz, Kelly D; Seif, Alix E; Fisher, Brian T; Aplenc, Richard
2017-01-01
Mature B-cell non-Hodgkin lymphoma (B-NHL) constitutes a collection of relatively rare pediatric malignancies. In order to utilize administrative data to perform large-scale epidemiologic studies within this population, a two-step process was used to assemble a 12-year cohort of B-NHL patients treated between 2004 and 2015 within the Pediatric Health Information System database. Patients were identified by ICD-9 codes, and their chemotherapy data were then manually reviewed against standard B-NHL treatment regimens. A total of 1,409 patients were eligible for cohort inclusion. This process was validated at a single center, utilizing both an institutional tumor registry and medical record review as the gold standards. The validation demonstrated appropriate sensitivity (91.5%) and positive predictive value (95.1%) to allow for the future use of this cohort for epidemiologic and comparative effectiveness research.
Such, Esperanza; Germing, Ulrich; Malcovati, Luca; Cervera, José; Kuendgen, Andrea; Della Porta, Matteo G; Nomdedeu, Benet; Arenillas, Leonor; Luño, Elisa; Xicoy, Blanca; Amigo, Mari L; Valcarcel, David; Nachtkamp, Kathrin; Ambaglio, Ilaria; Hildebrandt, Barbara; Lorenzo, Ignacio; Cazzola, Mario; Sanz, Guillermo
2013-04-11
The natural course of chronic myelomonocytic leukemia (CMML) is highly variable but a widely accepted prognostic scoring system for patients with CMML is not available. The main aim of this study was to develop a new CMML-specific prognostic scoring system (CPSS) in a large series of 558 patients with CMML (training cohort, Spanish Group of Myelodysplastic Syndromes) and to validate it in an independent series of 274 patients (validation cohort, Heinrich Heine University Hospital, Düsseldorf, Germany, and San Matteo Hospital, Pavia, Italy). The most relevant variables for overall survival (OS) and evolution to acute myeloblastic leukemia (AML) were FAB and WHO CMML subtypes, CMML-specific cytogenetic risk classification, and red blood cell (RBC) transfusion dependency. CPSS was able to segregate patients into 4 clearly different risk groups for OS (P < .001) and risk of AML evolution (P < .001) and its predictive capability was confirmed in the validation cohort. An alternative CPSS with hemoglobin instead of RBC transfusion dependency offered almost identical prognostic capability. This study confirms the prognostic impact of FAB and WHO subtypes, recognizes the importance of RBC transfusion dependency and cytogenetics, and offers a simple and powerful CPSS for accurately assessing prognosis and planning therapy in patients with CMML.
Vuong, Kylie; Armstrong, Bruce K; Weiderpass, Elisabete; Lund, Eiliv; Adami, Hans-Olov; Veierod, Marit B; Barrett, Jennifer H; Davies, John R; Bishop, D Timothy; Whiteman, David C; Olsen, Catherine M; Hopper, John L; Mann, Graham J; Cust, Anne E; McGeechan, Kevin
2016-08-01
Identifying individuals at high risk of melanoma can optimize primary and secondary prevention strategies. To develop and externally validate a risk prediction model for incident first-primary cutaneous melanoma using self-assessed risk factors. We used unconditional logistic regression to develop a multivariable risk prediction model. Relative risk estimates from the model were combined with Australian melanoma incidence and competing mortality rates to obtain absolute risk estimates. A risk prediction model was developed using the Australian Melanoma Family Study (629 cases and 535 controls) and externally validated using 4 independent population-based studies: the Western Australia Melanoma Study (511 case-control pairs), Leeds Melanoma Case-Control Study (960 cases and 513 controls), Epigene-QSkin Study (44 544, of which 766 with melanoma), and Swedish Women's Lifestyle and Health Cohort Study (49 259 women, of which 273 had melanoma). We validated model performance internally and externally by assessing discrimination using the area under the receiver operating curve (AUC). Additionally, using the Swedish Women's Lifestyle and Health Cohort Study, we assessed model calibration and clinical usefulness. The risk prediction model included hair color, nevus density, first-degree family history of melanoma, previous nonmelanoma skin cancer, and lifetime sunbed use. On internal validation, the AUC was 0.70 (95% CI, 0.67-0.73). On external validation, the AUC was 0.66 (95% CI, 0.63-0.69) in the Western Australia Melanoma Study, 0.67 (95% CI, 0.65-0.70) in the Leeds Melanoma Case-Control Study, 0.64 (95% CI, 0.62-0.66) in the Epigene-QSkin Study, and 0.63 (95% CI, 0.60-0.67) in the Swedish Women's Lifestyle and Health Cohort Study. Model calibration showed close agreement between predicted and observed numbers of incident melanomas across all deciles of predicted risk. In the external validation setting, there was higher net benefit when using the risk prediction model to classify individuals as high risk compared with classifying all individuals as high risk. The melanoma risk prediction model performs well and may be useful in prevention interventions reliant on a risk assessment using self-assessed risk factors.
Zafar, Farhan; Jaquiss, Robert D; Almond, Christopher S; Lorts, Angela; Chin, Clifford; Rizwan, Raheel; Bryant, Roosevelt; Tweddell, James S; Morales, David L S
2018-03-01
In this study we sought to quantify hazards associated with various donor factors into a cumulative risk scoring system (the Pediatric Heart Donor Assessment Tool, or PH-DAT) to predict 1-year mortality after pediatric heart transplantation (PHT). PHT data with complete donor information (5,732) were randomly divided into a derivation cohort and a validation cohort (3:1). From the derivation cohort, donor-specific variables associated with 1-year mortality (exploratory p-value < 0.2) were incorporated into a multivariate logistic regression model. Scores were assigned to independent predictors (p < 0.05) based on relative odds ratios (ORs). The final model had an acceptable predictive value (c-statistic = 0.62). The significant 5 variables (ischemic time, stroke as the cause of death, donor-to-recipient height ratio, donor left ventricular ejection fraction, glomerular filtration rate) were used for the scoring system. The validation cohort demonstrated a strong correlation between the observed and expected rates of 1-year mortality (r = 0.87). The risk of 1-year mortality increases by 11% (OR 1.11 [1.08 to 1.14]; p < 0.001) in the derivation cohort and 9% (OR 1.09 [1.04 to 1.14]; p = 0.001) in the validation cohort with an increase of 1-point in score. Mortality risk increased 5 times from the lowest to the highest donor score in this cohort. Based on this model, a donor score range of 10 to 28 predicted 1-year recipient mortality of 11% to 31%. This novel pediatric-specific, donor risk scoring system appears capable of predicting post-transplant mortality. Although the PH-DAT may benefit organ allocation and assessment of recipient risk while controlling for donor risk, prospective validation of this model is warranted. Copyright © 2018 International Society for the Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.
Qiu, Jiliang; Peng, Baogang; Tang, Yunqiang; Qian, Yeben; Guo, Pi; Li, Mengfeng; Luo, Junhang; Chen, Bin; Tang, Hui; Lu, Canliang; Cai, Muyan; Ke, Zunfu; He, Wei; Zheng, Yun; Xie, Dan; Li, Binkui; Yuan, Yunfei
2017-03-01
Purpose Early-stage hepatocellular carcinoma (E-HCC) is being diagnosed increasingly, and in one half of diagnosed patients, recurrence will develop. Thus, it is urgent to identify recurrence-related markers. We investigated the effectiveness of CpG methylation in predicting recurrence for patients with E-HCCs. Patients and Methods In total, 576 patients with E-HCC from four independent centers were sorted by three phases. In the discovery phase, 66 tumor samples were analyzed using the Illumina Methylation 450k Beadchip. Two algorithms, Least Absolute Shrinkage and Selector Operation and Support Vector Machine-Recursive Feature Elimination, were used to select significant CpGs. In the training phase, penalized Cox regression was used to further narrow CpGs into 140 samples. In the validation phase, candidate CpGs were validated using an internal cohort (n = 141) and two external cohorts (n = 191 and n =104). Results After combining the 46 CpGs selected by the Least Absolute Shrinkage and Selector Operation and the Support Vector Machine-Recursive Feature Elimination algorithms, three CpGs corresponding to SCAN domain containing 3, Src homology 3-domain growth factor receptor-bound 2-like interacting protein 1, and peptidase inhibitor 3 were highlighted as candidate predictors in the training phase. On the basis of the three CpGs, a methylation signature for E-HCC (MSEH) was developed to classify patients into high- and low-risk recurrence groups in the training cohort ( P < .001). The performance of MSEH was validated in the internal cohort ( P < .001) and in the two external cohorts ( P < .001; P = .002). Furthermore, a nomogram comprising MSEH, tumor differentiation, cirrhosis, hepatitis B virus surface antigen, and antivirus therapy was generated to predict the 5-year recurrence-free survival in the training cohort, and it performed well in the three validation cohorts (concordance index: 0.725, 0.697, and 0.693, respectively). Conclusion MSEH, a three-CpG-based signature, is useful in predicting recurrence for patients with E-HCC.
Derivation and Validation of a Renal Risk Score for People With Type 2 Diabetes
Elley, C. Raina; Robinson, Tom; Moyes, Simon A.; Kenealy, Tim; Collins, John; Robinson, Elizabeth; Orr-Walker, Brandon; Drury, Paul L.
2013-01-01
OBJECTIVE Diabetes has become the leading cause of end-stage renal disease (ESRD). Renal risk stratification could assist in earlier identification and targeted prevention. This study aimed to derive risk models to predict ESRD events in type 2 diabetes in primary care. RESEARCH DESIGN AND METHODS The nationwide derivation cohort included adults with type 2 diabetes from the New Zealand Diabetes Cohort Study initially assessed during 2000–2006 and followed until December 2010, excluding those with pre-existing ESRD. The outcome was fatal or nonfatal ESRD event (peritoneal dialysis or hemodialysis for ESRD, renal transplantation, or death from ESRD). Risk models were developed using Cox proportional hazards models, and their performance was assessed in a separate validation cohort. RESULTS The derivation cohort included 25,736 individuals followed for up to 11 years (180,497 person-years; 86% followed for ≥5 years). At baseline, mean age was 62 years, median diabetes duration 5 years, and median HbA1c 7.2% (55 mmol/mol); 37% had albuminuria; and median estimated glomerular filtration rate (eGFR) was 77 mL/min/1.73 m2. There were 637 ESRD events (2.5%) during follow-up. Models that included sex, ethnicity, age, diabetes duration, albuminuria, serum creatinine, systolic blood pressure, HbA1c, smoking status, and previous cardiovascular disease status performed well with good discrimination and calibration in the derivation cohort and the validation cohort (n = 5,877) (C-statistics 0.89–0.92), improving predictive performance compared with previous models. CONCLUSIONS These 5-year renal risk models performed very well in two large primary care populations with type 2 diabetes. More accurate risk stratification could facilitate earlier intervention than using eGFR and/or albuminuria alone. PMID:23801726
2013-01-01
Introduction Close monitoring and repeated risk assessment of sepsis patients in the intensive care unit (ICU) is important for decisions regarding care intensification or early discharge to the ward. We studied whether considering plasma kinetics of procalcitonin, a biomarker of systemic bacterial infection, over the first 72 critical care hours improved mortality prognostication of septic patients from two US settings. Methods This retrospective analysis included consecutively treated eligible adults with a diagnosis of sepsis from critical care units in two independent institutions in Clearwater, FL and Chicago, IL. Cohorts were used for derivation or validation to study the association between procalcitonin change over the first 72 critical care hours and mortality. Results ICU/in-hospital mortality rates were 29.2%/31.8% in the derivation cohort (n = 154) and 17.6%/29.4% in the validation cohort (n = 102). In logistic regression analysis of both cohorts, procalcitonin change was strongly associated with ICU and in-hospital mortality independent of clinical risk scores (Acute Physiology, Age and Chronic Health Evaluation IV or Simplified Acute Physiology Score II), with area under the curve (AUC) from 0.67 to 0.71. When procalcitonin decreased by at least 80%, the negative predictive value for ICU/in-hospital mortality was 90%/90% in the derivation cohort, and 91%/79% in the validation cohort. When procalcitonin showed no decrease or increased, the respective positive predictive values were 48%/48% and 36%/52%. Discussion In septic patients, procalcitonin kinetics over the first 72 critical care hours provide prognostic information beyond that available from clinical risk scores. If these observations are confirmed, procalcitonin monitoring may assist physician decision-making regarding care intensification or early transfer from the ICU to the floor. PMID:23787145
Rosmalen, J G M; Bos, E H; de Jonge, P
2012-12-01
Stress questionnaires are included in many epidemiological cohort studies but the psychometric characteristics of these questionnaires are largely unknown. The aim of this study was to describe these characteristics for two short questionnaires measuring the lifetime and past year occurrence of stress: the List of Threatening Events (LTE) as a measure of acute stress and the Long-term Difficulties Inventory (LDI) as a measure of chronic stress. This study was performed in a general population cohort consisting of 588 females (53.7%) and 506 males (46.3%), with a mean age of 53.5 years (s.d.=11.3 years). Respondents completed the LTE and the LDI for the past year, and for the age categories of 0-12, 13-18, 19-39, 40-60, and >60 years. They also completed questionnaires on perceived stress, psychological distress (the General Health Questionnaire, GHQ-12), anxiety and depression (the Symptom Checklist, SCL-8) and neuroticism (the Eysenck Personality Questionnaire - Revised Short Scale, EPQ-RSS-N). Approximately 2 years later, 976 respondents (89%) completed these questionnaires for a second time. The stability of the retrospective reporting of long-term difficulties and life events was satisfactory: 0.7 for the lifetime LDI and 0.6 for the lifetime LTE scores. The construct validity of these lists is indicated by their positive associations with psychological distress, mental health problems and neuroticism. This study in a large population-based sample shows that the LDI and LTE have sufficient validity and stability to include them in major epidemiological cohort studies.
Tang, Xin-Ran; Li, Ying-Qin; Liang, Shao-Bo; Jiang, Wei; Liu, Fang; Ge, Wen-Xiu; Tang, Ling-Long; Mao, Yan-Ping; He, Qing-Mei; Yang, Xiao-Jing; Zhang, Yuan; Wen, Xin; Zhang, Jian; Wang, Ya-Qin; Zhang, Pan-Pan; Sun, Ying; Yun, Jing-Ping; Zeng, Jing; Li, Li; Liu, Li-Zhi; Liu, Na; Ma, Jun
2018-03-01
Gene expression patterns can be used as prognostic biomarkers in various types of cancers. We aimed to identify a gene expression pattern for individual distant metastatic risk assessment in patients with locoregionally advanced nasopharyngeal carcinoma. In this multicentre, retrospective, cohort analysis, we included 937 patients with locoregionally advanced nasopharyngeal carcinoma from three Chinese hospitals: the Sun Yat-sen University Cancer Center (Guangzhou, China), the Affiliated Hospital of Guilin Medical University (Guilin, China), and the First People's Hospital of Foshan (Foshan, China). Using microarray analysis, we profiled mRNA gene expression between 24 paired locoregionally advanced nasopharyngeal carcinoma tumours from patients at Sun Yat-sen University Cancer Center with or without distant metastasis after radical treatment. Differentially expressed genes were examined using digital expression profiling in a training cohort (Guangzhou training cohort; n=410) to build a gene classifier using a penalised regression model. We validated the prognostic accuracy of this gene classifier in an internal validation cohort (Guangzhou internal validation cohort, n=204) and two external independent cohorts (Guilin cohort, n=165; Foshan cohort, n=158). The primary endpoint was distant metastasis-free survival. Secondary endpoints were disease-free survival and overall survival. We identified 137 differentially expressed genes between metastatic and non-metastatic locoregionally advanced nasopharyngeal carcinoma tissues. A distant metastasis gene signature for locoregionally advanced nasopharyngeal carcinoma (DMGN) that consisted of 13 genes was generated to classify patients into high-risk and low-risk groups in the training cohort. Patients with high-risk scores in the training cohort had shorter distant metastasis-free survival (hazard ratio [HR] 4·93, 95% CI 2·99-8·16; p<0·0001), disease-free survival (HR 3·51, 2·43-5·07; p<0·0001), and overall survival (HR 3·22, 2·18-4·76; p<0·0001) than patients with low-risk scores. The prognostic accuracy of DMGN was validated in the internal and external cohorts. Furthermore, among patients with low-risk scores in the combined training and internal cohorts, concurrent chemotherapy improved distant metastasis-free survival compared with those patients who did not receive concurrent chemotherapy (HR 0·40, 95% CI 0·19-0·83; p=0·011), whereas patients with high-risk scores did not benefit from concurrent chemotherapy (HR 1·03, 0·71-1·50; p=0·876). This was also validated in the two external cohorts combined. We developed a nomogram based on the DMGN and other variables that predicted an individual's risk of distant metastasis, which was strengthened by adding Epstein-Barr virus DNA status. The DMGN is a reliable prognostic tool for distant metastasis in patients with locoregionally advanced nasopharyngeal carcinoma and might be able to predict which patients benefit from concurrent chemotherapy. It has the potential to guide treatment decisions for patients at different risk of distant metastasis. The National Natural Science Foundation of China, the National Science & Technology Pillar Program during the Twelfth Five-year Plan Period, the Natural Science Foundation of Guang Dong Province, the National Key Research and Development Program of China, the Innovation Team Development Plan of the Ministry of Education, the Health & Medical Collaborative Innovation Project of Guangzhou City, China, and the Program of Introducing Talents of Discipline to Universities. Copyright © 2018 Elsevier Ltd. All rights reserved.
Validation of microRNA pathway polymorphisms in esophageal adenocarcinoma survival.
Faluyi, Olusola O; Eng, Lawson; Qiu, Xin; Che, Jiahua; Zhang, Qihuang; Cheng, Dangxiao; Ying, Nanjiao; Tse, Alvina; Kuang, Qin; Dodbiba, Lorin; Renouf, Daniel J; Marsh, Sharon; Savas, Sevtap; Mackay, Helen J; Knox, Jennifer J; Darling, Gail E; Wong, Rebecca K S; Xu, Wei; Azad, Abul Kalam; Liu, Geoffrey
2017-02-01
Polymorphisms in miRNA and miRNA pathway genes have been previously associated with cancer risk and outcome, but have not been studied in esophageal adenocarcinoma outcomes. Here, we evaluate candidate miRNA pathway polymorphisms in esophageal adenocarcinoma prognosis and attempt to validate them in an independent cohort of esophageal adenocarcinoma patients. Among 231 esophageal adenocarcinoma patients of all stages/treatment plans, 38 candidate genetic polymorphisms (17 biogenesis, 9 miRNA targets, 5 pri-miRNA, 7 pre-miRNA) were genotyped and analyzed. Cox proportional hazard models adjusted for sociodemographic and clinicopathological covariates helped assess the association of genetic polymorphisms with overall survival (OS) and progression-free survival (PFS). Significantly associated polymorphisms were then evaluated in an independent cohort of 137 esophageal adenocarcinoma patients. Among the 231 discovery cohort patients, 86% were male, median diagnosis age was 64 years, 34% were metastatic at diagnosis, and median OS and PFS were 20 and 12 months, respectively. GEMIN3 rs197412 (aHR = 1.37, 95%CI: [1.04-1.80]; P = 0.02), hsa-mir-124-1 rs531564 (aHR = 0.60, 95% CI: [0.53-0.90]; P = 0.05), and KIAA0423 rs1053667 (aHR = 0.51, 95% CI: [0.28-0.96]; P = 0.04) were found associated with OS. Furthermore, GEMIN3 rs197412 (aHR = 1.33, 95% CI: [1.03-1.74]; P = 0.03) and KRT81 rs3660 (aHR = 1.29, 95% CI: [1.01-1.64]; P = 0.04) were found associated with PFS. Although none of these polymorphisms were significant in the second cohort, hsa-mir-124-1 rs531564 and KIAA0423 rs1053667 had trends in the same direction; when both cohorts were combined together, GEMIN3 rs197412, hsa-mir-124-1 rs531564, and KIAA0423 rs1053667 remained significantly associated with OS. We demonstrate the association of multiple miRNA pathway polymorphisms with esophageal adenocarcinoma prognosis in a discovery cohort of patients, which did not validate in a separate cohort but had consistent associations in the pooled cohort. Larger studies are required to confirm/validate the prognostic value of these polymorphisms in esophageal adenocarcinoma. © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.
PLCO Ovarian Phase III Validation Study — EDRN Public Portal
Our preliminary data indicate that the performance of CA 125 as a screening test for ovarian cancer can be improved upon by additional biomarkers. With completion of one additional validation step, we will be ready to test the performance of a consensus marker panel in a phase III validation study. Given the original aims of the PLCO trial, we believe that the PLCO represents an ideal longitudinal cohort offering specimens for phase III validation of ovarian cancer biomarkers.
Winham, Stacey J.; Preuss, Ulrich W.; Geske, Jennifer R.; Zill, Peter; Heit, John A.; Bakalkin, Georgy; Biernacka, Joanna M.; Karpyak, Victor M.
2015-01-01
We previously demonstrated that prodynorphin (PDYN) haplotypes and single nucleotide polymorphism (SNP) rs2281285 are associated with alcohol dependence and the propensity to drink in negative emotional states, and recent studies suggest that PDYN gene effects on substance dependence risk may be sex-related. We examined sex-dependent associations of PDYN variation with alcohol dependence and related phenotypes, including negative craving, time until relapse after treatment and the length of sobriety episodes before seeking treatment, in discovery and validation cohorts of European ancestry. We found a significant haplotype-by-sex interaction (p = 0.03), suggesting association with alcohol dependence in males (p = 1E-4) but not females. The rs2281285 G allele increased risk for alcohol dependence in males in the discovery cohort (OR = 1.49, p = 0.002), with a similar trend in the validation cohort (OR = 1.35, p = 0.086). However, rs2281285 showed a trend towards association with increased negative craving in females in both the discovery (beta = 10.16, p = 0.045) and validation samples (OR = 7.11, p = 0.066). In the discovery cohort, rs2281285 was associated with time until relapse after treatment in females (HR = 1.72, p = 0.037); in the validation cohort, it was associated with increased length of sobriety episodes before treatment in males (beta = 13.49, p = 0.001). Our findings suggest that sex-dependent effects of PDYN variants in alcohol dependence are phenotype-specific. PMID:26502829
Winham, Stacey J; Preuss, Ulrich W; Geske, Jennifer R; Zill, Peter; Heit, John A; Bakalkin, Georgy; Biernacka, Joanna M; Karpyak, Victor M
2015-10-27
We previously demonstrated that prodynorphin (PDYN) haplotypes and single nucleotide polymorphism (SNP) rs2281285 are associated with alcohol dependence and the propensity to drink in negative emotional states, and recent studies suggest that PDYN gene effects on substance dependence risk may be sex-related. We examined sex-dependent associations of PDYN variation with alcohol dependence and related phenotypes, including negative craving, time until relapse after treatment and the length of sobriety episodes before seeking treatment, in discovery and validation cohorts of European ancestry. We found a significant haplotype-by-sex interaction (p = 0.03), suggesting association with alcohol dependence in males (p = 1E-4) but not females. The rs2281285 G allele increased risk for alcohol dependence in males in the discovery cohort (OR = 1.49, p = 0.002), with a similar trend in the validation cohort (OR = 1.35, p = 0.086). However, rs2281285 showed a trend towards association with increased negative craving in females in both the discovery (beta = 10.16, p = 0.045) and validation samples (OR = 7.11, p = 0.066). In the discovery cohort, rs2281285 was associated with time until relapse after treatment in females (HR = 1.72, p = 0.037); in the validation cohort, it was associated with increased length of sobriety episodes before treatment in males (beta = 13.49, p = 0.001). Our findings suggest that sex-dependent effects of PDYN variants in alcohol dependence are phenotype-specific.
Validation of Medicaid claims-based diagnosis of myocardial infarction using an HIV clinical cohort
Brouwer, Emily S.; Napravnik, Sonia; Eron, Joseph J; Simpson, Ross J; Brookhart, M. Alan; Stalzer, Brant; Vinikoor, Michael; Floris-Moore, Michelle; Stürmer, Til
2014-01-01
Background In non-experimental comparative effectiveness research using healthcare databases, outcome measurements must be validated to evaluate and potentially adjust for misclassification bias. We aimed to validate claims-based myocardial infarction algorithms in a Medicaid population using an HIV clinical cohort as the gold standard. Methods Medicaid administrative data were obtained for the years 2002–2008 and linked to the UNC CFAR HIV Clinical Cohort based on social security number, first name and last name and myocardial infarction were adjudicated. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated. Results There were 1,063 individuals included. Over a median observed time of 2.5 years, 17 had a myocardial infarction. Specificity ranged from 0.979–0.993 with the highest specificity obtained using criteria with the ICD-9 code in the primary and secondary position and a length of stay ≥ 3 days. Sensitivity of myocardial infarction ascertainment varied from 0.588–0.824 depending on algorithm. Conclusion: Specificities of varying claims-based myocardial infarction ascertainment criteria are high but small changes impact positive predictive value in a cohort with low incidence. Sensitivities vary based on ascertainment criteria. Type of algorithm used should be prioritized based on study question and maximization of specific validation parameters that will minimize bias while also considering precision. PMID:23604043
Chen, Yinsheng; Li, Zeju; Wu, Guoqing; Yu, Jinhua; Wang, Yuanyuan; Lv, Xiaofei; Ju, Xue; Chen, Zhongping
2018-07-01
Due to the totally different therapeutic regimens needed for primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM), accurate differentiation of the two diseases by noninvasive imaging techniques is important for clinical decision-making. Thirty cases of PCNSL and 66 cases of GBM with conventional T1-contrast magnetic resonance imaging (MRI) were analyzed in this study. Convolutional neural networks was used to segment tumor automatically. A modified scale invariant feature transform (SIFT) method was utilized to extract three-dimensional local voxel arrangement information from segmented tumors. Fisher vector was proposed to normalize the dimension of SIFT features. An improved genetic algorithm (GA) was used to extract SIFT features with PCNSL and GBM discrimination ability. The data-set was divided into a cross-validation cohort and an independent validation cohort by the ratio of 2:1. Support vector machine with the leave-one-out cross-validation based on 20 cases of PCNSL and 44 cases of GBM was employed to build and validate the differentiation model. Among 16,384 high-throughput features, 1356 features show significant differences between PCNSL and GBM with p < 0.05 and 420 features with p < 0.001. A total of 496 features were finally chosen by improved GA algorithm. The proposed method produces PCNSL vs. GBM differentiation with an area under the curve (AUC) curve of 99.1% (98.2%), accuracy 95.3% (90.6%), sensitivity 85.0% (80.0%) and specificity 100% (95.5%) on the cross-validation cohort (and independent validation cohort). Since the local voxel arrangement characterization provided by SIFT features, proposed method produced more competitive PCNSL and GBM differentiation performance by using conventional MRI than methods based on advanced MRI.
Fang, Wen-Feng; Douglas, Ivor S.; Chen, Yu-Mu; Lin, Chiung-Yu; Kao, Hsu-Ching; Fang, Ying-Tang; Huang, Chi-Han; Chang, Ya-Ting; Huang, Kuo-Tung; Wang, Yi-His; Wang, Chin-Chou
2017-01-01
Background Sepsis-induced immune dysfunction ranging from cytokines storm to immunoparalysis impacts outcomes. Monitoring immune dysfunction enables better risk stratification and mortality prediction and is mandatory before widely application of immunoadjuvant therapies. We aimed to develop and validate a scoring system according to patients’ immune dysfunction status for 28-day mortality prediction. Methods A prospective observational study from a cohort of adult sepsis patients admitted to ICU between August 2013 and June 2016 at Kaohsiung Chang Gung Memorial Hospital in Taiwan. We evaluated immune dysfunction status through measurement of baseline plasma Cytokine levels, Monocyte human leukocyte-DR expression by flow cytometry, and stimulated immune response using post LPS stimulated cytokine elevation ratio. An immune dysfunction score was created for 28-day mortality prediction and was validated. Results A total of 151 patients were enrolled. Data of the first consecutive 106 septic patients comprised the training cohort, and of other 45 patients comprised the validation cohort. Among the 106 patients, 21 died and 85 were still alive on day 28 after ICU admission. (mortality rate, 19.8%). Independent predictive factors revealed via multivariate logistic regression analysis included segmented neutrophil-to-monocyte ratio, granulocyte-colony stimulating factor, interleukin-10, and monocyte human leukocyte antigen-antigen D–related levels, all of which were selected to construct the score, which predicted 28-day mortality with area under the curve of 0.853 and 0.789 in the training and validation cohorts, respectively. Conclusions The immune dysfunction scoring system developed here included plasma granulocyte-colony stimulating factor level, interleukin-10 level, serum segmented neutrophil-to-monocyte ratio, and monocyte human leukocyte antigen-antigen D–related expression appears valid and reproducible for predicting 28-day mortality. PMID:29073262
Galvin, Rose; Joyce, Doireann; Downey, Eithne; Boland, Fiona; Fahey, Tom; Hill, Arnold K
2014-10-03
The number of primary care referrals of women with breast symptoms to symptomatic breast units (SBUs) has increased exponentially in the past decade in Ireland. The aim of this study is to develop and validate a clinical prediction rule (CPR) to identify women with breast cancer so that a more evidence based approach to referral from primary care to these SBUs can be developed. We analysed routine data from a prospective cohort of consecutive women reviewed at a SBU with breast symptoms. The dataset was split into a derivation and validation cohort. Regression analysis was used to derive a CPR from the patient's history and clinical findings. Validation of the CPR consisted of estimating the number of breast cancers predicted to occur compared with the actual number of observed breast cancers across deciles of risk. A total of 6,590 patients were included in the derivation study and 4.9% were diagnosed with breast cancer. Independent clinical predictors for breast cancer were: increasing age by year (adjusted odds ratio 1.08, 95% CI 1.07-1.09); presence of a lump (5.63, 95% CI 4.2-7.56); nipple change (2.77, 95% CI 1.68-4.58) and nipple discharge (2.09, 95% CI 1.1-3.97). Validation of the rule (n = 911) demonstrated that the probability of breast cancer was higher with an increasing number of these independent variables. The Hosmer-Lemeshow goodness of fit showed no overall significant difference between the expected and the observed numbers of breast cancer (χ(2)HL: 6.74, p-value: 0.56). This study derived and validated a CPR for breast cancer in women attending an Irish national SBU. We found that increasing age, presence of a lump, nipple discharge and nipple change are all associated with increased risk of breast cancer. Further validation of the rule is necessary as well as an assessment of its impact on referral practice.
Lessons Learned From Methodological Validation Research in E-Epidemiology.
Kesse-Guyot, Emmanuelle; Assmann, Karen; Andreeva, Valentina; Castetbon, Katia; Méjean, Caroline; Touvier, Mathilde; Salanave, Benoît; Deschamps, Valérie; Péneau, Sandrine; Fezeu, Léopold; Julia, Chantal; Allès, Benjamin; Galan, Pilar; Hercberg, Serge
2016-10-18
Traditional epidemiological research methods exhibit limitations leading to high logistics, human, and financial burden. The continued development of innovative digital tools has the potential to overcome many of the existing methodological issues. Nonetheless, Web-based studies remain relatively uncommon, partly due to persistent concerns about validity and generalizability. The objective of this viewpoint is to summarize findings from methodological studies carried out in the NutriNet-Santé study, a French Web-based cohort study. On the basis of the previous findings from the NutriNet-Santé e-cohort (>150,000 participants are currently included), we synthesized e-epidemiological knowledge on sample representativeness, advantageous recruitment strategies, and data quality. Overall, the reported findings support the usefulness of Web-based studies in overcoming common methodological deficiencies in epidemiological research, in particular with regard to data quality (eg, the concordance for body mass index [BMI] classification was 93%), reduced social desirability bias, and access to a wide range of participant profiles, including the hard-to-reach subgroups such as young (12.30% [15,118/122,912], <25 years) and old people (6.60% [8112/122,912], ≥65 years), unemployed or homemaker (12.60% [15,487/122,912]), and low educated (38.50% [47,312/122,912]) people. However, some selection bias remained (78.00% (95,871/122,912) of the participants were women, and 61.50% (75,590/122,912) had postsecondary education), which is an inherent aspect of cohort study inclusion; other specific types of bias may also have occurred. Given the rapidly growing access to the Internet across social strata, the recruitment of participants with diverse socioeconomic profiles and health risk exposures was highly feasible. Continued efforts concerning the identification of specific biases in e-cohorts and the collection of comprehensive and valid data are still needed. This summary of methodological findings from the NutriNet-Santé cohort may help researchers in the development of the next generation of high-quality Web-based epidemiological studies.
Vrijens, Karen; Winckelmans, Ellen; Tsamou, Maria; Baeyens, Willy; De Boever, Patrick; Jennen, Danyel; de Kok, Theo M; Den Hond, Elly; Lefebvre, Wouter; Plusquin, Michelle; Reynders, Hans; Schoeters, Greet; Van Larebeke, Nicolas; Vanpoucke, Charlotte; Kleinjans, Jos; Nawrot, Tim S
2017-04-01
Particulate matter (PM) exposure leads to premature death, mainly due to respiratory and cardiovascular diseases. Identification of transcriptomic biomarkers of air pollution exposure and effect in a healthy adult population. Microarray analyses were performed in 98 healthy volunteers (48 men, 50 women). The expression of eight sex-specific candidate biomarker genes (significantly associated with PM 10 in the discovery cohort and with a reported link to air pollution-related disease) was measured with qPCR in an independent validation cohort (75 men, 94 women). Pathway analysis was performed using Gene Set Enrichment Analysis. Average daily PM 2.5 and PM 10 exposures over 2-years were estimated for each participant's residential address using spatiotemporal interpolation in combination with a dispersion model. Average long-term PM 10 was 25.9 (± 5.4) and 23.7 (± 2.3) μg/m 3 in the discovery and validation cohorts, respectively. In discovery analysis, associations between PM 10 and the expression of individual genes differed by sex. In the validation cohort, long-term PM 10 was associated with the expression of DNAJB5 and EAPP in men and ARHGAP4 ( p = 0.053) in women. AKAP6 and LIMK1 were significantly associated with PM 10 in women, although associations differed in direction between the discovery and validation cohorts. Expression of the eight candidate genes in the discovery cohort differentiated between validation cohort participants with high versus low PM 10 exposure (area under the receiver operating curve = 0.92; 95% CI: 0.85, 1.00; p = 0.0002 in men, 0.86; 95% CI: 0.76, 0.96; p = 0.004 in women). Expression of the sex-specific candidate genes identified in the discovery population predicted PM 10 exposure in an independent cohort of adults from the same area. Confirmation in other populations may further support this as a new approach for exposure assessment, and may contribute to the discovery of molecular mechanisms for PM-induced health effects.
Guo, Jing; Chen, Shangxiang; Li, Shun; Sun, Xiaowei; Li, Wei; Zhou, Zhiwei; Chen, Yingbo; Xu, Dazhi
2018-01-12
Several studies have highlighted the prognostic value of the individual and the various combinations of the tumor markers for gastric cancer (GC). Our study was designed to assess establish a new novel model incorporating carcino-embryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 72-4 (CA72-4). A total of 1,566 GC patients (Primary cohort) between Jan 2000 and July 2013 were analyzed. The Primary cohort was randomly divided into Training set (n=783) and Validation set (n=783). A three-tumor marker classifier was developed in the Training set and validated in the Validation set by multivariate regression and risk-score analysis. We have identified a three-tumor marker classifier (including CEA, CA19-9 and CA72-4) for the cancer specific survival (CSS) of GC (p<0.001). Consistent results were obtained in the both Training set and Validation set. Multivariate analysis showed that the classifier was an independent predictor of GC (All p value <0.001 in the Training set, Validation set and Primary cohort). Furthermore, when the leave-one-out approach was performed, the classifier showed superior predictive value to the individual or two of them (with the highest AUC (Area Under Curve); 0.618 for the Training set, and 0.625 for the Validation set), which ascertained its predictive value. Our three-tumor marker classifier is closely associated with the CSS of GC and may serve as a novel model for future decisions concerning treatments.
Validation of Computerized Automatic Calculation of the Sequential Organ Failure Assessment Score
Harrison, Andrew M.; Pickering, Brian W.; Herasevich, Vitaly
2013-01-01
Purpose. To validate the use of a computer program for the automatic calculation of the sequential organ failure assessment (SOFA) score, as compared to the gold standard of manual chart review. Materials and Methods. Adult admissions (age > 18 years) to the medical ICU with a length of stay greater than 24 hours were studied in the setting of an academic tertiary referral center. A retrospective cross-sectional analysis was performed using a derivation cohort to compare automatic calculation of the SOFA score to the gold standard of manual chart review. After critical appraisal of sources of disagreement, another analysis was performed using an independent validation cohort. Then, a prospective observational analysis was performed using an implementation of this computer program in AWARE Dashboard, which is an existing real-time patient EMR system for use in the ICU. Results. Good agreement between the manual and automatic SOFA calculations was observed for both the derivation (N=94) and validation (N=268) cohorts: 0.02 ± 2.33 and 0.29 ± 1.75 points, respectively. These results were validated in AWARE (N=60). Conclusion. This EMR-based automatic tool accurately calculates SOFA scores and can facilitate ICU decisions without the need for manual data collection. This tool can also be employed in a real-time electronic environment. PMID:23936639
Validation and Adjustment of the Leipzig-Halifax Acute Aortic Dissection Type A Scorecard.
Mejàre-Berggren, Hanna; Olsson, Christian
2017-11-01
The novel Leipzig-Halifax (LH) scorecard for acute aortic dissection type A (AADA) stratifies risk of in-hospital death based on age, malperfusion syndromes, critical preoperative state, and coronary disease. The study aim was to externally validate the LH scorecard performance and, if adequate, propose adjustments. All consecutive AADA patients operated on from 1996 to 2016 (n = 509) were included to generate an external validation cohort. Variables related to in-hospital death were analyzed using univariable and multivariable analysis. The LH scorecard was applied to the validation cohort, compared with the original study, and variable selection was adjusted using validation measures for discrimination and calibration. In-hospital mortality rate was 17.7% (LH cohort 18.7%). Critical preoperative state and Penn class non-Aa were independent predictors (odds ratio [OR] 2.42 and 2.45, respectively) of in-hospital death. The LH scorecard was adjusted to include Penn class non-Aa, critical preoperative state, and coronary disease. Assessing discrimination, area under receiver operator characteristic curve for the LH scorecard was 0.61 versus 0.66 for the new scorecard (p = 0.086). In-hospital mortality rates in low-, medium-, and high-risk groups were 14%, 15%, and 48%, respectively (LH scorecard) versus 11%, 23%, and 43%, respectively (new scorecard), and goodness-of-fit p value was 0.01 versus 0.86, indicating better calibration by the new scorecard. A lower Akaike information criterion value, 464 versus 448, favored the new scorecard. Through adjustment of the LH scorecard after external validation, prognostic performance improved. Further validated, the LH scorecard could be a valuable risk prediction tool. Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.
Basehore, Monica J; Marlowe, Natalia M; Jones, Julie R; Behlendorf, Deborah E; Laver, Thomas A; Friez, Michael J
2012-06-01
Most individuals with intellectual disability and/or autism are tested for Fragile X syndrome at some point in their lifetime. Greater than 99% of individuals with Fragile X have an expanded CGG trinucleotide repeat motif in the promoter region of the FMR1 gene, and diagnostic testing involves determining the size of the CGG repeat as well as methylation status when an expansion is present. Using a previously described triplet repeat-primed polymerase chain reaction, we have performed additional validation studies using two cohorts with previous diagnostic testing results available for comparison purposes. The first cohort (n=88) consisted of both males and females and had a high percentage of abnormal samples, while the second cohort (n=624) consisted of only females and was not enriched for expansion mutations. Data from each cohort were completely concordant with the results previously obtained during the course of diagnostic testing. This study further demonstrates the utility of using laboratory-developed triplet repeat-primed FMR1 testing in a clinical setting.
Evans, Joseph R; Zhao, Shuang G; Chang, S Laura; Tomlins, Scott A; Erho, Nicholas; Sboner, Andrea; Schiewer, Matthew J; Spratt, Daniel E; Kothari, Vishal; Klein, Eric A; Den, Robert B; Dicker, Adam P; Karnes, R Jeffrey; Yu, Xiaochun; Nguyen, Paul L; Rubin, Mark A; de Bono, Johann; Knudsen, Karen E; Davicioni, Elai; Feng, Felix Y
2016-04-01
A substantial number of patients diagnosed with high-risk prostate cancer are at risk for metastatic progression after primary treatment. Better biomarkers are needed to identify patients at the highest risk to guide therapy intensification. To create a DNA damage and repair (DDR) pathway profiling method for use as a prognostic signature biomarker in high-risk prostate cancer. A cohort of 1090 patients with high-risk prostate cancer who underwent prostatectomy and were treated at 3 different academic institutions were divided into a training cohort (n = 545) and 3 pooled validation cohorts (n = 232, 130, and 183) assembled for case-control or case-cohort studies. Profiling of 9 DDR pathways using 17 gene sets for GSEA (Gene Set Enrichment Analysis) of high-density microarray gene expression data from formalin-fixed paraffin-embedded prostatectomy samples with median 10.3 years follow-up was performed. Prognostic signature development from DDR pathway profiles was studied, and DDR pathway gene mutation in published cohorts was analyzed. Biochemical recurrence-free, metastasis-free, and overall survival. Across the training cohort and pooled validation cohorts, 1090 men were studied; mean (SD) age at diagnosis was 65.3 (6.4) years. We found that there are distinct clusters of DDR pathways within the cohort, and DDR pathway enrichment is only weakly correlated with clinical variables such as age (Spearman ρ [ρ], range, -0.07 to 0.24), Gleason score (ρ, range, 0.03 to 0.20), prostate-specific antigen level (ρ, range, -0.07 to 0.10), while 13 of 17 DDR gene sets are strongly correlated with androgen receptor pathway enrichment (ρ, range, 0.33 to 0.82). In published cohorts, DDR pathway genes are rarely mutated. A DDR pathway profile prognostic signature built in the training cohort was significantly associated with biochemical recurrence-free, metastasis-free, and overall survival in the pooled validation cohorts independent of standard clinicopathological variables. The prognostic performance of the signature for metastasis-free survival appears to be stronger in the younger patients (HR, 1.67; 95% CI, 1.12-2.50) than in the older patients (HR, 0.77; 95% CI, 0.29-2.07) on multivariate Cox analysis. DNA damage and repair pathway profiling revealed patient-level variations and the DDR pathways are rarely affected by mutation. A DDR pathway signature showed strong prognostic performance with the long-term outcomes of metastasis-free and overall survival that may be useful for risk stratification of high-risk prostate cancer patients.
Wan, Eric Yuk Fai; Fong, Daniel Yee Tak; Fung, Colman Siu Cheung; Yu, Esther Yee Tak; Chin, Weng Yee; Chan, Anca Ka Chun; Lam, Cindy Lo Kuen
2017-06-01
This study aimed to develop and validate an all-cause mortality risk prediction model for Chinese primary care patients with type 2 diabetes mellitus(T2DM) in Hong Kong. A population-based retrospective cohort study was conducted on 132,462 Chinese patients who had received public primary care services during 2010. Each gender sample was randomly split on a 2:1 basis into derivation and validation cohorts and was followed-up for a median period of 5years. Gender-specific mortality risk prediction models showing the interaction effect between predictors and age were derived using Cox proportional hazards regression with forward stepwise approach. Developed models were compared with pre-existing models by Harrell's C-statistic and calibration plot using validation cohort. Common predictors of increased mortality risk in both genders included: age; smoking habit; diabetes duration; use of anti-hypertensive agents, insulin and lipid-lowering drugs; body mass index; hemoglobin A1c; systolic blood pressure(BP); total cholesterol to high-density lipoprotein-cholesterol ratio; urine albumin to creatinine ratio(urine ACR); and estimated glomerular filtration rate(eGFR). Prediction models showed better discrimination with Harrell"'s C-statistics of 0.768(males) and 0.782(females) and calibration power from the plots than previously established models. Our newly developed gender-specific models provide a more accurate predicted 5-year mortality risk for Chinese diabetic patients than other established models. Copyright © 2017 Elsevier Inc. All rights reserved.
Zhang, Zhongheng; Hong, Yucai
2017-07-25
There are several disease severity scores being used for the prediction of mortality in critically ill patients. However, none of them was developed and validated specifically for patients with severe sepsis. The present study aimed to develop a novel prediction score for severe sepsis. A total of 3206 patients with severe sepsis were enrolled, including 1054 non-survivors and 2152 survivors. The LASSO score showed the best discrimination (area under curve: 0.772; 95% confidence interval: 0.735-0.810) in the validation cohort as compared with other scores such as simplified acute physiology score II, acute physiological score III, Logistic organ dysfunction system, sequential organ failure assessment score, and Oxford Acute Severity of Illness Score. The calibration slope was 0.889 and Brier value was 0.173. The study employed a single center database called Medical Information Mart for Intensive Care-III) MIMIC-III for analysis. Severe sepsis was defined as infection and acute organ dysfunction. Clinical and laboratory variables used in clinical routines were included for screening. Subjects without missing values were included, and the whole dataset was split into training and validation cohorts. The score was coined LASSO score because variable selection was performed using the least absolute shrinkage and selection operator (LASSO) technique. Finally, the LASSO score was evaluated for its discrimination and calibration in the validation cohort. The study developed the LASSO score for mortality prediction in patients with severe sepsis. Although the score had good discrimination and calibration in a randomly selected subsample, external validations are still required.
Hannam, K; Deere, K C; Hartley, A; Clark, E M; Coulson, J; Ireland, A; Moss, C; Edwards, M H; Dennison, E; Gaysin, T; Cooper, R; Wong, A; McPhee, J S; Cooper, C; Kuh, D; Tobias, J H
2017-03-01
This observational study assessed vertical impacts experienced in older adults as part of their day-to-day physical activity using accelerometry and questionnaire data. Population-based older adults experienced very limited high-impact activity. The accelerometry method utilised appeared to be valid based on comparisons between different cohorts and with self-reported activity. We aimed to validate a novel method for evaluating day-to-day higher impact weight-bearing physical activity (PA) in older adults, thought to be important in protecting against osteoporosis, by comparing results between four cohorts varying in age and activity levels, and with self-reported PA levels. Participants were from three population-based cohorts, MRC National Survey of Health and Development (NSHD), Hertfordshire Cohort Study (HCS) and Cohort for Skeletal Health in Bristol and Avon (COSHIBA), and the Master Athlete Cohort (MAC). Y-axis peaks (reflecting the vertical when an individual is upright) from a triaxial accelerometer (sampling frequency 50 Hz, range 0-16 g) worn at the waist for 7 days were classified as low (0.5-1.0 g), medium (1.0-1.5 g) or higher (≥1.5 g) impacts. There were a median of 90, 41 and 39 higher impacts/week in NSHD (age 69.5), COSHIBA (age 76.8) and HCS (age 78.5) participants, respectively (total n = 1512). In contrast, MAC participants (age 68.5) had a median of 14,322 higher impacts/week. In the three population cohorts combined, based on comparison of beta coefficients, moderate-high-impact activities as assessed by PA questionnaire were suggestive of stronger association with higher impacts from accelerometers (0.25 [0.17, 0.34]), compared with medium (0.18 [0.09, 0.27]) and low impacts (0.13 [0.07,0.19]) (beta coefficient, with 95 % CI). Likewise in MAC, reported moderate-high-impact activities showed a stronger association with higher impacts (0.26 [0.14, 0.37]), compared with medium (0.14 [0.05, 0.22]) and low impacts (0.03 [-0.02, 0.08]). Our new accelerometer method appears to provide valid measures of higher vertical impacts in older adults. Results obtained from the three population-based cohorts indicate that older adults generally experience very limited higher impact weight-bearing PA.
Zastrow, Stefan; Brookman-May, Sabine; Cong, Thi Anh Phuong; Jurk, Stanislaw; von Bar, Immanuel; Novotny, Vladimir; Wirth, Manfred
2015-03-01
To predict outcome of patients with renal cell carcinoma (RCC) who undergo surgical therapy, risk models and nomograms are valuable tools. External validation on independent datasets is crucial for evaluating accuracy and generalizability of these models. The objective of the present study was to externally validate the postoperative nomogram developed by Karakiewicz et al. for prediction of cancer-specific survival. A total of 1,480 consecutive patients with a median follow-up of 82 months (IQR 46-128) were included into this analysis with 268 RCC-specific deaths. Nomogram-estimated survival probabilities were compared with survival probabilities of the actual cohort, and concordance indices were calculated. Calibration plots and decision curve analyses were used for evaluating calibration and clinical net benefit of the nomogram. Concordance between predictions of the nomogram and survival rates of the cohort was 0.911 after 12, 0.909 after 24 months and 0.896 after 60 months. Comparison of predicted probabilities and actual survival estimates with calibration plots showed an overestimation of tumor-specific survival based on nomogram predictions of high-risk patients, although calibration plots showed a reasonable calibration for probability ranges of interest. Decision curve analysis showed a positive net benefit of nomogram predictions for our patient cohort. The postoperative Karakiewicz nomogram provides a good concordance in this external cohort and is reasonably calibrated. It may overestimate tumor-specific survival in high-risk patients, which should be kept in mind when counseling patients. A positive net benefit of nomogram predictions was proven.
Mearelli, Filippo; Fiotti, Nicola; Giansante, Carlo; Casarsa, Chiara; Orso, Daniele; De Helmersen, Marco; Altamura, Nicola; Ruscio, Maurizio; Castello, Luigi Mario; Colonetti, Efrem; Marino, Rossella; Barbati, Giulia; Bregnocchi, Andrea; Ronco, Claudio; Lupia, Enrico; Montrucchio, Giuseppe; Muiesan, Maria Lorenza; Di Somma, Salvatore; Avanzi, Gian Carlo; Biolo, Gianni
2018-05-07
To derive and validate a predictive algorithm integrating a nomogram-based prediction of the pretest probability of infection with a panel of serum biomarkers, which could robustly differentiate sepsis/septic shock from noninfectious systemic inflammatory response syndrome. Multicenter prospective study. At emergency department admission in five University hospitals. Nine-hundred forty-seven adults in inception cohort and 185 adults in validation cohort. None. A nomogram, including age, Sequential Organ Failure Assessment score, recent antimicrobial therapy, hyperthermia, leukocytosis, and high C-reactive protein values, was built in order to take data from 716 infected patients and 120 patients with noninfectious systemic inflammatory response syndrome to predict pretest probability of infection. Then, the best combination of procalcitonin, soluble phospholypase A2 group IIA, presepsin, soluble interleukin-2 receptor α, and soluble triggering receptor expressed on myeloid cell-1 was applied in order to categorize patients as "likely" or "unlikely" to be infected. The predictive algorithm required only procalcitonin backed up with soluble phospholypase A2 group IIA determined in 29% of the patients to rule out sepsis/septic shock with a negative predictive value of 93%. In a validation cohort of 158 patients, predictive algorithm reached 100% of negative predictive value requiring biomarker measurements in 18% of the population. We have developed and validated a high-performing, reproducible, and parsimonious algorithm to assist emergency department physicians in distinguishing sepsis/septic shock from noninfectious systemic inflammatory response syndrome.
Vrijens, Karen; Winckelmans, Ellen; Tsamou, Maria; Baeyens, Willy; De Boever, Patrick; Jennen, Danyel; de Kok, Theo M.; Den Hond, Elly; Lefebvre, Wouter; Plusquin, Michelle; Reynders, Hans; Schoeters, Greet; Van Larebeke, Nicolas; Vanpoucke, Charlotte; Kleinjans, Jos; Nawrot, Tim S.
2016-01-01
Background: Particulate matter (PM) exposure leads to premature death, mainly due to respiratory and cardiovascular diseases. Objectives: Identification of transcriptomic biomarkers of air pollution exposure and effect in a healthy adult population. Methods: Microarray analyses were performed in 98 healthy volunteers (48 men, 50 women). The expression of eight sex-specific candidate biomarker genes (significantly associated with PM10 in the discovery cohort and with a reported link to air pollution-related disease) was measured with qPCR in an independent validation cohort (75 men, 94 women). Pathway analysis was performed using Gene Set Enrichment Analysis. Average daily PM2.5 and PM10 exposures over 2-years were estimated for each participant’s residential address using spatiotemporal interpolation in combination with a dispersion model. Results: Average long-term PM10 was 25.9 (± 5.4) and 23.7 (± 2.3) μg/m3 in the discovery and validation cohorts, respectively. In discovery analysis, associations between PM10 and the expression of individual genes differed by sex. In the validation cohort, long-term PM10 was associated with the expression of DNAJB5 and EAPP in men and ARHGAP4 (p = 0.053) in women. AKAP6 and LIMK1 were significantly associated with PM10 in women, although associations differed in direction between the discovery and validation cohorts. Expression of the eight candidate genes in the discovery cohort differentiated between validation cohort participants with high versus low PM10 exposure (area under the receiver operating curve = 0.92; 95% CI: 0.85, 1.00; p = 0.0002 in men, 0.86; 95% CI: 0.76, 0.96; p = 0.004 in women). Conclusions: Expression of the sex-specific candidate genes identified in the discovery population predicted PM10 exposure in an independent cohort of adults from the same area. Confirmation in other populations may further support this as a new approach for exposure assessment, and may contribute to the discovery of molecular mechanisms for PM-induced health effects. Citation: Vrijens K, Winckelmans E, Tsamou M, Baeyens W, De Boever P, Jennen D, de Kok TM, Den Hond E, Lefebvre W, Plusquin M, Reynders H, Schoeters G, Van Larebeke N, Vanpoucke C, Kleinjans J, Nawrot TS. 2017. Sex-specific associations between particulate matter exposure and gene expression in independent discovery and validation cohorts of middle-aged men and women. Environ Health Perspect 125:660–669; http://dx.doi.org/10.1289/EHP370 PMID:27740511
Liao, Katherine P; Ananthakrishnan, Ashwin N; Kumar, Vishesh; Xia, Zongqi; Cagan, Andrew; Gainer, Vivian S; Goryachev, Sergey; Chen, Pei; Savova, Guergana K; Agniel, Denis; Churchill, Susanne; Lee, Jaeyoung; Murphy, Shawn N; Plenge, Robert M; Szolovits, Peter; Kohane, Isaac; Shaw, Stanley Y; Karlson, Elizabeth W; Cai, Tianxi
2015-01-01
Typically, algorithms to classify phenotypes using electronic medical record (EMR) data were developed to perform well in a specific patient population. There is increasing interest in analyses which can allow study of a specific outcome across different diseases. Such a study in the EMR would require an algorithm that can be applied across different patient populations. Our objectives were: (1) to develop an algorithm that would enable the study of coronary artery disease (CAD) across diverse patient populations; (2) to study the impact of adding narrative data extracted using natural language processing (NLP) in the algorithm. Additionally, we demonstrate how to implement CAD algorithm to compare risk across 3 chronic diseases in a preliminary study. We studied 3 established EMR based patient cohorts: diabetes mellitus (DM, n = 65,099), inflammatory bowel disease (IBD, n = 10,974), and rheumatoid arthritis (RA, n = 4,453) from two large academic centers. We developed a CAD algorithm using NLP in addition to structured data (e.g. ICD9 codes) in the RA cohort and validated it in the DM and IBD cohorts. The CAD algorithm using NLP in addition to structured data achieved specificity >95% with a positive predictive value (PPV) 90% in the training (RA) and validation sets (IBD and DM). The addition of NLP data improved the sensitivity for all cohorts, classifying an additional 17% of CAD subjects in IBD and 10% in DM while maintaining PPV of 90%. The algorithm classified 16,488 DM (26.1%), 457 IBD (4.2%), and 245 RA (5.0%) with CAD. In a cross-sectional analysis, CAD risk was 63% lower in RA and 68% lower in IBD compared to DM (p<0.0001) after adjusting for traditional cardiovascular risk factors. We developed and validated a CAD algorithm that performed well across diverse patient populations. The addition of NLP into the CAD algorithm improved the sensitivity of the algorithm, particularly in cohorts where the prevalence of CAD was low. Preliminary data suggest that CAD risk was significantly lower in RA and IBD compared to DM.
Liao, Katherine P.; Ananthakrishnan, Ashwin N.; Kumar, Vishesh; Xia, Zongqi; Cagan, Andrew; Gainer, Vivian S.; Goryachev, Sergey; Chen, Pei; Savova, Guergana K.; Agniel, Denis; Churchill, Susanne; Lee, Jaeyoung; Murphy, Shawn N.; Plenge, Robert M.; Szolovits, Peter; Kohane, Isaac; Shaw, Stanley Y.; Karlson, Elizabeth W.; Cai, Tianxi
2015-01-01
Background Typically, algorithms to classify phenotypes using electronic medical record (EMR) data were developed to perform well in a specific patient population. There is increasing interest in analyses which can allow study of a specific outcome across different diseases. Such a study in the EMR would require an algorithm that can be applied across different patient populations. Our objectives were: (1) to develop an algorithm that would enable the study of coronary artery disease (CAD) across diverse patient populations; (2) to study the impact of adding narrative data extracted using natural language processing (NLP) in the algorithm. Additionally, we demonstrate how to implement CAD algorithm to compare risk across 3 chronic diseases in a preliminary study. Methods and Results We studied 3 established EMR based patient cohorts: diabetes mellitus (DM, n = 65,099), inflammatory bowel disease (IBD, n = 10,974), and rheumatoid arthritis (RA, n = 4,453) from two large academic centers. We developed a CAD algorithm using NLP in addition to structured data (e.g. ICD9 codes) in the RA cohort and validated it in the DM and IBD cohorts. The CAD algorithm using NLP in addition to structured data achieved specificity >95% with a positive predictive value (PPV) 90% in the training (RA) and validation sets (IBD and DM). The addition of NLP data improved the sensitivity for all cohorts, classifying an additional 17% of CAD subjects in IBD and 10% in DM while maintaining PPV of 90%. The algorithm classified 16,488 DM (26.1%), 457 IBD (4.2%), and 245 RA (5.0%) with CAD. In a cross-sectional analysis, CAD risk was 63% lower in RA and 68% lower in IBD compared to DM (p<0.0001) after adjusting for traditional cardiovascular risk factors. Conclusions We developed and validated a CAD algorithm that performed well across diverse patient populations. The addition of NLP into the CAD algorithm improved the sensitivity of the algorithm, particularly in cohorts where the prevalence of CAD was low. Preliminary data suggest that CAD risk was significantly lower in RA and IBD compared to DM. PMID:26301417
A Case for Transforming the Criterion of a Predictive Validity Study
ERIC Educational Resources Information Center
Patterson, Brian F.; Kobrin, Jennifer L.
2011-01-01
This study presents a case for applying a transformation (Box and Cox, 1964) of the criterion used in predictive validity studies. The goals of the transformation were to better meet the assumptions of the linear regression model and to reduce the residual variance of fitted (i.e., predicted) values. Using data for the 2008 cohort of first-time,…
Shulman, Eric; Kargoli, Faraj; Aagaard, Philip; Hoch, Ethan; Di Biase, Luigi; Fisher, John; Gross, Jay; Kim, Soo; Krumerman, Andrew; Ferrick, Kevin J
2016-01-01
A risk score for atrial fibrillation (AF) has been developed by the Framingham Heart Study and Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF consortium. However, validation of these risk scores in an inner-city population is uncertain. Thus, a validation model was built using the Framingham Risk Score for AF and CHARGE-AF covariates. An in and outpatient electrocardiographic database was interrogated from 2000 to 2013 for the development of AF. Patients were included if their age was >45 and <95 years, had <10-year follow-up, if their initial electrocardiogram was without AF, had ≥ 2 electrocardiograms, and declared a race and/or ethnicity as non-Hispanic white, African-American, or Hispanic. For the Framingham Heart Study, 49,599 patients met inclusion criteria, of which 4,860 developed AF. Discrimination analysis using area under the curve (AUC) for original risk equations: non-Hispanic white AUC = 0.712 (95% confidence interval [CI] 0.694 to 0.731), African-American AUC = 0.733 (95% CI 0.716 to 0.751), and Hispanic AUC = 0.740 (95% CI 0.723 to 0.757). For the CHARGE-AF, 45,571 patients met inclusion criteria, of which 4,512 developed AF. Non-Hispanic white AUC = 0.673 (95% CI 0.652 to 0.694), African-American AUC = 0.706 (95% CI 0.685 to 0.727), and Hispanic AUC = 0.711 (95% CI 0.691 to 0.732). Calibration analysis showed qualitative similarities between cohorts. In conclusion, this is the first study to validate both the Framingham Heart Study and CHARGE-AF risk scores in both a Hispanic and African-American cohort. All models predicted AF well across all race and ethnic cohorts. Copyright © 2016 Elsevier Inc. All rights reserved.
Pauling, L; Herman, Z S
1989-01-01
With the assumption of the validity of the Hardin Jones principle that the death rate of members of a homogeneous cohort of cancer patients is constant, three criteria for the validity of clinical trials of cancer treatments are formulated. These criteria are satisfied by most published clinical trials, but one trial was found to violate all three, rendering the validity of its reported results uncertain. PMID:2780542
A Two-Biomarker Model Predicts Mortality in the Critically Ill with Sepsis.
Mikacenic, Carmen; Price, Brenda L; Harju-Baker, Susanna; O'Mahony, D Shane; Robinson-Cohen, Cassianne; Radella, Frank; Hahn, William O; Katz, Ronit; Christiani, David C; Himmelfarb, Jonathan; Liles, W Conrad; Wurfel, Mark M
2017-10-15
Improving the prospective identification of patients with systemic inflammatory response syndrome (SIRS) and sepsis at low risk for organ dysfunction and death is a major clinical challenge. To develop and validate a multibiomarker-based prediction model for 28-day mortality in critically ill patients with SIRS and sepsis. A derivation cohort (n = 888) and internal test cohort (n = 278) were taken from a prospective study of critically ill intensive care unit (ICU) patients meeting two of four SIRS criteria at an academic medical center for whom plasma was obtained within 24 hours. The validation cohort (n = 759) was taken from a prospective cohort enrolled at another academic medical center ICU for whom plasma was obtained within 48 hours. We measured concentrations of angiopoietin-1, angiopoietin-2, IL-6, IL-8, soluble tumor necrosis factor receptor-1, soluble vascular cell adhesion molecule-1, granulocyte colony-stimulating factor, and soluble Fas. We identified a two-biomarker model in the derivation cohort that predicted mortality (area under the receiver operator characteristic curve [AUC], 0.79; 95% confidence interval [CI], 0.74-0.83). It performed well in the internal test cohort (AUC, 0.75; 95% CI, 0.65-0.85) and the external validation cohort (AUC, 0.77; 95% CI, 0.72-0.83). We determined a model score threshold demonstrating high negative predictive value (0.95) for death. In addition to a low risk of death, patients below this threshold had shorter ICU length of stay, lower incidence of acute kidney injury, acute respiratory distress syndrome, and need for vasopressors. We have developed a simple, robust biomarker-based model that identifies patients with SIRS/sepsis at low risk for death and organ dysfunction.
Karres, Julian; Kieviet, Noera; Eerenberg, Jan-Peter; Vrouenraets, Bart C
2018-01-01
Early mortality after hip fracture surgery is high and preoperative risk assessment for the individual patient is challenging. A risk model could identify patients in need of more intensive perioperative care, provide insight in the prognosis, and allow for risk adjustment in audits. This study aimed to develop and validate a risk prediction model for 30-day mortality after hip fracture surgery: the Hip fracture Estimator of Mortality Amsterdam (HEMA). Data on 1050 consecutive patients undergoing hip fracture surgery between 2004 and 2010 were retrospectively collected and randomly split into a development cohort (746 patients) and validation cohort (304 patients). Logistic regression analysis was performed in the development cohort to determine risk factors for the HEMA. Discrimination and calibration were assessed in both cohorts using the area under the receiver operating characteristic curve (AUC), the Hosmer-Lemeshow goodness-of-fit test, and by stratification into low-, medium- and high-risk groups. Nine predictors for 30-day mortality were identified and used in the final model: age ≥85 years, in-hospital fracture, signs of malnutrition, myocardial infarction, congestive heart failure, current pneumonia, renal failure, malignancy, and serum urea >9 mmol/L. The HEMA showed good discrimination in the development cohort (AUC = 0.81) and the validation cohort (AUC = 0.79). The Hosmer-Lemeshow test indicated no lack of fit in either cohort (P > 0.05). The HEMA is based on preoperative variables and can be used to predict the risk of 30-day mortality after hip fracture surgery for the individual patient. Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.
Márquez-González, Horacio; Jiménez-Báez, María Valeria; Muñoz-Ramírez, C Mireya; Yáñez-Gutiérrez, Lucelli; Huelgas-Plaza, Ana C; Almeida-Gutiérrez, Eduardo; Villa-Romero, Antonio Rafael
2015-06-01
Prognostic scales or scores are useful for physicians who work in neonatal intensive care units. There are several validated neonatal scores but they are mostly applicable to low birth weight infants. The aim of this study was to develop and validate a mortality prognostic score in newborn infants, that would include new prognostic outcome measures. The study was conducted in a mother and child hospital in the city of Mexico, part of the Instituto Mexicano del Seguro Social (Mexican Institute of Social Security). In the first phase of the study, a nested case-control study was designed (newborn infants admitted on the basis of severity criteria during the first day of life), in which a scale was identified and developed with gradual parameters of cumulative score consisting of nine independent outcome measures to predict death, as follows: weight, metabolic acidemia, lactate, PaO2/FiO2, p(A-a) O2, A/a, platelets and serum glucose.Validation was performed in a matched prospective cohort, using 7-day mortality as an endpoint. The initial cohort consisted of 424 newborn infants. Twenty-two cases and 132 controls were selected; and 9 outcome measures were identified, making up the scale named neonatal mortality score-9 Mexico. The validation cohort consisted of 227 newborn infants. Forty-four (19%) deaths were recorded, with an area under the curve (AUC) of 0.92. With a score between 16 and 18, an 85 (11-102) hazard ratio, 99% specificity, 71% positive predictive value and 90% negative predictive value were reported. Conclusions .The proposed scale is a reliable tool to predict severity in newborn infants.
Lung, For-Wey; Chen, Po-Fei; Shu, Bih-Ching
2012-08-01
This study aimed to investigate the concurrent validity of the parent-report Taiwan Birth Cohort Study Developmental Instrument (TBCS-DI) with the Bayley Scales of Infant Development-Second Edition (BSID-II) and the Wechsler Preschool and Primary Scale of Intelligence-Revised (WPPSI-R) at 6, 18, 36, and 60 months. 100 children were recruited at 6 months, 88 children followed-up at 18 months, 71 at 36 months, and 53 at 60 months. Longitudinally, the parent-report TBCS-DI, with the professional psychological assessments of the BSID-II and the WPPSI-R showed predictive validity. Looking at each time point in cross section, at 6 and 18 months the TBCS-DI had good concurrent validity with the BSID-II, and at 36 and 60 months the TBCS-DI was correlated only with the motor and performance domains of the BSID-II and WPPSI-R. With further investigation, the TBCS-DI may be used both in research and in clinical settings.
Novel Equations to Estimate Lean Body Mass in Maintenance Hemodialysis Patients
Noori, Nazanin; Kovesdy, Csaba P; Bross, Rachelle; Lee, Martin; Oreopoulos, Antigone; Benner, Deborah; Mehrotra, Rajnish; Kopple, Joel D; Kalantar-Zadeh, Kamyar
2010-01-01
Background Lean body mass (LBM) is an important nutritional measure representing muscle mass and somatic protein in hemodialysis patients, in whom we developed and tested equations to estimate LBM. Study Design A study of diagnostic test accuracy. Setting and Participants The development cohort included 118 hemodialysis patients, with LBM measured using dual-energy -X-ray absorptiometry (DEXA) and near-infrared (NIR) interactance. The validation cohort included 612 additional hemodialysis patients with LBM measured using portable NIR interactance technique during hemodialysis. Index Tests 3-month averaged serum concentrations of creatinine, albumin and prealbumin, normalized protein-nitrogen-appearance, mid-arm muscle circumference (MAMC), handgrip strength, and subjective global assessment of nutrition. Reference Test LBM measured via DEXA in the development cohort and via NIR interactance in validation cohorts. Results In the development cohort, DEXA and NIR interactance were strongly correlated (r=0.94, p<0.001). DEXA-measured LBM correlated with serum creatinine, MAMC, handgrip strength but not with other nutritional markers. Three regression equations to estimate DEXA-measured LBM were developed based on each of these three surrogates and gender, height, weight, and age (and urea reduction ratio for the serum creatinine regression). In the validation cohort, the validity of the equations were tested against the NIR interactance measured LBM. The equation estimates correlated well with NIR interactance measured LBM (R221 ≥0.88), although in higher LBM ranges they tended to underestimate it. Median differences between equation estimates and NIR interactance-measured LBM were 3.4 (25th–75th percentile, −3.2 to 12.0) and 3.0 (25th–75th percentile, 1.1–5.1) kg for serum creatinine and 4.0 (25th–75th percentile, −2.6 to 13.6) and 3.7 (25th–75th percentile, 1.3–6.0) kg for MAMC. Limitations DEXA measurements were performed on a non-dialysis day whereas NIR interactance was obtained during the hemodialysis treatment, with likelihood of confounding by volume status variations. Conclusions Comparing to reference measures of LBM, equations using serum creatinine, MAMC, or handgrip strength and demographic variables can accurately estimate LBM in long-term hemodialysis patients. PMID:21184920
Tangri, Navdeep; Grams, Morgan E.; Levey, Andrew S.; Coresh, Josef; Appel, Lawrence; Astor, Brad C.; Chodick, Gabriel; Collins, Allan J.; Djurdjev, Ognjenka; Elley, C. Raina; Evans, Marie; Garg, Amit X.; Hallan, Stein I.; Inker, Lesley; Ito, Sadayoshi; Jee, Sun Ha; Kovesdy, Csaba P.; Kronenberg, Florian; Lambers Heerspink, Hiddo J.; Marks, Angharad; Nadkarni, Girish N.; Navaneethan, Sankar D.; Nelson, Robert G.; Titze, Stephanie; Sarnak, Mark J.; Stengel, Benedicte; Woodward, Mark; Iseki, Kunitoshi
2016-01-01
Importance Identifying patients at risk of chronic kidney disease (CKD) progression may facilitate more optimal nephrology care. Kidney failure risk equations (KFREs) were previously developed and validated in two Canadian cohorts. Validation in other regions and in CKD populations not under the care of a nephrologist is needed. Objective To evaluate the accuracy of the KFREs across different geographic regions and patient populations through individual-participant data meta-analysis. Data Sources Thirty-one cohorts, including 721,357 participants with CKD Stages 3–5 in over 30 countries spanning 4 continents, were studied. These cohorts collected data from 1982 through 2014. Study Selection Cohorts participating in the CKD Prognosis Consortium with data on end-stage renal disease. Data Extraction and Synthesis Data were obtained and statistical analyses were performed between July 2012 and June 2015. Using the risk factors from the original KFREs, cohort-specific hazard ratios were estimated, and combined in meta-analysis to form new “pooled” KFREs. Original and pooled equation performance was compared, and the need for regional calibration factors was assessed. Main Outcome and Measure Kidney failure (treatment by dialysis or kidney transplantation). Results During a median follow-up of 4 years, 23,829 cases of kidney failure were observed. The original KFREs achieved excellent discrimination (ability to differentiate those who developed kidney failure from those who did not) across all cohorts (overall C statistic, 0.90 (95% CI 0.89–0.92) at 2 years and 0.88 (95% CI 0.86–0.90) at 5 years); discrimination in subgroups by age, race, and diabetes status was similar. There was no improvement with the pooled equations. Calibration (the difference between observed and predicted risk) was adequate in North American cohorts, but the original KFREs overestimated risk in some non-North American cohorts. Addition of a calibration factor that lowered the baseline risk by 32.9% at 2 years and 16.5% at 5 years improved the calibration in 12/15 and 10/13 non-North American cohorts at 2 and 5 years, respectively (p=0.04 and p=0.02). Conclusions and Relevance KFREs developed in a Canadian population showed high discrimination and adequate calibration when validated in 31 multinational cohorts. However, in some regions the addition of a calibration factor may be necessary. PMID:26757465
Development and validation of a prognostic index for 4-year mortality in older adults.
Lee, Sei J; Lindquist, Karla; Segal, Mark R; Covinsky, Kenneth E
2006-02-15
Both comorbid conditions and functional measures predict mortality in older adults, but few prognostic indexes combine both classes of predictors. Combining easily obtained measures into an accurate predictive model could be useful to clinicians advising patients, as well as policy makers and epidemiologists interested in risk adjustment. To develop and validate a prognostic index for 4-year mortality using information that can be obtained from patient report. Using the 1998 wave of the Health and Retirement Study (HRS), a population-based study of community-dwelling US adults older than 50 years, we developed the prognostic index from 11,701 individuals and validated the index with 8009. Individuals were asked about their demographic characteristics, whether they had specific diseases, and whether they had difficulty with a series of functional measures. We identified variables independently associated with mortality and weighted the variables to create a risk index. Death by December 31, 2002. The overall response rate was 81%. During the 4-year follow-up, there were 1361 deaths (12%) in the development cohort and 1072 deaths (13%) in the validation cohort. Twelve independent predictors of mortality were identified: 2 demographic variables (age: 60-64 years, 1 point; 65-69 years, 2 points; 70-74 years, 3 points; 75-79 years, 4 points; 80-84 years, 5 points, >85 years, 7 points and male sex, 2 points), 6 comorbid conditions (diabetes, 1 point; cancer, 2 points; lung disease, 2 points; heart failure, 2 points; current tobacco use, 2 points; and body mass index <25, 1 point), and difficulty with 4 functional variables (bathing, 2 points; walking several blocks, 2 points; managing money, 2 points, and pushing large objects, 1 point. Scores on the risk index were strongly associated with 4-year mortality in the validation cohort, with 0 to 5 points predicting a less than 4% risk, 6 to 9 points predicting a 15% risk, 10 to 13 points predicting a 42% risk, and 14 or more points predicting a 64% risk. The risk index showed excellent discrimination with a cstatistic of 0.84 in the development cohort and 0.82 in the validation cohort. This prognostic index, incorporating age, sex, self-reported comorbid conditions, and functional measures, accurately stratifies community-dwelling older adults into groups at varying risk of mortality.
Choo, Min Soo; Jeong, Seong Jin; Cho, Sung Yong; Yoo, Changwon; Jeong, Chang Wook; Ku, Ja Hyeon; Oh, Seung-June
2017-04-01
We aimed to externally validate the prediction model we developed for having bladder outlet obstruction (BOO) and requiring prostatic surgery using 2 independent data sets from tertiary referral centers, and also aimed to validate a mobile app for using this model through usability testing. Formulas and nomograms predicting whether a subject has BOO and needs prostatic surgery were validated with an external validation cohort from Seoul National University Bundang Hospital and Seoul Metropolitan Government-Seoul National University Boramae Medical Center between January 2004 and April 2015. A smartphone-based app was developed, and 8 young urologists were enrolled for usability testing to identify any human factor issues of the app. A total of 642 patients were included in the external validation cohort. No significant differences were found in the baseline characteristics of major parameters between the original (n=1,179) and the external validation cohort, except for the maximal flow rate. Predictions of requiring prostatic surgery in the validation cohort showed a sensitivity of 80.6%, a specificity of 73.2%, a positive predictive value of 49.7%, and a negative predictive value of 92.0%, and area under receiver operating curve of 0.84. The calibration plot indicated that the predictions have good correspondence. The decision curve showed also a high net benefit. Similar evaluation results using the external validation cohort were seen in the predictions of having BOO. Overall results of the usability test demonstrated that the app was user-friendly with no major human factor issues. External validation of these newly developed a prediction model demonstrated a moderate level of discrimination, adequate calibration, and high net benefit gains for predicting both having BOO and requiring prostatic surgery. Also a smartphone app implementing the prediction model was user-friendly with no major human factor issue.
Glenn, Beth A.; Bastani, Roshan; Maxwell, Annette E.
2013-01-01
Objective Threats to external validity including pretest sensitization and the interaction of selection and an intervention are frequently overlooked by researchers despite their potential to significantly influence study outcomes. The purpose of this investigation was to conduct secondary data analyses to assess the presence of external validity threats in the setting of a randomized trial designed to promote mammography use in a high risk sample of women. Design During the trial, recruitment and intervention implementation took place in three cohorts (with different ethnic composition), utilizing two different designs (pretest-posttest control group design; posttest only control group design). Results Results reveal that the intervention produced different outcomes across cohorts, dependent upon the research design used and the characteristics of the sample. Conclusion These results illustrate the importance of weighing the pros and cons of potential research designs before making a selection and attending more closely to issues of external validity. PMID:23289517
Glenn, Beth A; Bastani, Roshan; Maxwell, Annette E
2013-01-01
Threats to external validity, including pretest sensitisation and the interaction of selection and an intervention, are frequently overlooked by researchers despite their potential to significantly influence study outcomes. The purpose of this investigation was to conduct secondary data analyses to assess the presence of external validity threats in the setting of a randomised trial designed to promote mammography use in a high-risk sample of women. During the trial, recruitment and intervention, implementation took place in three cohorts (with different ethnic composition), utilising two different designs (pretest-posttest control group design and posttest only control group design). Results reveal that the intervention produced different outcomes across cohorts, dependent upon the research design used and the characteristics of the sample. These results illustrate the importance of weighing the pros and cons of potential research designs before making a selection and attending more closely to issues of external validity.
Cheong, Jae-Ho; Yang, Han-Kwang; Kim, Hyunki; Kim, Woo Ho; Kim, Young-Woo; Kook, Myeong-Cherl; Park, Young-Kyu; Kim, Hyung-Ho; Lee, Hye Seung; Lee, Kyung Hee; Gu, Mi Jin; Kim, Ha Yan; Lee, Jinae; Choi, Seung Ho; Hong, Soonwon; Kim, Jong Won; Choi, Yoon Young; Hyung, Woo Jin; Jang, Eunji; Kim, Hyeseon; Huh, Yong-Min; Noh, Sung Hoon
2018-05-01
Adjuvant chemotherapy after surgery improves survival of patients with stage II-III, resectable gastric cancer. However, the overall survival benefit observed after adjuvant chemotherapy is moderate, suggesting that not all patients with resectable gastric cancer treated with adjuvant chemotherapy benefit from it. We aimed to develop and validate a predictive test for adjuvant chemotherapy response in patients with resectable, stage II-III gastric cancer. In this multi-cohort, retrospective study, we developed through a multi-step strategy a predictive test consisting of two rule-based classifier algorithms with predictive value for adjuvant chemotherapy response and prognosis. Exploratory bioinformatics analyses identified biologically relevant candidate genes in gastric cancer transcriptome datasets. In the discovery analysis, a four-gene, real-time RT-PCR assay was developed and analytically validated in formalin-fixed, paraffin-embedded (FFPE) tumour tissues from an internal cohort of 307 patients with stage II-III gastric cancer treated at the Yonsei Cancer Center with D2 gastrectomy plus adjuvant fluorouracil-based chemotherapy (n=193) or surgery alone (n=114). The same internal cohort was used to evaluate the prognostic and chemotherapy response predictive value of the single patient classifier genes using associations with 5-year overall survival. The results were validated with a subset (n=625) of FFPE tumour samples from an independent cohort of patients treated in the CLASSIC trial (NCT00411229), who received D2 gastrectomy plus capecitabine and oxaliplatin chemotherapy (n=323) or surgery alone (n=302). The primary endpoint was 5-year overall survival. We identified four classifier genes related to relevant gastric cancer features (GZMB, WARS, SFRP4, and CDX1) that formed the single patient classifier assay. In the validation cohort, the prognostic single patient classifier (based on the expression of GZMB, WARS, and SFRP4) identified 79 (13%) of 625 patients as low risk, 296 (47%) as intermediate risk, and 250 (40%) as high risk, and 5-year overall survival for these groups was 83·2% (95% CI 75·2-92·0), 74·8% (69·9-80·1), and 66·0% (60·1-72·4), respectively (p=0·012). The predictive single patient classifier (based on the expression of GZMB, WARS, and CDX1) assigned 281 (45%) of 625 patients in the validation cohort to the chemotherapy-benefit group and 344 (55%) to the no-benefit group. In the predicted chemotherapy-benefit group, 5-year overall survival was significantly improved in those patients who had received adjuvant chemotherapy after surgery compared with those who received surgery only (80% [95% CI 73·5-87·1] vs 64·5% [56·8-73·3]; univariate hazard ratio 0·47 [95% CI 0·30-0·75], p=0·0015), whereas no such improvement in 5-year overall survival was observed in the no-benefit group (72·9% [66·5-79·9] in patients who received chemotherapy plus surgery vs 72·5% [65·8-79·9] in patients who only had surgery; 0·93 [0·62-1·38], p=0·71). The predictive single patient classifier groups (chemotherapy benefit vs no-benefit) could predict adjuvant chemotherapy benefit in terms of 5-year overall survival in the validation cohort (p interaction =0·036 in univariate analysis). Similar results were obtained in the internal evaluation cohort. The single patient classifiers validated in this study provide clinically important prognostic information independent of standard risk-stratification methods and predicted chemotherapy response after surgery in two independent cohorts of patients with resectable, stage II-III gastric cancer. The single patient classifiers could complement TNM staging to optimise decision making in patients with resectable gastric cancer who are eligible for adjuvant chemotherapy after surgery. Further validation of these results in prospective studies is warranted. Ministry of ICT and Future Planning; Ministry of Trade, Industry, and Energy; and Ministry of Health and Welfare. Copyright © 2018 Elsevier Ltd. All rights reserved.
Shahjehan, Khurram; Li, Guangxi; Dhokarh, Rajanigandha; Kashyap, Rahul; Janish, Christopher; Alsara, Anas; Jaffe, Allan S.; Hubmayr, Rolf D.; Gajic, Ognjen
2012-01-01
Background: At the onset of acute hypoxic respiratory failure, critically ill patients with acute lung injury (ALI) may be difficult to distinguish from those with cardiogenic pulmonary edema (CPE). No single clinical parameter provides satisfying prediction. We hypothesized that a combination of those will facilitate early differential diagnosis. Methods: In a population-based retrospective development cohort, validated electronic surveillance identified critically ill adult patients with acute pulmonary edema. Recursive partitioning and logistic regression were used to develop a decision support tool based on routine clinical information to differentiate ALI from CPE. Performance of the score was validated in an independent cohort of referral patients. Blinded post hoc expert review served as gold standard. Results: Of 332 patients in a development cohort, expert reviewers (κ, 0.86) classified 156 as having ALI and 176 as having CPE. The validation cohort had 161 patients (ALI = 113, CPE = 48). The score was based on risk factors for ALI and CPE, age, alcohol abuse, chemotherapy, and peripheral oxygen saturation/Fio2 ratio. It demonstrated good discrimination (area under curve [AUC] = 0.81; 95% CI, 0.77-0.86) and calibration (Hosmer-Lemeshow [HL] P = .16). Similar performance was obtained in the validation cohort (AUC = 0.80; 95% CI, 0.72-0.88; HL P = .13). Conclusions: A simple decision support tool accurately classifies acute pulmonary edema, reserving advanced testing for a subset of patients in whom satisfying prediction cannot be made. This novel tool may facilitate early inclusion of patients with ALI and CPE into research studies as well as improve and rationalize clinical management and resource use. PMID:22030803
Daniels, Susan E; Beineke, Philip; Rhees, Brian; McPherson, John A; Kraus, William E; Thomas, Gregory S; Rosenberg, Steven
2014-10-01
A gene expression score (GES) for obstructive coronary artery disease (CAD) has been validated in two multicenter studies. Receiver-operating characteristics (ROC) analysis of the GES on an expanded Personalized Risk Evaluation and Diagnosis in the Coronary Tree (PREDICT) cohort (NCT no. 00500617) with CAD defined by quantitative coronary angiography (QCA) or clinical reads yielded similar performance (area under the curve (AUC)=0.70, N=1,502) to the original validation cohort (AUC=0.70, N=526). Analysis of 138 non-Caucasian and 1,364 Caucasian patients showed very similar performance (AUCs=0.72 vs. 0.70). To assess analytic stability, stored samples of the original validation cohort (N=526) was re-tested after 5 years, and the mean score changed from 20.3 to 19.8 after 5 years (N=501, 95 %). To assess patient scores over time, GES was determined on samples from 173 Coronary Obstruction Detection by Molecular Personalized Gene Expression (COMPASS) study (NCT no. 01117506) patients at approximately 1 year post-enrollment. Mean scores increased slightly from 15.9 to 17.3, corresponding to a 2.5 % increase in obstructive CAD likelihood. Changes in cardiovascular medications did not show a significant change in GES.
Vermaat, Joost S; Gerritse, Frank L; van der Veldt, Astrid A; Roessingh, Wijnand M; Niers, Tatjana M; Oosting, Sjoukje F; Sleijfer, Stefan; Roodhart, Jeanine M; Beijnen, Jos H; Schellens, Jan H; Gietema, Jourik A; Boven, Epie; Richel, Dick J; Haanen, John B; Voest, Emile E
2012-10-01
We recently identified apolipoprotein A2 (ApoA2) and serum amyloid α (SAA) as independent prognosticators in metastatic renal cell carcinoma (mRCC) patients, thereby improving the accuracy of the Memorial-Sloan Kettering Cancer Center (MSKCC) model. Validate these results prospectively in a separate cohort of mRCC patients treated with tyrosine kinase inhibitors (TKIs). For training we used 114 interferon-treated mRCC patients (inclusion 2001-2006). For validation we studied 151 TKI-treated mRCC patients (inclusion 2003-2009). Using Cox proportional hazards regression analysis, SAA and ApoA2 were associated with progression-free survival (PFS) and overall survival (OS). In 72 TKI-treated patients, SAA levels were analyzed longitudinally as a potential early marker for treatment effect. Baseline ApoA2 and SAA levels significantly predicted PFS and OS in the training and validation cohorts. Multivariate analysis identified SAA in both separate patient sets as a robust and independent prognosticator for PFS and OS. In contrast to our previous findings, ApoA2 interacted with SAA in the validation cohort and did not contribute to a better predictive accuracy than SAA alone and was therefore excluded from further analysis. According to the tertiles of SAA levels, patients were categorized in three risk groups, demonstrating accurate risk prognostication. SAA as a single biomarker showed equal prognostic accuracy when compared with the multifactorial MSKCC risk mode. Using receiver operating characteristic analysis, SAA levels >71 ng/ml were designated as the optimal cut-off value in the training cohort, which was confirmed for its significant sensitivity and specificity in the validation cohort. Applying SAA >71 ng/ml as an additional risk factor significantly improved the predictive accuracy of the MSKCC model in both independent cohorts. Changes in SAA levels after 6-8 wk of TKI treatment had no value in predicting treatment outcome. SAA but not ApoA2 was shown to be a robust and independent prognosticator for PFS and OS in mRCC patients. When incorporated in the MSKCC model, SAA showed additional prognostic value for patient management. Copyright © 2012 European Association of Urology. Published by Elsevier B.V. All rights reserved.
O'Donnell, Martin J; Fang, Jiming; D'Uva, Cami; Saposnik, Gustavo; Gould, Linda; McGrath, Emer; Kapral, Moira K
2012-11-12
We sought to develop and validate a simple clinical prediction rule for death and severe disability after acute ischemic stroke that can be used by general clinicians at the time of hospital admission. We analyzed data from a registry of 9847 patients (4943 in the derivation cohort and 4904 in the validation cohort) hospitalized with acute ischemic stroke and included in the Registry of the Canadian Stroke Network (July 1, 2003, to March 31, 2008; 11 regional stroke centers in Ontario, Canada). Outcome measures were 30-day and 1-year mortality and a modified Rankin score of 5 to 6 at discharge. Overall 30-day mortality was 11.5% (derivation cohort) and 13.5% (validation cohort). In the final multivariate model, we included 9 clinical variables that could be categorized as preadmission comorbidities (5 points for preadmission dependence [1.5], cancer [1.5], congestive heart failure [1.0], and atrial fibrillation [1.0]), level of consciousness (5 points for reduced level of consciousness), age (10 points, 1 point/decade), and neurologic focal deficit (5 points for significant/total weakness of the leg [2], weakness of the arm [2], and aphasia or neglect [1]). Maximum score is 25. In the validation cohort, the PLAN score (derived from preadmission comorbidities, level of consciousness, age, and neurologic deficit) predicted 30-day mortality (C statistic, 0.87), death or severe dependence at discharge (0.88), and 1-year mortality (0.84). The PLAN score also predicted favorable outcome (modified Rankin score, 0-2) at discharge (C statistic, 0.80). The PLAN clinical prediction rule identifies patients who will have a poor outcome after hospitalization for acute ischemic stroke. The score comprises clinical data available at the time of admission and may be determined by nonspecialist clinicians. Additional studies to independently validate the PLAN rule in different populations and settings are required.
Gomes, Anna; van der Wijk, Lars; Proost, Johannes H; Sinha, Bhanu; Touw, Daan J
2017-01-01
Gentamicin shows large variations in half-life and volume of distribution (Vd) within and between individuals. Thus, monitoring and accurately predicting serum levels are required to optimize effectiveness and minimize toxicity. Currently, two population pharmacokinetic models are applied for predicting gentamicin doses in adults. For endocarditis patients the optimal model is unknown. We aimed at: 1) creating an optimal model for endocarditis patients; and 2) assessing whether the endocarditis and existing models can accurately predict serum levels. We performed a retrospective observational two-cohort study: one cohort to parameterize the endocarditis model by iterative two-stage Bayesian analysis, and a second cohort to validate and compare all three models. The Akaike Information Criterion and the weighted sum of squares of the residuals divided by the degrees of freedom were used to select the endocarditis model. Median Prediction Error (MDPE) and Median Absolute Prediction Error (MDAPE) were used to test all models with the validation dataset. We built the endocarditis model based on data from the modeling cohort (65 patients) with a fixed 0.277 L/h/70kg metabolic clearance, 0.698 (±0.358) renal clearance as fraction of creatinine clearance, and Vd 0.312 (±0.076) L/kg corrected lean body mass. External validation with data from 14 validation cohort patients showed a similar predictive power of the endocarditis model (MDPE -1.77%, MDAPE 4.68%) as compared to the intensive-care (MDPE -1.33%, MDAPE 4.37%) and standard (MDPE -0.90%, MDAPE 4.82%) models. All models acceptably predicted pharmacokinetic parameters for gentamicin in endocarditis patients. However, these patients appear to have an increased Vd, similar to intensive care patients. Vd mainly determines the height of peak serum levels, which in turn correlate with bactericidal activity. In order to maintain simplicity, we advise to use the existing intensive-care model in clinical practice to avoid potential underdosing of gentamicin in endocarditis patients.
van der Wijk, Lars; Proost, Johannes H.; Sinha, Bhanu; Touw, Daan J.
2017-01-01
Gentamicin shows large variations in half-life and volume of distribution (Vd) within and between individuals. Thus, monitoring and accurately predicting serum levels are required to optimize effectiveness and minimize toxicity. Currently, two population pharmacokinetic models are applied for predicting gentamicin doses in adults. For endocarditis patients the optimal model is unknown. We aimed at: 1) creating an optimal model for endocarditis patients; and 2) assessing whether the endocarditis and existing models can accurately predict serum levels. We performed a retrospective observational two-cohort study: one cohort to parameterize the endocarditis model by iterative two-stage Bayesian analysis, and a second cohort to validate and compare all three models. The Akaike Information Criterion and the weighted sum of squares of the residuals divided by the degrees of freedom were used to select the endocarditis model. Median Prediction Error (MDPE) and Median Absolute Prediction Error (MDAPE) were used to test all models with the validation dataset. We built the endocarditis model based on data from the modeling cohort (65 patients) with a fixed 0.277 L/h/70kg metabolic clearance, 0.698 (±0.358) renal clearance as fraction of creatinine clearance, and Vd 0.312 (±0.076) L/kg corrected lean body mass. External validation with data from 14 validation cohort patients showed a similar predictive power of the endocarditis model (MDPE -1.77%, MDAPE 4.68%) as compared to the intensive-care (MDPE -1.33%, MDAPE 4.37%) and standard (MDPE -0.90%, MDAPE 4.82%) models. All models acceptably predicted pharmacokinetic parameters for gentamicin in endocarditis patients. However, these patients appear to have an increased Vd, similar to intensive care patients. Vd mainly determines the height of peak serum levels, which in turn correlate with bactericidal activity. In order to maintain simplicity, we advise to use the existing intensive-care model in clinical practice to avoid potential underdosing of gentamicin in endocarditis patients. PMID:28475651
Huang, Kuo-Cheng; Evans, Andrew; Donnelly, Bryan; Bismar, Tarek A
2017-04-01
SPINK1 is proposed as potential prognostic marker in prostate cancer (PCA). However, its relation to PTEN and ERG in localized PCA remains unclear. The study population consisted of two independent cohorts of men treated by radical prostatectomy for localized PCA (discovery n = 218 and validation n = 129). Patterns of association between SPINK1 and each of ERG and PTEN were evaluated by immunohistochemistry and fluorescence in situ hybridization. Associations between SPINK1 expression and various pathologic parameters and clinical outcome were also investigated. SPINK1 was expressed in 15.3 % and 10.9 % of cases in the discovery and validation cohort, respectively. SPINK expression was observed in 5.56 % of high-grade prostatic intraepithelial neoplasia and 1.1 % of adjacent morphologically benign prostatic glands. SPINK1 and ERG expression were almost exclusive, with only 1.0 % of the cases co-expressing both in the same core sample. SPINK1 interfocal and within-core heterogeneity was noted in 29.2 % and 64.6 % of cases, respectively. SPINK1 expression was not significantly associated with PTEN deletion in the two cohorts (p = 0.871 for discovery cohort and p = 0.293 for validation cohort). While SPINK1 expression did occur with hemizygous PTEN deletion, there was a complete absence of SPINK1 expression in PCA showing homozygous PTEN deletion, which was confirmed in the validation cohort (p = 0.02). Despite SPINK1's association with higher Gleason score (>7) (p = 0.02), it was not associated with other pathological parameters or biochemical recurrence post-radical prostatectomy. We documented absolute exclusivity between SPINK1 overexpression and homozygous PTEN deletion in localized PCA. SPINK1 and ERG expressions are exclusive events in PCA. SPINK1 is not of added prognostic value in localized PCA.
The Basilar Artery on Computed Tomography Angiography Prognostic Score for Basilar Artery Occlusion.
Alemseged, Fana; Shah, Darshan G; Diomedi, Marina; Sallustio, Fabrizio; Bivard, Andrew; Sharma, Gagan; Mitchell, Peter J; Dowling, Richard J; Bush, Steven; Yan, Bernard; Caltagirone, Carlo; Floris, Roberto; Parsons, Mark W; Levi, Christopher R; Davis, Stephen M; Campbell, Bruce C V
2017-03-01
Basilar artery occlusion is associated with high risk of disability and mortality. This study aimed to assess the prognostic value of a new radiological score: the Basilar Artery on Computed Tomography Angiography (BATMAN) score. A retrospective analysis of consecutive stroke patients with basilar artery occlusion diagnosed on computed tomographic angiography was performed. BATMAN score is a 10-point computed tomographic angiography-based grading system which incorporates thrombus burden and the presence of collaterals. Reliability was assessed with intraclass coefficient correlation. Good outcome was defined as modified Rankin Scale score of ≤3 at 3 months and successful reperfusion as thrombolysis in cerebral infarction 2b-3. BATMAN score was externally validated and compared with the Posterior Circulation Collateral score. The derivation cohort included 83 patients with 41 in the validation cohort. In receiver operating characteristic (ROC) analysis, BATMAN score had an area under receiver operating characteristic curve of 0.81 (95% confidence interval [CI], 0.7-0.9) in derivation cohort and an area under receiver operating characteristic curve of 0.74 (95% CI, 0.6-0.9) in validation cohort. In logistic regression adjusted for age and clinical severity, BATMAN score of <7 was associated with poor outcome in derivation cohort (odds ratio, 5.5; 95% CI, 1.4-21; P =0.01), in validation cohort (odds ratio, 6.9; 95% CI, 1.4-33; P =0.01), and in endovascular patients, after adjustment for recanalization and time to treatment (odds ratio, 4.8; 95% CI, 1.2-18; P =0.01). BATMAN score of <7 was not associated with recanalization. Interrater agreement was substantial (intraclass coefficient correlation, 0.85; 95% CI, 0.8-0.9). BATMAN score had greater accuracy compared with Posterior Circulation Collateral score ( P =0.04). The addition of collateral quality to clot burden in BATMAN score seems to improve prognostic accuracy in basilar artery occlusion patients. © 2017 American Heart Association, Inc.
Mente, Andrew; de Koning, Lawrence; Shannon, Harry S; Anand, Sonia S
2009-04-13
Although a wealth of literature links dietary factors and coronary heart disease (CHD), the strength of the evidence supporting valid associations has not been evaluated systematically in a single investigation. We conducted a systematic search of MEDLINE for prospective cohort studies or randomized trials investigating dietary exposures in relation to CHD. We used the Bradford Hill guidelines to derive a causation score based on 4 criteria (strength, consistency, temporality, and coherence) for each dietary exposure in cohort studies and examined for consistency with the findings of randomized trials. Strong evidence supports valid associations (4 criteria satisfied) of protective factors, including intake of vegetables, nuts, and "Mediterranean" and high-quality dietary patterns with CHD, and associations of harmful factors, including intake of trans-fatty acids and foods with a high glycemic index or load. Among studies of higher methodologic quality, there was also strong evidence for monounsaturated fatty acids and "prudent" and "western" dietary patterns. Moderate evidence (3 criteria) of associations exists for intake of fish, marine omega-3 fatty acids, folate, whole grains, dietary vitamins E and C, beta carotene, alcohol, fruit, and fiber. Insufficient evidence (< or =2 criteria) of association is present for intake of supplementary vitamin E and ascorbic acid (vitamin C); saturated and polyunsaturated fatty acids; total fat; alpha-linolenic acid; meat; eggs; and milk. Among the dietary exposures with strong evidence of causation from cohort studies, only a Mediterranean dietary pattern is related to CHD in randomized trials. The evidence supports a valid association of a limited number of dietary factors and dietary patterns with CHD. Future evaluation of dietary patterns, including their nutrient and food components, in cohort studies and randomized trials is recommended.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kerns, Sarah L.; Departments of Pathology and Genetics, Albert Einstein College of Medicine, Bronx, New York; Stock, Richard
2013-01-01
Purpose: To identify single nucleotide polymorphisms (SNPs) associated with development of erectile dysfunction (ED) among prostate cancer patients treated with radiation therapy. Methods and Materials: A 2-stage genome-wide association study was performed. Patients were split randomly into a stage I discovery cohort (132 cases, 103 controls) and a stage II replication cohort (128 cases, 102 controls). The discovery cohort was genotyped using Affymetrix 6.0 genome-wide arrays. The 940 top ranking SNPs selected from the discovery cohort were genotyped in the replication cohort using Illumina iSelect custom SNP arrays. Results: Twelve SNPs identified in the discovery cohort and validated in themore » replication cohort were associated with development of ED following radiation therapy (Fisher combined P values 2.1 Multiplication-Sign 10{sup -5} to 6.2 Multiplication-Sign 10{sup -4}). Notably, these 12 SNPs lie in or near genes involved in erectile function or other normal cellular functions (adhesion and signaling) rather than DNA damage repair. In a multivariable model including nongenetic risk factors, the odds ratios for these SNPs ranged from 1.6 to 5.6 in the pooled cohort. There was a striking relationship between the cumulative number of SNP risk alleles an individual possessed and ED status (Sommers' D P value = 1.7 Multiplication-Sign 10{sup -29}). A 1-allele increase in cumulative SNP score increased the odds for developing ED by a factor of 2.2 (P value = 2.1 Multiplication-Sign 10{sup -19}). The cumulative SNP score model had a sensitivity of 84% and specificity of 75% for prediction of developing ED at the radiation therapy planning stage. Conclusions: This genome-wide association study identified a set of SNPs that are associated with development of ED following radiation therapy. These candidate genetic predictors warrant more definitive validation in an independent cohort.« less
Oakland, Kathryn; Jairath, Vipul; Uberoi, Raman; Guy, Richard; Ayaru, Lakshmana; Mortensen, Neil; Murphy, Mike F; Collins, Gary S
2017-09-01
Acute lower gastrointestinal bleeding is a common reason for emergency hospital admission, and identification of patients at low risk of harm, who are therefore suitable for outpatient investigation, is a clinical and research priority. We aimed to develop and externally validate a simple risk score to identify patients with lower gastrointestinal bleeding who could safely avoid hospital admission. We undertook model development with data from the National Comparative Audit of Lower Gastrointestinal Bleeding from 143 hospitals in the UK in 2015. Multivariable logistic regression modelling was used to identify predictors of safe discharge, defined as the absence of rebleeding, blood transfusion, therapeutic intervention, 28 day readmission, or death. The model was converted into a simplified risk scoring system and was externally validated in 288 patients admitted with lower gastrointestinal bleeding (184 safely discharged) from two UK hospitals (Charing Cross Hospital, London, and Hammersmith Hospital, London) that had not contributed data to the development cohort. We calculated C statistics for the new model and did a comparative assessment with six previously developed risk scores. Of 2336 prospectively identified admissions in the development cohort, 1599 (68%) were safely discharged. Age, sex, previous admission for lower gastrointestinal bleeding, rectal examination findings, heart rate, systolic blood pressure, and haemoglobin concentration strongly discriminated safe discharge in the development cohort (C statistic 0·84, 95% CI 0·82-0·86) and in the validation cohort (0·79, 0·73-0·84). Calibration plots showed the new risk score to have good calibration in the validation cohort. The score was better than the Rockall, Blatchford, Strate, BLEED, AIMS65, and NOBLADS scores in predicting safe discharge. A score of 8 or less predicts a 95% probability of safe discharge. We developed and validated a novel clinical prediction model with good discriminative performance to identify patients with lower gastrointestinal bleeding who are suitable for safe outpatient management, which has important economic and resource implications. Bowel Disease Research Foundation and National Health Service Blood and Transplant. Copyright © 2017 Elsevier Ltd. All rights reserved.
Jensen, Garrett; Tang, Chad; Hess, Kenneth R; Bishop, Andrew J; Pan, Hubert Y; Li, Jing; Yang, James N; Tannir, Nizar M; Amini, Behrang; Tatsui, Claudio; Rhines, Laurence; Brown, Paul D; Ghia, Amol J
2017-01-01
We sought to validate the Prognostic Index for Spinal Metastases (PRISM), a scoring system that stratifies patients into subgroups by overall survival.Methods and materials: The PRISM was previously created from multivariate Cox regression with patients enrolled in prospective single institution trials of stereotactic spine radiosurgery (SSRS) for spinal metastasis. We assess model calibration and discrimination within a validation cohort of patients treated off-trial with SSRS for metastatic disease at the same institution. The training and validation cohorts consisted of 205 and 249 patients respectively. Similar survival trends were shown in the 4 PRISM. Survival was significantly different between PRISM subgroups (P<0.0001). C-index for the validation cohort was 0.68 after stratification into subgroups. We internally validated the PRISM with patients treated off-protocol, demonstrating that it can distinguish subgroups by survival, which will be useful for individualizing treatment of spinal metastases and stratifying patients for clinical trials.
Natural Language Processing for Asthma Ascertainment in Different Practice Settings.
Wi, Chung-Il; Sohn, Sunghwan; Ali, Mir; Krusemark, Elizabeth; Ryu, Euijung; Liu, Hongfang; Juhn, Young J
We developed and validated NLP-PAC, a natural language processing (NLP) algorithm based on predetermined asthma criteria (PAC) for asthma ascertainment using electronic health records at Mayo Clinic. To adapt NLP-PAC in a different health care setting, Sanford Children Hospital, by assessing its external validity. The study was designed as a retrospective cohort study that used a random sample of 2011-2012 Sanford Birth cohort (n = 595). Manual chart review was performed on the cohort for asthma ascertainment on the basis of the PAC. We then used half of the cohort as a training cohort (n = 298) and the other half as a blind test cohort to evaluate the adapted NLP-PAC algorithm. Association of known asthma-related risk factors with the Sanford-NLP algorithm-driven asthma ascertainment was tested. Among the eligible test cohort (n = 297), 160 (53%) were males, 268 (90%) white, and the median age was 2.3 years (range, 1.5-3.1 years). NLP-PAC, after adaptation, and the human abstractor identified 74 (25%) and 72 (24%) subjects, respectively, with 66 subjects identified by both approaches. Sensitivity, specificity, positive predictive value, and negative predictive value for the NLP algorithm in predicting asthma status were 92%, 96%, 89%, and 97%, respectively. The known risk factors for asthma identified by NLP (eg, smoking history) were similar to the ones identified by manual chart review. Successful implementation of NLP-PAC for asthma ascertainment in 2 different practice settings demonstrates the feasibility of automated asthma ascertainment leveraging electronic health record data with a potential to enable large-scale, multisite asthma studies to improve asthma care and research. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.
Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study.
Loza, Matthew J; Djukanovic, Ratko; Chung, Kian Fan; Horowitz, Daniel; Ma, Keying; Branigan, Patrick; Barnathan, Elliot S; Susulic, Vedrana S; Silkoff, Philip E; Sterk, Peter J; Baribaud, Frédéric
2016-12-15
Asthma is a disease of varying severity and differing disease mechanisms. To date, studies aimed at stratifying asthma into clinically useful phenotypes have produced a number of phenotypes that have yet to be assessed for stability and to be validated in independent cohorts. The aim of this study was to define and validate, for the first time ever, clinically driven asthma phenotypes using two independent, severe asthma cohorts: ADEPT and U-BIOPRED. Fuzzy partition-around-medoid clustering was performed on pre-specified data from the ADEPT participants (n = 156) and independently on data from a subset of U-BIOPRED asthma participants (n = 82) for whom the same variables were available. Models for cluster classification probabilities were derived and applied to the 12-month longitudinal ADEPT data and to a larger subset of the U-BIOPRED asthma dataset (n = 397). High and low type-2 inflammation phenotypes were defined as high or low Th2 activity, indicated by endobronchial biopsies gene expression changes downstream of IL-4 or IL-13. Four phenotypes were identified in the ADEPT (training) cohort, with distinct clinical and biomarker profiles. Phenotype 1 was "mild, good lung function, early onset", with a low-inflammatory, predominantly Type-2, phenotype. Phenotype 2 had a "moderate, hyper-responsive, eosinophilic" phenotype, with moderate asthma control, mild airflow obstruction and predominant Type-2 inflammation. Phenotype 3 had a "mixed severity, predominantly fixed obstructive, non-eosinophilic and neutrophilic" phenotype, with moderate asthma control and low Type-2 inflammation. Phenotype 4 had a "severe uncontrolled, severe reversible obstruction, mixed granulocytic" phenotype, with moderate Type-2 inflammation. These phenotypes had good longitudinal stability in the ADEPT cohort. They were reproduced and demonstrated high classification probability in two subsets of the U-BIOPRED asthma cohort. Focusing on the biology of the four clinical independently-validated easy-to-assess ADEPT asthma phenotypes will help understanding the unmet need and will aid in developing tailored therapies. NCT01274507 (ADEPT), registered October 28, 2010 and NCT01982162 (U-BIOPRED), registered October 30, 2013.
Hirono, Akira; Kusunose, Kenya; Kageyama, Norihito; Sumitomo, Masayuki; Abe, Masahiro; Fujinaga, Hiroyuki; Sata, Masataka
2018-01-01
An inter-arm systolic blood pressure difference (IAD) is associated with cardiovascular disease. The aim of this study was to develop and validate the optimal cut-off value of IAD as a predictor of major adverse cardiac events in patients with arteriosclerosis risk factors. From 2009 to 2014, 1076 patients who had at least one cardiovascular risk factor were included in the analysis. We defined 700 randomly selected patients as a development cohort to confirm that IAD was the predictor of cardiovascular events and to determine optimal cut-off value of IAD. Next, we validated outcomes in the remaining 376 patients as a validation cohort. The blood pressure (BP) of both arms measurements were done simultaneously using the ankle-brachial blood pressure index (ABI) form of automatic device. The primary endpoint was the cardiovascular event and secondary endpoint was the all-cause mortality. During a median period of 2.8 years, 143 patients reached the primary endpoint in the development cohort. In the multivariate Cox proportional hazards analysis, IAD was the strong predictor of cardiovascular events (hazard ratio: 1.03, 95% confidence interval: 1.01-1.05, p=0.005). The receiver operating characteristic curve revealed that 5mmHg was the optimal cut-off point of IAD to predict cardiovascular events (p<0.001). In the validation cohort, the presence of a large IAD (IAD ≥5mmHg) was significantly associated with the primary endpoint (p=0.021). IAD is significantly associated with future cardiovascular events in patients with arteriosclerosis risk factors. The optimal cut-off value of IAD is 5mmHg. Copyright © 2017 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.
Buchowski, Maciej S; Matthews, Charles E; Cohen, Sarah S; Signorello, Lisa B; Fowke, Jay H; Hargreaves, Margaret K; Schlundt, David G; Blot, William J
2012-08-01
Low physical activity (PA) is linked to cancer and other diseases prevalent in racial/ethnic minorities and low-income populations. This study evaluated the PA questionnaire (PAQ) used in the Southern Cohort Community Study, a prospective investigation of health disparities between African-American and white adults. The PAQ was administered upon entry into the cohort (PAQ1) and after 12-15 months (PAQ2) in 118 participants (40-60 year-old, 48% male, 74% African-American). Test-retest reliability (PAQ1 versus PAQ2) was assessed using Spearman correlations and the Wilcoxon signed rank test. Criterion validity of the PAQ was assessed via comparison with a PA monitor and a last-month PA survey (LMPAS), administered up to 4 times in the study period. The PAQ test-retest reliability ranged from 0.25-0.54 for sedentary behaviors and 0.22-0.47 for active behaviors. The criterion validity for the PAQ compared with PA monitor ranged from 0.21-0.24 for sedentary behaviors and from 0.17-0.31 for active behaviors. There was general consistency in the magnitude of correlations between the PAQ and PA-monitor between African-Americans and whites. The SCCS-PAQ has fair to moderate test-retest reliability and demonstrated some evidence of criterion validity for ranking participants by their level of sedentary and active behaviors.
Validity of empirical models of exposure in asphalt paving
Burstyn, I; Boffetta, P; Burr, G; Cenni, A; Knecht, U; Sciarra, G; Kromhout, H
2002-01-01
Aims: To investigate the validity of empirical models of exposure to bitumen fume and benzo(a)pyrene, developed for a historical cohort study of asphalt paving in Western Europe. Methods: Validity was evaluated using data from the USA, Italy, and Germany not used to develop the original models. Correlation between observed and predicted exposures was examined. Bias and precision were estimated. Results: Models were imprecise. Furthermore, predicted bitumen fume exposures tended to be lower (-70%) than concentrations found during paving in the USA. This apparent bias might be attributed to differences between Western European and USA paving practices. Evaluation of the validity of the benzo(a)pyrene exposure model revealed a similar to expected effect of re-paving and a larger than expected effect of tar use. Overall, benzo(a)pyrene models underestimated exposures by 51%. Conclusions: Possible bias as a result of underestimation of the impact of coal tar on benzo(a)pyrene exposure levels must be explored in sensitivity analysis of the exposure–response relation. Validation of the models, albeit limited, increased our confidence in their applicability to exposure assessment in the historical cohort study of cancer risk among asphalt workers. PMID:12205236
ERIC Educational Resources Information Center
Breuer, Christoph; Wicker, Pamela
2009-01-01
According to cross-sectional studies in sport science literature, decreasing sports activity with increasing age is generally assumed. In this paper, the validity of this assumption is checked by applying more effective methods of analysis, such as longitudinal and cohort sequence analyses. With the help of 20 years' worth of data records from the…
Evans, Joseph R.; Zhao, Shuang G.; Chang, S. Laura; Tomlins, Scott A.; Erho, Nicholas; Sboner, Andrea; Schiewer, Matthew J.; Spratt, Daniel E.; Kothari, Vishal; Klein, Eric A.; Den, Robert B.; Dicker, Adam P.; Karnes, R. Jeffrey; Yu, Xiaochun; Nguyen, Paul L.; Rubin, Mark A.; de Bono, Johann; Knudsen, Karen E.; Davicioni, Elai; Feng, Felix Y.
2017-01-01
IMPORTANCE A substantial number of patients diagnosed with high-risk prostate cancer are at risk for metastatic progression after primary treatment. Better biomarkers are needed to identify patients at the highest risk to guide therapy intensification. OBJECTIVE To create a DNA damage and repair (DDR) pathway profiling method for use as a prognostic signature biomarker in high-risk prostate cancer. DESIGN, SETTING, AND PARTICIPANTS A cohort of 1090 patients with high-risk prostate cancer who underwent prostatectomy and were treated at 3 different academic institutions were divided into a training cohort (n = 545) and 3 pooled validation cohorts (n = 232, 130, and 183) assembled for case-control or case-cohort studies. Profiling of 9 DDR pathways using 17 gene sets for GSEA (Gene Set Enrichment Analysis) of high-density microarray gene expression data from formalin-fixed paraffin-embedded prostatectomy samples with median 10.3 years follow-up was performed. Prognostic signature development from DDR pathway profiles was studied, and DDR pathway gene mutation in published cohorts was analyzed. MAIN OUTCOMES AND MEASURES Biochemical recurrence-free, metastasis-free, and overall survival. RESULTS Across the training cohort and pooled validation cohorts, 1090 men were studied; mean (SD) age at diagnosis was 65.3 (6.4) years. We found that there are distinct clusters of DDR pathways within the cohort, and DDR pathway enrichment is only weakly correlated with clinical variables such as age (Spearman ρ [ρ], range, −0.07 to 0.24), Gleason score (ρ, range, 0.03 to 0.20), prostate-specific antigen level (ρ, range, −0.07 to 0.10), while 13 of 17 DDR gene sets are strongly correlated with androgen receptor pathway enrichment (ρ, range, 0.33 to 0.82). In published cohorts, DDR pathway genes are rarely mutated. A DDR pathway profile prognostic signature built in the training cohort was significantly associated with biochemical recurrence-free, metastasis-free, and overall survival in the pooled validation cohorts independent of standard clinicopathological variables. The prognostic performance of the signature for metastasis-free survival appears to be stronger in the younger patients (HR, 1.67; 95%CI, 1.12–2.50) than in the older patients (HR, 0.77; 95%CI, 0.29–2.07) on multivariate Cox analysis. CONCLUSIONS AND RELEVANCE DNA damage and repair pathway profiling revealed patient-level variations and the DDR pathways are rarely affected by mutation. A DDR pathway signature showed strong prognostic performance with the long-term outcomes of metastasis-free and overall survival that may be useful for risk stratification of high-risk prostate cancer patients. PMID:26746117
Reddy, Jay P; Atkinson, Rachel L; Larson, Richard; Burks, Jared K; Smith, Daniel; Debeb, Bisrat G; Ruffell, Brian; Creighton, Chad J; Bambhroliya, Arvind; Reuben, James M; Van Laere, Steven J; Krishnamurthy, Savitri; Symmans, William F; Brewster, Abenaa M; Woodward, Wendy A
2018-06-01
We hypothesized that breast tissue not involved by tumor in inflammatory breast cancer (IBC) patients contains intrinsic differences, including increased mammary stem cells and macrophage infiltration, which may promote the IBC phenotype. Normal breast parenchyma ≥ 5 cm away from primary tumors was obtained from mastectomy specimens. This included an initial cohort of 8 IBC patients and 60 non-IBC patients followed by a validation cohort of 19 IBC patients and 25 non-IBC patients. Samples were immunostained for either CD44 + CD49f + CD133/2 + mammary stem cell markers or the CD68 macrophage marker and correlated with IBC status. Quantitation of positive cells was determined using inForm software from PerkinElmer. We also examined the association between IBC status and previously published tumorigenic stem cell and IBC tumor signatures in the validation cohort samples. 8 of 8 IBC samples expressed isolated CD44 + CD49f + CD133/2 + stem cell marked cells in the initial cohort as opposed to 0/60 non-IBC samples (p = 0.001). Similarly, the median number of CD44 + CD49f + CD133/2 + cells was significantly higher in the IBC validation cohort as opposed to the non-IBC validation cohort (25.7 vs. 14.2, p = 0.007). 7 of 8 IBC samples expressed CD68 + histologically confirmed macrophages in initial cohort as opposed to 12/48 non-IBC samples (p = 0.001). In the validation cohort, the median number of CD68 + cells in IBC was 3.7 versus 1.0 in the non-IBC cohort (p = 0.06). IBC normal tissue was positively associated with a tumorigenic stem cell signature (p = 0.02) and with a 79-gene IBC signature (p < 0.001). Normal tissue from IBC patients is enriched for both mammary stem cells and macrophages and has higher association with both a tumorigenic stem cell signature and IBC-specific tumor signature. Collectively, these data suggest that IBC normal tissue differs from non-IBC tissue. Whether these changes occur before the tumor develops or is induced by tumor warrants further investigation.
Dear, James W; Clarke, Joanna I; Francis, Ben; Allen, Lowri; Wraight, Jonathan; Shen, Jasmine; Dargan, Paul I; Wood, David; Cooper, Jamie; Thomas, Simon H L; Jorgensen, Andrea L; Pirmohamed, Munir; Park, B Kevin; Antoine, Daniel J
2018-02-01
Paracetamol overdose is common but patient stratification is suboptimal. We investigated the usefulness of new biomarkers that have either enhanced liver specificity (microRNA-122 [miR-122]) or provide mechanistic insights (keratin-18 [K18], high mobility group box-1 [HMGB1], and glutamate dehydrogenase [GLDH]). The use of these biomarkers could help stratify patients for their risk of liver injury at hospital presentation. Using data from two prospective cohort studies, we assessed the potential for biomarkers to stratify patients who overdose with paracetamol. We completed two independent prospective studies: a derivation study (MAPP) in eight UK hospitals and a validation study (BIOPAR) in ten UK hospitals. Patients in both cohorts were adults (≥18 years in England, ≥16 years in Scotland), were diagnosed with paracetamol overdose, and gave written informed consent. Patients who needed intravenous acetylcysteine treatment for paracetamol overdose had circulating biomarkers measured at hospital presentation. The primary endpoint was acute liver injury indicating need for continued acetylcysteine treatment beyond the standard course (alanine aminotransferase [ALT] activity >100 U/L). Receiver operating characteristic (ROC) curves, category-free net reclassification index (cfNRI), and integrated discrimination index (IDI) were applied to assess endpoint prediction. Between June 2, 2010, and May 29, 2014, 1187 patients who required acetylcysteine treatment for paracetamol overdose were recruited (985 in the MAPP cohort; 202 in the BIOPAR cohort). In the derivation and validation cohorts, acute liver injury was predicted at hospital presentation by miR-122 (derivation cohort ROC-area under the curve [AUC] 0·97 [95% CI 0·95-0·98]), HMGB1 (0·95 [0·93-0·98]), and full-length K18 (0·95 [0·92-0·97]). Results were similar in the validation cohort (miR-122 AUC 0·97 [95% CI 0·95-0·99], HMGB1 0·98 [0·96-0·99], and full-length K18 0·93 [0·86-0·99]). A combined model of miR-122, HMGB1, and K18 predicted acute liver injury better than ALT alone (cfNRI 1·95 [95% CI 1·87-2·03], p<0·0001 in the MAPP cohort; 1·54 [1·08-2·00], p<0·0001 in the BIOPAR cohort). Personalised treatment pathways could be developed by use of miR-122, HMGB1, and full-length K18 at hospital presentation for patient stratification. This prospective study supports their use for hepatic safety assessment of new medicines. Edinburgh and Lothians Health Foundation, UK Medical Research Council. Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.
ERIC Educational Resources Information Center
Shakoor, Sania; Jaffee, Sara R.; Andreou, Penelope; Bowes, Lucy; Ambler, Antony P.; Caspi, Avshalom; Moffitt, Terrie E.; Arseneault, Louise
2011-01-01
Stressful events early in life can affect children's mental health problems. Collecting valid and reliable information about children's bad experiences is important for research and clinical purposes. This study aimed to (1) investigate whether mothers and children provide valid reports of bullying victimization, (2) examine the inter-rater…
Jacobs, Svenja; Stallmann, Christoph; Pigeot, Iris
2015-08-01
Cohort studies provide the best evidence of all epidemiological observational studies for the identification of causal relationships between risk factors and diseases. However, this design may lead to drawbacks that may affect the validity and reliability of the results. This follows in particular from systematic errors, such as selection bias or recall bias. One possibility to avoid or counteract some of these drawbacks is to link primary data from cohort studies with secondary and register data. The linkage of these data may also be used for mutual validations. Data that were previously linked with primary data within the context of cohort studies in Germany were obtained from statutory health insurances and pensions as well as data from the Federal Employment Agency and cancer registries. All these data have two features in common: First, they all cover detailed information about a large population and over a long period of time. Second, all sources are in principle able to provide data on an individual level such that an individual data linkage, e.g. with primary data, is possible. However, use and linkage of each of these data sources are restricted by several limitations. These have to be accounted for as well as numerous legal restrictions that exist in Germany to especially prevent the misuse of social data.
Comparing current definitions of return to work: a measurement approach.
Steenstra, I A; Lee, H; de Vroome, E M M; Busse, J W; Hogg-Johnson, S J
2012-09-01
Return-to-work (RTW) status is an often used outcome in work and health research. In low back pain, work is regarded as a normal activity a worker should return to in order to fully recover. Comparing outcomes across studies and even jurisdictions using different definitions of RTW can be challenging for readers in general and when performing a systematic review in particular. In this study, the measurement properties of previously defined RTW outcomes were examined with data from two studies from two countries. Data on RTW in low back pain (LBP) from the Canadian Early Claimant Cohort (ECC); a workers' compensation based study, and the Dutch Amsterdam Sherbrooke Evaluation (ASE) study were analyzed. Correlations between outcomes, differences in predictive validity when using different outcomes and construct validity when comparing outcomes to a functional status outcome were analyzed. In the ECC all definitions were highly correlated and performed similarly in predictive validity. When compared to functional status, RTW definitions in the ECC study performed fair to good on all time points. In the ASE study all definitions were highly correlated and performed similarly in predictive validity. The RTW definitions, however, failed to compare or compared poorly with functional status. Only one definition compared fairly on one time point. Differently defined outcomes are highly correlated, give similar results in prediction, but seem to differ in construct validity when compared to functional status depending on societal context or possibly birth cohort. Comparison of studies using different RTW definitions appears valid as long as RTW status is not considered as a measure of functional status.
Development and validation of a predictive risk model for all-cause mortality in type 2 diabetes.
Robinson, Tom E; Elley, C Raina; Kenealy, Tim; Drury, Paul L
2015-06-01
Type 2 diabetes is common and is associated with an approximate 80% increase in the rate of mortality. Management decisions may be assisted by an estimate of the patient's absolute risk of adverse outcomes, including death. This study aimed to derive a predictive risk model for all-cause mortality in type 2 diabetes. We used primary care data from a large national multi-ethnic cohort of patients with type 2 diabetes in New Zealand and linked mortality records to develop a predictive risk model for 5-year risk of mortality. We then validated this model using information from a separate cohort of patients with type 2 diabetes. 26,864 people were included in the development cohort with a median follow up time of 9.1 years. We developed three models initially using demographic information and then progressively more clinical detail. The final model, which also included markers of renal disease, proved to give best prediction of all-cause mortality with a C-statistic of 0.80 in the development cohort and 0.79 in the validation cohort (7610 people) and was well calibrated. Ethnicity was a major factor with hazard ratios of 1.37 for indigenous Maori, 0.41 for East Asian and 0.55 for Indo Asian compared with European (P<0.001). We have developed a model using information usually available in primary care that provides good assessment of patient's risk of death. Results are similar to models previously published from smaller cohorts in other countries and apply to a wider range of patient ethnic groups. Copyright © 2015. Published by Elsevier Ireland Ltd.
Yang, Xueli; Li, Jianxin; Hu, Dongsheng; Chen, Jichun; Li, Ying; Huang, Jianfeng; Liu, Xiaoqing; Liu, Fangchao; Cao, Jie; Shen, Chong; Yu, Ling; Lu, Fanghong; Wu, Xianping; Zhao, Liancheng; Wu, Xigui; Gu, Dongfeng
2016-11-08
The accurate assessment of individual risk can be of great value to guiding and facilitating the prevention of atherosclerotic cardiovascular disease (ASCVD). However, prediction models in common use were formulated primarily in white populations. The China-PAR project (Prediction for ASCVD Risk in China) is aimed at developing and validating 10-year risk prediction equations for ASCVD from 4 contemporary Chinese cohorts. Two prospective studies followed up together with a unified protocol were used as the derivation cohort to develop 10-year ASCVD risk equations in 21 320 Chinese participants. The external validation was evaluated in 2 independent Chinese cohorts with 14 123 and 70 838 participants. Furthermore, model performance was compared with the Pooled Cohort Equations reported in the American College of Cardiology/American Heart Association guideline. Over 12 years of follow-up in the derivation cohort with 21 320 Chinese participants, 1048 subjects developed a first ASCVD event. Sex-specific equations had C statistics of 0.794 (95% confidence interval, 0.775-0.814) for men and 0.811 (95% confidence interval, 0.787-0.835) for women. The predicted rates were similar to the observed rates, as indicated by a calibration χ 2 of 13.1 for men (P=0.16) and 12.8 for women (P=0.17). Good internal and external validations of our equations were achieved in subsequent analyses. Compared with the Chinese equations, the Pooled Cohort Equations had lower C statistics and much higher calibration χ 2 values in men. Our project developed effective tools with good performance for 10-year ASCVD risk prediction among a Chinese population that will help to improve the primary prevention and management of cardiovascular disease. © 2016 American Heart Association, Inc.
Bharamgoudar, Reshma; Sonsale, Aniket; Hodson, James; Griffiths, Ewen
2018-07-01
The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45-85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p < 0.001), with the proportions of operations lasting > 90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care.
Automated chart review utilizing natural language processing algorithm for asthma predictive index.
Kaur, Harsheen; Sohn, Sunghwan; Wi, Chung-Il; Ryu, Euijung; Park, Miguel A; Bachman, Kay; Kita, Hirohito; Croghan, Ivana; Castro-Rodriguez, Jose A; Voge, Gretchen A; Liu, Hongfang; Juhn, Young J
2018-02-13
Thus far, no algorithms have been developed to automatically extract patients who meet Asthma Predictive Index (API) criteria from the Electronic health records (EHR) yet. Our objective is to develop and validate a natural language processing (NLP) algorithm to identify patients that meet API criteria. This is a cross-sectional study nested in a birth cohort study in Olmsted County, MN. Asthma status ascertained by manual chart review based on API criteria served as gold standard. NLP-API was developed on a training cohort (n = 87) and validated on a test cohort (n = 427). Criterion validity was measured by sensitivity, specificity, positive predictive value and negative predictive value of the NLP algorithm against manual chart review for asthma status. Construct validity was determined by associations of asthma status defined by NLP-API with known risk factors for asthma. Among the eligible 427 subjects of the test cohort, 48% were males and 74% were White. Median age was 5.3 years (interquartile range 3.6-6.8). 35 (8%) had a history of asthma by NLP-API vs. 36 (8%) by abstractor with 31 by both approaches. NLP-API predicted asthma status with sensitivity 86%, specificity 98%, positive predictive value 88%, negative predictive value 98%. Asthma status by both NLP and manual chart review were significantly associated with the known asthma risk factors, such as history of allergic rhinitis, eczema, family history of asthma, and maternal history of smoking during pregnancy (p value < 0.05). Maternal smoking [odds ratio: 4.4, 95% confidence interval 1.8-10.7] was associated with asthma status determined by NLP-API and abstractor, and the effect sizes were similar between the reviews with 4.4 vs 4.2 respectively. NLP-API was able to ascertain asthma status in children mining from EHR and has a potential to enhance asthma care and research through population management and large-scale studies when identifying children who meet API criteria.
Lessons Learned From Methodological Validation Research in E-Epidemiology
Assmann, Karen; Andreeva, Valentina; Castetbon, Katia; Méjean, Caroline; Touvier, Mathilde; Salanave, Benoît; Deschamps, Valérie; Péneau, Sandrine; Fezeu, Léopold; Julia, Chantal; Allès, Benjamin; Galan, Pilar; Hercberg, Serge
2016-01-01
Background Traditional epidemiological research methods exhibit limitations leading to high logistics, human, and financial burden. The continued development of innovative digital tools has the potential to overcome many of the existing methodological issues. Nonetheless, Web-based studies remain relatively uncommon, partly due to persistent concerns about validity and generalizability. Objective The objective of this viewpoint is to summarize findings from methodological studies carried out in the NutriNet-Santé study, a French Web-based cohort study. Methods On the basis of the previous findings from the NutriNet-Santé e-cohort (>150,000 participants are currently included), we synthesized e-epidemiological knowledge on sample representativeness, advantageous recruitment strategies, and data quality. Results Overall, the reported findings support the usefulness of Web-based studies in overcoming common methodological deficiencies in epidemiological research, in particular with regard to data quality (eg, the concordance for body mass index [BMI] classification was 93%), reduced social desirability bias, and access to a wide range of participant profiles, including the hard-to-reach subgroups such as young (12.30% [15,118/122,912], <25 years) and old people (6.60% [8112/122,912], ≥65 years), unemployed or homemaker (12.60% [15,487/122,912]), and low educated (38.50% [47,312/122,912]) people. However, some selection bias remained (78.00% (95,871/122,912) of the participants were women, and 61.50% (75,590/122,912) had postsecondary education), which is an inherent aspect of cohort study inclusion; other specific types of bias may also have occurred. Conclusions Given the rapidly growing access to the Internet across social strata, the recruitment of participants with diverse socioeconomic profiles and health risk exposures was highly feasible. Continued efforts concerning the identification of specific biases in e-cohorts and the collection of comprehensive and valid data are still needed. This summary of methodological findings from the NutriNet-Santé cohort may help researchers in the development of the next generation of high-quality Web-based epidemiological studies. PMID:27756715
de Souza E Silva, Christina G; Kaminsky, Leonard A; Arena, Ross; Christle, Jeffrey W; Araújo, Claudio Gil S; Lima, Ricardo M; Ashley, Euan A; Myers, Jonathan
2018-05-01
Background Maximal oxygen uptake (VO 2 max) is a powerful predictor of health outcomes. Valid and portable reference values are integral to interpreting measured VO 2 max; however, available reference standards lack validation and are specific to exercise mode. This study was undertaken to develop and validate a single equation for normal standards for VO 2 max for the treadmill or cycle ergometer in men and women. Methods Healthy individuals ( N = 10,881; 67.8% men, 20-85 years) who performed a maximal cardiopulmonary exercise test on either a treadmill or a cycle ergometer were studied. Of these, 7617 and 3264 individuals were randomly selected for development and validation of the equation, respectively. A Brazilian sample (1619 individuals) constituted a second validation cohort. The prediction equation was determined using multiple regression analysis, and comparisons were made with the widely-used Wasserman and European equations. Results Age, sex, weight, height and exercise mode were significant predictors of VO 2 max. The regression equation was: VO 2 max (ml kg -1 min -1 ) = 45.2 - 0.35*Age - 10.9*Sex (male = 1; female = 2) - 0.15*Weight (pounds) + 0.68*Height (inches) - 0.46*Exercise Mode (treadmill = 1; bike = 2) ( R = 0.79, R 2 = 0.62, standard error of the estimate = 6.6 ml kg -1 min -1 ). Percentage predicted VO 2 max for the US and Brazilian validation cohorts were 102.8% and 95.8%, respectively. The new equation performed better than traditional equations, particularly among women and individuals ≥60 years old. Conclusion A combined equation was developed for normal standards for VO 2 max for different exercise modes derived from a US national registry. The equation provided a lower average error between measured and predicted VO 2 max than traditional equations even when applied to an independent cohort. Additional studies are needed to determine its portability.
Husbands, Adrian; Mathieson, Alistair; Dowell, Jonathan; Cleland, Jennifer; MacKenzie, Rhoda
2014-04-23
The UK Clinical Aptitude Test (UKCAT) was designed to address issues identified with traditional methods of selection. This study aims to examine the predictive validity of the UKCAT and compare this to traditional selection methods in the senior years of medical school. This was a follow-up study of two cohorts of students from two medical schools who had previously taken part in a study examining the predictive validity of the UKCAT in first year. The sample consisted of 4th and 5th Year students who commenced their studies at the University of Aberdeen or University of Dundee medical schools in 2007. Data collected were: demographics (gender and age group), UKCAT scores; Universities and Colleges Admissions Service (UCAS) form scores; admission interview scores; Year 4 and 5 degree examination scores. Pearson's correlations were used to examine the relationships between admissions variables, examination scores, gender and age group, and to select variables for multiple linear regression analysis to predict examination scores. Ninety-nine and 89 students at Aberdeen medical school from Years 4 and 5 respectively, and 51 Year 4 students in Dundee, were included in the analysis. Neither UCAS form nor interview scores were statistically significant predictors of examination performance. Conversely, the UKCAT yielded statistically significant validity coefficients between .24 and .36 in four of five assessments investigated. Multiple regression analysis showed the UKCAT made a statistically significant unique contribution to variance in examination performance in the senior years. Results suggest the UKCAT appears to predict performance better in the later years of medical school compared to earlier years and provides modest supportive evidence for the UKCAT's role in student selection within these institutions. Further research is needed to assess the predictive validity of the UKCAT against professional and behavioural outcomes as the cohort commences working life.
2014-01-01
Background The UK Clinical Aptitude Test (UKCAT) was designed to address issues identified with traditional methods of selection. This study aims to examine the predictive validity of the UKCAT and compare this to traditional selection methods in the senior years of medical school. This was a follow-up study of two cohorts of students from two medical schools who had previously taken part in a study examining the predictive validity of the UKCAT in first year. Methods The sample consisted of 4th and 5th Year students who commenced their studies at the University of Aberdeen or University of Dundee medical schools in 2007. Data collected were: demographics (gender and age group), UKCAT scores; Universities and Colleges Admissions Service (UCAS) form scores; admission interview scores; Year 4 and 5 degree examination scores. Pearson’s correlations were used to examine the relationships between admissions variables, examination scores, gender and age group, and to select variables for multiple linear regression analysis to predict examination scores. Results Ninety-nine and 89 students at Aberdeen medical school from Years 4 and 5 respectively, and 51 Year 4 students in Dundee, were included in the analysis. Neither UCAS form nor interview scores were statistically significant predictors of examination performance. Conversely, the UKCAT yielded statistically significant validity coefficients between .24 and .36 in four of five assessments investigated. Multiple regression analysis showed the UKCAT made a statistically significant unique contribution to variance in examination performance in the senior years. Conclusions Results suggest the UKCAT appears to predict performance better in the later years of medical school compared to earlier years and provides modest supportive evidence for the UKCAT’s role in student selection within these institutions. Further research is needed to assess the predictive validity of the UKCAT against professional and behavioural outcomes as the cohort commences working life. PMID:24762134
Effect of using truncated versus total foot length to calculate the arch height ratio.
McPoil, Thomas G; Cornwall, Mark W; Vicenzino, Bill; Teyhen, Deydre S; Molloy, Joseph M; Christie, Douglas S; Collins, Natalie
2008-12-01
The purpose of this study was to determine the arch height ratio in a large cohort of subjects as well as to assess the reliability and validity of the foot measurements utilized in the study. Eight hundred and fifty subjects, 393 women and 457 men, consented to participate in the study. The dorsal arch height, total foot length, and the truncated foot length were used to calculate two variations of the arch height ratio. In addition to determining within- and between-rater measurement reliability, radiographs were used to establish validity. The truncated arch height ratio can be estimated using the total foot length, unless toe deformities are present in the individual being assessed. All foot measurements had high levels of intra- and inter-rater reliability and the validity of measuring the dorsal arch height while standing with equal weight on both feet was established. This investigation provides normative values from a large cohort of healthy female and male subjects for two variations of the arch height ratio. The arch height ratio is a reliable and valid measurement that may prove useful to clinicians and researchers for the classification of foot posture.
Yang, Lin; Xia, Liangping; Wang, Yan; He, Shasha; Chen, Haiyang; Liang, Shaobo; Peng, Peijian; Hong, Shaodong; Chen, Yong
2017-09-06
The skeletal system is the most common site of distant metastasis in nasopharyngeal carcinoma (NPC); various prognostic factors have been reported for skeletal metastasis, though most studies have focused on a single factor. We aimed to establish nomograms to effectively predict skeletal metastasis at initial diagnosis (SMAD) and skeletal metastasis-free survival (SMFS) in NPC. A total of 2685 patients with NPC who received bone scintigraphy (BS) and/or 18F-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and 2496 patients without skeletal metastasis were retrospectively assessed to develop individual nomograms for SMAD and SMFS. The models were validated externally using separate cohorts of 1329 and 1231 patients treated at two other institutions. Five independent prognostic factors were included in each nomogram. The SMAD nomogram had a significantly higher c-index than the TNM staging system (training cohort, P = 0.005; validation cohort, P < 0.001). The SMFS nomogram had significantly higher c-index values in the training and validation sets than the TNM staging system (P < 0.001 and P = 0.005, respectively). Three proposed risk stratification groups were created using the nomograms, and enabled significant discrimination of SMFS for each risk group. The prognostic nomograms established in this study enable accurate stratification of distinct risk groups for skeletal metastasis, which may improve counseling and facilitate individualized management of patients with NPC.
Kim, Jung Kwon; Ha, Seung Beom; Jeon, Chan Hoo; Oh, Jong Jin; Cho, Sung Yong; Oh, Seung-June; Kim, Hyeon Hoe; Jeong, Chang Wook
2016-01-01
Purpose Shock-wave lithotripsy (SWL) is accepted as the first line treatment modality for uncomplicated upper urinary tract stones; however, validated prediction models with regards to stone-free rates (SFRs) are still needed. We aimed to develop nomograms predicting SFRs after the first and within the third session of SWL. Computed tomography (CT) information was also modeled for constructing nomograms. Materials and Methods From March 2006 to December 2013, 3028 patients were treated with SWL for ureter and renal stones at our three tertiary institutions. Four cohorts were constructed: Total-development, Total-validation, CT-development, and CT-validation cohorts. The nomograms were developed using multivariate logistic regression models with selected significant variables in a univariate logistic regression model. A C-index was used to assess the discrimination accuracy of nomograms and calibration plots were used to analyze the consistency of prediction. Results The SFR, after the first and within the third session, was 48.3% and 68.8%, respectively. Significant variables were sex, stone location, stone number, and maximal stone diameter in the Total-development cohort, and mean Hounsfield unit (HU) and grade of hydronephrosis (HN) were additional parameters in the CT-development cohort. The C-indices were 0.712 and 0.723 for after the first and within the third session of SWL in the Total-development cohort, and 0.755 and 0.756, in the CT-development cohort, respectively. The calibration plots showed good correspondences. Conclusions We constructed and validated nomograms to predict SFR after SWL. To the best of our knowledge, these are the first graphical nomograms to be modeled with CT information. These may be useful for patient counseling and treatment decision-making. PMID:26890006
Gilman, Robert H.; Sanchez-Abanto, Jose R.; Study Group, CRONICAS Cohort
2016-01-01
Objective. To develop and validate a risk score for detecting cases of undiagnosed diabetes in a resource-constrained country. Methods. Two population-based studies in Peruvian population aged ≥35 years were used in the analysis: the ENINBSC survey (n = 2,472) and the CRONICAS Cohort Study (n = 2,945). Fasting plasma glucose ≥7.0 mmol/L was used to diagnose diabetes in both studies. Coefficients for risk score were derived from the ENINBSC data and then the performance was validated using both baseline and follow-up data of the CRONICAS Cohort Study. Results. The prevalence of undiagnosed diabetes was 2.0% in the ENINBSC survey and 2.9% in the CRONICAS Cohort Study. Predictors of undiagnosed diabetes were age, diabetes in first-degree relatives, and waist circumference. Score values ranged from 0 to 4, with an optimal cutoff ≥2 and had a moderate performance when applied in the CRONICAS baseline data (AUC = 0.68; 95% CI: 0.62–0.73; sensitivity 70%; specificity 59%). When predicting incident cases, the AUC was 0.66 (95% CI: 0.61–0.71), with a sensitivity of 69% and specificity of 59%. Conclusions. A simple nonblood based risk score based on age, diabetes in first-degree relatives, and waist circumference can be used as a simple screening tool for undiagnosed and incident cases of diabetes in Peru. PMID:27689096
Hasbun, Rodrigo; Bijlsma, Merijn; Brouwer, Matthijs C; Khoury, Nabil; Hadi, Christiane M; van der Ende, Arie; Wootton, Susan H; Salazar, Lucrecia; Hossain, Md Monir; Beilke, Mark; van de Beek, Diederik
2013-08-01
We aimed to derive and validate a risk score that identifies adults with cerebrospinal fluid (CSF) pleocytosis and a negative CSF Gram stain at low risk for an urgent treatable cause. Patients with CSF pleocytosis and a negative CSF Gram stain were stratified into a prospective derivation (n = 193) and a retrospective validation (n = 567) cohort. Clinically related baseline characteristics were grouped into three composite variables, each independently associated with a set of predefined urgent treatable causes. We subsequently derived a risk score classifying patients into low (0 composite variables present) or high (≥ 1 composite variables present) risk for an urgent treatable cause. The sensitivity of the risk score was determined in the validation cohort and in a prospective case series of 214 adults with CSF-culture proven bacterial meningitis, CSF pleocytosis and a negative Gram stain. A total of 41 of 193 patients (21%) in the derivation cohort and 71 of 567 (13%) in the validation cohort had an urgent treatable cause. Sensitivity of the dichotomized risk score to detect an urgent treatable cause was 100.0% (95% CI 93.9-100.0%) in the validation cohort and 100.0% (95% CI 97.8-100.0%) in bacterial meningitis patients. The risk score can be used to identify adults with CSF pleocytosis and a negative CSF Gram stain at low risk for an urgent treatable cause. Copyright © 2013 The British Infection Association. Published by Elsevier Ltd. All rights reserved.
Hasbun, Rodrigo; Bijlsma, Merijn; Brouwer, Matthijs C; Khoury, Nabil; Hadi, Christiane M; van der Ende, Arie; Wootton, Susan H.; Salazar, Lucrecia; Hossain, Md Monir; Beilke, Mark; van de Beek, Diederik
2013-01-01
Background We aimed to derive and validate a risk score that identifies adults with cerebrospinal fluid (CSF) pleocytosis and a negative CSF Gram stain at low risk for an urgent treatable cause. Methods Patients with CSF pleocytosis and a negative CSF Gram stain were stratified into a prospective derivation (n=193) and a retrospective validation (n=567) cohort. Clinically related baseline characteristics were grouped into three composite variables, each independently associated with a set of predefined urgent treatable causes. We subsequently derived a risk score classifying patients into low (0 composite variables present) or high ( ≥ 1 composite variables present) risk for an urgent treatable cause. The sensitivity of the risk score was determined in the validation cohort and in a prospective case series of 214 adults with CSF-culture proven bacterial meningitis, CSF pleocytosis and a negative Gram stain. Findings A total of 41 of 193 patients (21%) in the derivation cohort and 71 of 567 (13%) in the validation cohort had an urgent treatable cause. Sensitivity of the dichotomized risk score to detect an urgent treatable cause was 100.0% (95%CI 93.9-100.0%) in the validation cohort and 100.0% (95%CI 97.8-100.0%) in bacterial meningitis patients. Interpretation The risk score can be used to identify adults with CSF pleocytosis and a negative CSF Gram stain at low risk for an urgent treatable cause. PMID:23619080
P21, COX-2, and E-cadherin are potential prognostic factors for esophageal squamous cell carcinoma.
Lin, Yao; Shen, Lu-Yan; Fu, Hao; Dong, Bin; Yang, He-Li; Yan, Wan-Pu; Kang, Xiao-Zheng; Dai, Liang; Zhou, Hai-Tao; Yang, Yong-Bo; Liang, Zhen; Chen, Ke-Neng
2017-02-01
Much research effort has been devoted to identifying prognostic factors for esophageal squamous cell carcinoma (ESCC) by immunohistochemistry; however, no conclusive findings have been reached thus far. We hypothesized that certain molecules identified in previous studies might serve as useful prognostic markers for ESCC. Therefore, the aim of the current study was to validate the most relevant markers showing potential for ESCC prognosis in our prospective esophageal cancer database. A literature search was performed using the PubMed database for papers published between 1980 and 2015 using the following key words: 'esophageal cancer,' 'prognosis,' and 'immunohistochemistry.' Literature selection criteria were established to identify the most widely studied markers, and we further validated the selected markers in a cohort from our single-surgeon team, including 153 esophageal cancer patients treated from 2000 to 2010. A total of 1799 articles were identified, 82 of which met the selection criteria. Twelve markers were found to be the most widely studied, and the validation results indicated that only P21, COX-2, and E-cadherin were independent prognostic factors for ESCC patients in this series. The systemic review and cohort validation suggest that P21, COX-2, and E-cadherin are potential prognostic factors for ESCC, paving the way for more targeted prospective validation in the future. © 2016 International Society for Diseases of the Esophagus.
Pannu, Neesh; Hemmelgarn, Brenda R.; Austin, Peter C.; Tan, Zhi; McArthur, Eric; Manns, Braden J.; Tonelli, Marcello; Wald, Ron; Quinn, Robert R.; Ravani, Pietro; Garg, Amit X.
2017-01-01
Importance Some patients will develop chronic kidney disease after a hospitalization with acute kidney injury; however, no risk-prediction tools have been developed to identify high-risk patients requiring follow-up. Objective To derive and validate predictive models for progression of acute kidney injury to advanced chronic kidney disease. Design, Setting, and Participants Data from 2 population-based cohorts of patients with a prehospitalization estimated glomerular filtration rate (eGFR) of more than 45 mL/min/1.73 m2 and who had survived hospitalization with acute kidney injury (defined by a serum creatinine increase during hospitalization > 0.3 mg/dL or > 50% of their prehospitalization baseline), were used to derive and validate multivariable prediction models. The risk models were derived from 9973 patients hospitalized in Alberta, Canada (April 2004-March 2014, with follow-up to March 2015). The risk models were externally validated with data from a cohort of 2761 patients hospitalized in Ontario, Canada (June 2004-March 2012, with follow-up to March 2013). Exposures Demographic, laboratory, and comorbidity variables measured prior to discharge. Main Outcomes and Measures Advanced chronic kidney disease was defined by a sustained reduction in eGFR less than 30 mL/min/1.73 m2 for at least 3 months during the year after discharge. All participants were followed up for up to 1 year. Results The participants (mean [SD] age, 66 [15] years in the derivation and internal validation cohorts and 69 [11] years in the external validation cohort; 40%-43% women per cohort) had a mean (SD) baseline serum creatinine level of 1.0 (0.2) mg/dL and more than 20% had stage 2 or 3 acute kidney injury. Advanced chronic kidney disease developed in 408 (2.7%) of 9973 patients in the derivation cohort and 62 (2.2%) of 2761 patients in the external validation cohort. In the derivation cohort, 6 variables were independently associated with the outcome: older age, female sex, higher baseline serum creatinine value, albuminuria, greater severity of acute kidney injury, and higher serum creatinine value at discharge. In the external validation cohort, a multivariable model including these 6 variables had a C statistic of 0.81 (95% CI, 0.75-0.86) and improved discrimination and reclassification compared with reduced models that included age, sex, and discharge serum creatinine value alone (integrated discrimination improvement, 2.6%; 95% CI, 1.1%-4.0%; categorical net reclassification index, 13.5%; 95% CI, 1.9%-25.1%) or included age, sex, and acute kidney injury stage alone (integrated discrimination improvement, 8.0%; 95% CI, 5.1%-11.0%; categorical net reclassification index, 79.9%; 95% CI, 60.9%-98.9%). Conclusions and Relevance A multivariable model using routine laboratory data was able to predict advanced chronic kidney disease following hospitalization with acute kidney injury. The utility of this model in clinical care requires further research. PMID:29136443
James, Matthew T; Pannu, Neesh; Hemmelgarn, Brenda R; Austin, Peter C; Tan, Zhi; McArthur, Eric; Manns, Braden J; Tonelli, Marcello; Wald, Ron; Quinn, Robert R; Ravani, Pietro; Garg, Amit X
2017-11-14
Some patients will develop chronic kidney disease after a hospitalization with acute kidney injury; however, no risk-prediction tools have been developed to identify high-risk patients requiring follow-up. To derive and validate predictive models for progression of acute kidney injury to advanced chronic kidney disease. Data from 2 population-based cohorts of patients with a prehospitalization estimated glomerular filtration rate (eGFR) of more than 45 mL/min/1.73 m2 and who had survived hospitalization with acute kidney injury (defined by a serum creatinine increase during hospitalization > 0.3 mg/dL or > 50% of their prehospitalization baseline), were used to derive and validate multivariable prediction models. The risk models were derived from 9973 patients hospitalized in Alberta, Canada (April 2004-March 2014, with follow-up to March 2015). The risk models were externally validated with data from a cohort of 2761 patients hospitalized in Ontario, Canada (June 2004-March 2012, with follow-up to March 2013). Demographic, laboratory, and comorbidity variables measured prior to discharge. Advanced chronic kidney disease was defined by a sustained reduction in eGFR less than 30 mL/min/1.73 m2 for at least 3 months during the year after discharge. All participants were followed up for up to 1 year. The participants (mean [SD] age, 66 [15] years in the derivation and internal validation cohorts and 69 [11] years in the external validation cohort; 40%-43% women per cohort) had a mean (SD) baseline serum creatinine level of 1.0 (0.2) mg/dL and more than 20% had stage 2 or 3 acute kidney injury. Advanced chronic kidney disease developed in 408 (2.7%) of 9973 patients in the derivation cohort and 62 (2.2%) of 2761 patients in the external validation cohort. In the derivation cohort, 6 variables were independently associated with the outcome: older age, female sex, higher baseline serum creatinine value, albuminuria, greater severity of acute kidney injury, and higher serum creatinine value at discharge. In the external validation cohort, a multivariable model including these 6 variables had a C statistic of 0.81 (95% CI, 0.75-0.86) and improved discrimination and reclassification compared with reduced models that included age, sex, and discharge serum creatinine value alone (integrated discrimination improvement, 2.6%; 95% CI, 1.1%-4.0%; categorical net reclassification index, 13.5%; 95% CI, 1.9%-25.1%) or included age, sex, and acute kidney injury stage alone (integrated discrimination improvement, 8.0%; 95% CI, 5.1%-11.0%; categorical net reclassification index, 79.9%; 95% CI, 60.9%-98.9%). A multivariable model using routine laboratory data was able to predict advanced chronic kidney disease following hospitalization with acute kidney injury. The utility of this model in clinical care requires further research.
van der Meer, Adriaan J; Hansen, Bettina E; Fattovich, Giovanna; Feld, Jordan J; Wedemeyer, Heiner; Dufour, Jean-François; Lammert, Frank; Duarte-Rojo, Andres; Manns, Michael P; Ieluzzi, Donatella; Zeuzem, Stefan; Hofmann, W Peter; de Knegt, Robert J; Veldt, Bart J; Janssen, Harry L A
2015-02-01
Reliable tools to predict long-term outcome among patients with well compensated advanced liver disease due to chronic HCV infection are lacking. Risk scores for mortality and for cirrhosis-related complications were constructed with Cox regression analysis in a derivation cohort and evaluated in a validation cohort, both including patients with chronic HCV infection and advanced fibrosis. In the derivation cohort, 100/405 patients died during a median 8.1 (IQR 5.7-11.1) years of follow-up. Multivariate Cox analyses showed age (HR=1.06, 95% CI 1.04 to 1.09, p<0.001), male sex (HR=1.91, 95% CI 1.10 to 3.29, p=0.021), platelet count (HR=0.91, 95% CI 0.87 to 0.95, p<0.001) and log10 aspartate aminotransferase/alanine aminotransferase ratio (HR=1.30, 95% CI 1.12 to 1.51, p=0.001) were independently associated with mortality (C statistic=0.78, 95% CI 0.72 to 0.83). In the validation cohort, 58/296 patients with cirrhosis died during a median of 6.6 (IQR 4.4-9.0) years. Among patients with estimated 5-year mortality risks <5%, 5-10% and >10%, the observed 5-year mortality rates in the derivation cohort and validation cohort were 0.9% (95% CI 0.0 to 2.7) and 2.6% (95% CI 0.0 to 6.1), 8.1% (95% CI 1.8 to 14.4) and 8.0% (95% CI 1.3 to 14.7), 21.8% (95% CI 13.2 to 30.4) and 20.9% (95% CI 13.6 to 28.1), respectively (C statistic in validation cohort = 0.76, 95% CI 0.69 to 0.83). The risk score for cirrhosis-related complications also incorporated HCV genotype (C statistic = 0.80, 95% CI 0.76 to 0.83 in the derivation cohort; and 0.74, 95% CI 0.68 to 0.79 in the validation cohort). Prognosis of patients with chronic HCV infection and compensated advanced liver disease can be accurately assessed with risk scores including readily available objective clinical parameters. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Study Protocol, Sample Characteristics, and Loss to Follow-Up: The OPPERA Prospective Cohort Study
Bair, Eric; Brownstein, Naomi C.; Ohrbach, Richard; Greenspan, Joel D.; Dubner, Ron; Fillingim, Roger B.; Maixner, William; Smith, Shad; Diatchenko, Luda; Gonzalez, Yoly; Gordon, Sharon; Lim, Pei-Feng; Ribeiro-Dasilva, Margarete; Dampier, Dawn; Knott, Charles; Slade, Gary D.
2013-01-01
When studying incidence of pain conditions such as temporomandibular disorders (TMDs), repeated monitoring is needed in prospective cohort studies. However, monitoring methods usually have limitations and, over a period of years, some loss to follow-up is inevitable. The OPPERA prospective cohort study of first-onset TMD screened for symptoms using quarterly questionnaires and examined symptomatic participants to definitively ascertain TMD incidence. During the median 2.8-year observation period, 16% of the 3,263 enrollees completed no follow-up questionnaires, others provided incomplete follow-up, and examinations were not conducted for one third of symptomatic episodes. Although screening methods and examinations were found to have excellent reliability and validity, they were not perfect. Loss to follow-up varied according to some putative TMD risk factors, although multiple imputation to correct the problem suggested that bias was minimal. A second method of multiple imputation that evaluated bias associated with omitted and dubious examinations revealed a slight underestimate of incidence and some small biases in hazard ratios used to quantify effects of risk factors. Although “bottom line” statistical conclusions were not affected, multiply-imputed estimates should be considered when evaluating the large number of risk factors under investigation in the OPPERA study. Perspective These findings support the validity of the OPPERA prospective cohort study for the purpose of investigating the etiology of first-onset TMD, providing the foundation for other papers investigating risk factors hypothesized in the OPPERA project. PMID:24275220
Cohort profile: cerebral palsy in the Norwegian and Danish birth cohorts (MOBAND-CP)
Tollånes, Mette C; Strandberg-Larsen, Katrine; Forthun, Ingeborg; Petersen, Tanja Gram; Moster, Dag; Andersen, Anne-Marie Nybo; Stoltenberg, Camilla; Olsen, Jørn; Wilcox, Allen J
2016-01-01
Purpose The purpose of MOthers and BAbies in Norway and Denmark cerebral palsy (MOBAND-CP) was to study CP aetiology in a prospective design. Participants MOBAND-CP is a cohort of more than 210 000 children, created as a collaboration between the world's two largest pregnancy cohorts—the Norwegian Mother and Child Cohort study (MoBa) and the Danish National Birth Cohort. MOBAND-CP includes maternal interview/questionnaire data collected during pregnancy and follow-up, plus linked information from national health registries. Findings to date Initial harmonisation of data from the 2 cohorts has created 140 variables for children and their mothers. In the MOBAND-CP cohort, 438 children with CP have been identified through record linkage with validated national registries, providing by far the largest such sample with prospectively collected detailed pregnancy data. Several studies investigating various hypotheses regarding CP aetiology are currently on-going. Future plans Additional data can be harmonised as necessary to meet requirements of new projects. Biological specimens collected during pregnancy and at delivery are potentially available for assay, as are results from assays conducted on these specimens for other projects. The study size allows consideration of CP subtypes, which is rare in aetiological studies of CP. In addition, MOBAND-CP provides a platform within the context of a merged birth cohort of exceptional size that could, after appropriate permissions have been sought, be used for cohort and case-cohort studies of other relatively rare health conditions of infants and children. PMID:27591025
Hippisley-Cox, Julia; Coupland, Carol
2017-11-20
Objectives To derive and validate updated QDiabetes-2018 prediction algorithms to estimate the 10 year risk of type 2 diabetes in men and women, taking account of potential new risk factors, and to compare their performance with current approaches. Design Prospective open cohort study. Setting Routinely collected data from 1457 general practices in England contributing to the QResearch database: 1094 were used to develop the scores and a separate set of 363 were used to validate the scores. Participants 11.5 million people aged 25-84 and free of diabetes at baseline: 8.87 million in the derivation cohort and 2.63 million in the validation cohort. Methods Cox proportional hazards models were used in the derivation cohort to derive separate risk equations in men and women for evaluation at 10 years. Risk factors considered included those already in QDiabetes (age, ethnicity, deprivation, body mass index, smoking, family history of diabetes in a first degree relative, cardiovascular disease, treated hypertension, and regular use of corticosteroids) and new risk factors: atypical antipsychotics, statins, schizophrenia or bipolar affective disorder, learning disability, gestational diabetes, and polycystic ovary syndrome. Additional models included fasting blood glucose and glycated haemoglobin (HBA1c). Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for individual subgroups by age group, ethnicity, and baseline disease status. Main outcome measure Incident type 2 diabetes recorded on the general practice record. Results In the derivation cohort, 178 314 incident cases of type 2 diabetes were identified during follow-up arising from 42.72 million person years of observation. In the validation cohort, 62 326 incident cases of type 2 diabetes were identified from 14.32 million person years of observation. All new risk factors considered met our model inclusion criteria. Model A included age, ethnicity, deprivation, body mass index, smoking, family history of diabetes in a first degree relative, cardiovascular disease, treated hypertension, and regular use of corticosteroids, and new risk factors: atypical antipsychotics, statins, schizophrenia or bipolar affective disorder, learning disability, and gestational diabetes and polycystic ovary syndrome in women. Model B included the same variables as model A plus fasting blood glucose. Model C included HBA1c instead of fasting blood glucose. All three models had good calibration and high levels of explained variation and discrimination. In women, model B explained 63.3% of the variation in time to diagnosis of type 2 diabetes (R 2 ), the D statistic was 2.69 and the Harrell's C statistic value was 0.89. The corresponding values for men were 58.4%, 2.42, and 0.87. Model B also had the highest sensitivity compared with current recommended practice in the National Health Service based on bands of either fasting blood glucose or HBA1c. However, only 16% of patients had complete data for blood glucose measurements, smoking, and body mass index. Conclusions Three updated QDiabetes risk models to quantify the absolute risk of type 2 diabetes were developed and validated: model A does not require a blood test and can be used to identify patients for fasting blood glucose (model B) or HBA1c (model C) testing. Model B had the best performance for predicting 10 year risk of type 2 diabetes to identify those who need interventions and more intensive follow-up, improving on current approaches. Additional external validation of models B and C in datasets with more completely collected data on blood glucose would be valuable before the models are used in clinical practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
ERIC Educational Resources Information Center
Lievens, Filip; Sackett, Paul R.
2012-01-01
This study provides conceptual and empirical arguments why an assessment of applicants' procedural knowledge about interpersonal behavior via a video-based situational judgment test might be valid for academic and postacademic success criteria. Four cohorts of medical students (N = 723) were followed from admission to employment. Procedural…
ERIC Educational Resources Information Center
Ali, Syed Haris; Carr, Patrick A.; Ruit, Kenneth G.
2016-01-01
Plausible distractors are important for accurate measurement of knowledge via multiple-choice questions (MCQs). This study demonstrates the impact of higher distractor functioning on validity and reliability of scores obtained on MCQs. Freeresponse (FR) and MCQ versions of a neurohistology practice exam were given to four cohorts of Year 1 medical…
Liu, Xun; Li, Ning-shan; Lv, Lin-sheng; Huang, Jian-hua; Tang, Hua; Chen, Jin-xia; Ma, Hui-juan; Wu, Xiao-ming; Lou, Tan-qi
2013-12-01
Accurate estimation of glomerular filtration rate (GFR) is important in clinical practice. Current models derived from regression are limited by the imprecision of GFR estimates. We hypothesized that an artificial neural network (ANN) might improve the precision of GFR estimates. A study of diagnostic test accuracy. 1,230 patients with chronic kidney disease were enrolled, including the development cohort (n=581), internal validation cohort (n=278), and external validation cohort (n=371). Estimated GFR (eGFR) using a new ANN model and a new regression model using age, sex, and standardized serum creatinine level derived in the development and internal validation cohort, and the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) 2009 creatinine equation. Measured GFR (mGFR). GFR was measured using a diethylenetriaminepentaacetic acid renal dynamic imaging method. Serum creatinine was measured with an enzymatic method traceable to isotope-dilution mass spectrometry. In the external validation cohort, mean mGFR was 49±27 (SD) mL/min/1.73 m2 and biases (median difference between mGFR and eGFR) for the CKD-EPI, new regression, and new ANN models were 0.4, 1.5, and -0.5 mL/min/1.73 m2, respectively (P<0.001 and P=0.02 compared to CKD-EPI and P<0.001 comparing the new regression and ANN models). Precisions (IQRs for the difference) were 22.6, 14.9, and 15.6 mL/min/1.73 m2, respectively (P<0.001 for both compared to CKD-EPI and P<0.001 comparing the new ANN and new regression models). Accuracies (proportions of eGFRs not deviating >30% from mGFR) were 50.9%, 77.4%, and 78.7%, respectively (P<0.001 for both compared to CKD-EPI and P=0.5 comparing the new ANN and new regression models). Different methods for measuring GFR were a source of systematic bias in comparisons of new models to CKD-EPI, and both the derivation and validation cohorts consisted of a group of patients who were referred to the same institution. An ANN model using 3 variables did not perform better than a new regression model. Whether ANN can improve GFR estimation using more variables requires further investigation. Copyright © 2013 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.
Jing, Chu-Yu; Fu, Yi-Peng; Zheng, Su-Su; Yi, Yong; Shen, Hu-Jia; Huang, Jin-Long; Xu, Xin; Lin, Jia-Jia; Zhou, Jian; Fan, Jia; Ren, Zheng-Gang; Qiu, Shuang-Jian; Zhang, Bo-Heng
2017-01-01
Abstract Adjuvant transarterial chemoembolization (TACE) is a major option for postoperative hepatocellular carcinoma (HCC) patients with recurrence risk factors. However, individualized predictive models for subgroup of these patients are limited. This study aimed to develop a prognostic nomogram for patients with HCC underwent adjuvant TACE following curative resection. A cohort comprising 144 HCC patients who received adjuvant TACE following curative resection in the Zhongshan Hospital were analyzed. The nomogram was formulated based on independent prognostic indicators for overall survival (OS). The performance of the nomogram was evaluated by the concordance index (C-index), calibration curve, and decision curve analysis (DCA) and compared with the conventional staging systems. The results were validated in an independent cohort of 86 patients with the same inclusion criteria. Serum alpha-fetoprotein (AFP), hyper-sensitive C-reactive protein (hs-CRP), incomplete tumor encapsulation, and double positive staining of Cytokeratin 7 and Cytokeratin 19 on tumor cells were identified as independent predictors for OS. The C-indices of the nomogram for OS prediction in the training cohort and validation cohort were 0.787 (95%CI 0.775–0.799) and 0.714 (95%CI 0.695–0.733), respectively. In both the training and validation cohorts, the calibration plot showed good consistency between the nomogram-predicted and the observed survival. Furthermore, the established nomogram was superior to the conventional staging systems in terms of C-index and clinical net benefit on DCA. The proposed nomogram provided an accurate prediction on risk stratification for HCC patients underwent adjuvant TACE following curative resection. PMID:28296727
The heterogeneity of systemic inflammation in bronchiectasis.
Saleh, Aarash D; Chalmers, James D; De Soyza, Anthony; Fardon, Thomas C; Koustas, Spiro O; Scott, Jonathan; Simpson, A John; Brown, Jeremy S; Hurst, John R
2017-06-01
Systemic inflammation in bronchiectasis is poorly studied in relation to aetiology and severity. We hypothesized that molecular patterns of inflammation may define particular aetiology and severity groups in bronchiectasis. We assayed blood concentrations of 31 proteins from 90 bronchiectasis patients (derivation cohort) and conducted PCA to examine relationships between these markers, disease aetiology and severity. Key results were validated in two separate cohorts of 97 and 79 patients from other centres. There was significant heterogeneity in protein concentrations across the derivation population. Increasing severity of bronchiectasis (BSI) was associated with increasing fibrinogen (rho = 0.34, p = 0.001 -validated in a second cohort), and higher fibrinogen was associated with worse lung function, Pseudomonas colonisation and impaired health-status. There were generally similar patterns of inflammation in patients with idiopathic and post-infectious disease. However, patients with primary immunodeficiency had exaggerated IL-17 responses, validated in a second cohort (n = 79, immunodeficient 12.82 pg/ml versus idiopathic/post-infectious 4.95 pg/ml, p = 0.001), and thus IL-17 discriminated primary immunodeficiency from other aetiologies (AUC 0.769 (95%CI 0.661-0.877)). Bronchiectasis is associated with heterogeneity of systemic inflammatory proteins not adequately explained by differences in disease aetiology or severity. More severe disease is associated with enhanced acute-phase responses. Plasma fibrinogen was associated with bronchiectasis severity in two cohorts, Pseudomonas colonisation and health status, and offers potential as a useful biomarker. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.
Falcone, M; Tiseo, G; Tascini, C; Russo, A; Sozio, E; Raponi, G; Rosin, C; Pignatelli, P; Carfagna, P; Farcomeni, A; Luzzati, R; Violi, F; Menichetti, F; Venditti, M
2017-06-01
An increasing prevalence of candidemia has been reported in Internal Medicine wards (IMWs). The aim of our study was to identify risk factors for candidemia among non-neutropenic patients hospitalized in IMWs. A multicenter case-control study was performed in three hospitals in Italy. Patients developing candidemia (cases) were compared to patients without candidemia (controls) matched by age, time of admission and duration of hospitalization. A logistic regression analysis identified risk factors for candidemia, and a new risk score was developed. Validation was performed on an external cohort of patients. Overall, 951 patients (317 cases of candidemia and 634 controls) were included in the derivation cohort, while 270 patients (90 patients with candidemia and 180 controls) constituted the validation cohort. Severe sepsis or septic shock, recent Clostridium difficile infection, diabetes mellitus, total parenteral nutrition, chronic obstructive pulmonary disease, concomitant intravenous glycopeptide therapy, presence of peripherally inserted central catheter, previous antibiotic therapy and immunosuppressive therapy were factors independently associated with candidemia. The new risk score showed good area under the curve (AUC) values in both derivation (AUC 0.973 95% CI 0.809-0.997, p<0.001) and validation cohort (0.867 95% CI 0.710-0.931, p<0.001). A threshold of 3 leads to a sensitivity of 87% and a specificity of 83%. Non-neutropenic patients admitted in IMWs have peculiar risk factors for candidemia. A new risk score with a good performance could facilitate the identification of candidates to early antifungal therapy. Copyright © 2017 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.
Skopp, Nancy A; Smolenski, Derek J; Schwesinger, Daniel A; Johnson, Christopher J; Metzger-Abamukong, Melinda J; Reger, Mark A
2017-06-01
Accurate knowledge of the vital status of individuals is critical to the validity of mortality research. National Death Index (NDI) and NDI-Plus are comprehensive epidemiological resources for mortality ascertainment and cause of death data that require additional user validation. Currently, there is a gap in methods to guide validation of NDI search results rendered for active duty service members. The purpose of this research was to adapt and evaluate the CDC National Program of Cancer Registries (NPCR) algorithm for mortality ascertainment in a large military cohort. We adapted and applied the NPCR algorithm to a cohort of 7088 service members on active duty at the time of death at some point between 2001 and 2009. We evaluated NDI validity and NDI-Plus diagnostic agreement against the Department of Defense's Armed Forces Medical Examiner System (AFMES). The overall sensitivity of the NDI to AFMES records after the application of the NPCR algorithm was 97.1%. Diagnostic estimates of measurement agreement between the NDI-Plus and the AFMES cause of death groups were high. The NDI and NDI-Plus can be successfully used with the NPCR algorithm to identify mortality and cause of death among active duty military cohort members who die in the United States. Published by Elsevier Inc.
Validation of the DECAF score to predict hospital mortality in acute exacerbations of COPD
Echevarria, C; Steer, J; Heslop-Marshall, K; Stenton, SC; Hickey, PM; Hughes, R; Wijesinghe, M; Harrison, RN; Steen, N; Simpson, AJ; Gibson, GJ; Bourke, SC
2016-01-01
Background Hospitalisation due to acute exacerbations of COPD (AECOPD) is common, and subsequent mortality high. The DECAF score was derived for accurate prediction of mortality and risk stratification to inform patient care. We aimed to validate the DECAF score, internally and externally, and to compare its performance to other predictive tools. Methods The study took place in the two hospitals within the derivation study (internal validation) and in four additional hospitals (external validation) between January 2012 and May 2014. Consecutive admissions were identified by screening admissions and searching coding records. Admission clinical data, including DECAF indices, and mortality were recorded. The prognostic value of DECAF and other scores were assessed by the area under the receiver operator characteristic (AUROC) curve. Results In the internal and external validation cohorts, 880 and 845 patients were recruited. Mean age was 73.1 (SD 10.3) years, 54.3% were female, and mean (SD) FEV1 45.5 (18.3) per cent predicted. Overall mortality was 7.7%. The DECAF AUROC curve for inhospital mortality was 0.83 (95% CI 0.78 to 0.87) in the internal cohort and 0.82 (95% CI 0.77 to 0.87) in the external cohort, and was superior to other prognostic scores for inhospital or 30-day mortality. Conclusions DECAF is a robust predictor of mortality, using indices routinely available on admission. Its generalisability is supported by consistent strong performance; it can identify low-risk patients (DECAF 0–1) potentially suitable for Hospital at Home or early supported discharge services, and high-risk patients (DECAF 3–6) for escalation planning or appropriate early palliation. Trial registration number UKCRN ID 14214. PMID:26769015
Shi, K-Q; Zhou, Y-Y; Yan, H-D; Li, H; Wu, F-L; Xie, Y-Y; Braddock, M; Lin, X-Y; Zheng, M-H
2017-02-01
At present, there is no ideal model for predicting the short-term outcome of patients with acute-on-chronic hepatitis B liver failure (ACHBLF). This study aimed to establish and validate a prognostic model by using the classification and regression tree (CART) analysis. A total of 1047 patients from two separate medical centres with suspected ACHBLF were screened in the study, which were recognized as derivation cohort and validation cohort, respectively. CART analysis was applied to predict the 3-month mortality of patients with ACHBLF. The accuracy of the CART model was tested using the area under the receiver operating characteristic curve, which was compared with the model for end-stage liver disease (MELD) score and a new logistic regression model. CART analysis identified four variables as prognostic factors of ACHBLF: total bilirubin, age, serum sodium and INR, and three distinct risk groups: low risk (4.2%), intermediate risk (30.2%-53.2%) and high risk (81.4%-96.9%). The new logistic regression model was constructed with four independent factors, including age, total bilirubin, serum sodium and prothrombin activity by multivariate logistic regression analysis. The performances of the CART model (0.896), similar to the logistic regression model (0.914, P=.382), exceeded that of MELD score (0.667, P<.001). The results were confirmed in the validation cohort. We have developed and validated a novel CART model superior to MELD for predicting three-month mortality of patients with ACHBLF. Thus, the CART model could facilitate medical decision-making and provide clinicians with a validated practical bedside tool for ACHBLF risk stratification. © 2016 John Wiley & Sons Ltd.
Palliative care and prognosis in COPD: a systematic review with a validation cohort.
Almagro, Pere; Yun, Sergi; Sangil, Ana; Rodríguez-Carballeira, Mónica; Marine, Meritxell; Landete, Pedro; Soler-Cataluña, Juan José; Soriano, Joan B; Miravitlles, Marc
2017-01-01
Current recommendations to consider initiation of palliative care (PC) in COPD patients are often based on an expected poor prognosis. However, this approach is not evidence-based, and which and when COPD patients should start PC is controversial. We aimed to assess whether current suggested recommendations for initiating PC were sufficiently reliable. We identified prognostic variables proposed in the literature for initiating PC; then, we ascertained their relationship with 1-year mortality, and finally, we validated their utility in our cohort of 697 patients hospitalized for COPD exacerbation. From 24 articles of 499 screened, we selected 20 variables and retrieved 48 original articles in which we were able to calculate the relationship between each of them and 1-year mortality. The number of studies where 1-year mortality was detailed for these variables ranged from 9 for previous hospitalizations or FEV 1 ≤30% to none for albumin ≤25 mg/dL. The percentage of 1-year mortality in the literature for these variables ranged from 5% to 60%. In the validation cohort study, the prevalence of these proposed variables ranged from 8% to 64%; only 10 of the 18 variables analyzed in our cohort reached statistical significance with Cox regression analysis, and none overcame an area under the curve ≥0.7. We conclude that none of the suggested criteria for initiating PC based on an expected poor vital prognosis in COPD patients in the short or medium term offers sufficient reliability, and consequently, they should be avoided as exclusive criteria for considering PC or at least critically appraised.
Palliative care and prognosis in COPD: a systematic review with a validation cohort
Almagro, Pere; Yun, Sergi; Sangil, Ana; Rodríguez-Carballeira, Mónica; Marine, Meritxell; Landete, Pedro; Soler-Cataluña, Juan José; Soriano, Joan B; Miravitlles, Marc
2017-01-01
Current recommendations to consider initiation of palliative care (PC) in COPD patients are often based on an expected poor prognosis. However, this approach is not evidence-based, and which and when COPD patients should start PC is controversial. We aimed to assess whether current suggested recommendations for initiating PC were sufficiently reliable. We identified prognostic variables proposed in the literature for initiating PC; then, we ascertained their relationship with 1-year mortality, and finally, we validated their utility in our cohort of 697 patients hospitalized for COPD exacerbation. From 24 articles of 499 screened, we selected 20 variables and retrieved 48 original articles in which we were able to calculate the relationship between each of them and 1-year mortality. The number of studies where 1-year mortality was detailed for these variables ranged from 9 for previous hospitalizations or FEV1 ≤30% to none for albumin ≤25 mg/dL. The percentage of 1-year mortality in the literature for these variables ranged from 5% to 60%. In the validation cohort study, the prevalence of these proposed variables ranged from 8% to 64%; only 10 of the 18 variables analyzed in our cohort reached statistical significance with Cox regression analysis, and none overcame an area under the curve ≥0.7. We conclude that none of the suggested criteria for initiating PC based on an expected poor vital prognosis in COPD patients in the short or medium term offers sufficient reliability, and consequently, they should be avoided as exclusive criteria for considering PC or at least critically appraised. PMID:28652724
Perlis, Roy H
2013-07-01
Early identification of depressed individuals at high risk for treatment resistance could be helpful in selecting optimal setting and intensity of care. At present, validated tools to facilitate this risk stratification are rarely used in psychiatric practice. Data were drawn from the first two treatment levels of a multicenter antidepressant effectiveness study in major depressive disorder, the STAR*D (Sequenced Treatment Alternatives to Relieve Depression) cohort. This cohort was divided into training, testing, and validation subsets. Only clinical or sociodemographic variables available by or readily amenable to self-report were considered. Multivariate models were developed to discriminate individuals reaching remission with a first or second pharmacological treatment trial from those not reaching remission despite two trials. A logistic regression model achieved an area under the receiver operating characteristic curve exceeding .71 in training, testing, and validation cohorts and maintained good calibration across cohorts. Performance of three alternative models with machine learning approaches--a naïve Bayes classifier and a support vector machine, and a random forest model--was less consistent. Similar performance was observed between more and less severe depression, men and women, and primary versus specialty care sites. A web-based calculator was developed that implements this tool and provides graphical estimates of risk. Risk for treatment resistance among outpatients with major depressive disorder can be estimated with a simple model incorporating baseline sociodemographic and clinical features. Future studies should examine the performance of this model in other clinical populations and its utility in treatment selection or clinical trial design. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
Tilki, Derya; Mandel, Philipp; Schlomm, Thorsten; Chun, Felix K-H; Tennstedt, Pierre; Pehrke, Dirk; Haese, Alexander; Huland, Hartwig; Graefen, Markus; Salomon, Georg
2015-06-01
The CAPRA-S score predicts prostate cancer recurrence based on pathological information from radical prostatectomy. To our knowledge CAPRA-S has never been externally validated in a European cohort. We independently validated CAPRA-S in a single institution European database. The study cohort comprised 14,532 patients treated with radical prostatectomy between January 1992 and August 2012. Prediction of biochemical recurrence, metastasis and cancer specific mortality by CAPRA-S was assessed by Kaplan-Meier analysis and the c-index. CAPRA-S performance to predict biochemical recurrence was evaluated by calibration plot and decision curve analysis. Median followup was 50.8 months (IQR 25.0-96.0). Biochemical recurrence developed in 20.3% of men at a median of 21.2 months (IQR 7.7-44.9). When stratifying patients by CAPRA-S risk group, estimated 5-year biochemical recurrence-free survival was 91.4%, 70.4% and 29.3% in the low, intermediate and high risk groups, respectively. The CAPRA-S c-index to predict biochemical recurrence, metastasis and cancer specific mortality was 0.80, 0.85 and 0.88, respectively. Metastasis developed in 417 men and 196 men died of prostate cancer. The CAPRA-S score was accurate when applied in a European study cohort. It predicted biochemical recurrence, metastasis and cancer specific mortality after radical prostatectomy with a c-index of greater than 0.80. The score can be valuable in regard to decision making for adjuvant therapy. Copyright © 2015. Published by Elsevier Inc.
Little, Paul; Moore, Michael; Hobbs, F D R; Mant, David; McNulty, Cliodna; Williamson, Ian; Cheng, Edith; Stuart, Beth; Kelly, Joanne; Barnett, Jane; Mullee, Mark
2013-01-01
Objective To assess the association between features of acute sore throat and the growth of streptococci from culturing a throat swab. Design Diagnostic cohort. Setting UK general practices. Participants Patients aged 5 or over presenting with an acute sore throat. Patients were recruited for a second cohort (cohort 2, n=517) consecutively after the first (cohort 1, n=606) from similar practices. Main outcome Predictors of the presence of Lancefield A/C/G streptococci. Results The clinical score developed from cohort 1 had poor discrimination in cohort 2 (bootstrapped estimate of area under the receiver operator characteristic (ROC) curve (0.65), due to the poor validity of the individual items in the second data set. Variables significant in multivariate analysis in both cohorts were rapid attendance (prior duration 3 days or less; multivariate adjusted OR 1.92 cohort, 1.67 cohort 2); fever in the last 24 h (1.69, 2.40); and doctor assessment of severity (severely inflamed pharynx/tonsils (2.28, 2.29)). The absence of coryza or cough and purulent tonsils were significant in univariate analysis in both cohorts and in multivariate analysis in one cohort. A five-item score based on Fever, Purulence, Attend rapidly (3 days or less), severely Inflamed tonsils and No cough or coryza (FeverPAIN) had moderate predictive value (bootstrapped area under the ROC curve 0.73 cohort 1, 0.71 cohort 2) and identified a substantial number of participants at low risk of streptococcal infection (38% in cohort 1, 36% in cohort 2 scored ≤1, associated with a streptococcal percentage of 13% and 18%, respectively). A Centor score of ≤1 identified 23% and 26% of participants with streptococcal percentages of 10% and 28%, respectively. Conclusions Items widely used to help identify streptococcal sore throat may not be the most consistent. A modified clinical scoring system (FeverPAIN) which requires further validation may be clinically helpful in identifying individuals who are unlikely to have major pathogenic streptococci. PMID:24163209
Little, Paul; Moore, Michael; Hobbs, F D R; Mant, David; McNulty, Cliodna; Williamson, Ian; Cheng, Edith; Stuart, Beth; Kelly, Joanne; Barnett, Jane; Mullee, Mark
2013-10-25
To assess the association between features of acute sore throat and the growth of streptococci from culturing a throat swab. Diagnostic cohort. UK general practices. Patients aged 5 or over presenting with an acute sore throat. Patients were recruited for a second cohort (cohort 2, n=517) consecutively after the first (cohort 1, n=606) from similar practices. Predictors of the presence of Lancefield A/C/G streptococci. The clinical score developed from cohort 1 had poor discrimination in cohort 2 (bootstrapped estimate of area under the receiver operator characteristic (ROC) curve (0.65), due to the poor validity of the individual items in the second data set. Variables significant in multivariate analysis in both cohorts were rapid attendance (prior duration 3 days or less; multivariate adjusted OR 1.92 cohort, 1.67 cohort 2); fever in the last 24 h (1.69, 2.40); and doctor assessment of severity (severely inflamed pharynx/tonsils (2.28, 2.29)). The absence of coryza or cough and purulent tonsils were significant in univariate analysis in both cohorts and in multivariate analysis in one cohort. A five-item score based on Fever, Purulence, Attend rapidly (3 days or less), severely Inflamed tonsils and No cough or coryza (FeverPAIN) had moderate predictive value (bootstrapped area under the ROC curve 0.73 cohort 1, 0.71 cohort 2) and identified a substantial number of participants at low risk of streptococcal infection (38% in cohort 1, 36% in cohort 2 scored ≤1, associated with a streptococcal percentage of 13% and 18%, respectively). A Centor score of ≤1 identified 23% and 26% of participants with streptococcal percentages of 10% and 28%, respectively. Items widely used to help identify streptococcal sore throat may not be the most consistent. A modified clinical scoring system (FeverPAIN) which requires further validation may be clinically helpful in identifying individuals who are unlikely to have major pathogenic streptococci.
Buchowski, Maciej S.; Matthews, Charles E.; Cohen, Sarah S.; Signorello, Lisa B.; Fowke, Jay H.; Hargreaves, Margaret K.; Schlundt, David G.; Blot, William J.
2012-01-01
Background Low physical activity (PA) is linked to cancer and other diseases prevalent in racial/ethnic minorities and low-income populations. This study evaluated the PA questionnaire (PAQ) used in the Southern Cohort Community Study, a prospective investigation of health disparities between African-American and white adults. Methods The PAQ was administered upon entry into the cohort (PAQ1) and after 12–15 months (PAQ2) in 118 participants (40–60 year-old, 48% male, 74% African-American). Test-retest reliability (PAQ1 versus PAQ2) was assessed using Spearman correlations and the Wilcoxon signed rank test. Criterion validity of the PAQ was assessed via comparison with a PA monitor and a last-month PA survey (LMPAS), administered up to 4 times in the study period. Results The PAQ test-retest reliability ranged from 0.25–0.54 for sedentary behaviors and 0.22–0.47 for active behaviors. The criterion validity for the PAQ compared with PA monitor ranged from 0.21–0.24 for sedentary behaviors and from 0.17–0.31 for active behaviors. There was general consistency in the magnitude of correlations between the PAQ and PA-monitor between African-Americans and whites. Conclusions The SCCS-PAQ has fair to moderate test-retest reliability and demonstrated some evidence of criterion validity for ranking participants by their level of sedentary and active behaviors. PMID:21952413
Hippisley-Cox, Julia; Coupland, Carol
2017-09-20
Objectives To derive and validate a risk prediction equation to estimate the short term risk of death, and to develop a classification method for frailty based on risk of death and risk of unplanned hospital admission. Design Prospective open cohort study. Participants Routinely collected data from 1436 general practices contributing data to QResearch in England between 2012 and 2016. 1079 practices were used to develop the scores and a separate set of 357 practices to validate the scores. 1.47 million patients aged 65-100 years were in the derivation cohort and 0.50 million patients in the validation cohort. Methods Cox proportional hazards models in the derivation cohort were used to derive separate risk equations in men and women for evaluation of the risk of death at one year. Risk factors considered were age, sex, ethnicity, deprivation, smoking status, alcohol intake, body mass index, medical conditions, specific drugs, social factors, and results of recent investigations. Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for each age and ethnic group. The new mortality equation was used in conjunction with the existing QAdmissions equation (which predicts risk of unplanned hospital admission) to classify patients into frailty groups. Main outcome measure The primary outcome was all cause mortality. Results During follow-up 180 132 deaths were identified in the derivation cohort arising from 4.39 million person years of observation. The final model included terms for age, body mass index, Townsend score, ethnic group, smoking status, alcohol intake, unplanned hospital admissions in the past 12 months, atrial fibrillation, antipsychotics, cancer, asthma or chronic obstructive pulmonary disease, living in a care home, congestive heart failure, corticosteroids, cardiovascular disease, dementia, epilepsy, learning disability, leg ulcer, chronic liver disease or pancreatitis, Parkinson's disease, poor mobility, rheumatoid arthritis, chronic kidney disease, type 1 diabetes, type 2 diabetes, venous thromboembolism, anaemia, abnormal liver function test result, high platelet count, visited doctor in the past year with either appetite loss, unexpected weight loss, or breathlessness. The model had good calibration and high levels of explained variation and discrimination. In women, the equation explained 55.6% of the variation in time to death (R 2 ), and had very good discrimination-the D statistic was 2.29, and Harrell's C statistic value was 0.85. The corresponding values for men were 53.1%, 2.18, and 0.84. By combining predicted risks of mortality and unplanned hospital admissions, 2.7% of patients (n=13 665) were classified as severely frail, 9.4% (n=46 770) as moderately frail, 43.1% (n=215 253) as mildly frail, and 44.8% (n=223 790) as fit. Conclusions We have developed new equations to predict the short term risk of death in men and women aged 65 or more, taking account of demographic, social, and clinical variables. The equations had good performance on a separate validation cohort. The QMortality equations can be used in conjunction with the QAdmissions equations, to classify patients into four frailty groups (known as QFrailty categories) to enable patients to be identified for further assessment or interventions. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Brantsaeter, Anne Lise; Haugen, Margaretha; Alexander, Jan; Meltzer, Helle Margrete
2008-01-01
The aim of the present study was to examine the relative validity of foods and nutrients calculated by a new food frequency questionnaire (FFQ) in the Norwegian Mother and Child Cohort Study (MoBa). Reference measures were a 4-day weighed food diary (FD), a motion sensor for measuring total energy expenditure, one 24-h urine collection for analysis of nitrogen and iodine excretion, and a venous blood specimen for analysis of plasma 25-hydroxy-vitamin D and serum folate. A total of 119 women participated in the validation study, and 112 completed the motion sensor registration. Overall, the level of agreement between the FFQ and the FD was satisfactory, and significant correlations were found for all major food groups and for all nutrients except vitamin E. The average correlation coefficient between the FFQ and the FD for daily intake was 0.48 for foods and 0.36 for nutrients, and on average, 68% of the participants were classified into the same or adjacent quintiles by the two methods. Estimated total energy expenditure indicated that under-reporting of energy intake was more extensive with the FD than with the FFQ. The biological markers confirmed that the FFQ was able to distinguish between high and low intakes of nutrients, as measured by vitamin D, folate, protein and iodine. This validation study indicates that the MoBa FFQ produces reasonable valid intake estimates and is a valid tool to rank pregnant women according to low and high intakes of energy, nutrients and foods.
Towards personalized therapy for multiple sclerosis: prediction of individual treatment response.
Kalincik, Tomas; Manouchehrinia, Ali; Sobisek, Lukas; Jokubaitis, Vilija; Spelman, Tim; Horakova, Dana; Havrdova, Eva; Trojano, Maria; Izquierdo, Guillermo; Lugaresi, Alessandra; Girard, Marc; Prat, Alexandre; Duquette, Pierre; Grammond, Pierre; Sola, Patrizia; Hupperts, Raymond; Grand'Maison, Francois; Pucci, Eugenio; Boz, Cavit; Alroughani, Raed; Van Pesch, Vincent; Lechner-Scott, Jeannette; Terzi, Murat; Bergamaschi, Roberto; Iuliano, Gerardo; Granella, Franco; Spitaleri, Daniele; Shaygannejad, Vahid; Oreja-Guevara, Celia; Slee, Mark; Ampapa, Radek; Verheul, Freek; McCombe, Pamela; Olascoaga, Javier; Amato, Maria Pia; Vucic, Steve; Hodgkinson, Suzanne; Ramo-Tello, Cristina; Flechter, Shlomo; Cristiano, Edgardo; Rozsa, Csilla; Moore, Fraser; Luis Sanchez-Menoyo, Jose; Laura Saladino, Maria; Barnett, Michael; Hillert, Jan; Butzkueven, Helmut
2017-09-01
Timely initiation of effective therapy is crucial for preventing disability in multiple sclerosis; however, treatment response varies greatly among patients. Comprehensive predictive models of individual treatment response are lacking. Our aims were: (i) to develop predictive algorithms for individual treatment response using demographic, clinical and paraclinical predictors in patients with multiple sclerosis; and (ii) to evaluate accuracy, and internal and external validity of these algorithms. This study evaluated 27 demographic, clinical and paraclinical predictors of individual response to seven disease-modifying therapies in MSBase, a large global cohort study. Treatment response was analysed separately for disability progression, disability regression, relapse frequency, conversion to secondary progressive disease, change in the cumulative disease burden, and the probability of treatment discontinuation. Multivariable survival and generalized linear models were used, together with the principal component analysis to reduce model dimensionality and prevent overparameterization. Accuracy of the individual prediction was tested and its internal validity was evaluated in a separate, non-overlapping cohort. External validity was evaluated in a geographically distinct cohort, the Swedish Multiple Sclerosis Registry. In the training cohort (n = 8513), the most prominent modifiers of treatment response comprised age, disease duration, disease course, previous relapse activity, disability, predominant relapse phenotype and previous therapy. Importantly, the magnitude and direction of the associations varied among therapies and disease outcomes. Higher probability of disability progression during treatment with injectable therapies was predominantly associated with a greater disability at treatment start and the previous therapy. For fingolimod, natalizumab or mitoxantrone, it was mainly associated with lower pretreatment relapse activity. The probability of disability regression was predominantly associated with pre-baseline disability, therapy and relapse activity. Relapse incidence was associated with pretreatment relapse activity, age and relapsing disease course, with the strength of these associations varying among therapies. Accuracy and internal validity (n = 1196) of the resulting predictive models was high (>80%) for relapse incidence during the first year and for disability outcomes, moderate for relapse incidence in Years 2-4 and for the change in the cumulative disease burden, and low for conversion to secondary progressive disease and treatment discontinuation. External validation showed similar results, demonstrating high external validity for disability and relapse outcomes, moderate external validity for cumulative disease burden and low external validity for conversion to secondary progressive disease and treatment discontinuation. We conclude that demographic, clinical and paraclinical information helps predict individual response to disease-modifying therapies at the time of their commencement. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Jesinghaus, Moritz; Strehl, Johanna; Boxberg, Melanie; Brühl, Frido; Wenzel, Adrian; Konukiewitz, Björn; Schlitter, Anna M; Steiger, Katja; Warth, Arne; Schnelzer, Andreas; Kiechle, Marion; Beckmann, Matthias W; Noske, Aurelia; Hartmann, Arndt; Mehlhorn, Grit; Koch, Martin C; Weichert, Wilko
2018-04-01
A novel histopathological grading system based on tumour budding and cell nest size has recently been shown to outperform conventional (WHO-based) grading algorithms in several tumour entities such as lung, oral, and oesophageal squamous cell carcinoma (SCC) in terms of prognostic patient stratification. Here, we tested the prognostic value of this innovative grading approach in two completely independent cohorts of SCC of the uterine cervix. To improve morphology-based grading, we investigated tumour budding activity and cell nest size as well as several other histomorphological factors (e.g., keratinization, nuclear size, mitotic activity) in a test cohort (n = 125) and an independent validation cohort (n = 122) of cervical SCC. All parameters were correlated with clinicopathological factors and patient outcome. Small cell nest size and high tumour budding activity were strongly associated with a dismal patient prognosis (p < 0.001 for overall survival [OS], disease-specific survival, and disease-free survival; test cohort) in both cohorts of cervical SCC. A novel grading algorithm combining these two parameters proved to be a highly effective, stage-independent prognosticator in both cohorts (OS: p < 0.001, test cohort; p = 0.001, validation cohort). In the test cohort, multivariate statistical analysis of the novel grade revealed that the hazard ratio (HR) for OS was 2.3 for G2 and 5.1 for G3 tumours compared to G1 neoplasms (p = 0.010). In the validation cohort, HR for OS was 3.0 for G2 and 7.2 for G3 tumours (p = 0.012). In conclusion, our novel grading algorithm incorporating cell nest size and tumour budding allows strongly prognostic histopathological grading of cervical SCC superior to WHO-based grading. Therefore, our data can be regarded as a cross-organ validation of previous results demonstrated for oesophageal, lung, and oral SCC. We suggest this grading algorithm as an additional morphology-based parameter for the routine diagnostic assessment of this tumour entity. © 2018 The Authors The Journal of Pathology: Clinical Research published by The Pathological Society of Great Britain and Ireland and John Wiley & Sons Ltd.
Kiehl, Erich L; Parker, Alex M; Matar, Ralph M; Gottbrecht, Matthew F; Johansen, Michelle C; Adams, Mark P; Griffiths, Lori A; Dunn, Steven P; Bidwell, Katherine L; Menon, Venu; Enfield, Kyle B; Gimple, Lawrence W
2017-05-20
Out-of-hospital cardiac arrest (OHCA) results in significant morbidity and mortality, primarily from neurologic injury. Predicting neurologic outcome early post-OHCA remains difficult in patients receiving targeted temperature management. Retrospective analysis was performed on consecutive OHCA patients receiving targeted temperature management (32-34°C) for 24 hours at a tertiary-care center from 2008 to 2012 (development cohort, n=122). The primary outcome was favorable neurologic outcome at hospital discharge, defined as cerebral performance category 1 to 2 (poor 3-5). Patient demographics, pre-OHCA diagnoses, and initial laboratory studies post-resuscitation were compared between favorable and poor neurologic outcomes with multivariable logistic regression used to develop a simple scoring system ( C-GRApH ). The C-GRApH score ranges 0 to 5 using equally weighted variables: ( C ): coronary artery disease, known pre-OHCA; ( G ): glucose ≥200 mg/dL; ( R ): rhythm of arrest not ventricular tachycardia/fibrillation; ( A ): age >45; ( pH ): arterial pH ≤7.0. A validation cohort (n=344) included subsequent patients from the initial site (n=72) and an external quaternary-care health system (n=272) from 2012 to 2014. The c-statistic for predicting neurologic outcome was 0.82 (0.74-0.90, P <0.001) in the development cohort and 0.81 (0.76-0.87, P <0.001) in the validation cohort. When subdivided by C-GRApH score, similar rates of favorable neurologic outcome were seen in both cohorts, 70% each for low (0-1, n=60), 22% versus 19% for medium (2-3, n=307), and 0% versus 2% for high (4-5, n=99) C-GRApH scores in the development and validation cohorts, respectively. C-GRApH stratifies neurologic outcomes following OHCA in patients receiving targeted temperature management (32-34°C) using objective data available at hospital presentation, identifying patient subsets with disproportionally favorable ( C-GRApH ≤1) and poor ( C-GRApH ≥4) prognoses. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.
Novel equations to estimate lean body mass in maintenance hemodialysis patients.
Noori, Nazanin; Kovesdy, Csaba P; Bross, Rachelle; Lee, Martin; Oreopoulos, Antigone; Benner, Deborah; Mehrotra, Rajnish; Kopple, Joel D; Kalantar-Zadeh, Kamyar
2011-01-01
Lean body mass (LBM) is an important nutritional measure representing muscle mass and somatic protein in hemodialysis patients, for whom we developed and tested equations to estimate LBM. A study of diagnostic test accuracy. The development cohort included 118 hemodialysis patients with LBM measured using dual-energy x-ray absorptiometry (DEXA) and near-infrared (NIR) interactance. The validation cohort included 612 additional hemodialysis patients with LBM measured using a portable NIR interactance technique during hemodialysis. 3-month averaged serum concentrations of creatinine, albumin, and prealbumin; normalized protein nitrogen appearance; midarm muscle circumference (MAMC); handgrip strength; and subjective global assessment of nutrition. LBM measured using DEXA in the development cohort and NIR interactance in validation cohorts. In the development cohort, DEXA and NIR interactance correlated strongly (r = 0.94, P < 0.001). DEXA-measured LBM correlated with serum creatinine level, MAMC, and handgrip strength, but not with other nutritional markers. Three regression equations to estimate DEXA-measured LBM were developed based on each of these 3 surrogates and sex, height, weight, and age (and urea reduction ratio for the serum creatinine regression). In the validation cohort, the validity of the equations was tested against the NIR interactance-measured LBM. The equation estimates correlated well with NIR interactance-measured LBM (R² ≥ 0.88), although in higher LBM ranges, they tended to underestimate it. Median (95% confidence interval) differences and interquartile range for differences between equation estimates and NIR interactance-measured LBM were 3.4 (-3.2 to 12.0) and 3.0 (1.1-5.1) kg for serum creatinine and 4.0 (-2.6 to 13.6) and 3.7 (1.3-6.0) kg for MAMC, respectively. DEXA measurements were obtained on a nondialysis day, whereas NIR interactance was performed during hemodialysis treatment, with the likelihood of confounding by volume status variations. Compared with reference measures of LBM, equations using serum creatinine level, MAMC, or handgrip strength and demographic variables can estimate LBM accurately in long-term hemodialysis patients. Copyright © 2010 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.
Kanai, Masashi; Okamoto, Kazuya; Yamamoto, Yosuke; Yoshioka, Akira; Hiramoto, Shuji; Nozaki, Akira; Nishikawa, Yoshitaka; Yamaguchi, Daisuke; Tomono, Teruko; Nakatsui, Masahiko; Baba, Mika; Morita, Tatsuya; Matsumoto, Shigemi; Kuroda, Tomohiro; Okuno, Yasushi; Muto, Manabu
2017-01-01
Background We aimed to develop an adaptable prognosis prediction model that could be applied at any time point during the treatment course for patients with cancer receiving chemotherapy, by applying time-series real-world big data. Methods Between April 2004 and September 2014, 4,997 patients with cancer who had received systemic chemotherapy were registered in a prospective cohort database at the Kyoto University Hospital. Of these, 2,693 patients with a death record were eligible for inclusion and divided into training (n = 1,341) and test (n = 1,352) cohorts. In total, 3,471,521 laboratory data at 115,738 time points, representing 40 laboratory items [e.g., white blood cell counts and albumin (Alb) levels] that were monitored for 1 year before the death event were applied for constructing prognosis prediction models. All possible prediction models comprising three different items from 40 laboratory items (40C3 = 9,880) were generated in the training cohort, and the model selection was performed in the test cohort. The fitness of the selected models was externally validated in the validation cohort from three independent settings. Results A prognosis prediction model utilizing Alb, lactate dehydrogenase, and neutrophils was selected based on a strong ability to predict death events within 1–6 months and a set of six prediction models corresponding to 1,2, 3, 4, 5, and 6 months was developed. The area under the curve (AUC) ranged from 0.852 for the 1 month model to 0.713 for the 6 month model. External validation supported the performance of these models. Conclusion By applying time-series real-world big data, we successfully developed a set of six adaptable prognosis prediction models for patients with cancer receiving chemotherapy. PMID:28837592
Reliability and validity of the Modified Erikson Psychosocial Stage Inventory in diverse samples.
Leidy, N K; Darling-Fisher, C S
1995-04-01
The Modified Erikson Psychosocial Stage Inventory (MEPSI) is a relatively simple survey measure designed to assess the strength of psychosocial attributes that arise from progression through Erikson's eight stages of development. The purpose of this study was to employ secondary analysis to evaluate the internal-consistency reliability and construct validity of the MEPSI across four diverse samples: healthy young adults, hemophilic men, healthy older adults, and older adults with chronic obstructive pulmonary disease. Special attention was given to the performance of the measure across gender, with exploratory analyses examining possible age cohort and health status effects. Internal-consistency estimates for the aggregate measure were high, whereas subscale reliability levels varied across age groups. Construct validity was supported across samples. Gender, cohort, and health effects offered interesting psychometric and theoretical insights and direction for further research. Findings indicated that the MEPSI might be a useful instrument for operationalizing and testing Eriksonian developmental theory in adults.
Validation of a computer case definition for sudden cardiac death in opioid users.
Kawai, Vivian K; Murray, Katherine T; Stein, C Michael; Cooper, William O; Graham, David J; Hall, Kathi; Ray, Wayne A
2012-08-31
To facilitate the use of automated databases for studies of sudden cardiac death, we previously developed a computerized case definition that had a positive predictive value between 86% and 88%. However, the definition has not been specifically validated for prescription opioid users, for whom out-of-hospital overdose deaths may be difficult to distinguish from sudden cardiac death. We assembled a cohort of persons 30-74 years of age prescribed propoxyphene or hydrocodone who had no life-threatening non-cardiovascular illness, diagnosed drug abuse, residence in a nursing home in the past year, or hospital stay within the past 30 days. Medical records were sought for a sample of 140 cohort deaths within 30 days of a prescription fill meeting the computer case definition. Of the 140 sampled deaths, 81 were adjudicated; 73 (90%) were sudden cardiac deaths. Two deaths had possible opioid overdose; after removing these two the positive predictive value was 88%. These findings are consistent with our previous validation studies and suggest the computer case definition of sudden cardiac death is a useful tool for pharmacoepidemiologic studies of opioid analgesics.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Martens, Milou H., E-mail: mh.martens@hotmail.com; Department of Surgery, Maastricht University Medical Center, Maastricht; GROW School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht
2015-12-01
Purpose: To review the available literature on tumor size/volume measurements on magnetic resonance imaging for response assessment after chemoradiotherapy, and validate these cut-offs in an independent multicenter patient cohort. Methods and Materials: The study included 2 parts. (1) Review of the literature: articles were included that assessed the accuracy of tumor size/volume measurements on magnetic resonance imaging for tumor response assessment. Size/volume cut-offs were extracted; (2) Multicenter validation: extracted cut-offs from the literature were tested in a multicenter cohort (n=146). Accuracies were calculated and compared with reported results from the literature. Results: The review included 14 articles, in which 3more » different measurement methods were assessed: (1) tumor length; (2) 3-dimensonial tumor size; and (3) whole volume. Study outcomes consisted of (1) complete response (ypT0) versus residual tumor; (2) tumor regression grade 1 to 2 versus 3 to 5; and (3) T-downstaging (ypT« less
ERIC Educational Resources Information Center
Murray, Catherine; Johnson, Wendy; Wolf, Michael S.; Deary, Ian J.
2011-01-01
Three hundred and four participants in the Lothian Birth Cohort 1936 study took a validated IQ-type test at age 11 years and a battery of cognitive tests at age 70 years. Three tests of health literacy were completed at age 72 years; the Rapid Estimate of Adult Literacy in Medicine (REALM), the Test of Functional Health Literacy in Adults…
Lalande, Laure; Bourguignon, Laurent; Carlier, Chloé; Ducher, Michel
2013-06-01
Falls in geriatry are associated with important morbidity, mortality and high healthcare costs. Because of the large number of variables related to the risk of falling, determining patients at risk is a difficult challenge. The aim of this work was to validate a tool to detect patients with high risk of fall using only bibliographic knowledge. Thirty articles corresponding to 160 studies were used to modelize fall risk. A retrospective case-control cohort including 288 patients (88 ± 7 years) and a prospective cohort including 106 patients (89 ± 6 years) from two geriatric hospitals were used to validate the performances of our model. We identified 26 variables associated with an increased risk of fall. These variables were split into illnesses, medications, and environment. The combination of the three associated scores gives a global fall score. The sensitivity and the specificity were 31.4, 81.6, 38.5, and 90 %, respectively, for the retrospective and the prospective cohort. The performances of the model are similar to results observed with already existing prediction tools using model adjustment to data from numerous cohort studies. This work demonstrates that knowledge from the literature can be synthesized with Bayesian networks.
Dealing with dietary measurement error in nutritional cohort studies.
Freedman, Laurence S; Schatzkin, Arthur; Midthune, Douglas; Kipnis, Victor
2011-07-20
Dietary measurement error creates serious challenges to reliably discovering new diet-disease associations in nutritional cohort studies. Such error causes substantial underestimation of relative risks and reduction of statistical power for detecting associations. On the basis of data from the Observing Protein and Energy Nutrition Study, we recommend the following approaches to deal with these problems. Regarding data analysis of cohort studies using food-frequency questionnaires, we recommend 1) using energy adjustment for relative risk estimation; 2) reporting estimates adjusted for measurement error along with the usual relative risk estimates, whenever possible (this requires data from a relevant, preferably internal, validation study in which participants report intakes using both the main instrument and a more detailed reference instrument such as a 24-hour recall or multiple-day food record); 3) performing statistical adjustment of relative risks, based on such validation data, if they exist, using univariate (only for energy-adjusted intakes such as densities or residuals) or multivariate regression calibration. We note that whereas unadjusted relative risk estimates are biased toward the null value, statistical significance tests of unadjusted relative risk estimates are approximately valid. Regarding study design, we recommend increasing the sample size to remedy loss of power; however, it is important to understand that this will often be an incomplete solution because the attenuated signal may be too small to distinguish from unmeasured confounding in the model relating disease to reported intake. Future work should be devoted to alleviating the problem of signal attenuation, possibly through the use of improved self-report instruments or by combining dietary biomarkers with self-report instruments.
Yates, Janet; James, David
2010-07-28
The UK Clinical Aptitude Test (UKCAT) was introduced in 2006 as an additional tool for the selection of medical students. It tests mental ability in four distinct domains (Quantitative Reasoning, Verbal Reasoning, Abstract Reasoning, and Decision Analysis), and the results are available to students and admissions panels in advance of the selection process. As yet the predictive validity of the test against course performance is largely unknown.The study objective was to determine whether UKCAT scores predict performance during the first two years of the 5-year undergraduate medical course at Nottingham. We studied a single cohort of students, who entered Nottingham Medical School in October 2007 and had taken the UKCAT. We used linear regression analysis to identify independent predictors of marks for different parts of the 2-year preclinical course. Data were available for 204/260 (78%) of the entry cohort. The UKCAT total score had little predictive value. Quantitative Reasoning was a significant independent predictor of course marks in Theme A ('The Cell'), (p = 0.005), and Verbal Reasoning predicted Theme C ('The Community') (p < 0.001), but otherwise the effects were slight or non-existent. This limited study from a single entry cohort at one medical school suggests that the predictive value of the UKCAT, particularly the total score, is low. Section scores may predict success in specific types of course assessment.The ultimate test of validity will not be available for some years, when current cohorts of students graduate. However, if this test of mental ability does not predict preclinical performance, it is arguably less likely to predict the outcome in the clinical years. Further research from medical schools with different types of curriculum and assessment is needed, with longitudinal studies throughout the course.
Signorello, Lisa B; Buchowski, Maciej S; Cai, Qiuyin; Munro, Heather M; Hargreaves, Margaret K; Blot, William J
2010-02-15
Few food frequency questionnaires (FFQs) have been developed specifically for use among African Americans, and reports of FFQ performance among African Americans or low-income groups assessed using biochemical indicators are scarce. The authors conducted a validation study within the Southern Community Cohort Study to evaluate FFQ-estimated intakes of alpha-carotene, beta-carotene, beta-cryptoxanthin, lutein/zeaxanthin, lycopene, folate, and alpha-tocopherol in relation to blood levels of these nutrients. Included were 255 nonsmoking participants (125 African Americans, 130 non-Hispanic whites) who provided a blood sample at the time of study enrollment and FFQ administration in 2002-2004. Levels of biochemical indicators of each micronutrient (alpha-tocopherol among women only) significantly increased with increasing FFQ-estimated intake (adjusted correlation coefficients: alpha-carotene, 0.35; beta-carotene, 0.28; beta-cryptoxanthin, 0.35; lutein/zeaxanthin, 0.28; lycopene, 0.15; folate, 0.26; alpha-tocopherol, 0.26 among women; all P's < 0.05). Subjects in the top decile of FFQ intake had blood levels that were 27% (lycopene) to 178% (beta-cryptoxanthin) higher than those of subjects in the lowest decile. Satisfactory FFQ performance was noted even for participants with less than a high school education. Some variation was noted in the FFQ's ability to predict blood levels for subgroups defined by race, sex, and other characteristics, but overall the Southern Community Cohort Study FFQ appears to generate useful dietary exposure rankings in the cohort.
Quah, Phaik Ling; Cheung, Yin Bun; Pang, Wei Wei; Toh, Jia Ying; Saw, Seang-Mei; Godfrey, Keith M; Yap, Fabian; Chong, Yap Seng; Mary, Chong Foong-Fong
2017-06-01
The Children's Eating Behaviour Questionnaire (CEBQ) was developed to measure eating behaviors related to obesity risk in children. However, this questionnaire has not been validated for use in South East Asia, where parenting practices are different from those in western countries and child obesity rates are increasing. The aim of this study was to examine the validity of the CEBQ administered to mothers of children aged 3 years in Singapore. Confirmatory factor analysis (CFA) was used to examine if the original 35-item, 8-factor model was supported in our cohort. Participants were 636 mother-child dyads (mean (SD) child age = 36.7 (1.6) months), from the Growing Up in Singapore Towards healthy Outcomes (GUSTO) birth cohort in which the mothers were characterized in pregnancy and children were followed up to age 3 years. The CFA showed a poor model fit; RMSEA = 0.072 (PCLOSE<0.001), SRMR = 0.094, CFI = 0.826, and TLI = 0.805. Exploratory factor analysis revealed a 35 item, 7-factor structure (factor loadings ≥ 0.35): enjoyment of food, food fussiness, emotional overeating, desire to drink, emotional under eating, satiety responsiveness and slowness in eating. Cronbach's alpha estimates ranged from 0.70 to 0.88 for the 7 subscales. Convergent validity tests via correlation analysis revealed that emotional under eating (r = -0.14), slowness in eating (r = -0.16) and satiety responsiveness (r = -0.11) were negatively correlated with BMI z-score at 3 years, while enjoyment of food (r = 0.12) was positively correlated, p < 0.05. In conclusion, we found a revised 7-factor structure of the CEBQ more appropriate for examining eating behavior in 3 year old children in the Singapore setting. Further replication studies in a separate cohort study are warranted before further use of these factor structures generated. Copyright © 2017 Elsevier Ltd. All rights reserved.
Graafland, Maurits; Bok, Kiki; Schreuder, Henk W R; Schijven, Marlies P
2014-06-01
Untrained laparoscopic camera assistants in minimally invasive surgery (MIS) may cause suboptimal view of the operating field, thereby increasing risk for errors. Camera navigation is often performed by the least experienced member of the operating team, such as inexperienced surgical residents, operating room nurses, and medical students. The operating room nurses and medical students are currently not included as key user groups in structured laparoscopic training programs. A new virtual reality laparoscopic camera navigation (LCN) module was specifically developed for these key user groups. This multicenter prospective cohort study assesses face validity and construct validity of the LCN module on the Simendo virtual reality simulator. Face validity was assessed through a questionnaire on resemblance to reality and perceived usability of the instrument among experts and trainees. Construct validity was assessed by comparing scores of groups with different levels of experience on outcome parameters of speed and movement proficiency. The results obtained show uniform and positive evaluation of the LCN module among expert users and trainees, signifying face validity. Experts and intermediate experience groups performed significantly better in task time and camera stability during three repetitions, compared to the less experienced user groups (P < .007). Comparison of learning curves showed significant improvement of proficiency in time and camera stability for all groups during three repetitions (P < .007). The results of this study show face validity and construct validity of the LCN module. The module is suitable for use in training curricula for operating room nurses and novice surgical trainees, aimed at improving team performance in minimally invasive surgery. © The Author(s) 2013.
A microRNA-based prediction model for lymph node metastasis in hepatocellular carcinoma.
Zhang, Li; Xiang, Zuo-Lin; Zeng, Zhao-Chong; Fan, Jia; Tang, Zhao-You; Zhao, Xiao-Mei
2016-01-19
We developed an efficient microRNA (miRNA) model that could predict the risk of lymph node metastasis (LNM) in hepatocellular carcinoma (HCC). We first evaluated a training cohort of 192 HCC patients after hepatectomy and found five LNM associated predictive factors: vascular invasion, Barcelona Clinic Liver Cancer stage, miR-145, miR-31, and miR-92a. The five statistically independent factors were used to develop a predictive model. The predictive value of the miRNA-based model was confirmed in a validation cohort of 209 consecutive HCC patients. The prediction model was scored for LNM risk from 0 to 8. The cutoff value 4 was used to distinguish high-risk and low-risk groups. The model sensitivity and specificity was 69.6 and 80.2%, respectively, during 5 years in the validation cohort. And the area under the curve (AUC) for the miRNA-based prognostic model was 0.860. The 5-year positive and negative predictive values of the model in the validation cohort were 30.3 and 95.5%, respectively. Cox regression analysis revealed that the LNM hazard ratio of the high-risk versus low-risk groups was 11.751 (95% CI, 5.110-27.021; P < 0.001) in the validation cohort. In conclusion, the miRNA-based model is reliable and accurate for the early prediction of LNM in patients with HCC.
Hao, Lu; Pan, Jun; Wang, Dan; Bi, Ya-Wei; Ji, Jun-Tao; Xin, Lei; Liao, Zhuan; Du, Ting-Ting; Lin, Jin-Huan; Zhang, Di; Zeng, Xiang-Peng; Ye, Bo; Zou, Wen-Bin; Chen, Hui; Xie, Ting; Li, Bai-Rong; Zheng, Zhao-Hong; Hu, Liang-Hao; Li, Zhao-Shen
2017-07-01
Pancreatic pseudocyst is a common complication of chronic pancreatitis. The identification of risk factors and development of a nomogram for pancreatic pseudocysts in chronic pancreatitis patients may contribute to the early diagnosis and intervention of pancreatic pseudocysts. Patients with chronic pancreatitis admitted to our center from January 2000 to December 2013 were enrolled. Cumulative rates of pancreatic pseudocysts after the onset of chronic pancreatitis and after the diagnosis of chronic pancreatitis were calculated. Patients were randomly assigned, in a 2:1 ratio, to the training and validation cohort. Based on the training cohort, risk factors were identified through Cox proportional hazards regression model, and nomogram was developed. Internal and external validations were performed based on the training and validation cohort, respectively. With a total of 1998 patients, pancreatic pseudocysts were detected in 228 (11.41%) patients. Age at the onset of chronic pancreatitis, smoking, and severe acute pancreatitis were identified risk factors for pancreatic pseudocysts development while steatorrhea and pancreatic stones were protective factors. Incorporating these five factors, the nomogram achieved good concordance indexes of 0.735 and 0.628 in the training and validation cohorts, respectively, with well-fitted calibration curves. The nomogram achieved an individualized prediction of pancreatic pseudocysts development in chronic pancreatitis. It may help the early diagnosis and management of pancreatic pseudocysts. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.
Nogueira, Dália Santos; Ferreira, Pedro Lopes; Reis, Elizabeth Azevedo; Lopes, Inês Sousa
2015-10-01
The purpose of this study was to evaluate the validity and the reliability of the European Portuguese version of the EAT-10 (P-EAT-10). This research was conducted in three phases: (i) cultural and linguistic adaptation; (ii) feasibility and reliability test; and (iii) validity tests. The final sample was formed by a cohort of 520 subjects. The P-EAT-10 index was compared for socio-demographic and clinic variables. It was also compared for both dysphagic and non-dysphagic groups as well as for the results of the 3Oz wst. Lastly, the P-EAT-10 scores were correlated with the EuroQol Group Portuguese EQ-5D index. The Cronbach's α obtained for the P-EAT-10 scale was 0.952 and it remained excellent even if any item was deleted. The item-total and the intraclass correlation coefficients were very good. The P-EAT-10 mean of the non-dysphagic cohort was 0.56 and that of the dysphagic cohort was 14.26, the mean comparison between the 3Oz wst groups and the P-EAT-10 scores were significant. A significant higher perception of QoL was also found among the non-dysphagic subjects. P-EAT-10 is a valid and reliable measure that may be used to document dysphagia which makes it useful both for screening in clinical practice and in research.
Amra, Sakusic; O'Horo, John C; Singh, Tarun D; Wilson, Gregory A; Kashyap, Rahul; Petersen, Ronald; Roberts, Rosebud O; Fryer, John D; Rabinstein, Alejandro A; Gajic, Ognjen
2017-02-01
Long-term cognitive impairment is a common and important problem in survivors of critical illness. We developed electronic search algorithms to identify cognitive impairment and dementia from the electronic medical records (EMRs) that provide opportunity for big data analysis. Eligible patients met 2 criteria. First, they had a formal cognitive evaluation by The Mayo Clinic Study of Aging. Second, they were hospitalized in intensive care unit at our institution between 2006 and 2014. The "criterion standard" for diagnosis was formal cognitive evaluation supplemented by input from an expert neurologist. Using all available EMR data, we developed and improved our algorithms in the derivation cohort and validated them in the independent validation cohort. Of 993 participants who underwent formal cognitive testing and were hospitalized in intensive care unit, we selected 151 participants at random to form the derivation and validation cohorts. The automated electronic search algorithm for cognitive impairment was 94.3% sensitive and 93.0% specific. The search algorithms for dementia achieved respective sensitivity and specificity of 97% and 99%. EMR search algorithms significantly outperformed International Classification of Diseases codes. Automated EMR data extractions for cognitive impairment and dementia are reliable and accurate and can serve as acceptable and efficient alternatives to time-consuming manual data review. Copyright © 2016 Elsevier Inc. All rights reserved.
2017-10-01
been shown in many studies to improve predictive accuracy for cancer on initial biopsy,3,7-9 and to be correlated with more aggressive cancer at...our multi-center, prospectively accrued prostate cancer active surveillance cohort – the Canary Prostate Active Surveillance Study (PASS). We are in...objective of the study is to utilize analytically validated assays that take into account tumor heterogeneity to measure biomarkers in specimens that were
Singal, Amit G.; Mukherjee, Ashin; Elmunzer, B. Joseph; Higgins, Peter DR; Lok, Anna S.; Zhu, Ji; Marrero, Jorge A; Waljee, Akbar K
2015-01-01
Background Predictive models for hepatocellular carcinoma (HCC) have been limited by modest accuracy and lack of validation. Machine learning algorithms offer a novel methodology, which may improve HCC risk prognostication among patients with cirrhosis. Our study's aim was to develop and compare predictive models for HCC development among cirrhotic patients, using conventional regression analysis and machine learning algorithms. Methods We enrolled 442 patients with Child A or B cirrhosis at the University of Michigan between January 2004 and September 2006 (UM cohort) and prospectively followed them until HCC development, liver transplantation, death, or study termination. Regression analysis and machine learning algorithms were used to construct predictive models for HCC development, which were tested on an independent validation cohort from the Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) Trial. Both models were also compared to the previously published HALT-C model. Discrimination was assessed using receiver operating characteristic curve analysis and diagnostic accuracy was assessed with net reclassification improvement and integrated discrimination improvement statistics. Results After a median follow-up of 3.5 years, 41 patients developed HCC. The UM regression model had a c-statistic of 0.61 (95%CI 0.56-0.67), whereas the machine learning algorithm had a c-statistic of 0.64 (95%CI 0.60–0.69) in the validation cohort. The machine learning algorithm had significantly better diagnostic accuracy as assessed by net reclassification improvement (p<0.001) and integrated discrimination improvement (p=0.04). The HALT-C model had a c-statistic of 0.60 (95%CI 0.50-0.70) in the validation cohort and was outperformed by the machine learning algorithm (p=0.047). Conclusion Machine learning algorithms improve the accuracy of risk stratifying patients with cirrhosis and can be used to accurately identify patients at high-risk for developing HCC. PMID:24169273
Schultz, I Z; Crook, J; Berkowitz, J; Milner, R; Meloche, G R
2005-09-01
This paper reports on the predictive validity of a Psychosocial Risk for Occupational Disability Scale in the workers' compensation environment using a paper and pencil version of a previously validated multimethod instrument on a new, subacute sample of workers with low back pain. A cohort longitudinal study design with a randomly selected cohort off work for 4-6 weeks was applied. The questionnaire was completed by 111 eligible workers at 4-6 weeks following injury. Return to work status data at three months was obtained from 100 workers. Sixty-four workers had returned to work (RTW) and 36 had not (NRTW). Stepwise backward elimination resulted in a model with these predictors: Expectations of Recovery, SF-36 Vitality, SF-36 Mental Health, and Waddell Symptoms. The correct classification of RTW/NRTW was 79%, with sensitivity (NRTW) of 61% and specificity (RTW) of 89%. The area under the ROC curve was 84%. New evidence for predictive validity for the Psychosocial Risk-for-Disability Instrument was provided. The instrument can be useful and practical for prediction of return to work outcomes in the subacute stage after low back injury in the workers' compensation context.
Robinson, Tom; Elley, C Raina; Wells, Sue; Robinson, Elizabeth; Kenealy, Tim; Pylypchuk, Romana; Bramley, Dale; Arroll, Bruce; Crengle, Sue; Riddell, Tania; Ameratunga, Shanthi; Metcalf, Patricia; Drury, Paul L
2012-09-01
New Zealand (NZ) guidelines recommend treating people for cardiovascular disease (CVD) risk on the basis of five-year absolute risk using a NZ adaptation of the Framingham risk equation. A diabetes-specific Diabetes Cohort Study (DCS) CVD predictive risk model has been developed and validated using NZ Get Checked data. To revalidate the DCS model with an independent cohort of people routinely assessed using PREDICT, a web-based CVD risk assessment and management programme. People with Type 2 diabetes without pre-existing CVD were identified amongst people who had a PREDICT risk assessment between 2002 and 2005. From this group we identified those with sufficient data to allow estimation of CVD risk with the DCS models. We compared the DCS models with the NZ Framingham risk equation in terms of discrimination, calibration, and reclassification implications. Of 3044 people in our study cohort, 1829 people had complete data and therefore had CVD risks calculated. Of this group, 12.8% (235) had a cardiovascular event during the five-year follow-up. The DCS models had better discrimination than the currently used equation, with C-statistics being 0.68 for the two DCS models and 0.65 for the NZ Framingham model. The DCS models were superior to the NZ Framingham equation at discriminating people with diabetes who will have a cardiovascular event. The adoption of a DCS model would lead to a small increase in the number of people with diabetes who are treated with medication, but potentially more CVD events would be avoided.
Genetic risk prediction and neurobiological understanding of alcoholism
Levey, D F; Le-Niculescu, H; Frank, J; Ayalew, M; Jain, N; Kirlin, B; Learman, R; Winiger, E; Rodd, Z; Shekhar, A; Schork, N; Kiefe, F; Wodarz, N; Müller-Myhsok, B; Dahmen, N; Nöthen, M; Sherva, R; Farrer, L; Smith, A H; Kranzler, H R; Rietschel, M; Gelernter, J; Niculescu, A B
2014-01-01
We have used a translational Convergent Functional Genomics (CFG) approach to discover genes involved in alcoholism, by gene-level integration of genome-wide association study (GWAS) data from a German alcohol dependence cohort with other genetic and gene expression data, from human and animal model studies, similar to our previous work in bipolar disorder and schizophrenia. A panel of all the nominally significant P-value SNPs in the top candidate genes discovered by CFG (n=135 genes, 713 SNPs) was used to generate a genetic risk prediction score (GRPS), which showed a trend towards significance (P=0.053) in separating alcohol dependent individuals from controls in an independent German test cohort. We then validated and prioritized our top findings from this discovery work, and subsequently tested them in three independent cohorts, from two continents. In order to validate and prioritize the key genes that drive behavior without some of the pleiotropic environmental confounds present in humans, we used a stress-reactive animal model of alcoholism developed by our group, the D-box binding protein (DBP) knockout mouse, consistent with the surfeit of stress theory of addiction proposed by Koob and colleagues. A much smaller panel (n=11 genes, 66 SNPs) of the top CFG-discovered genes for alcoholism, cross-validated and prioritized by this stress-reactive animal model showed better predictive ability in the independent German test cohort (P=0.041). The top CFG scoring gene for alcoholism from the initial discovery step, synuclein alpha (SNCA) remained the top gene after the stress-reactive animal model cross-validation. We also tested this small panel of genes in two other independent test cohorts from the United States, one with alcohol dependence (P=0.00012) and one with alcohol abuse (a less severe form of alcoholism; P=0.0094). SNCA by itself was able to separate alcoholics from controls in the alcohol-dependent cohort (P=0.000013) and the alcohol abuse cohort (P=0.023). So did eight other genes from the panel of 11 genes taken individually, albeit to a lesser extent and/or less broadly across cohorts. SNCA, GRM3 and MBP survived strict Bonferroni correction for multiple comparisons. Taken together, these results suggest that our stress-reactive DBP animal model helped to validate and prioritize from the CFG-discovered genes some of the key behaviorally relevant genes for alcoholism. These genes fall into a series of biological pathways involved in signal transduction, transmission of nerve impulse (including myelination) and cocaine addiction. Overall, our work provides leads towards a better understanding of illness, diagnostics and therapeutics, including treatment with omega-3 fatty acids. We also examined the overlap between the top candidate genes for alcoholism from this work and the top candidate genes for bipolar disorder, schizophrenia, anxiety from previous CFG analyses conducted by us, as well as cross-tested genetic risk predictions. This revealed the significant genetic overlap with other major psychiatric disorder domains, providing a basis for comorbidity and dual diagnosis, and placing alcohol use in the broader context of modulating the mental landscape. PMID:24844177
Establishment and Validation of GV-SAPS II Scoring System for Non-Diabetic Critically Ill Patients.
Liu, Wen-Yue; Lin, Shi-Gang; Zhu, Gui-Qi; Poucke, Sven Van; Braddock, Martin; Zhang, Zhongheng; Mao, Zhi; Shen, Fei-Xia; Zheng, Ming-Hua
2016-01-01
Recently, glucose variability (GV) has been reported as an independent risk factor for mortality in non-diabetic critically ill patients. However, GV is not incorporated in any severity scoring system for critically ill patients currently. The aim of this study was to establish and validate a modified Simplified Acute Physiology Score II scoring system (SAPS II), integrated with GV parameters and named GV-SAPS II, specifically for non-diabetic critically ill patients to predict short-term and long-term mortality. Training and validation cohorts were exacted from the Multiparameter Intelligent Monitoring in Intensive Care database III version 1.3 (MIMIC-III v1.3). The GV-SAPS II score was constructed by Cox proportional hazard regression analysis and compared with the original SAPS II, Sepsis-related Organ Failure Assessment Score (SOFA) and Elixhauser scoring systems using area under the curve of the receiver operator characteristic (auROC) curve. 4,895 and 5,048 eligible individuals were included in the training and validation cohorts, respectively. The GV-SAPS II score was established with four independent risk factors, including hyperglycemia, hypoglycemia, standard deviation of blood glucose levels (GluSD), and SAPS II score. In the validation cohort, the auROC values of the new scoring system were 0.824 (95% CI: 0.813-0.834, P< 0.001) and 0.738 (95% CI: 0.725-0.750, P< 0.001), respectively for 30 days and 9 months, which were significantly higher than other models used in our study (all P < 0.001). Moreover, Kaplan-Meier plots demonstrated significantly worse outcomes in higher GV-SAPS II score groups both for 30-day and 9-month mortality endpoints (all P< 0.001). We established and validated a modified prognostic scoring system that integrated glucose variability for non-diabetic critically ill patients, named GV-SAPS II. It demonstrated a superior prognostic capability and may be an optimal scoring system for prognostic evaluation in this patient group.
Briggs, Andrew H; Baker, Timothy; Risebrough, Nancy A; Chambers, Mike; Gonzalez-McQuire, Sebastian; Ismaila, Afisi S; Exuzides, Alex; Colby, Chris; Tabberer, Maggie; Muellerova, Hana; Locantore, Nicholas; Rutten van Mölken, Maureen P M H; Lomas, David A
2017-05-01
The recent joint International Society for Pharmacoeconomics and Outcomes Research / Society for Medical Decision Making Modeling Good Research Practices Task Force emphasized the importance of conceptualizing and validating models. We report a new model of chronic obstructive pulmonary disease (COPD) (part of the Galaxy project) founded on a conceptual model, implemented using a novel linked-equation approach, and internally validated. An expert panel developed a conceptual model including causal relationships between disease attributes, progression, and final outcomes. Risk equations describing these relationships were estimated using data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study, with costs estimated from the TOwards a Revolution in COPD Health (TORCH) study. Implementation as a linked-equation model enabled direct estimation of health service costs and quality-adjusted life years (QALYs) for COPD patients over their lifetimes. Internal validation compared 3 years of predicted cohort experience with ECLIPSE results. At 3 years, the Galaxy COPD model predictions of annual exacerbation rate and annual decline in forced expiratory volume in 1 second fell within the ECLIPSE data confidence limits, although 3-year overall survival was outside the observed confidence limits. Projections of the risk equations over time permitted extrapolation to patient lifetimes. Averaging the predicted cost/QALY outcomes for the different patients within the ECLIPSE cohort gives an estimated lifetime cost of £25,214 (undiscounted)/£20,318 (discounted) and lifetime QALYs of 6.45 (undiscounted/5.24 [discounted]) per ECLIPSE patient. A new form of model for COPD was conceptualized, implemented, and internally validated, based on a series of linked equations using epidemiological data (ECLIPSE) and cost data (TORCH). This Galaxy model predicts COPD outcomes from treatment effects on disease attributes such as lung function, exacerbations, symptoms, or exercise capacity; further external validation is required.
Massol, Jacques; Janin, Gérard; Bachot, Camille; Gousset, Christophe; Deville, Geoffroy Sainte-Claire; Chalopin, Jean-Marc
2017-02-01
Before establishing a prospective cohort, an initial pilot study is recommended. However, there are no precise guidelines on this subject. This paper reports the findings of a French regional pilot study carried out in three nephrology departments, before realizing a major prospective Non Dialysis Chronic Renal Insufficiency study (ND-CRIS). We carried out an internal pilot study. The objectives of this pilot study were to validate the feasibility (regulatory approval, providing patients with information, availability of variables, refusal rate of eligible patients) and quality criteria (missing data, rate of patients lost to follow-up, characteristics of the patients included and non-included eligible patients, quality control of the data gathered) and estimate the human resources necessary (number of clinical research associates required). The authorizations obtained (CCTIRS - CNIL) and the contracts signed with hospitals have fulfilled the regulatory requirements. After validating the information on the study provided to patients, 1849 of them were included in three centres (university hospital, intercommunal hospital, town hospital) between April 2012 and September 2015. The low refusal rate (51 patients) and the characteristics of non-included patients have confirmed the benefit for patients of participating in the study and provide evidence of the feasibility and representativeness of the population studied. The lack of missing data on the variables studied, the quality of the data analyzed and the low number of patients lost to follow-up are evidence of the quality of the study. By taking into account the time spent by CRAs to enter data and to travel, as well as the annual patient numbers in each hospital, we estimate that five CRAs will be required in total. With no specific guidelines on how to realize a pilot study before implementing a major prospective cohort, we considered it pertinent to report our experience of P-ND-CRIS. This experience confirms that i) feasibility, ii) quality of data and iii) evaluating the resources required must be validated before carrying out a large prospective cohort study such as ND-CRIS.
Li, Bailiang; Cui, Yi; Diehn, Maximilian; Li, Ruijiang
2017-11-01
The prevalence of early-stage non-small cell lung cancer (NSCLC) is expected to increase with recent implementation of annual screening programs. Reliable prognostic biomarkers are needed to identify patients at a high risk for recurrence to guide adjuvant therapy. To develop a robust, individualized immune signature that can estimate prognosis in patients with early-stage nonsquamous NSCLC. This retrospective study analyzed the gene expression profiles of frozen tumor tissue samples from 19 public NSCLC cohorts, including 18 microarray data sets and 1 RNA-Seq data set for The Cancer Genome Atlas (TCGA) lung adenocarcinoma cohort. Only patients with nonsquamous NSCLC with clinical annotation were included. Samples were from 2414 patients with nonsquamous NSCLC, divided into a meta-training cohort (729 patients), meta-testing cohort (716 patients), and 3 independent validation cohorts (439, 323, and 207 patients). All patients underwent surgery with a negative surgical margin, received no adjuvant or neoadjuvant therapy, and had publicly available gene expression data and survival information. Data were collected from July 22 through September 8, 2016. Overall survival. Of 2414 patients (1205 men [50%], 1111 women [46%], and 98 of unknown sex [4%]; median age [range], 64 [15-90] years), a prognostic immune signature of 25 gene pairs consisting of 40 unique genes was constructed using the meta-training data set. In the meta-testing and validation cohorts, the immune signature significantly stratified patients into high- vs low-risk groups in terms of overall survival across and within subpopulations with stage I, IA, IB, or II disease and remained as an independent prognostic factor in multivariate analyses (hazard ratio range, 1.72 [95% CI, 1.26-2.33; P < .001] to 2.36 [95% CI, 1.47-3.79; P < .001]) after adjusting for clinical and pathologic factors. Several biological processes, including chemotaxis, were enriched among genes in the immune signature. The percentage of neutrophil infiltration (5.6% vs 1.8%) and necrosis (4.6% vs 1.5%) was significantly higher in the high-risk immune group compared with the low-risk groups in TCGA data set (P < .003). The immune signature achieved a higher accuracy (mean concordance index [C-index], 0.64) than 2 commercialized multigene signatures (mean C-index, 0.53 and 0.61) for estimation of survival in comparable validation cohorts. When integrated with clinical characteristics such as age and stage, the composite clinical and immune signature showed improved prognostic accuracy in all validation data sets relative to molecular signatures alone (mean C-index, 0.70 vs 0.63) and another commercialized clinical-molecular signature (mean C-index, 0.68 vs 0.65). The proposed clinical-immune signature is a promising biomarker for estimating overall survival in nonsquamous NSCLC, including early-stage disease. Prospective studies are needed to test the clinical utility of the biomarker in individualized management of nonsquamous NSCLC.
Rudmik, Luke; Xu, Yuan; Kukec, Edward; Liu, Mingfu; Dean, Stafford; Quan, Hude
2016-11-01
Pharmacoepidemiological research using administrative databases has become increasingly popular for chronic rhinosinusitis (CRS); however, without a validated case definition the cohort evaluated may be inaccurate resulting in biased and incorrect outcomes. The objective of this study was to develop and validate a generalizable administrative database case definition for CRS using International Classification of Diseases, 9th edition (ICD-9)-coded claims. A random sample of 100 patients with a guideline-based diagnosis of CRS and 100 control patients were selected and then linked to a Canadian physician claims database from March 31, 2010, to March 31, 2015. The proportion of CRS ICD-9-coded claims (473.x and 471.x) for each of these 200 patients were reviewed and the validity of 7 different ICD-9-based coding algorithms was evaluated. The CRS case definition of ≥2 claims with a CRS ICD-9 code (471.x or 473.x) within 2 years of the reference case provides a balanced validity with a sensitivity of 77% and specificity of 79%. Applying this CRS case definition to the claims database produced a CRS cohort of 51,000 patients with characteristics that were consistent with published demographics and rates of comorbid asthma, allergic rhinitis, and depression. This study has validated several coding algorithms; based on the results a case definition of ≥2 physician claims of CRS (ICD-9 of 471.x or 473.x) within 2 years provides an optimal level of validity. Future studies will need to validate this administrative case definition from different health system perspectives and using larger retrospective chart reviews from multiple providers. © 2016 ARS-AAOA, LLC.
Das, Anirban; Trehan, Amita; Oberoi, Sapna; Bansal, Deepak
2017-06-01
The study aims to validate a score predicting risk of complications in pediatric patients with chemotherapy-related febrile neutropenia (FN) and evaluate the performance of previously published models for risk stratification. Children diagnosed with cancer and presenting with FN were evaluated in a prospective single-center study. A score predicting the risk of complications, previously derived in the unit, was validated on a prospective cohort. Performance of six predictive models published from geographically distinct settings was assessed on the same cohort. Complications were observed in 109 (26.3%) of 414 episodes of FN over 15 months. A risk score based on undernutrition (two points), time from last chemotherapy (<7 days = two points), presence of a nonupper respiratory focus of infection (two points), C-reactive protein (>60 mg/l = five points), and absolute neutrophil count (<100 per μl = two points) was used to stratify patients into "low risk" (score <7, n = 208) and assessed using the following parameters: overall performance (Nagelkerke R 2 = 34.4%), calibration (calibration slope = 0.39; P = 0.25 in Hosmer-Lemeshow test), discrimination (c-statistic = 0.81), overall sensitivity (86%), negative predictive value (93%), and clinical net benefit (0.43). Six previously published rules demonstrated inferior performance in this cohort. An indigenous decision rule using five simple predefined variables was successful in identifying children at risk for complications. Prediction models derived in developed nations may not be appropriate for low-middle-income settings and need to be validated before use. © 2016 Wiley Periodicals, Inc.
Genetic risk prediction and neurobiological understanding of alcoholism.
Levey, D F; Le-Niculescu, H; Frank, J; Ayalew, M; Jain, N; Kirlin, B; Learman, R; Winiger, E; Rodd, Z; Shekhar, A; Schork, N; Kiefer, F; Kiefe, F; Wodarz, N; Müller-Myhsok, B; Dahmen, N; Nöthen, M; Sherva, R; Farrer, L; Smith, A H; Kranzler, H R; Rietschel, M; Gelernter, J; Niculescu, A B
2014-05-20
We have used a translational Convergent Functional Genomics (CFG) approach to discover genes involved in alcoholism, by gene-level integration of genome-wide association study (GWAS) data from a German alcohol dependence cohort with other genetic and gene expression data, from human and animal model studies, similar to our previous work in bipolar disorder and schizophrenia. A panel of all the nominally significant P-value SNPs in the top candidate genes discovered by CFG (n=135 genes, 713 SNPs) was used to generate a genetic risk prediction score (GRPS), which showed a trend towards significance (P=0.053) in separating alcohol dependent individuals from controls in an independent German test cohort. We then validated and prioritized our top findings from this discovery work, and subsequently tested them in three independent cohorts, from two continents. A panel of all the nominally significant P-value single-nucleotide length polymorphisms (SNPs) in the top candidate genes discovered by CFG (n=135 genes, 713 SNPs) were used to generate a Genetic Risk Prediction Score (GRPS), which showed a trend towards significance (P=0.053) in separating alcohol-dependent individuals from controls in an independent German test cohort. In order to validate and prioritize the key genes that drive behavior without some of the pleiotropic environmental confounds present in humans, we used a stress-reactive animal model of alcoholism developed by our group, the D-box binding protein (DBP) knockout mouse, consistent with the surfeit of stress theory of addiction proposed by Koob and colleagues. A much smaller panel (n=11 genes, 66 SNPs) of the top CFG-discovered genes for alcoholism, cross-validated and prioritized by this stress-reactive animal model showed better predictive ability in the independent German test cohort (P=0.041). The top CFG scoring gene for alcoholism from the initial discovery step, synuclein alpha (SNCA) remained the top gene after the stress-reactive animal model cross-validation. We also tested this small panel of genes in two other independent test cohorts from the United States, one with alcohol dependence (P=0.00012) and one with alcohol abuse (a less severe form of alcoholism; P=0.0094). SNCA by itself was able to separate alcoholics from controls in the alcohol-dependent cohort (P=0.000013) and the alcohol abuse cohort (P=0.023). So did eight other genes from the panel of 11 genes taken individually, albeit to a lesser extent and/or less broadly across cohorts. SNCA, GRM3 and MBP survived strict Bonferroni correction for multiple comparisons. Taken together, these results suggest that our stress-reactive DBP animal model helped to validate and prioritize from the CFG-discovered genes some of the key behaviorally relevant genes for alcoholism. These genes fall into a series of biological pathways involved in signal transduction, transmission of nerve impulse (including myelination) and cocaine addiction. Overall, our work provides leads towards a better understanding of illness, diagnostics and therapeutics, including treatment with omega-3 fatty acids. We also examined the overlap between the top candidate genes for alcoholism from this work and the top candidate genes for bipolar disorder, schizophrenia, anxiety from previous CFG analyses conducted by us, as well as cross-tested genetic risk predictions. This revealed the significant genetic overlap with other major psychiatric disorder domains, providing a basis for comorbidity and dual diagnosis, and placing alcohol use in the broader context of modulating the mental landscape.
Measuring Knowledge Integration Learning of Energy Topics: A two-year longitudinal study
NASA Astrophysics Data System (ADS)
Liu, Ou Lydia; Ryoo, Kihyun; Linn, Marcia C.; Sato, Elissa; Svihla, Vanessa
2015-05-01
Although researchers call for inquiry learning in science, science assessments rarely capture the impact of inquiry instruction. This paper reports on the development and validation of assessments designed to measure middle-school students' progress in gaining integrated understanding of energy while studying an inquiry-oriented curriculum. The assessment development was guided by the knowledge integration framework. Over 2 years of implementation, more than 4,000 students from 4 schools participated in the study, including a cross-sectional and a longitudinal cohort. Results from item response modeling analyses revealed that: (a) the assessments demonstrated satisfactory psychometric properties in terms of reliability and validity; (b) both the cross-sectional and longitudinal cohorts made progress on integrating their understanding energy concepts; and (c) among many factors (e.g. gender, grade, school, and home language) associated with students' science performance, unit implementation was the strongest predictor.
Hijazi, Ziad; Oldgren, Jonas; Lindbäck, Johan; Alexander, John H; Connolly, Stuart J; Eikelboom, John W; Ezekowitz, Michael D; Held, Claes; Hylek, Elaine M; Lopes, Renato D; Yusuf, Salim; Granger, Christopher B; Siegbahn, Agneta; Wallentin, Lars
2018-01-01
Abstract Aims In atrial fibrillation (AF), mortality remains high despite effective anticoagulation. A model predicting the risk of death in these patients is currently not available. We developed and validated a risk score for death in anticoagulated patients with AF including both clinical information and biomarkers. Methods and results The new risk score was developed and internally validated in 14 611 patients with AF randomized to apixaban vs. warfarin for a median of 1.9 years. External validation was performed in 8548 patients with AF randomized to dabigatran vs. warfarin for 2.0 years. Biomarker samples were obtained at study entry. Variables significantly contributing to the prediction of all-cause mortality were assessed by Cox-regression. Each variable obtained a weight proportional to the model coefficients. There were 1047 all-cause deaths in the derivation and 594 in the validation cohort. The most important predictors of death were N-terminal pro B-type natriuretic peptide, troponin-T, growth differentiation factor-15, age, and heart failure, and these were included in the ABC (Age, Biomarkers, Clinical history)-death risk score. The score was well-calibrated and yielded higher c-indices than a model based on all clinical variables in both the derivation (0.74 vs. 0.68) and validation cohorts (0.74 vs. 0.67). The reduction in mortality with apixaban was most pronounced in patients with a high ABC-death score. Conclusion A new biomarker-based score for predicting risk of death in anticoagulated AF patients was developed, internally and externally validated, and well-calibrated in two large cohorts. The ABC-death risk score performed well and may contribute to overall risk assessment in AF. ClinicalTrials.gov identifier NCT00412984 and NCT00262600 PMID:29069359
Validated Risk Score for Predicting 6-Month Mortality in Infective Endocarditis.
Park, Lawrence P; Chu, Vivian H; Peterson, Gail; Skoutelis, Athanasios; Lejko-Zupa, Tatjana; Bouza, Emilio; Tattevin, Pierre; Habib, Gilbert; Tan, Ren; Gonzalez, Javier; Altclas, Javier; Edathodu, Jameela; Fortes, Claudio Querido; Siciliano, Rinaldo Focaccia; Pachirat, Orathai; Kanj, Souha; Wang, Andrew
2016-04-18
Host factors and complications have been associated with higher mortality in infective endocarditis (IE). We sought to develop and validate a model of clinical characteristics to predict 6-month mortality in IE. Using a large multinational prospective registry of definite IE (International Collaboration on Endocarditis [ICE]-Prospective Cohort Study [PCS], 2000-2006, n=4049), a model to predict 6-month survival was developed by Cox proportional hazards modeling with inverse probability weighting for surgery treatment and was internally validated by the bootstrapping method. This model was externally validated in an independent prospective registry (ICE-PLUS, 2008-2012, n=1197). The 6-month mortality was 971 of 4049 (24.0%) in the ICE-PCS cohort and 342 of 1197 (28.6%) in the ICE-PLUS cohort. Surgery during the index hospitalization was performed in 48.1% and 54.0% of the cohorts, respectively. In the derivation model, variables related to host factors (age, dialysis), IE characteristics (prosthetic or nosocomial IE, causative organism, left-sided valve vegetation), and IE complications (severe heart failure, stroke, paravalvular complication, and persistent bacteremia) were independently associated with 6-month mortality, and surgery was associated with a lower risk of mortality (Harrell's C statistic 0.715). In the validation model, these variables had similar hazard ratios (Harrell's C statistic 0.682), with a similar, independent benefit of surgery (hazard ratio 0.74, 95% CI 0.62-0.89). A simplified risk model was developed by weight adjustment of these variables. Six-month mortality after IE is ≈25% and is predicted by host factors, IE characteristics, and IE complications. Surgery during the index hospitalization is associated with lower mortality but is performed less frequently in the highest risk patients. A simplified risk model may be used to identify specific risk subgroups in IE. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.
Azagra, R; Zwart, M; Aguyé, A; Martín-Sánchez, J C; Casado, E; Díaz-Herrera, M A; Moriña, D; Cooper, C; Díez-Pérez, A; Dennison, E M
2016-01-01
To perform an external validation of FRAX algorithm thresholds for reporting level of risk of fracture in Spanish women (low < 5%; intermediate ≥ 5% and < 7.5%; high ≥ 7.5%) taken from a prospective cohort "FRIDEX". A retrospective study of 1090 women aged ≥ 40 and ≤ 90 years old obtained from the general population (FROCAT cohort). FRAX was calculated with data registered in 2002. All fractures were validated in 2012. Sensitivity analysis was performed. When analyzing the cohort (884) excluding current or past anti osteoporotic medication (AOM), using our nominated thresholds, among the 621 (70.2%) women at low risk of fracture, 5.2% [CI95%: 3.4-7.6] sustained a fragility fracture; among the 99 at intermediate risk, 12.1% [6.4-20.2]; and among the 164 defined as high risk, 15.9% [10.6-24.2]. Sensitivity analysis against model risk stratification FRIDEX of FRAX Spain shows no significant difference. By including 206 women with AOM, the sensitivity analysis shows no difference in the group of intermediate and high risk and minimal differences in the low risk group. Our findings support and validate the use of FRIDEX thresholds of FRAX when discussing the risk of fracture and the initiation of therapy with patients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Wise, Frances M; Harris, Darren W; Olver, John H
2017-01-01
Considerable research has been undertaken in evaluating the DASS-21 in a variety of clinical populations, but studies of the instrument's psychometric adequacy in healthcare professionals is lacking. This study aimed to establish and improve the construct validity and reliability of the DASS-21 in a cohort of Australian health professionals. 343 rehabilitation health professionals completed the DASS-21, along with a demographic questionnaire. Principal components analysis was performed to identify potential factors in the DASS-21. Factors were interpreted against theoretical constructs underlying the instrument. Items loading on separate factors were then subjected to reliability analysis to determine internal consistency of subscales. Items that demonstrated poor fit, or loaded onto more than one factor, were deleted to maximise the reliability of each subscale. Principal components analysis identified three dimensions (depression, anxiety, stress) in a modified version of the DASS-21 (renamed DASS-14), with appropriate construct validity and good reliability (a=0.73 to 0.88). The three dimensions accounted for over 62% of variance between items. The modified DASS-14 scale is a more parsimonious measure of depression, anxiety, and stress, with acceptable reliability and construct validity, in rehabilitation health professionals and is appropriate for use in studies of similar populations.
Christopoulos, Georgios; Kandzari, David E; Yeh, Robert W; Jaffer, Farouc A; Karmpaliotis, Dimitri; Wyman, Michael R; Alaswad, Khaldoon; Lombardi, William; Grantham, J Aaron; Moses, Jeffrey; Christakopoulos, Georgios; Tarar, Muhammad Nauman J; Rangan, Bavana V; Lembo, Nicholas; Garcia, Santiago; Cipher, Daisha; Thompson, Craig A; Banerjee, Subhash; Brilakis, Emmanouil S
2016-01-11
This study sought to develop a novel parsimonious score for predicting technical success of chronic total occlusion (CTO) percutaneous coronary intervention (PCI) performed using the hybrid approach. Predicting technical success of CTO PCI can facilitate clinical decision making and procedural planning. We analyzed clinical and angiographic parameters from 781 CTO PCIs included in PROGRESS CTO (Prospective Global Registry for the Study of Chronic Total Occlusion Intervention) using a derivation and validation cohort (2:1 sampling ratio). Variables with strong association with technical success in multivariable analysis were assigned 1 point, and a 4-point score was developed from summing all points. The PROGRESS CTO score was subsequently compared with the J-CTO (Multicenter Chronic Total Occlusion Registry in Japan) score in the validation cohort. Technical success was 92.9%. On multivariable analysis, factors associated with technical success included proximal cap ambiguity (beta coefficient [b] = 0.88), moderate/severe tortuosity (b = 1.18), circumflex artery CTO (b = 0.99), and absence of "interventional" collaterals (b = 0.88). The resulting score demonstrated good calibration and discriminatory capacity in the derivation (Hosmer-Lemeshow chi-square = 2.633; p = 0.268, and receiver-operator characteristic [ROC] area = 0.778) and validation (Hosmer-Lemeshow chi-square = 5.333; p = 0.070, and ROC area = 0.720) subset. In the validation cohort, the PROGRESS CTO and J-CTO scores performed similarly in predicting technical success (ROC area 0.720 vs. 0.746, area under the curve difference = 0.026, 95% confidence interval = -0.093 to 0.144). The PROGRESS CTO score is a novel useful tool for estimating technical success in CTO PCI performed using the hybrid approach. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Matsui, Kenji; Lie, Reidar K.; Turin, Tanvir C.; Kita, Yoshikuni
2012-01-01
Background Although the amount of detail in informed consent documents has increased over time and the documents have therefore become very long, there is little research on whether longer informed consent documents actually result in (1) better informed research subjects or (2) higher consent rates. We therefore conducted an add-on randomized controlled trial to the Takashima Study, a prospective Japanese population-based genetic cohort study, to test the hypothesis that a shorter informed consent form would satisfy both of the above goals. Methods Standard (10 459 words, 11 pages) and short (3602 words, 5 pages) consent forms in Japanese were developed and distributed using cluster-randomization to 293 potential cohort subjects living in 9 medico-social units and 288 subjects in 8 medico-social units, respectively. Results Few differences were found between the 2 groups with regard to outcome measures, including participants’ self-perceived understanding, recall of information, concerns, voluntariness, trust, satisfaction, sense of duty, and consent rates. Conclusions A short informed consent form was no less valid than a standard form with regard to fulfilling ethical requirements and securing the scientific validity of research. PMID:22447213
Gildersleeve, R.; Cooper, P.
2013-01-01
Background The Centers for Medicare and Medicaid Services’ Readmissions Reduction Program adjusts payments to hospitals based on 30-day readmission rates for patients with acute myocardial infarction, heart failure, and pneumonia. This holds hospitals accountable for a complex phenomenon about which there is little evidence regarding effective interventions. Further study may benefit from a method for efficiently and inexpensively identifying patients at risk of readmission. Several models have been developed to assess this risk, many of which may not translate to a U.S. community hospital setting. Objective To develop a real-time, automated tool to stratify risk of 30-day readmission at a semirural community hospital. Methods A derivation cohort was created by extracting demographic and clinical variables from the data repository for adult discharges from calendar year 2010. Multivariate logistic regression identified variables that were significantly associated with 30-day hospital readmission. Those variables were incorporated into a formula to produce a Risk of Readmission Score (RRS). A validation cohort from 2011 assessed the predictive value of the RRS. A SQL stored procedure was created to calculate the RRS for any patient and publish its value, along with an estimate of readmission risk and other factors, to a secure intranet site. Results Eleven variables were significantly associated with readmission in the multivariate analysis of each cohort. The RRS had an area under the receiver operating characteristic curve (c-statistic) of 0.74 (95% CI 0.73-0.75) in the derivation cohort and 0.70 (95% CI 0.69-0.71) in the validation cohort. Conclusion Clinical and administrative data available in a typical community hospital database can be used to create a validated, predictive scoring system that automatically assigns a probability of 30-day readmission to hospitalized patients. This does not require manual data extraction or manipulation and uses commonly available systems. Additional study is needed to refine and confirm the findings. PMID:23874355
Sandoval, Yader; Smith, Stephen W; Shah, Anoop S V; Anand, Atul; Chapman, Andrew R; Love, Sara A; Schulz, Karen; Cao, Jing; Mills, Nicholas L; Apple, Fred S
2017-01-01
Rapid rule-out strategies using high-sensitivity cardiac troponin assays are largely supported by studies performed outside the US in selected cohorts of patients with chest pain that are atypical of US practice, and focused exclusively on ruling out acute myocardial infarction (AMI), rather than acute myocardial injury, which is more common and associated with a poor prognosis. Prospective, observational study of consecutive patients presenting to emergency departments [derivation (n = 1647) and validation (n = 2198) cohorts], where high-sensitivity cardiac troponin I (hs-cTnI) was measured on clinical indication. The negative predictive value (NPV) and diagnostic sensitivity of an hs-cTnI concentration
Wang, Yanhua; Duan, Huawei; Meng, Tao; Shen, Meili; Ji, Qianpeng; Xing, Jie; Wang, Qingrong; Wang, Ting; Niu, Yong; Yu, Tao; Liu, Zhong; Jia, Hongbing; Zhan, Yuliang; Chen, Wen; Zhang, Zhihu; Su, Wenge; Dai, Yufei; Zhang, Xuchun; Zheng, Yuxin
2018-03-01
Exposure to fine particulate matter (PM 2.5 ) pollution is associated with increased morbidity and mortality from respiratory diseases. However, few population-based studies have been conducted to assess the alterations in circulating pulmonary proteins due to long-term PM 2.5 exposure. We designed a two-stage study. In the first stage (training set), we assessed the associations between PM 2.5 exposure and levels of pulmonary damage markers (CC16, SP-A and SP-D) and lung function in a coke oven emission (COE) cohort with 558 coke plant workers and 210 controls. In the second stage (validation set), significant initial findings were validated by an independent diesel engine exhaust (DEE) cohort with 50 DEE exposed workers and 50 controls. Serum CC16 levels decreased in a dose response manner in association with both external and internal PM 2.5 exposures in the two cohorts. In the training set, serum CC16 levels decreased with increasing duration of occupational PM 2.5 exposure history. An interquartile range (IQR) (122.0μg/m 3 ) increase in PM 2.5 was associated with a 5.76% decrease in serum CC16 levels, whereas an IQR (1.06μmol/mol creatinine) increase in urinary 1-hydroxypyrene (1-OHP) concentration was associated with a 5.36% decrease in serum CC16 levels in the COE cohort. In the validation set, the concentration of serum CC16 in the PM 2.5 exposed group was 22.42% lower than that of the controls and an IQR (1.24μmol/mol creatinine) increase in urinary 1-OHP concentration was associated with a 12.24% decrease in serum CC16 levels in the DEE cohort. Serum CC16 levels may be a sensitive marker for pulmonary damage in populations with high PM 2.5 exposure. Copyright © 2017 Elsevier Ltd. All rights reserved.
Chiari, Paolo; Poli, Marco; Magli, Claudia; Bascelli, Emanuele; Rocchi, Roberto; Bolognini, Silvia; Tartari, Piero; Armuzzi, Roberta; Rossi, Gianna; Peghetti, Angela; Biavati, Catia; Fontana, Mirella; Gazineo, Domenica; Cordella, Simona; Tiozzo, Emanuela; Ciliento, Gaetano; Carta, Giovanna; Taddia, Patrizia
2012-01-01
Multicenter prospective cohort study, to validate the Italian version of the Braden Q scale for the risk of pressure sores in newborns and up to 8 years old children. Children admitted to Intensive care Units (ICU), oncology and neurology/neurosurgery wards are at risk of developing pressure sores. To validate the Italian version of the Braden Q scale for the assessment of the risk of developing pressure sores in children. Children from 21 days to 8 years, admitted to intensive and sub intensive units were recruited. Premature babies, children admitted with a pressure sore and with a story of congenital cardiomiopathy were excluded. In this cohort, multicentre and with repeated measurements study, the first assessment was performed after 24 hours from hospital admission, using the Braden Q Scale (Suddaby's version). The pressure sores were assessed with the Skin assessment Tool and staged according to the National Pressure Ulcer Advisory Panel. RESULTS. On the 157 children 524 observation were conducted. The incidence of pressure sores was 17.2%. Only the analysis on specific subgroups of patients showed a good diagnostic accuracy: 71.4% on children 3-8 years; 85.6% in sub intensive wards. The Braden Q scale may be reliably used and shows a good diagnostic accuracy in children 3-8 years of age admitted to sub-intensive, neurology, oncology and heamatology wards.
Clinical prognostic rules for severe acute respiratory syndrome in low- and high-resource settings.
Cowling, Benjamin J; Muller, Matthew P; Wong, Irene O L; Ho, Lai-Ming; Lo, Su-Vui; Tsang, Thomas; Lam, Tai Hing; Louie, Marie; Leung, Gabriel M
2006-07-24
An accurate prognostic model for patients with severe acute respiratory syndrome (SARS) could provide a practical clinical decision aid. We developed and validated prognostic rules for both high- and low-resource settings based on data available at the time of admission. We analyzed data on all 1755 and 291 patients with SARS in Hong Kong (derivation cohort) and Toronto (validation cohort), respectively, using a multivariable logistic scoring method with internal and external validation. Scores were assigned on the basis of patient history in a basic model, and a full model additionally incorporated radiological and laboratory results. The main outcome measure was death. Predictors for mortality in the basic model included older age, male sex, and the presence of comorbid conditions. Additional predictors in the full model included haziness or infiltrates on chest radiography, less than 95% oxygen saturation on room air, high lactate dehydrogenase level, and high neutrophil and low platelet counts. The basic model had an area under the receiver operating characteristic (ROC) curve of 0.860 in the derivation cohort, which was maintained on external validation with an area under the ROC curve of 0.882. The full model improved discrimination with areas under the ROC curve of 0.877 and 0.892 in the derivation and validation cohorts, respectively. The model performs well and could be useful in assessing prognosis for patients who are infected with re-emergent SARS.
Mejias, Asuncion; Dimo, Blerta; Suarez, Nicolas M.; Garcia, Carla; Suarez-Arrabal, M. Carmen; Jartti, Tuomas; Blankenship, Derek; Jordan-Villegas, Alejandro; Ardura, Monica I.; Xu, Zhaohui; Banchereau, Jacques; Chaussabel, Damien; Ramilo, Octavio
2013-01-01
Background Respiratory syncytial virus (RSV) is the leading cause of viral lower respiratory tract infection (LRTI) and hospitalization in infants. Mostly because of the incomplete understanding of the disease pathogenesis, there is no licensed vaccine, and treatment remains symptomatic. We analyzed whole blood transcriptional profiles to characterize the global host immune response to acute RSV LRTI in infants, to characterize its specificity compared with influenza and human rhinovirus (HRV) LRTI, and to identify biomarkers that can objectively assess RSV disease severity. Methods and Findings This was a prospective observational study over six respiratory seasons including a cohort of infants hospitalized with RSV (n = 135), HRV (n = 30), and influenza (n = 16) LRTI, and healthy age- and sex-matched controls (n = 39). A specific RSV transcriptional profile was identified in whole blood (training cohort, n = 45 infants; Dallas, Texas, US) and validated in three different cohorts (test cohort, n = 46, Dallas, Texas, US; validation cohort A, n = 16, Turku, Finland; validation cohort B, n = 28, Columbus, Ohio, US) with high sensitivity (94% [95% CI 87%–98%]) and specificity (98% [95% CI 88%–99%]). It classified infants with RSV LRTI versus HRV or influenza LRTI with 95% accuracy. The immune dysregulation induced by RSV (overexpression of neutrophil, inflammation, and interferon genes, and suppression of T and B cell genes) persisted beyond the acute disease, and immune dysregulation was greatly impaired in younger infants (<6 mo). We identified a genomic score that significantly correlated with outcomes of care including a clinical disease severity score and, more importantly, length of hospitalization and duration of supplemental O2. Conclusions Blood RNA profiles of infants with RSV LRTI allow specific diagnosis, better understanding of disease pathogenesis, and assessment of disease severity. This study opens new avenues for biomarker discovery and identification of potential therapeutic or preventive targets, and demonstrates that large microarray datasets can be translated into a biologically meaningful context and applied to the clinical setting. Please see later in the article for the Editors' Summary PMID:24265599
Wahbi, Karim; Porcher, Raphaël; Laforêt, Pascal; Fayssoil, Abdallah; Bécane, Henri Marc; Lazarus, Arnaud; Sochala, Maximilien; Stojkovic, Tanya; Béhin, Anthony; Leonard-Louis, Sarah; Arnaud, Pauline; Furling, Denis; Probst, Vincent; Babuty, Dominique; Pellieux, Sybille; Clementy, Nicolas; Bassez, Guillaume; Péréon, Yann; Eymard, Bruno; Duboc, Denis
2018-05-01
Life expectancy is greatly shortened in patients presenting with myotonic dystrophy type 1 (DM1), the most common neuromuscular disease. A reliable prediction of survival in patients with DM1 is critically important to plan personalized health supervision. To develop and validate a prognostic score to predict 10-year survival in patients with DM1. In this longitudinal cohort study, between January 2000 and November 2014, we enrolled 1296 adults referred to 4 tertiary neuromuscular centers in France for management of genetically proven DM1, including 1066 patients in the derivation cohort and 230 in the validation cohort. Data were analyzed from December 2016 to March 2017. Factors associated with survival by multiple variable Cox modeling, including 95% confidence intervals, and development of a predictive score validated internally and externally. Mean values are reported with their standard deviations. Of the 1296 included patients, 670 (51.7%) were women, and the mean (SD) age was 39.8 (13.7) years. Among the 1066 patients (82.3%) in the derivation cohort, 241 (22.6%) died over a median (interquartile range) follow-up of 11.7 (7.7-14.3) years. Age, diabetes, need for support when walking, heart rate, systolic blood pressure, first-degree atrioventricular block, bundle-branch block, and lung vital capacity were associated with death. Simplified score points were attributed to each predictor, and adding these points yielded scores between 0 and 20, with 0 indicating the lowest and 20 the highest risk of death. The 10-year survival rate was 96.6% (95% CI, 94.4-98.9) in the group with 0 to 4 points, 92.2% (95% CI, 88.8-95.6) in the group with 5 to 7 points, 80.7% (95% CI, 75.4-86.1) in the group with 8 to 10 points, 57.9% (95% CI, 49.2-66.6) in the group with 11 to 13 points, and 19.4% (95% CI, 8.6-30.1) in the group with 14 points or more. In 230 patients (17.7%) included in the validation cohort, the 10-year survival rates for the groups with 0 to 4, 5 to 7, 8 to 10, 11 to 13, and 14 points or more were 99.3% (95% CI, 95.0-100), 80.6% (95% CI, 67.1-96.7), 79.3% (95% CI, 66.2-95.1), 43.2% (95% CI, 28.2-66.1), and 21.6% (95% CI, 10.0-46.8), respectively. The calibration curves did not deviate from the reference line. The C index was 0.753 (95% CI, 0.722-0.785) in the derivation cohort and 0.806 (95% CI, 0.758-0.855) in the validation cohort. The DM1 prognostic score is associated with long-term survival.
Visscher, H; Ross, C J D; Rassekh, S R; Sandor, G S S; Caron, H N; van Dalen, E C; Kremer, L C; van der Pal, H J; Rogers, P C; Rieder, M J; Carleton, B C; Hayden, M R
2013-08-01
The use of anthracyclines as effective antineoplastic drugs is limited by the occurrence of cardiotoxicity. Multiple genetic variants predictive of anthracycline-induced cardiotoxicity (ACT) in children were recently identified. The current study was aimed to assess replication of these findings in an independent cohort of children. . Twenty-three variants were tested for association with ACT in an independent cohort of 218 patients. Predictive models including genetic and clinical risk factors were constructed in the original cohort and assessed in the current replication cohort. . We confirmed the association of rs17863783 in UGT1A6 and ACT in the replication cohort (P = 0.0062, odds ratio (OR) 7.98). Additional evidence for association of rs7853758 (P = 0.058, OR 0.46) and rs885004 (P = 0.058, OR 0.42) in SLC28A3 was found (combined P = 1.6 × 10(-5) and P = 3.0 × 10(-5), respectively). A previously constructed prediction model did not significantly improve risk prediction in the replication cohort over clinical factors alone. However, an improved prediction model constructed using replicated genetic variants as well as clinical factors discriminated significantly better between cases and controls than clinical factors alone in both original (AUC 0.77 vs. 0.68, P = 0.0031) and replication cohort (AUC 0.77 vs. 0.69, P = 0.060). . We validated genetic variants in two genes predictive of ACT in an independent cohort. A prediction model combining replicated genetic variants as well as clinical risk factors might be able to identify high- and low-risk patients who could benefit from alternative treatment options. Copyright © 2013 Wiley Periodicals, Inc.
Fisher, Brian T; Harris, Tracey; Torp, Kari; Seif, Alix E; Shah, Ami; Huang, Yuan-Shung V; Bailey, L Charles; Kersun, Leslie S; Reilly, Anne F; Rheingold, Susan R; Walker, Dana; Li, Yimei; Aplenc, Richard
2014-01-01
Acute lymphoblastic leukemia (ALL) accounts for almost one quarter of pediatric cancer in the United States. Despite cooperative group therapeutic trials, there remains a paucity of large cohort data on which to conduct epidemiology and comparative effectiveness research studies. We designed a 3-step process utilizing International Classification of Diseases-9 Clinical Modification (ICD-9) discharge diagnoses codes and chemotherapy exposure data contained in the Pediatric Health Information System administrative database to establish a cohort of children with de novo ALL. This process was validated by chart review at 1 of the pediatric centers. An ALL cohort of 8733 patients was identified with a sensitivity of 88% [95% confidence interval (CI), 83%-92%] and a positive predictive value of 93% (95% CI, 89%-96%). The 30-day all cause inpatient case fatality rate using this 3-step process was 0.80% (95% CI, 0.63%-1.01%), which was significantly different than the case fatality rate of 1.40% (95% CI, 1.23%-1.60%) when ICD-9 codes alone were used. This is the first report of assembly and validation of a cohort of de novo ALL patients from a database representative of free-standing children's hospitals across the United States. Our data demonstrate that the use of ICD-9 codes alone to establish cohorts will lead to substantial patient misclassification and result in biased outcome estimates. Systematic methods beyond the use of just ICD-9 codes must be used before analysis to establish accurate cohorts of patients with malignancy. A similar approach should be followed when establishing future cohorts from administrative data.
Randhawa, April K.; Chau, Tran T. H.; Bang, Nguyen D.; Yen, Nguyen T. B.; Farrar, Jeremy J.; Dunstan, Sarah J.; Hawn, Thomas R.
2012-01-01
(See the editorial commentary by Wilkinson, on pages 525–7.) Background. Tuberculosis has been associated with genetic variation in host immunity. We hypothesized that single-nucleotide polymorphisms (SNPs) in SIGIRR, a negative regulator of Toll-like receptor/IL-1R signaling, are associated with susceptibility to tuberculosis. Methods. We used a case-population study design in Vietnam with cases that had either tuberculous meningitis or pulmonary tuberculosis. We genotyped 6 SNPs in the SIGIRR gene region (including the adjacent genes PKP3 and TMEM16J) in a discovery cohort of 352 patients with tuberculosis and 382 controls. Significant associations were genotyped in a validation cohort (339 patients with tuberculosis, 376 controls). Results. Three SNPs (rs10902158, rs7105848, rs7111432) were associated with tuberculosis in discovery and validation cohorts. The polymorphisms were associated with both tuberculous meningitis and pulmonary tuberculosis and were strongest with a recessive genetic model (odds ratios, 1.5–1.6; P = .0006–.001). Coinheritance of these polymorphisms with previously identified risk alleles in Toll-like receptor 2 and TIRAP was associated with an additive risk of tuberculosis susceptibility. Conclusions. These results demonstrate a strong association of SNPs in the PKP3-SIGIRR-TMEM16J gene region and tuberculosis in discovery and validation cohorts. To our knowledge, these are the first associations of polymorphisms in this region with any disease. PMID:22223854
Polites, Stephanie F; Potter, Donald D; Glasgow, Amy E; Klinkner, Denise B; Moir, Christopher R; Ishitani, Michael B; Habermann, Elizabeth B
2017-08-01
Postoperative unplanned readmissions are costly and decrease patient satisfaction; however, little is known about this complication in pediatric surgery. The purpose of this study was to determine rates and predictors of unplanned readmission in a multi-institutional cohort of pediatric surgical patients. Unplanned 30-day readmissions following general and thoracic surgical procedures in children <18 were identified from the 2012-2014 National Surgical Quality Improvement Program- Pediatric. Time-dependent rates of readmission per 30 person-days were determined to account for varied postoperative length of stay (pLOS). Patients were randomly divided into 70% derivation and 30% validation cohorts which were used for creation and validation of a risk model for readmission. Readmission occurred in 1948 (3.6%) of 54,870 children for a rate of 4.3% per 30 person-days. Adjusted predictors of readmission included hepatobiliary procedures, increased wound class, operative duration, complications, and pLOS. The predictive model discriminated well in the derivation and validation cohorts (AUROC 0.710 and 0.701) with good calibration between observed and expected readmission events in both cohorts (p>.05). Unplanned readmission occurs less frequently in pediatric surgery than what is described in adults, calling into question its use as a quality indicator in this population. Factors that predict readmission including type of procedure, complications, and pLOS can be used to identify at-risk children and develop prevention strategies. III. Copyright © 2017 Elsevier Inc. All rights reserved.
Estimating residual kidney function in dialysis patients without urine collection
Shafi, Tariq; Michels, Wieneke M.; Levey, Andrew S.; Inker, Lesley A.; Dekker, Friedo W.; Krediet, Raymond T.; Hoekstra, Tiny; Schwartz, George J.; Eckfeldt, John H.; Coresh, Josef
2016-01-01
Residual kidney function contributes substantially to solute clearance in dialysis patients but cannot be assessed without urine collection. We used serum filtration markers to develop dialysis-specific equations to estimate urinary urea clearance without the need for urine collection. In our development cohort, we measured 24-hour urine clearances under close supervision in 44 patients and validated these equations in 826 patients from the Netherlands Cooperative Study on the Adequacy of Dialysis. For the development and validation cohorts, median urinary urea clearance was 2.6 and 2.4 mL/min, respectively. During the 24-hour visit in the development cohort, serum β-trace protein concentrations remained in steady state but concentrations of all other markers increased. In the validation cohort, bias (median measured minus estimated clearance) was low for all equations. Precision was significantly better for β-trace protein and β2-microglobulin equations and the accuracy was significantly greater for β-trace protein, β2-microglobulin and cystatin C equations, compared with the urea plus creatinine equation. Area under the receiver operator characteristic curve for detecting measured urinary urea clearance by equation-estimated urinary urea clearance (both 2 mL/min or more) were 0.821, 0.850 and 0.796 for β-trace protein, β2-microglobulin and cystatin C equations, respectively; significantly greater than the 0.663 for the urea plus creatinine equation. Thus, residual renal function can be estimated in dialysis patients without urine collections. PMID:26924062
Estimating residual kidney function in dialysis patients without urine collection.
Shafi, Tariq; Michels, Wieneke M; Levey, Andrew S; Inker, Lesley A; Dekker, Friedo W; Krediet, Raymond T; Hoekstra, Tiny; Schwartz, George J; Eckfeldt, John H; Coresh, Josef
2016-05-01
Residual kidney function contributes substantially to solute clearance in dialysis patients but cannot be assessed without urine collection. We used serum filtration markers to develop dialysis-specific equations to estimate urinary urea clearance without the need for urine collection. In our development cohort, we measured 24-hour urine clearances under close supervision in 44 patients and validated these equations in 826 patients from the Netherlands Cooperative Study on the Adequacy of Dialysis. For the development and validation cohorts, median urinary urea clearance was 2.6 and 2.4 ml/min, respectively. During the 24-hour visit in the development cohort, serum β-trace protein concentrations remained in steady state but concentrations of all other markers increased. In the validation cohort, bias (median measured minus estimated clearance) was low for all equations. Precision was significantly better for β-trace protein and β2-microglobulin equations and the accuracy was significantly greater for β-trace protein, β2-microglobulin, and cystatin C equations, compared with the urea plus creatinine equation. Area under the receiver operator characteristic curve for detecting measured urinary urea clearance by equation-estimated urinary urea clearance (both 2 ml/min or more) were 0.821, 0.850, and 0.796 for β-trace protein, β2-microglobulin, and cystatin C equations, respectively; significantly greater than the 0.663 for the urea plus creatinine equation. Thus, residual renal function can be estimated in dialysis patients without urine collections. Copyright © 2016 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.
Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury
2013-01-01
Introduction Acute kidney injury (AKI) can evolve quickly and clinical measures of function often fail to detect AKI at a time when interventions are likely to provide benefit. Identifying early markers of kidney damage has been difficult due to the complex nature of human AKI, in which multiple etiologies exist. The objective of this study was to identify and validate novel biomarkers of AKI. Methods We performed two multicenter observational studies in critically ill patients at risk for AKI - discovery and validation. The top two markers from discovery were validated in a second study (Sapphire) and compared to a number of previously described biomarkers. In the discovery phase, we enrolled 522 adults in three distinct cohorts including patients with sepsis, shock, major surgery, and trauma and examined over 300 markers. In the Sapphire validation study, we enrolled 744 adult subjects with critical illness and without evidence of AKI at enrollment; the final analysis cohort was a heterogeneous sample of 728 critically ill patients. The primary endpoint was moderate to severe AKI (KDIGO stage 2 to 3) within 12 hours of sample collection. Results Moderate to severe AKI occurred in 14% of Sapphire subjects. The two top biomarkers from discovery were validated. Urine insulin-like growth factor-binding protein 7 (IGFBP7) and tissue inhibitor of metalloproteinases-2 (TIMP-2), both inducers of G1 cell cycle arrest, a key mechanism implicated in AKI, together demonstrated an AUC of 0.80 (0.76 and 0.79 alone). Urine [TIMP-2]·[IGFBP7] was significantly superior to all previously described markers of AKI (P <0.002), none of which achieved an AUC >0.72. Furthermore, [TIMP-2]·[IGFBP7] significantly improved risk stratification when added to a nine-variable clinical model when analyzed using Cox proportional hazards model, generalized estimating equation, integrated discrimination improvement or net reclassification improvement. Finally, in sensitivity analyses [TIMP-2]·[IGFBP7] remained significant and superior to all other markers regardless of changes in reference creatinine method. Conclusions Two novel markers for AKI have been identified and validated in independent multicenter cohorts. Both markers are superior to existing markers, provide additional information over clinical variables and add mechanistic insight into AKI. Trial registration ClinicalTrials.gov number NCT01209169. PMID:23388612
Cohort profile: cerebral palsy in the Norwegian and Danish birth cohorts (MOBAND-CP).
Tollånes, Mette C; Strandberg-Larsen, Katrine; Forthun, Ingeborg; Petersen, Tanja Gram; Moster, Dag; Andersen, Anne-Marie Nybo; Stoltenberg, Camilla; Olsen, Jørn; Wilcox, Allen J
2016-09-02
The purpose of MOthers and BAbies in Norway and Denmark cerebral palsy (MOBAND-CP) was to study CP aetiology in a prospective design. MOBAND-CP is a cohort of more than 210 000 children, created as a collaboration between the world's two largest pregnancy cohorts-the Norwegian Mother and Child Cohort study (MoBa) and the Danish National Birth Cohort. MOBAND-CP includes maternal interview/questionnaire data collected during pregnancy and follow-up, plus linked information from national health registries. Initial harmonisation of data from the 2 cohorts has created 140 variables for children and their mothers. In the MOBAND-CP cohort, 438 children with CP have been identified through record linkage with validated national registries, providing by far the largest such sample with prospectively collected detailed pregnancy data. Several studies investigating various hypotheses regarding CP aetiology are currently on-going. Additional data can be harmonised as necessary to meet requirements of new projects. Biological specimens collected during pregnancy and at delivery are potentially available for assay, as are results from assays conducted on these specimens for other projects. The study size allows consideration of CP subtypes, which is rare in aetiological studies of CP. In addition, MOBAND-CP provides a platform within the context of a merged birth cohort of exceptional size that could, after appropriate permissions have been sought, be used for cohort and case-cohort studies of other relatively rare health conditions of infants and children. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Gleeson, Elizabeth M; Shaikh, Mohammad F; Shewokis, Patricia A; Clarke, John R; Meyers, William C; Pitt, Henry A; Bowne, Wilbur B
2016-11-01
Pancreaticoduodenectomy needs simple, validated risk models to better identify 30-day mortality. The goal of this study is to develop a simple risk score to predict 30-day mortality after pancreaticoduodenectomy. We reviewed cases of pancreaticoduodenectomy from 2005-2012 in the American College of Surgeons-National Surgical Quality Improvement Program databases. Logistic regression was used to identify preoperative risk factors for morbidity and mortality from a development cohort. Scores were created using weighted beta coefficients, and predictive accuracy was assessed on the validation cohort using receiver operator characteristic curves and measuring area under the curve. The 30-day mortality rate was 2.7% for patients who underwent pancreaticoduodenectomy (n = 14,993). We identified 8 independent risk factors. The score created from weighted beta coefficients had an area under the curve of 0.71 (95% confidence interval, 0.66-0.77) on the validation cohort. Using the score WHipple-ABACUS (hypertension With medication + History of cardiac surgery + Age >62 + 2 × Bleeding disorder + Albumin <3.5 g/dL + 2 × disseminated Cancer + 2 × Use of steroids + 2 × Systemic inflammatory response syndrome), mortality rates increase with increasing score (P < .001). While other risk scores exist for 30-day mortality after pancreaticoduodenectomy, we present a simple, validated score developed using exclusively preoperative predictors surgeons could use to identify patients at risk for this procedure. Copyright © 2016 Elsevier Inc. All rights reserved.
Shriberg, Lawrence D; Strand, Edythe A; Fourakis, Marios; Jakielski, Kathy J; Hall, Sheryl D; Karlsson, Heather B; Mabie, Heather L; McSweeny, Jane L; Tilkens, Christie M; Wilson, David L
2017-04-14
The purpose of this 2nd article in this supplement is to report validity support findings for the Pause Marker (PM), a proposed single-sign diagnostic marker of childhood apraxia of speech (CAS). PM scores and additional perceptual and acoustic measures were obtained from 296 participants in cohorts with idiopathic and neurogenetic CAS, adult-onset apraxia of speech and primary progressive apraxia of speech, and idiopathic speech delay. Adjusted for questionable specificity disagreements with a pediatric Mayo Clinic diagnostic standard, the estimated sensitivity and specificity, respectively, of the PM were 86.8% and 100% for the CAS cohort, yielding positive and negative likelihood ratios of 56.45 (95% confidence interval [CI]: [1.15, 2763.31]) and 0.13 (95% CI [0.06, 0.30]). Specificity of the PM for 4 cohorts totaling 205 participants with speech delay was 98.5%. These findings are interpreted as providing support for the PM as a near-conclusive diagnostic marker of CAS.
Lin, Daniel W; Crawford, E David; Keane, Thomas; Evans, Brent; Reid, Julia; Rajamani, Saradha; Brown, Krystal; Gutin, Alexander; Tward, Jonathan; Scardino, Peter; Brawer, Michael; Stone, Steven; Cuzick, Jack
2018-06-01
A combined clinical cell-cycle risk (CCR) score that incorporates prognostic molecular and clinical information has been recently developed and validated to improve prostate cancer mortality (PCM) risk stratification over clinical features alone. As clinical features are currently used to select men for active surveillance (AS), we developed and validated a CCR score threshold to improve the identification of men with low-risk disease who are appropriate for AS. The score threshold was selected based on the 90th percentile of CCR scores among men who might typically be considered for AS based on NCCN low/favorable-intermediate risk criteria (CCR = 0.8). The threshold was validated using 10-year PCM in an unselected, conservatively managed cohort and in the subset of the same cohort after excluding men with high-risk features. The clinical effect was evaluated in a contemporary clinical cohort. In the unselected validation cohort, men with CCR scores below the threshold had a predicted mean 10-year PCM of 2.7%, and the threshold significantly dichotomized low- and high-risk disease (P = 1.2 × 10 -5 ). After excluding high-risk men from the validation cohort, men with CCR scores below the threshold had a predicted mean 10-year PCM of 2.3%, and the threshold significantly dichotomized low- and high-risk disease (P = 0.020). There were no prostate cancer-specific deaths in men with CCR scores below the threshold in either analysis. The proportion of men in the clinical testing cohort identified as candidates for AS was substantially higher using the threshold (68.8%) compared to clinicopathologic features alone (42.6%), while mean 10-year predicted PCM risks remained essentially identical (1.9% vs. 2.0%, respectively). The CCR score threshold appropriately dichotomized patients into low- and high-risk groups for 10-year PCM, and may enable more appropriate selection of patients for AS. Copyright © 2018 Elsevier Inc. All rights reserved.
Sengupta, Neil; Tapper, Elliot B
2017-05-01
There are limited data to predict which patients with lower gastrointestinal bleeding are at risk for adverse outcomes. We aimed to develop a clinical tool based on admission variables to predict 30-day mortality in lower gastrointestinal bleeding. We used a validated machine learning algorithm to identify adult patients hospitalized with lower gastrointestinal bleeding at an academic medical center between 2008 and 2015. The cohort was split randomly into derivation and validation cohorts. In the derivation cohort, we used multiple logistic regression on all candidate admission variables to create a prediction model for 30-day mortality, using area under the receiving operator characteristic curve and misclassification rate to estimate prediction accuracy. Regression coefficients were used to derive an integer score, and mortality risk associated with point totals was assessed. In the derivation cohort (n = 4044), 8 variables were most associated with 30-day mortality: age, dementia, metastatic cancer, chronic kidney disease, chronic pulmonary disease, anticoagulant use, admission hematocrit, and albumin. The model yielded a misclassification rate of 0.06 and area under the curve of 0.81. The integer score ranged from -10 to 26 in the derivation cohort, with a misclassification rate of 0.11 and area under the curve of 0.74. In the validation cohort (n = 2060), the score had an area under the curve of 0.72 with a misclassification rate of 0.12. After dividing the score into 4 quartiles of risk, 30-day mortality in the derivation and validation sets was 3.6% and 4.4% in quartile 1, 4.9% and 7.3% in quartile 2, 9.9% and 9.1% in quartile 3, and 24% and 26% in quartile 4, respectively. A clinical tool can be used to predict 30-day mortality in patients hospitalized with lower gastrointestinal bleeding. Copyright © 2017 Elsevier Inc. All rights reserved.
Body, Richard; Sperrin, Matthew; Lewis, Philip S; Burrows, Gillian; Carley, Simon; McDowell, Garry; Buchan, Iain; Greaves, Kim; Mackway-Jones, Kevin
2017-01-01
Background The original Manchester Acute Coronary Syndromes model (MACS) ‘rules in’ and ‘rules out’ acute coronary syndromes (ACS) using high sensitivity cardiac troponin T (hs-cTnT) and heart-type fatty acid binding protein (H-FABP) measured at admission. The latter is not always available. We aimed to refine and validate MACS as Troponin-only Manchester Acute Coronary Syndromes (T-MACS), cutting down the biomarkers to just hs-cTnT. Methods We present secondary analyses from four prospective diagnostic cohort studies including patients presenting to the ED with suspected ACS. Data were collected and hs-cTnT measured on arrival. The primary outcome was ACS, defined as prevalent acute myocardial infarction (AMI) or incident death, AMI or coronary revascularisation within 30 days. T-MACS was built in one cohort (derivation set) and validated in three external cohorts (validation set). Results At the ‘rule out’ threshold, in the derivation set (n=703), T-MACS had 99.3% (95% CI 97.3% to 99.9%) negative predictive value (NPV) and 98.7% (95.3%–99.8%) sensitivity for ACS, ‘ruling out’ 37.7% patients (specificity 47.6%, positive predictive value (PPV) 34.0%). In the validation set (n=1459), T-MACS had 99.3% (98.3%–99.8%) NPV and 98.1% (95.2%–99.5%) sensitivity, ‘ruling out’ 40.4% (n=590) patients (specificity 47.0%, PPV 23.9%). T-MACS would ‘rule in’ 10.1% and 4.7% patients in the respective sets, of which 100.0% and 91.3% had ACS. C-statistics for the original and refined rules were similar (T-MACS 0.91 vs MACS 0.90 on validation). Conclusions T-MACS could ‘rule out’ ACS in 40% of patients, while ‘ruling in’ 5% at highest risk using a single hs-cTnT measurement on arrival. As a clinical decision aid, T-MACS could therefore help to conserve healthcare resources. PMID:27565197
Yoon, Sungroh; Park, Man Sik; Choi, Hoon; Bae, Jae Hyun; Moon, Du Geon; Hong, Sung Kyu; Lee, Sang Eun; Park, Chanwang
2017-01-01
Purpose We developed the Korean Prostate Cancer Risk Calculator for High-Grade Prostate Cancer (KPCRC-HG) that predicts the probability of prostate cancer (PC) of Gleason score 7 or higher at the initial prostate biopsy in a Korean cohort (http://acl.snu.ac.kr/PCRC/RISC/). In addition, KPCRC-HG was validated and compared with internet-based Western risk calculators in a validation cohort. Materials and Methods Using a logistic regression model, KPCRC-HG was developed based on the data from 602 previously unscreened Korean men who underwent initial prostate biopsies. Using 2,313 cases in a validation cohort, KPCRC-HG was compared with the European Randomized Study of Screening for PC Risk Calculator for high-grade cancer (ERSPCRC-HG) and the Prostate Cancer Prevention Trial Risk Calculator 2.0 for high-grade cancer (PCPTRC-HG). The predictive accuracy was assessed using the area under the receiver operating characteristic curve (AUC) and calibration plots. Results PC was detected in 172 (28.6%) men, 120 (19.9%) of whom had PC of Gleason score 7 or higher. Independent predictors included prostate-specific antigen levels, digital rectal examination findings, transrectal ultrasound findings, and prostate volume. The AUC of the KPCRC-HG (0.84) was higher than that of the PCPTRC-HG (0.79, p<0.001) but not different from that of the ERSPCRC-HG (0.83) on external validation. Calibration plots also revealed better performance of KPCRC-HG and ERSPCRC-HG than that of PCPTRC-HG on external validation. At a cut-off of 5% for KPCRC-HG, 253 of the 2,313 men (11%) would not have been biopsied, and 14 of the 614 PC cases with Gleason score 7 or higher (2%) would not have been diagnosed. Conclusions KPCRC-HG is the first web-based high-grade prostate cancer prediction model in Korea. It had higher predictive accuracy than PCPTRC-HG in a Korean population and showed similar performance with ERSPCRC-HG in a Korean population. This prediction model could help avoid unnecessary biopsy and reduce overdiagnosis and overtreatment in clinical settings. PMID:28046017
Park, Jae Young; Yoon, Sungroh; Park, Man Sik; Choi, Hoon; Bae, Jae Hyun; Moon, Du Geon; Hong, Sung Kyu; Lee, Sang Eun; Park, Chanwang; Byun, Seok-Soo
2017-01-01
We developed the Korean Prostate Cancer Risk Calculator for High-Grade Prostate Cancer (KPCRC-HG) that predicts the probability of prostate cancer (PC) of Gleason score 7 or higher at the initial prostate biopsy in a Korean cohort (http://acl.snu.ac.kr/PCRC/RISC/). In addition, KPCRC-HG was validated and compared with internet-based Western risk calculators in a validation cohort. Using a logistic regression model, KPCRC-HG was developed based on the data from 602 previously unscreened Korean men who underwent initial prostate biopsies. Using 2,313 cases in a validation cohort, KPCRC-HG was compared with the European Randomized Study of Screening for PC Risk Calculator for high-grade cancer (ERSPCRC-HG) and the Prostate Cancer Prevention Trial Risk Calculator 2.0 for high-grade cancer (PCPTRC-HG). The predictive accuracy was assessed using the area under the receiver operating characteristic curve (AUC) and calibration plots. PC was detected in 172 (28.6%) men, 120 (19.9%) of whom had PC of Gleason score 7 or higher. Independent predictors included prostate-specific antigen levels, digital rectal examination findings, transrectal ultrasound findings, and prostate volume. The AUC of the KPCRC-HG (0.84) was higher than that of the PCPTRC-HG (0.79, p<0.001) but not different from that of the ERSPCRC-HG (0.83) on external validation. Calibration plots also revealed better performance of KPCRC-HG and ERSPCRC-HG than that of PCPTRC-HG on external validation. At a cut-off of 5% for KPCRC-HG, 253 of the 2,313 men (11%) would not have been biopsied, and 14 of the 614 PC cases with Gleason score 7 or higher (2%) would not have been diagnosed. KPCRC-HG is the first web-based high-grade prostate cancer prediction model in Korea. It had higher predictive accuracy than PCPTRC-HG in a Korean population and showed similar performance with ERSPCRC-HG in a Korean population. This prediction model could help avoid unnecessary biopsy and reduce overdiagnosis and overtreatment in clinical settings.
Development and Validation of a Chronic Pancreatitis Prognosis Score in 2 Independent Cohorts.
Beyer, Georg; Mahajan, Ujjwal M; Budde, Christoph; Bulla, Thomas J; Kohlmann, Thomas; Kuhlmann, Louise; Schütte, Kerstin; Aghdassi, Ali A; Weber, Eckhard; Weiss, F Ulrich; Drewes, Asbjørn M; Olesen, Søren S; Lerch, Markus M; Mayerle, Julia
2017-12-01
The clinical course of chronic pancreatitis is unpredictable. There is no model to assess disease severity or progression or predict patient outcomes. We performed a prospective study of 91 patients with chronic pancreatitis; data were collected from patients seen at academic centers in Europe from January 2011 through April 2014. We analyzed correlations between clinical, laboratory, and imaging data with number of hospital readmissions and in-hospital days over the next 12 months; the parameters with the highest degree of correlation were used to develop a 3-stage chronic pancreatitis prognosis score (COPPS). The predictive strength was validated in 129 independent subjects identified from 2 prospective databases. The mean number of hospital admissions was 1.9 (95% confidence interval [CI], 1.39-2.44) and 15.2 for hospital days (95% CI, 10.76-19.71) for the development cohort and 10.9 for the validation cohort (95% CI, 7.54-14.30) (P = .08). Based on bivariate correlations, pain (numeric rating scale), level of glycated hemoglobin A1c, level of C-reactive protein, body mass index, and platelet count were used to develop the COPPS system. The patients' median COPPS was 8.9 points (range, 5-14). The system accurately discriminated stages of disease severity (low to high): A (5-6 points), B (7-9), and C (10-15). In Pearson correlation analysis of the development cohort, the COPPS correlated with hospital admissions (0.39; P < .01) and number of hospital days (0.33; P < .01). The correlation was validated in the validation set (Pearson correlation values of 0.36 and 0.44; P < .01). COPPS did not correlate with results from the Cambridge classification system. We developed and validated an easy to use dynamic multivariate scoring system, similar to the Child-Pugh-Score for liver cirrhosis. The COPPS allows objective monitoring of patients with chronic pancreatitis, determining risk for readmission to hospital and potential length of hospital stay. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.
Analysis of the construct of dignity and content validity of the patient dignity inventory
2011-01-01
Background Maintaining dignity, the quality of being worthy of esteem or respect, is considered as a goal of palliative care. The aim of this study was to analyse the construct of personal dignity and to assess the content validity of the Patient Dignity Inventory (PDI) in people with an advance directive in the Netherlands. Methods Data were collected within the framework of an advance directives cohort study. This cohort study is aiming to get a better insight into how decisions are made at the end of life with regard to advance directives in the Netherlands. One half of the cohort (n = 2404) received an open-ended question concerning factors relevant to dignity. Content labels were assigned to issues mentioned in the responses to the open-ended question. The other half of the cohort (n = 2537) received a written questionnaire including the PDI. The relevance and comprehensiveness of the PDI items were assessed with the COSMIN checklist ('COnsensus-based Standards for the selection of health status Measurement INstruments'). Results The majority of the PDI items were found to be relevant for the construct to be measured, the study population, and the purpose of the study but the items were not completely comprehensive. The responses to the open-ended question indicated that communication and care-related aspects were also important for dignity. Conclusions This study demonstrated that the PDI items were relevant for people with an advance directive in the Netherlands. The comprehensiveness of the items can be improved by including items concerning communication and care. PMID:21682924
Analysis of the construct of dignity and content validity of the patient dignity inventory.
Albers, Gwenda; Pasman, H Roeline W; Rurup, Mette L; de Vet, Henrica C W; Onwuteaka-Philipsen, Bregje D
2011-06-19
Maintaining dignity, the quality of being worthy of esteem or respect, is considered as a goal of palliative care. The aim of this study was to analyse the construct of personal dignity and to assess the content validity of the Patient Dignity Inventory (PDI) in people with an advance directive in the Netherlands. Data were collected within the framework of an advance directives cohort study. This cohort study is aiming to get a better insight into how decisions are made at the end of life with regard to advance directives in the Netherlands. One half of the cohort (n = 2404) received an open-ended question concerning factors relevant to dignity. Content labels were assigned to issues mentioned in the responses to the open-ended question. The other half of the cohort (n = 2537) received a written questionnaire including the PDI. The relevance and comprehensiveness of the PDI items were assessed with the COSMIN checklist ('COnsensus-based Standards for the selection of health status Measurement INstruments'). The majority of the PDI items were found to be relevant for the construct to be measured, the study population, and the purpose of the study but the items were not completely comprehensive. The responses to the open-ended question indicated that communication and care-related aspects were also important for dignity. This study demonstrated that the PDI items were relevant for people with an advance directive in the Netherlands. The comprehensiveness of the items can be improved by including items concerning communication and care.
Lee, Su Hyun; Chang, Jung Min; Kim, Won Hwa; Bae, Min Sun; Seo, Mirinae; Koo, Hye Ryoung; Chu, A Jung; Gweon, Hye Mi; Cho, Nariya; Moon, Woo Kyung
2014-10-01
To evaluate the additional value of shear-wave elastography (SWE) to B-mode ultrasonography (US) and to determine an appropriate guideline for the combined assessment of screening US-detected breast masses. This study was conducted with institutional review board approval, and written informed consent was obtained. From March 2010 to February 2012, B-mode US and SWE were performed in 159 US-detected breast masses before biopsy. For each lesion, Breast Imaging Reporting and Data System (BI-RADS) category on B-mode US images and the maximum stiffness color and elasticity values on SWE images were assessed. A guideline for adding SWE data to B-mode US was developed with the retrospective cohort to improve diagnostic performance in sensitivity and specificity and was validated in a distinct prospective cohort of 207 women prior to biopsy. Twenty-one of 159 masses in the development cohort and 12 of 207 breast masses in the validation cohort were malignant. In the development cohort, when BI-RADS category 4a masses showing a dark blue color or a maximum elasticity value of 30 kPa or less on SWE images were downgraded to category 3, specificity increased from 9.4% (13 of 138) to 59.4% (82 of 138) and 57.2% (79 of 138) (P < .001), respectively, without loss in sensitivity (100% [21 of 21]). In the validation cohort, specificity increased from 17.4% (34 of 195) to 62.1% (121 of 195) and 53.3% (104 of 195) (P < .001) respectively, without loss in sensitivity (91.7% [11 of 12]). The addition of SWE to B-mode US improved diagnostic performance with increased specificity for screening US-detected breast masses. BI-RADS category 4a masses detected at US screening that showed a dark blue color or a maximum elasticity value of 30 kPa or less on SWE images can be safely followed up instead of performing biopsy. © RSNA, 2014.
ERIC Educational Resources Information Center
Shriberg, Lawrence D.; Strand, Edythe A.; Fourakis, Marios; Jakielski, Kathy J.; Hall, Sheryl D.; Karlsson, Heather B.; Mabie, Heather L.; McSweeny, Jane L.; Tilkens, Christie M.; Wilson, David L.
2017-01-01
Purpose: The purpose of this 2nd article in this supplement is to report validity support findings for the Pause Marker (PM), a proposed single-sign diagnostic marker of childhood apraxia of speech (CAS). Method: PM scores and additional perceptual and acoustic measures were obtained from 296 participants in cohorts with idiopathic and…
Serum proteomic profiling of major depressive disorder
Bot, M; Chan, M K; Jansen, R; Lamers, F; Vogelzangs, N; Steiner, J; Leweke, F M; Rothermundt, M; Cooper, J; Bahn, S; Penninx, B W J H
2015-01-01
Much has still to be learned about the molecular mechanisms of depression. This study aims to gain insight into contributing mechanisms by identifying serum proteins related to major depressive disorder (MDD) in a large psychiatric cohort study. Our sample consisted of 1589 participants of the Netherlands Study of Depression and Anxiety, comprising 687 individuals with current MDD (cMDD), 482 individuals with remitted MDD (rMDD) and 420 controls. We studied the relationship between MDD status and the levels of 171 serum proteins detected on a multi-analyte profiling platform using adjusted linear regression models. Pooled analyses of two independent validation cohorts (totaling 78 MDD cases and 156 controls) was carried out to validate our top markers. Twenty-eight analytes differed significantly between cMDD cases and controls (P<0.05), whereas 10 partly overlapping markers differed significantly between rMDD cases and controls. Antidepressant medication use and comorbid anxiety status did not substantially impact on these findings. Sixteen of the cMDD-related markers had been assayed in the pooled validation cohorts, of which seven were associated with MDD. The analytes prominently associated with cMDD related to diverse cell communication and signal transduction processes (pancreatic polypeptide, macrophage migration inhibitory factor, ENRAGE, interleukin-1 receptor antagonist and tenascin-C), immune response (growth-regulated alpha protein) and protein metabolism (von Willebrand factor). Several proteins were implicated in depression. Changes were more prominent in cMDD, suggesting that molecular alterations in serum are associated with acute depression symptomatology. These findings may help to establish serum-based biomarkers of depression and could improve our understanding of its pathophysiology. PMID:26171980
NYU Lung Cancer Biomarker Center — EDRN Public Portal
A. SPECIFIC AIMS 1. To develop and prospectively follow a large cohort at high-risk for lung cancer. Individuals are recruited to one of two different study groups: The Screening Cohort includes people with and without increased risk for lung cancer. The Rule-Out Lung Cancer Patient Group is recruited from patients referred for evaluation of suspicious nodules. All individuals answer a questionnaire, obtain PFTs, chest CT scan, sputum induction and phlebotomy. For patients undergoing lung resections or biopsies, tissue samples are collected and banked. Individuals are recruited for research bronchoscopy. All participants are then followed prospectively. The specimens obtained are banked and used for biomarker discovery and validation studies. 2. To identify and validate biomarkers for the early detection of lung cancer, and to describe preneoplastic cellular changes and lesions. Biomarker studies include DNA adducts, DNA methylation, protein markers, and other collaborations. Preneoplasia studies include: fluorescence and Superdimension bronchoscopies to obtain biopsies of preneoplastic lesions and biomarker studies in individuals with preneoplasias.
Cohen-Stavi, Chandra; Leventer-Roberts, Maya; Balicer, Ran D
2017-01-01
Objective To directly compare the performance and externally validate the three most studied prediction tools for osteoporotic fractures—QFracture, FRAX, and Garvan—using data from electronic health records. Design Retrospective cohort study. Setting Payer provider healthcare organisation in Israel. Participants 1 054 815 members aged 50 to 90 years for comparison between tools and cohorts of different age ranges, corresponding to those in each tools’ development study, for tool specific external validation. Main outcome measure First diagnosis of a major osteoporotic fracture (for QFracture and FRAX tools) and hip fractures (for all three tools) recorded in electronic health records from 2010 to 2014. Observed fracture rates were compared to probabilities predicted retrospectively as of 2010. Results The observed five year hip fracture rate was 2.7% and the rate for major osteoporotic fractures was 7.7%. The areas under the receiver operating curve (AUC) for hip fracture prediction were 82.7% for QFracture, 81.5% for FRAX, and 77.8% for Garvan. For major osteoporotic fractures, AUCs were 71.2% for QFracture and 71.4% for FRAX. All the tools underestimated the fracture risk, but the average observed to predicted ratios and the calibration slopes of FRAX were closest to 1. Tool specific validation analyses yielded hip fracture prediction AUCs of 88.0% for QFracture (among those aged 30-100 years), 81.5% for FRAX (50-90 years), and 71.2% for Garvan (60-95 years). Conclusions Both QFracture and FRAX had high discriminatory power for hip fracture prediction, with QFracture performing slightly better. This performance gap was more pronounced in previous studies, likely because of broader age inclusion criteria for QFracture validations. The simpler FRAX performed almost as well as QFracture for hip fracture prediction, and may have advantages if some of the input data required for QFracture are not available. However, both tools require calibration before implementation. PMID:28104610
Model to Determine Risk of Pancreatic Cancer in Patients with New-onset Diabetes.
Sharma, Ayush; Kandlakunta, Harika; Singh Nagpal, Sajan Jiv; Ziding, Feng; Hoos, William; Petersen, Gloria M; Chari, Suresh T
2018-05-15
Of subjects with new-onset diabetes (based on glycemia) over the age of 50 years, approximately 1% are diagnosed with pancreatic cancer within 3 years. We aimed to develop and validate a model to determine risk of pancreatic cancer in individuals with new-onset diabetes. We retrospectively collected data from 4 independent, non-overlapping cohorts of patients (n=1561) with new-onset diabetes (based on glycemia; data collected at date of diagnosis and 12 months before) in the Rochester Epidemiology Project, from January 1, 2000 through December 31, 2015 to create our model. The model weighed scores for the 3 factors identified in the discovery cohort to be most strongly associated with pancreatic cancer (64 patients with pancreatic cancer and 192 with type-2 diabetes): change in weight, change in blood glucose, and age at onset of diabetes. We called our model enriching new-onset diabetes for pancreatic cancer (END-PAC). We validated the locked-down model and cutoff score in an independent population-based cohort of 1096 patients with diabetes; of these 9 patients (.82%) had pancreatic within 3 years of meeting the criteria for new-onset diabetes. In the discovery cohort the END-PAC model identified patients who developed pancreatic cancer within 3 years of onset of diabetes with an area under the receiver operating characteristic curve value of 0.87; a score of >3 identified patients who developed pancreatic cancer with 80% sensitivity and specificity. In the validation cohort, a score of >3 identified 7/9 patients with pancreatic cancer (78%), with 85% specificity; the prevalence of pancreatic cancer in subjects with score of >3 (3.6%) was 4.4-fold more than in patients with new-onset diabetes. A high END-PAC score in subjects who did not have pancreatic cancer (false positives) was often due to such factors as recent steroid use or different malignancy. An END-PAC score <0 (in 49% of subjects) meant that patients had an extremely low-risk for pancreatic cancer. An END-PAC score >3 identified 75% of subjects in the discovery cohort >6 months before a diagnosis of pancreatic cancer. Based on change in weight, change in blood glucose, and age at onset of diabetes, we developed and validated a model to determine risk of pancreatic cancer in patients with new-onset diabetes, based on glycemia (the END-PAC model). An independent, prospective study is needed to further validate this model, which could contribute to early detection of pancreatic cancer. Copyright © 2018 AGA Institute. Published by Elsevier Inc. All rights reserved.
Ion channel gene expression predicts survival in glioma patients
Wang, Rong; Gurguis, Christopher I.; Gu, Wanjun; Ko, Eun A; Lim, Inja; Bang, Hyoweon; Zhou, Tong; Ko, Jae-Hong
2015-01-01
Ion channels are important regulators in cell proliferation, migration, and apoptosis. The malfunction and/or aberrant expression of ion channels may disrupt these important biological processes and influence cancer progression. In this study, we investigate the expression pattern of ion channel genes in glioma. We designate 18 ion channel genes that are differentially expressed in high-grade glioma as a prognostic molecular signature. This ion channel gene expression based signature predicts glioma outcome in three independent validation cohorts. Interestingly, 16 of these 18 genes were down-regulated in high-grade glioma. This signature is independent of traditional clinical, molecular, and histological factors. Resampling tests indicate that the prognostic power of the signature outperforms random gene sets selected from human genome in all the validation cohorts. More importantly, this signature performs better than the random gene signatures selected from glioma-associated genes in two out of three validation datasets. This study implicates ion channels in brain cancer, thus expanding on knowledge of their roles in other cancers. Individualized profiling of ion channel gene expression serves as a superior and independent prognostic tool for glioma patients. PMID:26235283
Schmit, Stephanie L.; Stadler, Zsofia K.; Joseph, Vijai; Zhang, Lu; Willis, Joseph E.; Scacheri, Peter; Veigl, Martina; Adams, Mark D.; Raskin, Leon; Sullivan, John F.; Stratton, Kelly; Shia, Jinru; Ellis, Nathan; Rennert, Hedy S.; Manschreck, Christopher; Li, Li; Offit, Kenneth; Elston, Robert C.; Rennert, Gadi; Gruber, Stephen B.
2016-01-01
We tested for germline variants showing association to colon cancer metastasis using a genome-wide association study that compared Ashkenazi Jewish individuals with stage IV metastatic colon cancers versus those with stage I or II non-metastatic colon cancers. In a two-stage study design, we demonstrated significant association to developing metastatic disease for rs60745952, that in Ashkenazi discovery and validation cohorts, respectively, showed an odds ratio (OR) = 2.3 (P = 2.73E-06) and OR = 1.89 (P = 8.05E-04) (exceeding validation threshold of 0.0044). Significant association to metastatic colon cancer was further confirmed by a meta-analysis of rs60745952 in these datasets plus an additional Ashkenazi validation cohort (OR = 1.92; 95% CI: 1.28–2.87), and by a permutation test that demonstrated a significantly longer haplotype surrounding rs60745952 in the stage IV samples. rs60745952, located in an intergenic region on chromosome 4q31.1, and not previously associated with cancer, is, thus, a germline genetic marker for susceptibility to developing colon cancer metastases among Ashkenazi Jews. PMID:26751797
Guerra, Beniamino; Haile, Sarah R; Lamprecht, Bernd; Ramírez, Ana S; Martinez-Camblor, Pablo; Kaiser, Bernhard; Alfageme, Inmaculada; Almagro, Pere; Casanova, Ciro; Esteban-González, Cristóbal; Soler-Cataluña, Juan J; de-Torres, Juan P; Miravitlles, Marc; Celli, Bartolome R; Marin, Jose M; Ter Riet, Gerben; Sobradillo, Patricia; Lange, Peter; Garcia-Aymerich, Judith; Antó, Josep M; Turner, Alice M; Han, Meilan K; Langhammer, Arnulf; Leivseth, Linda; Bakke, Per; Johannessen, Ane; Oga, Toru; Cosio, Borja; Ancochea-Bermúdez, Julio; Echazarreta, Andres; Roche, Nicolas; Burgel, Pierre-Régis; Sin, Don D; Soriano, Joan B; Puhan, Milo A
2018-03-02
External validations and comparisons of prognostic models or scores are a prerequisite for their use in routine clinical care but are lacking in most medical fields including chronic obstructive pulmonary disease (COPD). Our aim was to externally validate and concurrently compare prognostic scores for 3-year all-cause mortality in mostly multimorbid patients with COPD. We relied on 24 cohort studies of the COPD Cohorts Collaborative International Assessment consortium, corresponding to primary, secondary, and tertiary care in Europe, the Americas, and Japan. These studies include globally 15,762 patients with COPD (1871 deaths and 42,203 person years of follow-up). We used network meta-analysis adapted to multiple score comparison (MSC), following a frequentist two-stage approach; thus, we were able to compare all scores in a single analytical framework accounting for correlations among scores within cohorts. We assessed transitivity, heterogeneity, and inconsistency and provided a performance ranking of the prognostic scores. Depending on data availability, between two and nine prognostic scores could be calculated for each cohort. The BODE score (body mass index, airflow obstruction, dyspnea, and exercise capacity) had a median area under the curve (AUC) of 0.679 [1st quartile-3rd quartile = 0.655-0.733] across cohorts. The ADO score (age, dyspnea, and airflow obstruction) showed the best performance for predicting mortality (difference AUC ADO - AUC BODE = 0.015 [95% confidence interval (CI) = -0.002 to 0.032]; p = 0.08) followed by the updated BODE (AUC BODE updated - AUC BODE = 0.008 [95% CI = -0.005 to +0.022]; p = 0.23). The assumption of transitivity was not violated. Heterogeneity across direct comparisons was small, and we did not identify any local or global inconsistency. Our analyses showed best discriminatory performance for the ADO and updated BODE scores in patients with COPD. A limitation to be addressed in future studies is the extension of MSC network meta-analysis to measures of calibration. MSC network meta-analysis can be applied to prognostic scores in any medical field to identify the best scores, possibly paving the way for stratified medicine, public health, and research.
A patient-centered electronic tool for weight loss outcomes after Roux-en-Y gastric bypass.
Wood, G Craig; Benotti, Peter; Gerhard, Glenn S; Miller, Elaina K; Zhang, Yushan; Zaccone, Richard J; Argyropoulos, George A; Petrick, Anthony T; Still, Christopher D
2014-01-01
BACKGROUND. Current patient education and informed consent regarding weight loss expectations for bariatric surgery candidates are largely based on averages from large patient cohorts. The variation in weight loss outcomes illustrates the need for establishing more realistic weight loss goals for individual patients. This study was designed to develop a simple web-based tool which provides patient-specific weight loss expectations. METHODS. Postoperative weight measurements after Roux-en-Y gastric bypass (RYGB) were collected and analyzed with patient characteristics known to influence weight loss outcomes. Quantile regression was used to create expected weight loss curves (25th, 50th, and 75th %tile) for the 24 months after RYGB. The resulting equations were validated and used to develop web-based tool for predicting weight loss outcomes. RESULTS. Weight loss data from 2986 patients (2608 in the primary cohort and 378 in the validation cohort) were included. Preoperative body mass index (BMI) and age were found to have a high correlation with weight loss accomplishment (P < 0.0001 for each). An electronic tool was created that provides easy access to patient-specific, 24-month weight loss trajectories based on initial BMI and age. CONCLUSIONS. This validated, patient-centered electronic tool will assist patients and providers in patient teaching, informed consent, and postoperative weight loss management.
Logistic regression model for diagnosis of transition zone prostate cancer on multi-parametric MRI.
Dikaios, Nikolaos; Alkalbani, Jokha; Sidhu, Harbir Singh; Fujiwara, Taiki; Abd-Alazeez, Mohamed; Kirkham, Alex; Allen, Clare; Ahmed, Hashim; Emberton, Mark; Freeman, Alex; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit
2015-02-01
We aimed to develop logistic regression (LR) models for classifying prostate cancer within the transition zone on multi-parametric magnetic resonance imaging (mp-MRI). One hundred and fifty-five patients (training cohort, 70 patients; temporal validation cohort, 85 patients) underwent mp-MRI and transperineal-template-prostate-mapping (TPM) biopsy. Positive cores were classified by cancer definitions: (1) any-cancer; (2) definition-1 [≥Gleason 4 + 3 or ≥ 6 mm cancer core length (CCL)] [high risk significant]; and (3) definition-2 (≥Gleason 3 + 4 or ≥ 4 mm CCL) cancer [intermediate-high risk significant]. For each, logistic-regression mp-MRI models were derived from the training cohort and validated internally and with the temporal cohort. Sensitivity/specificity and the area under the receiver operating characteristic (ROC-AUC) curve were calculated. LR model performance was compared to radiologists' performance. Twenty-eight of 70 patients from the training cohort, and 25/85 patients from the temporal validation cohort had significant cancer on TPM. The ROC-AUC of the LR model for classification of cancer was 0.73/0.67 at internal/temporal validation. The radiologist A/B ROC-AUC was 0.65/0.74 (temporal cohort). For patients scored by radiologists as Prostate Imaging Reporting and Data System (Pi-RADS) score 3, sensitivity/specificity of radiologist A 'best guess' and LR model was 0.14/0.54 and 0.71/0.61, respectively; and radiologist B 'best guess' and LR model was 0.40/0.34 and 0.50/0.76, respectively. LR models can improve classification of Pi-RADS score 3 lesions similar to experienced radiologists. • MRI helps find prostate cancer in the anterior of the gland • Logistic regression models based on mp-MRI can classify prostate cancer • Computers can help confirm cancer in areas doctors are uncertain about.
Wagener, A H; de Nijs, S B; Lutter, R; Sousa, A R; Weersink, E J M; Bel, E H; Sterk, P J
2015-02-01
Monitoring sputum eosinophils in asthma predicts exacerbations and improves management of asthma. Thus far, blood eosinophils and FE(NO) show contradictory results in predicting eosinophilic airway inflammation. More recently, serum periostin was proposed as a novel biomarker for eosinophilic inflammation. Quantifying the mutual relationships of blood eosinophils, FE(NO), and serum periostin with sputum eosinophils by external validation in two independent cohorts across various severities of asthma. The first cohort consisted of 110 patients with mild to moderate asthma (external validation cohort). The replication cohort consisted of 37 patients with moderate to severe asthma. Both cohorts were evaluated cross-sectionally. Sputum was induced for the assessment of eosinophils. In parallel, blood eosinophil counts, serum periostin concentrations and FENO were assessed. The diagnostic accuracy of these markers to identify eosinophilic asthma (sputum eosinophils ≥3%) was calculated using receiver operating characteristics area under the curve (ROC AUC). In the external validation cohort, ROC AUC for blood eosinophils was 89% (p<0.001) and for FE(NO) level 78% (p<0.001) to detect sputum eosinophilia ≥3%. Serum periostin was not able to distinguish eosinophilic from non-eosinophilic airway inflammation (ROC AUC=55%, p=0.44). When combining these three variables, no improvement was seen. The diagnostic value of blood eosinophils was confirmed in the replication cohort (ROC AUC 85%, p<0.001). In patients with mild to moderate asthma, as well as patients with more severe asthma, blood eosinophils had the highest accuracy in the identification of sputum eosinophilia in asthma. The use of blood eosinophils can facilitate individualised treatment and management of asthma. NTR1846 and NTR2364. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Coronary risk stratification of patients undergoing surgery for valvular heart disease.
Hasselbalch, Rasmus Bo; Engstrøm, Thomas; Pries-Heje, Mia; Heitmann, Merete; Pedersen, Frants; Schou, Morten; Mickley, Hans; Elming, Hanne; Steffensen, Rolf; Køber, Lars; Iversen, Kasper
2017-01-15
Multislice computed tomography (MSCT) is a non-invasive, less expensive, low-radiation alternative to coronary angiography (CAG) prior to valvular heart surgery. MSCT has a high negative predictive value for coronary artery disease (CAD) but previous studies of patients with valvular disease have shown that MSCT, as the primary evaluation technique, lead to re-evaluation with CAG in about a third of cases and it is therefore not recommended. If a subgroup of patients with low- to intermediate risk of CAD could be identified and examined with MSCT, it could be cost-effective, reduce radiation and the risk of complications associated with CAG. The study cohort was derived from a national registry of patients undergoing CAG prior to valvular heart surgery. Using logistic regression, we identified significant risk factors for CAD and developed a risk score (CT-valve score). The score was validated on a similar cohort of patients from another registry. The study cohort consisted of 2221 patients, 521 (23.5%) had CAD. The validation cohort consisted of 2575 patients, 771 (29.9%) had CAD. The identified risk factors were male sex, age, smoking, hyperlipidemia, hypertension, aortic valve disease, extracardiac arteriopathy, ejection fraction <30% and diabetes mellitus. CT-valve score could identify a third of the population with a risk about 10%. A score based on risk factors of CAD can identify patients that might benefit from using MSCT as a gatekeeper to CAG prior to heart valve surgery. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Tangri, Navdeep; Grams, Morgan E; Levey, Andrew S; Coresh, Josef; Appel, Lawrence J; Astor, Brad C; Chodick, Gabriel; Collins, Allan J; Djurdjev, Ognjenka; Elley, C Raina; Evans, Marie; Garg, Amit X; Hallan, Stein I; Inker, Lesley A; Ito, Sadayoshi; Jee, Sun Ha; Kovesdy, Csaba P; Kronenberg, Florian; Heerspink, Hiddo J Lambers; Marks, Angharad; Nadkarni, Girish N; Navaneethan, Sankar D; Nelson, Robert G; Titze, Stephanie; Sarnak, Mark J; Stengel, Benedicte; Woodward, Mark; Iseki, Kunitoshi
2016-01-12
Identifying patients at risk of chronic kidney disease (CKD) progression may facilitate more optimal nephrology care. Kidney failure risk equations, including such factors as age, sex, estimated glomerular filtration rate, and calcium and phosphate concentrations, were previously developed and validated in 2 Canadian cohorts. Validation in other regions and in CKD populations not under the care of a nephrologist is needed. To evaluate the accuracy of the risk equations across different geographic regions and patient populations through individual participant data meta-analysis. Thirty-one cohorts, including 721,357 participants with CKD stages 3 to 5 in more than 30 countries spanning 4 continents, were studied. These cohorts collected data from 1982 through 2014. Cohorts participating in the CKD Prognosis Consortium with data on end-stage renal disease. Data were obtained and statistical analyses were performed between July 2012 and June 2015. Using the risk factors from the original risk equations, cohort-specific hazard ratios were estimated and combined using random-effects meta-analysis to form new pooled kidney failure risk equations. Original and pooled kidney failure risk equation performance was compared, and the need for regional calibration factors was assessed. Kidney failure (treatment by dialysis or kidney transplant). During a median follow-up of 4 years of 721,357 participants with CKD, 23,829 cases kidney failure were observed. The original risk equations achieved excellent discrimination (ability to differentiate those who developed kidney failure from those who did not) across all cohorts (overall C statistic, 0.90; 95% CI, 0.89-0.92 at 2 years; C statistic at 5 years, 0.88; 95% CI, 0.86-0.90); discrimination in subgroups by age, race, and diabetes status was similar. There was no improvement with the pooled equations. Calibration (the difference between observed and predicted risk) was adequate in North American cohorts, but the original risk equations overestimated risk in some non-North American cohorts. Addition of a calibration factor that lowered the baseline risk by 32.9% at 2 years and 16.5% at 5 years improved the calibration in 12 of 15 and 10 of 13 non-North American cohorts at 2 and 5 years, respectively (P = .04 and P = .02). Kidney failure risk equations developed in a Canadian population showed high discrimination and adequate calibration when validated in 31 multinational cohorts. However, in some regions the addition of a calibration factor may be necessary.
Stop Using the Modified Work APGAR to Measure Job Satisfaction
Mielenz, Thelma J.; DeVellis, Robert F.; Battie, Michele C.; Carey, Timothy S.
2011-01-01
Background. The psychometric properties of the Modified Work APGAR (MWA) scale are not established, yet researchers use this scale as an overall measure of job satisfaction. Objective. Perform psychometric analyses on the MWA scale using data from two populations. Methods. A landmark occupational cohort and a clinical cohort are populations with low back pain studied. The first five items of the MWA scale measure social support from coworkers, one item measures dissatisfaction with job tasks, and the sixth item measures lack of social support from a supervisor. Exploratory principal components analyses were conducted in both cohorts. Results. In both cohorts, the first five items of the MWA scale loaded consistently onto one factor, social support from coworkers subscale. Conclusions. Unless researchers are interested in measuring social support from coworkers only, future studies should use other reliable and valid instruments to measure a broad range of psychosocial work characteristics. PMID:22191021
Eure, Gregg; Germany, Raymond; Given, Robert; Lu, Ruixiao; Shindel, Alan W; Rothney, Megan; Glowacki, Richard; Henderson, Jonathan; Richardson, Tim; Goldfischer, Evan; Febbo, Phillip G; Denes, Bela S
2017-09-01
To study the impact of genomic testing in shared decision making for men with clinically low-risk prostate cancer (PCa). Patients with clinically low-risk PCa were enrolled in a prospective, multi-institutional study of a validated 17-gene tissue-based reverse transcription polymerase chain reaction assay (Genomic Prostate Score [GPS]). In this paper we report on outcomes in the first 297 patients enrolled in the study with valid 17-gene assay results and decision-change data. The primary end points were shared decision on initial management and persistence on active surveillance (AS) at 1 year post diagnosis. AS utilization and persistence were compared with similar end points in a group of patients who did not have genomic testing (baseline cohort). Secondary end points included perceived utility of the assay and patient decisional conflict before and after testing. One-year results were available on 258 patients. Shift between initial recommendation and shared decision occurred in 23% of patients. Utilization of AS was higher in the GPS-tested cohort than in the untested baseline cohort (62% vs 40%). The proportion of men who selected and persisted on AS at 1 year was 55% and 34% in the GPS and baseline cohorts, respectively. Physicians reported that GPS was useful in 90% of cases. Mean decisional conflict scores declined in patients after GPS testing. Patients who received GPS testing were more likely to select and persist on AS for initial management compared with a matched baseline group. These data indicate that GPS help guide shared decisions in clinically low-risk PCa. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Anderson, Christopher D.; Biffi, Alessandro; Nalls, Michael A.; Devan, William J.; Schwab, Kristin; Ayres, Alison M.; Valant, Valerie; Ross, Owen A.; Rost, Natalia S.; Saxena, Richa; Viswanathan, Anand; Worrall, Bradford B.; Brott, Thomas G.; Goldstein, Joshua N.; Brown, Devin; Broderick, Joseph P.; Norrving, Bo; Greenberg, Steven M.; Silliman, Scott L.; Hansen, Björn M.; Tirschwell, David L.; Lindgren, Arne; Slowik, Agnieszka; Schmidt, Reinhold; Selim, Magdy; Roquer, Jaume; Montaner, Joan; Singleton, Andrew B.; Kidwell, Chelsea S.; Woo, Daniel; Furie, Karen L.; Meschia, James F.; Rosand, Jonathan
2013-01-01
Background and Purpose Prior studies demonstrated association between mitochondrial DNA variants and ischemic stroke (IS). We investigated whether variants within a larger set of oxidative phosphorylation (OXPHOS) genes encoded by both autosomal and mitochondrial DNA were associated with risk of IS and, based on our results, extended our investigation to intracerebral hemorrhage (ICH). Methods This association study employed a discovery cohort of 1643 individuals, a validation cohort of 2432 individuals for IS, and an extension cohort of 1476 individuals for ICH. Gene-set enrichment analysis (GSEA) was performed on all structural OXPHOS genes, as well as genes contributing to individual respiratory complexes. Gene-sets passing GSEA were tested by constructing genetic scores using common variants residing within each gene. Associations between each variant and IS that emerged in the discovery cohort were examined in validation and extension cohorts. Results IS was associated with genetic risk scores in OXPHOS as a whole (odds ratio (OR)=1.17, p=0.008) and Complex I (OR=1.06, p=0.050). Among IS subtypes, small vessel (SV) stroke showed association with OXPHOS (OR=1.16, p=0.007), Complex I (OR=1.13, p=0.027) and Complex IV (OR 1.14, p=0.018). To further explore this SV association, we extended our analysis to ICH, revealing association between deep hemispheric ICH and Complex IV (OR=1.08, p=0.008). Conclusions This pathway analysis demonstrates association between common genetic variants within OXPHOS genes and stroke. The associations for SV stroke and deep ICH suggest that genetic variation in OXPHOS influences small vessel pathobiology. Further studies are needed to identify culprit genetic variants and assess their functional consequences. PMID:23362085
Major prognostic role of Ki67 in localized adrenocortical carcinoma after complete resection.
Beuschlein, Felix; Weigel, Jens; Saeger, Wolfgang; Kroiss, Matthias; Wild, Vanessa; Daffara, Fulvia; Libé, Rosella; Ardito, Arianna; Al Ghuzlan, Abir; Quinkler, Marcus; Oßwald, Andrea; Ronchi, Cristina L; de Krijger, Ronald; Feelders, Richard A; Waldmann, Jens; Willenberg, Holger S; Deutschbein, Timo; Stell, Anthony; Reincke, Martin; Papotti, Mauro; Baudin, Eric; Tissier, Frédérique; Haak, Harm R; Loli, Paola; Terzolo, Massimo; Allolio, Bruno; Müller, Hans-Helge; Fassnacht, Martin
2015-03-01
Recurrence of adrenocortical carcinoma (ACC) even after complete (R0) resection occurs frequently. The aim of this study was to identify markers with prognostic value for patients in this clinical setting. From the German ACC registry, 319 patients with the European Network for the Study of Adrenal Tumors stage I-III were identified. As an independent validation cohort, 250 patients from three European countries were included. Clinical, histological, and immunohistochemical markers were correlated with recurrence-free (RFS) and overall survival (OS). Although univariable analysis within the German cohort suggested several factors with potential prognostic power, upon multivariable adjustment only a few including age, tumor size, venous tumor thrombus (VTT), and the proliferation marker Ki67 retained significance. Among these, Ki67 provided the single best prognostic value for RFS (hazard ratio [HR] for recurrence, 1.042 per 1% increase; P < .0001) and OS (HR for death, 1.051; P < .0001) which was confirmed in the validation cohort. Accordingly, clinical outcome differed significantly between patients with Ki67 <10%, 10-19%, and ≥20% (for the German cohort: median RFS, 53.2 vs 31.6 vs 9.4 mo; median OS, 180.5 vs 113.5 vs 42.0 mo). Using the combined cohort prognostic scores including tumor size, VTT, and Ki67 were established. Although these scores discriminated slightly better between subgroups, there was no clinically meaningful advantage in comparison with Ki67 alone. This largest study on prognostic markers in localized ACC identified Ki67 as the single most important factor predicting recurrence in patients following R0 resection. Thus, evaluation of Ki67 indices should be introduced as standard grading in all pathology reports of patients with ACC.
Scheinemann, Katrin; Grotzer, Michael; Kompis, Martin; Kuehni, Claudia E.
2017-01-01
Background Hearing loss is a potential late effect after childhood cancer. Questionnaires are often used to assess hearing in large cohorts of childhood cancer survivors and it is important to know if they can provide valid measures of hearing loss. We therefore assessed agreement and validity of questionnaire-reported hearing in childhood cancer survivors using medical records as reference. Procedure In this validation study, we studied 361 survivors of childhood cancer from the Swiss Childhood Cancer Survivor Study (SCCSS) who had been diagnosed after 1989 and had been exposed to ototoxic cancer treatment. Questionnaire-reported hearing was compared to the information in medical records. Hearing loss was defined as ≥ grade 1 according to the SIOP Boston Ototoxicity Scale. We assessed agreement and validity of questionnaire-reported hearing overall and stratified by questionnaire respondents (survivor or parent), sociodemographic characteristics, time between follow-up and questionnaire and severity of hearing loss. Results Questionnaire reports agreed with medical records in 85% of respondents (kappa 0.62), normal hearing was correctly assessed in 92% of those with normal hearing (n = 249), and hearing loss was correctly assessed in 69% of those with hearing loss (n = 112). Sensitivity of the questionnaires was 92%, 74%, and 39% for assessment of severe, moderate and mild bilateral hearing loss; and 50%, 33% and 10% for severe, moderate and mild unilateral hearing loss, respectively. Results did not differ by sociodemographic characteristics of the respondents, and survivor- and parent-reports were equally valid. Conclusions Questionnaires are a useful tool to assess hearing in large cohorts of childhood cancer survivors, but underestimate mild and unilateral hearing loss. Further research should investigate whether the addition of questions with higher sensitivity for mild degrees of hearing loss could improve the results. PMID:28333999
Validation of a computer case definition for sudden cardiac death in opioid users
2012-01-01
Background To facilitate the use of automated databases for studies of sudden cardiac death, we previously developed a computerized case definition that had a positive predictive value between 86% and 88%. However, the definition has not been specifically validated for prescription opioid users, for whom out-of-hospital overdose deaths may be difficult to distinguish from sudden cardiac death. Findings We assembled a cohort of persons 30-74 years of age prescribed propoxyphene or hydrocodone who had no life-threatening non-cardiovascular illness, diagnosed drug abuse, residence in a nursing home in the past year, or hospital stay within the past 30 days. Medical records were sought for a sample of 140 cohort deaths within 30 days of a prescription fill meeting the computer case definition. Of the 140 sampled deaths, 81 were adjudicated; 73 (90%) were sudden cardiac deaths. Two deaths had possible opioid overdose; after removing these two the positive predictive value was 88%. Conclusions These findings are consistent with our previous validation studies and suggest the computer case definition of sudden cardiac death is a useful tool for pharmacoepidemiologic studies of opioid analgesics. PMID:22938531
Crona, D J; Ramirez, J; Qiao, W; de Graan, A-J; Ratain, M J; van Schaik, R H N; Mathijssen, R H J; Rosner, G L; Innocenti, F
2016-02-01
The overall goal of this study was to provide evidence for the clinical validity of nine genetic variants in five genes previously associated with irinotecan neutropenia and pharmacokinetics. Variants associated with absolute neutrophil count (ANC) nadir and/or irinotecan pharmacokinetics in a discovery cohort of cancer patients were genotyped in an independent replication cohort of 108 cancer patients. Patients received single-agent irinotecan every 3 weeks. For ANC nadir, we replicated UGT1A1*28, UGT1A1*93 and SLCO1B1*1b in univariate analyses. For irinotecan area under the concentration-time curve (AUC0-24), we replicated ABCC2 -24C>T; however, ABCC2 -24C>T only predicted a small fraction of the variance. For SN-38 AUC0-24 and the glucuronidation ratio, we replicated UGT1A1*28 and UGT1A1*93. In addition to UGT1A1*28, this study independently validated UGT1A1*93 and SLCO1B1*1b as new predictors of irinotecan neutropenia. Further demonstration of their clinical utility will optimize irinotecan therapy in cancer patients.
Louis Simonet, Martine; Kossovsky, Michel P; Chopard, Pierre; Sigaud, Philippe; Perneger, Thomas V; Gaspoz, Jean-Michel
2008-01-01
Background Early identification of patients who need post-acute care (PAC) may improve discharge planning. The purposes of the study were to develop and validate a score predicting discharge to a post-acute care (PAC) facility and to determine its best assessment time. Methods We conducted a prospective study including 349 (derivation cohort) and 161 (validation cohort) consecutive patients in a general internal medicine service of a teaching hospital. We developed logistic regression models predicting discharge to a PAC facility, based on patient variables measured on admission (day 1) and on day 3. The value of each model was assessed by its area under the receiver operating characteristics curve (AUC). A simple numerical score was derived from the best model, and was validated in a separate cohort. Results Prediction of discharge to a PAC facility was as accurate on day 1 (AUC: 0.81) as on day 3 (AUC: 0.82). The day-3 model was more parsimonious, with 5 variables: patient's partner inability to provide home help (4 pts); inability to self-manage drug regimen (4 pts); number of active medical problems on admission (1 pt per problem); dependency in bathing (4 pts) and in transfers from bed to chair (4 pts) on day 3. A score ≥ 8 points predicted discharge to a PAC facility with a sensitivity of 87% and a specificity of 63%, and was significantly associated with inappropriate hospital days due to discharge delays. Internal and external validations confirmed these results. Conclusion A simple score computed on the 3rd hospital day predicted discharge to a PAC facility with good accuracy. A score > 8 points should prompt early discharge planning. PMID:18647410
Murphy, Malia S Q; Hawken, Steven; Atkinson, Katherine M; Milburn, Jennifer; Pervin, Jesmin; Gravett, Courtney; Stringer, Jeffrey S A; Rahman, Anisur; Lackritz, Eve; Chakraborty, Pranesh; Wilson, Kumanan
2017-01-01
Background Knowledge of gestational age (GA) is critical for guiding neonatal care and quantifying regional burdens of preterm birth. In settings where access to ultrasound dating is limited, postnatal estimates are frequently used despite the issues of accuracy associated with postnatal approaches. Newborn metabolic profiles are known to vary by severity of preterm birth. Recent work by our group and others has highlighted the accuracy of postnatal GA estimation algorithms derived from routinely collected newborn screening profiles. This protocol outlines the validation of a GA model originally developed in a North American cohort among international newborn cohorts. Methods Our primary objective is to use blood spot samples collected from infants born in Zambia and Bangladesh to evaluate our algorithm’s capacity to correctly classify GA within 1, 2, 3 and 4 weeks. Secondary objectives are to 1) determine the algorithm's accuracy in small-for-gestational-age and large-for-gestational-age infants, 2) determine its ability to correctly discriminate GA of newborns across dichotomous thresholds of preterm birth (≤34 weeks, <37 weeks GA) and 3) compare the relative performance of algorithms derived from newborn screening panels including all available analytes and those restricted to analyte subsets. The study population will consist of infants born to mothers already enrolled in one of two preterm birth cohorts in Lusaka, Zambia, and Matlab, Bangladesh. Dried blood spot samples will be collected and sent for analysis in Ontario, Canada, for model validation. Discussion This study will determine the validity of a GA estimation algorithm across ethnically diverse infant populations and assess population specific variations in newborn metabolic profiles. PMID:29104765
Impact of positive and negative lesion site remodeling on clinical outcomes: insights from PROSPECT.
Inaba, Shinji; Mintz, Gary S; Farhat, Naim Z; Fajadet, Jean; Dudek, Dariusz; Marzocchi, Antonio; Templin, Barry; Weisz, Giora; Xu, Ke; de Bruyne, Bernard; Serruys, Patrick W; Stone, Gregg W; Maehara, Akiko
2014-01-01
This study investigated coronary artery remodeling patterns associated with clinical outcomes. In the prospective, multicenter PROSPECT (Providing Regional Observations to Study Predictors of Events in the Coronary Tree: An Imaging Study in Patients With Unstable Atherosclerotic Lesions) study, reported predictors of nonculprit lesion (NCL) major adverse cardiac events (MACE) were an intravascular ultrasound (IVUS) minimal lumen area (MLA) ≤4 mm(2), a plaque burden ≥70%, and a IVUS-virtual histology (VH) thin-cap fibroatheroma (TCFA), but not lesion site remodeling. Overall, 697 consecutive patients with an acute coronary syndrome were enrolled and underwent 3-vessel gray-scale and IVUS-VH; 3,223 NCLs were identified by IVUS. The remodeling index (RI) was calculated as the external elastic membrane area at the MLA site divided by the average of the proximal and distal reference external elastic membrane areas. First, one third of the patients were randomly selected to determine RI cutoffs related to NCL MACE (development cohort). Receiver-operating characteristic analysis showed that there were 2 separate cut points that predicted NCL MACE: RI = 0.8789 and RI = 1.0046 (area under the curve = 0.663). These cut points were used to define negative remodeling as an RI <0.88, intermediate remodeling as an RI of 0.88 to 1.00, and positive remodeling as an RI >1.00. Second, we used the remaining two-thirds of patients to validate these cut points with respect to lesion morphology and clinical outcomes (validation cohort). Kaplan-Meier curve analysis in the validation cohort showed that NCL MACE occurred more frequent (and equally) in negative and positive remodeling lesions compared with intermediate remodeling lesions. In this cohort, negative remodeling lesions had the smallest MLA, positive remodeling lesions had the largest plaque burden, and VH TCFA, especially VH TCFA with multiple necrotic cores, was most common in negatively remodeling lesions. The present study showed the novel concept that positive and negative lesion site remodeling was associated with unanticipated NCL MACE in the PROSPECT study. ( An Imaging Study in Patients With Unstable Atherosclerotic Lesions [PROSPECT]; NCT00180466). Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Mills, Sarah D; Kwakkenbos, Linda; Carrier, Marie-Eve; Gholizadeh, Shadi; Fox, Rina S; Jewett, Lisa R; Gottesman, Karen; Roesch, Scott C; Thombs, Brett D; Malcarne, Vanessa L
2018-01-17
Systemic sclerosis (SSc) is an autoimmune disease that can cause disfiguring changes in appearance. This study examined the structural validity, internal consistency reliability, convergent validity, and measurement equivalence of the Social Appearance Anxiety Scale (SAAS) across SSc disease subtypes. Patients enrolled in the Scleroderma Patient-centered Intervention Network Cohort completed the SAAS and measures of appearance-related concerns and psychological distress. Confirmatory factor analysis (CFA) was used to examine the structural validity of the SAAS. Multiple-group CFA was used to determine if SAAS scores can be compared across patients with limited and diffuse disease subtypes. Cronbach's alpha was used to examine internal consistency reliability. Correlations of SAAS scores with measures of body image dissatisfaction, fear of negative evaluation, social anxiety, and depression were used to examine convergent validity. SAAS scores were hypothesized to be positively associated with all convergent validity measures, with correlations significant and moderate to large in size. A total of 938 patients with SSc were included. CFA supported a one-factor structure (CFI: .92; SRMR: .04; RMSEA: .08), and multiple-group CFA indicated that the scalar invariance model best fit the data. Internal consistency reliability was good in the total sample (α = .96) and in disease subgroups. Overall, evidence of convergent validity was found with measures of body image dissatisfaction, fear of negative evaluation, social anxiety, and depression. The SAAS can be reliably and validly used to assess fear of appearance evaluation in patients with SSc, and SAAS scores can be meaningfully compared across disease subtypes. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Genetic susceptibility for Alzheimer disease neuritic plaque pathology.
Shulman, Joshua M; Chen, Kewei; Keenan, Brendan T; Chibnik, Lori B; Fleisher, Adam; Thiyyagura, Pradeep; Roontiva, Auttawut; McCabe, Cristin; Patsopoulos, Nikolaos A; Corneveaux, Jason J; Yu, Lei; Huentelman, Matthew J; Evans, Denis A; Schneider, Julie A; Reiman, Eric M; De Jager, Philip L; Bennett, David A
2013-09-01
While numerous genetic susceptibility loci have been identified for clinical Alzheimer disease (AD), it is important to establish whether these variants are risk factors for the underlying disease pathology, including neuritic plaques. To investigate whether AD susceptibility loci from genome-wide association studies affect neuritic plaque pathology and to additionally identify novel risk loci for this trait. Candidate analysis of single-nucleotide polymorphisms and genome-wide association study in a joint clinicopathologic cohort, including 725 deceased subjects from the Religious Orders Study and the Rush Memory and Aging Project (2 prospective, community-based studies), followed by targeted validation in an independent neuroimaging cohort, including 114 subjects from multiple clinical and research centers. A quantitative measure of neuritic plaque pathologic burden, based on assessments of silver-stained tissue averaged from multiple brain regions. Validation based on β-amyloid load by immunocytochemistry, and replication with fibrillar β-amyloid positron emission tomographic imaging with Pittsburgh Compound B or florbetapir. Besides the previously reported APOE and CR1 loci, we found that the ABCA7 (rs3764650; P = .02) and CD2AP (rs9349407; P = .03) AD susceptibility loci are associated with neuritic plaque burden. In addition, among the top results of our genome-wide association study, we discovered a novel variant near the amyloid precursor protein gene (APP, rs2829887) that is associated with neuritic plaques (P = 3.3 × 10-6). This polymorphism was associated with postmortem β-amyloid load as well as fibrillar β-amyloid in 2 independent cohorts of adults with normal cognition. These findings enhance understanding of AD risk factors by relating validated susceptibility alleles to increased neuritic plaque pathology and implicate common genetic variation at the APP locus in the earliest, presymptomatic stages of AD.
The Bronchiectasis Severity Index. An International Derivation and Validation Study
Goeminne, Pieter; Aliberti, Stefano; McDonnell, Melissa J.; Lonni, Sara; Davidson, John; Poppelwell, Lucy; Salih, Waleed; Pesci, Alberto; Dupont, Lieven J.; Fardon, Thomas C.; De Soyza, Anthony; Hill, Adam T.
2014-01-01
Rationale: There are no risk stratification tools for morbidity and mortality in bronchiectasis. Identifying patients at risk of exacerbations, hospital admissions, and mortality is vital for future research. Objectives: This study describes the derivation and validation of the Bronchiectasis Severity Index (BSI). Methods: Derivation of the BSI used data from a prospective cohort study (Edinburgh, UK, 2008–2012) enrolling 608 patients. Cox proportional hazard regression was used to identify independent predictors of mortality and hospitalization over 4-year follow-up. The score was validated in independent cohorts from Dundee, UK (n = 218); Leuven, Belgium (n = 253); Monza, Italy (n = 105); and Newcastle, UK (n = 126). Measurements and Main Results: Independent predictors of future hospitalization were prior hospital admissions, Medical Research Council dyspnea score greater than or equal to 4, FEV1 < 30% predicted, Pseudomonas aeruginosa colonization, colonization with other pathogenic organisms, and three or more lobes involved on high-resolution computed tomography. Independent predictors of mortality were older age, low FEV1, lower body mass index, prior hospitalization, and three or more exacerbations in the year before the study. The derived BSI predicted mortality and hospitalization: area under the receiver operator characteristic curve (AUC) 0.80 (95% confidence interval, 0.74–0.86) for mortality and AUC 0.88 (95% confidence interval, 0.84–0.91) for hospitalization, respectively. There was a clear difference in exacerbation frequency and quality of life using the St. George’s Respiratory Questionnaire between patients classified as low, intermediate, and high risk by the score (P < 0.0001 for all comparisons). In the validation cohorts, the AUC for mortality ranged from 0.81 to 0.84 and for hospitalization from 0.80 to 0.88. Conclusions: The BSI is a useful clinical predictive tool that identifies patients at risk of future mortality, hospitalization, and exacerbations across healthcare systems. PMID:24328736
Huang, Yanqi; He, Lan; Dong, Di; Yang, Caiyun; Liang, Cuishan; Chen, Xin; Ma, Zelan; Huang, Xiaomei; Yao, Su; Liang, Changhong; Tian, Jie; Liu, Zaiyi
2018-02-01
To develop and validate a radiomics prediction model for individualized prediction of perineural invasion (PNI) in colorectal cancer (CRC). After computed tomography (CT) radiomics features extraction, a radiomics signature was constructed in derivation cohort (346 CRC patients). A prediction model was developed to integrate the radiomics signature and clinical candidate predictors [age, sex, tumor location, and carcinoembryonic antigen (CEA) level]. Apparent prediction performance was assessed. After internal validation, independent temporal validation (separate from the cohort used to build the model) was then conducted in 217 CRC patients. The final model was converted to an easy-to-use nomogram. The developed radiomics nomogram that integrated the radiomics signature and CEA level showed good calibration and discrimination performance [Harrell's concordance index (c-index): 0.817; 95% confidence interval (95% CI): 0.811-0.823]. Application of the nomogram in validation cohort gave a comparable calibration and discrimination (c-index: 0.803; 95% CI: 0.794-0.812). Integrating the radiomics signature and CEA level into a radiomics prediction model enables easy and effective risk assessment of PNI in CRC. This stratification of patients according to their PNI status may provide a basis for individualized auxiliary treatment.
Villodre, Celia; Rebasa, Pere; Estrada, José Luís; Zaragoza, Carmen; Zapater, Pedro; Mena, Luís; Lluís, Félix
2016-11-01
In a previous study, we found that Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) overpredicts morbidity risk in emergency gastrointestinal surgery. Our aim was to find a POSSUM equation adjustment. A prospective observational study was performed on 2,361 patients presenting with a community-acquired gastrointestinal surgical emergency. The first 1,000 surgeries constituted the development cohort, the second 1,000 events were the first validation intramural cohort, and the remaining 361 cases belonged to a second validation extramural cohort. (1) A modified POSSUM equation was obtained. (2) Logistic regression was used to yield a statistically significant equation that included age, hemoglobin, white cell count, sodium and operative severity. (3) A chi-square automatic interaction detector decision tree analysis yielded a statistically significant equation with 4 variables, namely cardiac failure, sodium, operative severity, and peritoneal soiling. A modified POSSUM equation and a simplified scoring system (aLicante sUrgical Community Emergencies New Tool for the enUmeration of Morbidities [LUCENTUM]) are described. Both tools significantly improve prediction of surgical morbidity in community-acquired gastrointestinal surgical emergencies. Copyright © 2016 Elsevier Inc. All rights reserved.
Liu, Xing; Ye, Yongkai; Mi, Qi; Huang, Wei; He, Ting; Huang, Pin; Xu, Nana; Wu, Qiaoyu; Wang, Anli; Li, Ying; Yuan, Hong
2016-01-01
Background Acute kidney injury (AKI) is a serious post-surgery complication; however, few preoperative risk models for AKI have been developed for hypertensive patients undergoing general surgery. Thus, in this study involving a large Chinese cohort, we developed and validated a risk model for surgery-related AKI using preoperative risk factors. Methods and Findings This retrospective cohort study included 24,451 hypertensive patients aged ≥18 years who underwent general surgery between 2007 and 2015. The endpoints for AKI classification utilized by the KDIGO (Kidney Disease: Improving Global Outcomes) system were assessed. The most discriminative predictor was selected using Fisher scores and was subsequently used to construct a stepwise multivariate logistic regression model, whose performance was evaluated via comparisons with models used in other published works using the net reclassification index (NRI) and integrated discrimination improvement (IDI) index. Results Surgery-related AKI developed in 1994 hospitalized patients (8.2%). The predictors identified by our Xiang-ya Model were age, gender, eGFR, NLR, pulmonary infection, prothrombin time, thrombin time, hemoglobin, uric acid, serum potassium, serum albumin, total cholesterol, and aspartate amino transferase. The area under the receiver-operating characteristic curve (AUC) for the validation set and cross validation set were 0.87 (95% CI 0.86–0.89) and (0.89; 95% CI 0.88–0.90), respectively, and was therefore similar to the AUC for the training set (0.89; 95% CI 0.88–0.90). The optimal cutoff value was 0.09. Our model outperformed that developed by Kate et al., which exhibited an NRI of 31.38% (95% CI 25.7%-37.1%) and an IDI of 8% (95% CI 5.52%-10.50%) for patients who underwent cardiac surgery (n = 2101). Conclusions/Significance We developed an AKI risk model based on preoperative risk factors and biomarkers that demonstrated good performance when predicting events in a large cohort of hypertensive patients who underwent general surgery. PMID:27802302
Savla, Jill J; Fisher, Brian T; Faerber, Jennifer A; Huang, Yuan-Shung V; Mercer-Rosa, Laura
2017-12-12
The surgical strategy for neonates with tetralogy of Fallot (TOF) consists of complete or staged repair. Assessing the comparative effectiveness of these approaches is facilitated by a large multicenter cohort. We propose a novel process for cohort assembly using the Pediatric Health Information System (PHIS), an administrative database that contains clinical and billing data for inpatient and emergency department stays from tertiary children's hospitals. A 4-step process was used to identify neonates with TOF: (1) screen neonates in PHIS with International Classification of Diseases-9 (ICD-9) diagnosis or procedure codes for TOF; (2) include patients with TOF procedures before 30 days of age; (3) exclude patients with missing 2-year follow-up data; (4) analyze patients' 2-year surgery sequence patterns, exclude patients inconsistent with a treatment strategy for TOF, and designate patients as complete or staged repair. Manual chart review at 1 PHIS center was performed to validate this process. Between January 2004 and March 2015, 5862 patients were identified in step 1. Step 2 of cohort assembly excluded 3425 patients (58%); step 3 excluded 148 patients (3%); and step 4 excluded 54 patients (1%). The final cohort consisted of 2235 neonates with TOF from 45 hospitals. Manual chart review of 336 patients showed a positive predictive value for accurate PHIS identification of 44% after step 1 and 97% after step 4. This systematic cohort identification algorithm resulted in a high positive predictive value to appropriately categorize patients. This carefully assembled cohort offers a unique opportunity for future studies in neonatal TOF outcomes.
Bedi, Pallavi; Chalmers, James D; Goeminne, Pieter C; Mai, Cindy; Saravanamuthu, Pira; Velu, Prasad Palani; Cartlidge, Manjit K; Loebinger, Michael R; Jacob, Joe; Kamal, Faisal; Schembri, Nicola; Aliberti, Stefano; Hill, Uta; Harrison, Mike; Johnson, Christopher; Screaton, Nicholas; Haworth, Charles; Polverino, Eva; Rosales, Edmundo; Torres, Antoni; Benegas, Michael N; Rossi, Adriano G; Patel, Dilip; Hill, Adam T
2018-05-01
The goal of this study was to develop a simplified radiological score that could assess clinical disease severity in bronchiectasis. The Bronchiectasis Radiologically Indexed CT Score (BRICS) was devised based on a multivariable analysis of the Bhalla score and its ability in predicting clinical parameters of severity. The score was then externally validated in six centers in 302 patients. A total of 184 high-resolution CT scans were scored for the validation cohort. In a multiple logistic regression model, disease severity markers significantly associated with the Bhalla score were percent predicted FEV 1 , sputum purulence, and exacerbations requiring hospital admission. Components of the Bhalla score that were significantly associated with the disease severity markers were bronchial dilatation and number of bronchopulmonary segments with emphysema. The BRICS was developed with these two parameters. The receiver operating-characteristic curve values for BRICS in the derivation cohort were 0.79 for percent predicted FEV 1 , 0.71 for sputum purulence, and 0.75 for hospital admissions per year; these values were 0.81, 0.70, and 0.70, respectively, in the validation cohort. Sputum free neutrophil elastase activity was significantly elevated in the group with emphysema on CT imaging. A simplified CT scoring system can be used as an adjunct to clinical parameters to predict disease severity in patients with idiopathic and postinfective bronchiectasis. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.
Determinants of breast-feeding in a Finnish birth cohort.
Erkkola, Maijaliisa; Salmenhaara, Maija; Kronberg-Kippilä, Carina; Ahonen, Suvi; Arkkola, Tuula; Uusitalo, Liisa; Pietinen, Pirjo; Veijola, Riitta; Knip, Mikael; Virtanen, Suvi M
2010-04-01
To assess milk feeding on the maternity ward and during infancy, and their relationship to sociodemographic determinants. The validity of our 3-month questionnaire in measuring hospital feeding was assessed. A prospective Finnish birth cohort with increased risk to type 1 diabetes recruited between 1996 and 2004. The families completed a follow-up form on the age at introduction of new foods and age-specific dietary questionnaires. Type 1 Diabetes Prediction and Prevention (DIPP) project, Finland. A cohort of 5993 children (77 % of those invited) participated in the main study, and 117 randomly selected infants in the validation study. Breast milk was the predominant milk on the maternity ward given to 99 % of the infants. Altogether, 80 % of the women recalled their child being fed supplementary milk (donated breast milk or infant formula) on the maternity ward. The median duration of exclusive breast-feeding was 1.4 months (range 0-8) and that of total breast-feeding 7.0 months (0-25). Additional milk feeding on the maternity ward, short parental education, maternal smoking during pregnancy, small gestational age and having no siblings were associated with a risk of short duration of both exclusive and total breast-feeding. In the validation study, 78 % of the milk types given on the maternity ward fell into the same category, according to the questionnaire and hospital records. The recommendations for infant feeding were not achieved. Infant feeding is strongly influenced by sociodemographic determinants and feeding practices on the maternity wards. Long-term breast-feeding may be supported by active promotion on the maternity ward.
de Laat, Joanne M; Tham, Emma; Pieterman, Carolina R C; Vriens, Menno R; Dorresteijn, Johannes A N; Bots, Michiel L; Nordenskjöld, Magnus; van der Luijt, Rob B; Valk, Gerlof D
2012-08-01
Endocrine diseases that can be part of the rare inheritable syndrome multiple endocrine neoplasia type 1 (MEN1) commonly occur in the general population. Patients at risk for MEN1, and consequently their families, must be identified to prevent morbidity through periodic screening for the detection and treatment of manifestations in an early stage. The aim of the study was to develop a model for predicting MEN1 in individual patients with sporadically occurring endocrine tumors. Cross-sectional study. In a nationwide study in The Netherlands, patients with sporadically occurring endocrine tumors in whom the referring physician suspected the MEN1 syndrome were identified between 1998 and 2011 (n=365). Logistic regression analysis with internal validation using bootstrapping and external validation with a cohort from Sweden was used. A MEN1 mutation was found in 15.9% of 365 patients. Recurrent primary hyperparathyroidism (pHPT; odds ratio (OR) 162.40); nonrecurrent pHPT (OR 25.78); pancreatic neuroendocrine tumors (pNETs) and duodenal NETs (OR 17.94); pituitary tumor (OR 4.71); NET of stomach, thymus, or bronchus (OR 25.84); positive family history of NET (OR 4.53); and age (OR 0.96) predicted MEN1. The c-statistic of the prediction model was 0.86 (95% confidence interval (95% CI) 0.81-0.90) in the derivation cohort and 0.77 (95% CI 0.66-0.88) in the validation cohort. With the prediction model, the risk of MEN1 can be calculated in patients suspected for MEN1 with sporadically occurring endocrine tumors.
Toledano, Mireille B; Auvinen, Anssi; Tettamanti, Giorgio; Cao, Yang; Feychting, Maria; Ahlbom, Anders; Fremling, Karin; Heinävaara, Sirpa; Kojo, Katja; Knowles, Gemma; Smith, Rachel B; Schüz, Joachim; Johansen, Christoffer; Poulsen, Aslak Harbo; Deltour, Isabelle; Vermeulen, Roel; Kromhout, Hans; Elliott, Paul; Hillert, Lena
2018-01-01
This study investigates validity of self-reported mobile phone use in a subset of 75 993 adults from the COSMOS cohort study. Agreement between self-reported and operator-derived mobile call frequency and duration for a 3-month period was assessed using Cohen's weighted Kappa (κ). Sensitivity and specificity of both self-reported high (≥10 calls/day or ≥4h/week) and low (≤6 calls/week or <30min/week) mobile phone use were calculated, as compared to operator data. For users of one mobile phone, agreement was fair for call frequency (κ=0.35, 95% CI: 0.35, 0.36) and moderate for call duration (κ=0.50, 95% CI: 0.49, 0.50). Self-reported low call frequency and duration demonstrated high sensitivity (87% and 76% respectively), but for high call frequency and duration sensitivity was lower (38% and 56% respectively), reflecting a tendency for greater underestimation than overestimation. Validity of self-reported mobile phone use was lower in women, younger age groups and those reporting symptoms during/shortly after using a mobile phone. This study highlights the ongoing value of using self-report data to measure mobile phone use. Furthermore, compared to continuous scale estimates used by previous studies, categorical response options used in COSMOS appear to improve validity considerably, most likely by preventing unrealistically high estimates from being reported. Copyright © 2017 Elsevier GmbH. All rights reserved.
Search Strategy to Identify Dental Survival Analysis Articles Indexed in MEDLINE.
Layton, Danielle M; Clarke, Michael
2016-01-01
Articles reporting survival outcomes (time-to-event outcomes) in patients over time are challenging to identify in the literature. Research shows the words authors use to describe their dental survival analyses vary, and that allocation of medical subject headings by MEDLINE indexers is inconsistent. Together, this undermines accurate article identification. The present study aims to develop and validate a search strategy to identify dental survival analyses indexed in MEDLINE (Ovid). A gold standard cohort of articles was identified to derive the search terms, and an independent gold standard cohort of articles was identified to test and validate the proposed search strategies. The first cohort included all 6,955 articles published in the 50 dental journals with the highest impact factors in 2008, of which 95 articles were dental survival articles. The second cohort included all 6,514 articles published in the 50 dental journals with the highest impact factors for 2012, of which 148 were dental survival articles. Each cohort was identified by a systematic hand search. Performance parameters of sensitivity, precision, and number needed to read (NNR) for the search strategies were calculated. Sensitive, precise, and optimized search strategies were developed and validated. The performances of the search strategy maximizing sensitivity were 92% sensitivity, 14% precision, and 7.11 NNR; the performances of the strategy maximizing precision were 93% precision, 10% sensitivity, and 1.07 NNR; and the performances of the strategy optimizing the balance between sensitivity and precision were 83% sensitivity, 24% precision, and 4.13 NNR. The methods used to identify search terms were objective, not subjective. The search strategies were validated in an independent group of articles that included different journals and different publication years. Across the three search strategies, dental survival articles can be identified with sensitivity up to 92%, precision up to 93%, and NNR of less than two articles to identify relevant records. This research has highlighted the impact that variation in reporting and indexing has on article identification and has improved researchers' ability to identify dental survival articles.
Gupta, Sumit; Nathan, Paul C; Baxter, Nancy N; Lau, Cindy; Daly, Corinne; Pole, Jason D
2018-06-01
Despite the importance of estimating population level cancer outcomes, most registries do not collect critical events such as relapse. Attempts to use health administrative data to identify these events have focused on older adults and have been mostly unsuccessful. We developed and tested administrative data-based algorithms in a population-based cohort of adolescents and young adults with cancer. We identified all Ontario adolescents and young adults 15-21 years old diagnosed with leukemia, lymphoma, sarcoma, or testicular cancer between 1992-2012. Chart abstraction determined the end of initial treatment (EOIT) date and subsequent cancer-related events (progression, relapse, second cancer). Linkage to population-based administrative databases identified fee and procedure codes indicating cancer treatment or palliative care. Algorithms determining EOIT based on a time interval free of treatment-associated codes, and new cancer-related events based on billing codes, were compared with chart-abstracted data. The cohort comprised 1404 patients. Time periods free of treatment-associated codes did not validly identify EOIT dates; using subsequent codes to identify new cancer events was thus associated with low sensitivity (56.2%). However, using administrative data codes that occurred after the EOIT date based on chart abstraction, the first cancer-related event was identified with excellent validity (sensitivity, 87.0%; specificity, 93.3%; positive predictive value, 81.5%; negative predictive value, 95.5%). Although administrative data alone did not validly identify cancer-related events, administrative data in combination with chart collected EOIT dates was associated with excellent validity. The collection of EOIT dates by cancer registries would significantly expand the potential of administrative data linkage to assess cancer outcomes.
West, Roianne; Mills, Kyly; Rowland, Dale; Creedy, Debra K
2018-05-01
Health professional graduates require the capacity to work safely, both clinically and culturally, when delivering care to Indigenous peoples worldwide. In the Australian context, the Aboriginal and Torres Strait Islander Health Curriculum Framework (The Framework) provides guidance for health professional programs to integrate, teach and assess Aboriginal and Torres Strait Islander peoples' (First Peoples) health content. There is, however, a lack of validated tools that measure the development of students' cultural capabilities. To validate the Cultural Capability Measurement Tool with a cohort of health professional students. A descriptive cohort design was used. All students (N = 753) enrolled in a discrete First Peoples Health course at an Australian university were invited to complete the Cultural Capability Measurement Tool. The tool was tested for reliability, content and construct validity using confirmatory factor analysis; and concurrent validity using and the Cultural Understanding Self-Assessment Tool. A sample of 418 (73% response rate) was recruited. Most participants were enrolled in the Bachelor of Nursing program (n = 369, 82%). The Cultural Capability Measurement Tool had a Cronbach's alpha coefficient of 0.86. A five-factor solution was confirmed which reflected the cultural capability domains and accounted for 51% of the variance. Scores correlated with students' cultural understanding (r = 0.28, p < 0.001). Successful implementation of The Framework requires instruments to measure changes in students' cultural capabilities. Measuring nursing students' cultural capabilities can inform their development, identify areas of strengths and deficits for educators, and will ultimately contribute to the development of a culturally safe nursing workforce. Copyright © 2018 Elsevier Ltd. All rights reserved.
Development and validation of a surgical-pathologic staging and scoring system for cervical cancer.
Li, Shuang; Li, Xiong; Zhang, Yuan; Zhou, Hang; Tang, Fangxu; Jia, Yao; Hu, Ting; Sun, Haiying; Yang, Ru; Chen, Yile; Cheng, Xiaodong; Lv, Weiguo; Wu, Li; Zhou, Jin; Wang, Shaoshuai; Huang, Kecheng; Wang, Lin; Yao, Yuan; Yang, Qifeng; Yang, Xingsheng; Zhang, Qinghua; Han, Xiaobing; Lin, Zhongqiu; Xing, Hui; Qu, Pengpeng; Cai, Hongbing; Song, Xiaojie; Tian, Xiaoyu; Shen, Jian; Xi, Ling; Li, Kezhen; Deng, Dongrui; Wang, Hui; Wang, Changyu; Wu, Mingfu; Zhu, Tao; Chen, Gang; Gao, Qinglei; Wang, Shixuan; Hu, Junbo; Kong, Beihua; Xie, Xing; Ma, Ding
2016-04-12
Most cervical cancer patients worldwide receive surgical treatments, and yet the current International Federation of Gynecology and Obstetrics (FIGO) staging system do not consider surgical-pathologic data. We propose a more comprehensive and prognostically valuable surgical-pathologic staging and scoring system (SPSs). Records from 4,220 eligible cervical cancer cases (Cohort 1) were screened for surgical-pathologic risk factors. We constructed a surgical-pathologic staging and SPSs, which was subsequently validated in a prospective study of 1,104 cervical cancer patients (Cohort 2). In Cohort 1, seven independent risk factors were associated with patient outcome: lymph node metastasis (LNM), parametrial involvement, histological type, grade, tumor size, stromal invasion, and lymph-vascular space invasion (LVSI). The FIGO staging system was revised and expanded into a surgical-pathologic staging system by including additional criteria of LNM, stromal invasion, and LVSI. LNM was subdivided into three categories based on number and location of metastases. Inclusion of all seven prognostic risk factors improves practical applicability. Patients were stratified into three SPSs risk categories: zero-, low-, and high-score with scores of 0, 1 to 3, and ≥4 (P=1.08E-45; P=6.15E-55). In Cohort 2, 5-year overall survival (OS) and disease-free survival (DFS) outcomes decreased with increased SPSs scores (P=9.04E-15; P=3.23E-16), validating the approach. Surgical-pathologic staging and SPSs show greater homogeneity and discriminatory utility than FIGO staging. Surgical-pathologic staging and SPSs improve characterization of tumor severity and disease invasion, which may more accurately predict outcome and guide postoperative therapy.
A sensitive NanoString-based assay to score STK11 (LKB1) pathway disruption in lung adenocarcinoma
Chen, Lu; Engel, Brienne E.; Welsh, Eric A.; Yoder, Sean J.; Brantley, Stephen G.; Chen, Dung-Tsa; Beg, Amer A.; Cao, Chunxia; Kaye, Frederic J.; Haura, Eric B.; Schabath, Matthew B.; Cress, W. Douglas
2016-01-01
Introduction Serine/threonine kinase 11 (STK11), better known as LKB1, is a tumor-suppressor commonly mutated in lung adenocarcinoma (LUAD). Previous work has shown that mutational inactivation of the STK11 pathway may serve as a predictive biomarker for cancer treatments including phenformin and COX-2 inhibition. Although immunohistochemistry and diagnostic sequencing are employed to measure STK11 pathway disruption, there are serious limitations to these methods emphasizing the importance to validate a clinically useful assay. Methods An initial STK11 mutation mRNA signature was generated using cell line data and refined using three large, independent patient databases. The signature was validated as a classifier using The Cancer Genome Anatomy Project (TCGA) LUAD cohort as well as a 442-patient LUAD cohort developed at Moffitt. Finally, the signature was adapted into a NanoString -based format and validated using RNA samples isolated from FFPE tissue blocks corresponding to a cohort of 150 LUAD patients. For comparison, STK11 immunochemistry was also performed. Results The STK11 signature was found to correlate with null mutations identified by exon sequencing in multiple cohorts using both microarray and NanoString formats. While there was a statistically significant correlation between reduced STK11 protein expression by IHC and mutation status, the NanoString-based assay showed superior overall performance with a −0.1588 improvement in area under the curve in receiver-operator characteristic curve analysis (p<0.012). Conclusion The described NanoString-based STK11 assay is a sensitive biomarker to study emerging therapeutic modalities in clinical trials. PMID:26917230
Person mobility in the design and analysis of cluster-randomized cohort prevention trials.
Vuchinich, Sam; Flay, Brian R; Aber, Lawrence; Bickman, Leonard
2012-06-01
Person mobility is an inescapable fact of life for most cluster-randomized (e.g., schools, hospitals, clinic, cities, state) cohort prevention trials. Mobility rates are an important substantive consideration in estimating the effects of an intervention. In cluster-randomized trials, mobility rates are often correlated with ethnicity, poverty and other variables associated with disparity. This raises the possibility that estimated intervention effects may generalize to only the least mobile segments of a population and, thus, create a threat to external validity. Such mobility can also create threats to the internal validity of conclusions from randomized trials. Researchers must decide how to deal with persons who leave study clusters during a trial (dropouts), persons and clusters that do not comply with an assigned intervention, and persons who enter clusters during a trial (late entrants), in addition to the persons who remain for the duration of a trial (stayers). Statistical techniques alone cannot solve the key issues of internal and external validity raised by the phenomenon of person mobility. This commentary presents a systematic, Campbellian-type analysis of person mobility in cluster-randomized cohort prevention trials. It describes four approaches for dealing with dropouts, late entrants and stayers with respect to data collection, analysis and generalizability. The questions at issue are: 1) From whom should data be collected at each wave of data collection? 2) Which cases should be included in the analyses of an intervention effect? and 3) To what populations can trial results be generalized? The conclusions lead to recommendations for the design and analysis of future cluster-randomized cohort prevention trials.
Obi, N; Waldmann, A; Babaev, V; Katalinic, A
2011-07-01
A precondition for the evaluation of outcomes in cohort studies and screening programmes is the availability of follow-up data. In Germany, established cancer registries provide such data for incident primary cancer diseases and mortality. To utilise these cancer registry data a person's identifying code has to be correctly linked to study or programme records, a procedure which, up to date, has been only rarely used in Germany. Exemplarily, the feasibility and validity of record linkage of a cohort of 173 050 patients from the Quality-assured Mamma Diagnostic programme (QuaMaDi) to the cancer registry Schleswig-Holstein was assessed by the accuracy of the classified outcome. Name, date of birth and address of the QuaMaDi cohort members were coded in the confidential administration center of the registry. These codes were passed by the codes of 129 455 female cancer registry records. Datasets were synchronised for each match, so that QuaMaDi participants could be identified in the registry file. In a next step epidemiological registry records were linked to the QuaMaDi study records. The accuracy of classifying outcome was assessed by agreement measures, i. e., Cohen's kappa. In cases of disagreement, a questionnaire has been sent to QuaMaDi patients' gynaecologists to validate the final diagnosis. Synchronisation of both cohorts resulted in 18 689 one to one matches with any kind of malignant tumour, therein 8 449 breast cancers (ICD-10 C50, D05). Absolute agreement between files according to diagnosed or suspected breast cancer was 97.6% with a kappa value of 0.79. When suspicious BIRADS 4 cases from QuaMaDi were excluded, agreement and kappa rose to 99.5% and 0.948, respectively. After correction of the final diagnosis according to the physician's responses, agreement measures slightly improved in both groups of ascertained diagnosis including and excluding the suspected cases. Within QuaMaDi the diagnosed breast cancer cases were predominantly notified in the cancer registry. Discordant matches (false negatives and false positives) may have resulted due to various causes, thereof a very low percentage of record linkages from different persons. In conclusion, synchronisation of study cohort files to registry files using pseudonymous personal data is feasible and valid. The generated combined datasets can be used for comparative analysis of several objectives. One of them will be the evaluation of screening programmes in the near future. © Georg Thieme Verlag KG Stuttgart · New York.
Validation of Robotic Surgery Simulator (RoSS).
Kesavadas, Thenkurussi; Stegemann, Andrew; Sathyaseelan, Gughan; Chowriappa, Ashirwad; Srimathveeravalli, Govindarajan; Seixas-Mikelus, Stéfanie; Chandrasekhar, Rameella; Wilding, Gregory; Guru, Khurshid
2011-01-01
Recent growth of daVinci Robotic Surgical System as a minimally invasive surgery tool has led to a call for better training of future surgeons. In this paper, a new virtual reality simulator, called RoSS is presented. Initial results from two studies - face and content validity, are very encouraging. 90% of the cohort of expert robotic surgeons felt that the simulator was excellent or somewhat close to the touch and feel of the daVinci console. Content validity of the simulator received 90% approval in some cases. These studies demonstrate that RoSS has the potential of becoming an important training tool for the daVinci surgical robot.
Wei, Caimiao; Gould, Rebekah; Yu, Xian; Zhang, Ya; Liu, Mei; Walls, Andrew; Bousamra, Alex; Ramineni, Maheshwari; Sinn, Bruno; Hunt, Kelly; Buchholz, Thomas A.; Valero, Vicente; Buzdar, Aman U.; Yang, Wei; Brewster, Abenaa M.; Moulder, Stacy; Pusztai, Lajos; Hatzis, Christos; Hortobagyi, Gabriel N.
2017-01-01
Purpose To determine the long-term prognosis in each phenotypic subset of breast cancer related to residual cancer burden (RCB) after neoadjuvant chemotherapy alone, or with concurrent human epidermal growth factor receptor 2 (HER2)–targeted treatment. Methods We conducted a pathologic review to measure the continuous RCB index (wherein pathologic complete response has RCB = 0; residual disease is categorized into three predefined classes of RCB index [RCB-I, RCB-II, and RCB-III]), and yp-stage of residual disease. Patients were prospectively observed for survival. Three patient cohorts received paclitaxel (T) followed by fluorouracil, doxorubicin, and cyclophosphamide (T/FAC): original development cohort (T/FAC-1), validation cohort (T/FAC-2), and independent validation cohort (T/FAC-3). Another validation cohort received FAC chemotherapy only, and a fifth cohort received concurrent trastuzumab (H) with sequential paclitaxel and fluorouracil, epirubicin, and cyclophosphamide (FEC; H+T/FEC). Phenotypic subsets were defined by hormone receptor (HR) and HER2 status at diagnosis, classified as HR-positive/HER2-negative, HER2-positive (HR-negative/HER2-positive or HR-positive/HER2-positive), or triple receptor–negative. Relapse-free survival estimates were determined from Kaplan-Meier analysis and compared using the log-rank test. Results Five cohorts (T/FAC-1 [n = 219], T/FAC-2 [n = 262], T/FAC-3 [n = 342], FAC [n = 132], and H+T/FEC [n = 203]) had median event-free follow-up of 13.5, 9.1, 6.8, 16.4, and 7.1 years, respectively. Continuous RCB index was prognostic within each phenotypic subset, independent of other clinical-pathologic variables. RCB classes stratified prognostic risk overall, within each phenotypic subset, and within yp-stage categories. Estimates of 10-year relapse-free survival rates in the four RCB classes (pathologic complete response, RCB-I, RCB-II, and RCB-III) were 86%, 81%, 55%, and 23% for triple receptor–negative; 83%, 97%, 74%, and 52% for HR-positive/HER2-negative in the combined T/FAC cohorts; and 95%, 77%, 47%, and 21% in the H+T/FEC cohort. Conclusion RCB was prognostic for long-term survival after neoadjuvant chemotherapy in all three phenotypic subsets of breast cancer. Our institutional findings should be externally validated. PMID:28135148
Validation of the Colorado Retinopathy of Prematurity Screening Model.
McCourt, Emily A; Ying, Gui-Shuang; Lynch, Anne M; Palestine, Alan G; Wagner, Brandie D; Wymore, Erica; Tomlinson, Lauren A; Binenbaum, Gil
2018-04-01
The Colorado Retinopathy of Prematurity (CO-ROP) model uses birth weight, gestational age, and weight gain at the first month of life (WG-28) to predict risk of severe retinopathy of prematurity (ROP). In previous validation studies, the model performed very well, predicting virtually all cases of severe ROP and potentially reducing the number of infants who need ROP examinations, warranting validation in a larger, more diverse population. To validate the performance of the CO-ROP model in a large multicenter cohort. This study is a secondary analysis of data from the Postnatal Growth and Retinopathy of Prematurity (G-ROP) Study, a retrospective multicenter cohort study conducted in 29 hospitals in the United States and Canada between January 2006 and June 2012 of 6351 premature infants who received ROP examinations. Sensitivity and specificity for severe (early treatment of ROP [ETROP] type 1 or 2) ROP, and reduction in infants receiving examinations. The CO-ROP model was applied to the infants in the G-ROP data set with all 3 data points (infants would have received examinations if they met all 3 criteria: birth weight, <1501 g; gestational age, <30 weeks; and WG-28, <650 g). Infants missing WG-28 information were included in a secondary analysis in which WG-28 was considered fewer than 650 g. Of 7438 infants in the G-ROP study, 3575 (48.1%) were girls, and maternal race/ethnicity was 2310 (31.1%) African American, 3615 (48.6%) white, 233 (3.1%) Asian, 40 (0.52%) American Indian/Alaskan Native, and 93 (1.3%) Pacific Islander. In the study cohort, 747 infants (11.8%) had type 1 or 2 ROP, 2068 (32.6%) had lower-grade ROP, and 3536 (55.6%) had no ROP. The CO-ROP model had a sensitivity of 96.9% (95% CI, 95.4%-97.9%) and a specificity of 40.9% (95% CI, 39.3%-42.5%). It missed 23 (3.1%) infants who developed severe ROP. The CO-ROP model would have reduced the number of infants who received examinations by 26.1% (95% CI, 25.0%-27.2%). The CO-ROP model demonstrated high but not 100% sensitivity for severe ROP and missed infants who might require treatment in this large validation cohort. The model requires all 3 criteria to be met to signal a need for examinations, but some infants with a birth weight or gestational age above the thresholds developed severe ROP. Most of these infants who were not detected by the CO-ROP model had obvious deviation in expected weight trajectories or nonphysiologic weight gain. These findings suggest that the CO-ROP model needs to be revised before considering implementation into clinical practice.
Wong, Vincent Wai-Sun; Petta, Salvatore; Hiriart, Jean-Baptiste; Cammà, Calogero; Wong, Grace Lai-Hung; Marra, Fabio; Vergniol, Julien; Chan, Anthony Wing-Hung; Tuttolomondo, Antonino; Merrouche, Wassil; Chan, Henry Lik-Yuen; Le Bail, Brigitte; Arena, Umberto; Craxì, Antonio; de Lédinghen, Victor
2017-09-01
Controlled attenuation parameter (CAP) can be performed together with liver stiffness measurement (LSM) by transient elastography (TE) and is often used to diagnose fatty liver. We aimed to define the validity criteria of CAP. CAP was measured by the M probe prior to liver biopsy in 754 consecutive patients with different liver diseases at three centers in Europe and Hong Kong (derivation cohort, n=340; validation cohort, n=414; 101 chronic hepatitis B, 154 chronic hepatitis C, 349 non-alcoholic fatty liver disease, 37 autoimmune hepatitis, 49 cholestatic liver disease, 64 others; 277 F3-4; age 52±14; body mass index 27.2±5.3kg/m 2 ). The primary outcome was the diagnosis of fatty liver, defined as steatosis involving ≥5% of hepatocytes. The area under the receiver-operating characteristics curve (AUROC) for CAP diagnosis of fatty liver was 0.85 (95% CI 0.82-0.88). The interquartile range (IQR) of CAP had a negative correlation with CAP (r=-0.32, p<0.001), suggesting the IQR-to-median ratio of CAP would be an inappropriate validity parameter. In the derivation cohort, the IQR of CAP was associated with the accuracy of CAP (AUROC 0.86, 0.89 and 0.76 in patients with IQR of CAP <20 [15% of patients], 20-39 [51%], and ≥40dB/m [33%], respectively). Likewise, the AUROC of CAP in the validation cohort was 0.90 and 0.77 in patients with IQR of CAP <40 and ≥40dB/m, respectively (p=0.004). The accuracy of CAP in detecting grade 2 and 3 steatosis was lower among patients with body mass index ≥30kg/m 2 and F3-4 fibrosis. The validity of CAP for the diagnosis of fatty liver is lower if the IQR of CAP is ≥40dB/m. Lay summary: Controlled attenuation parameter (CAP) is measured by transient elastography (TE) for the detection of fatty liver. In this large study, using liver biopsy as a reference, we show that the variability of CAP measurements based on its interquartile range can reflect the accuracy of fatty liver diagnosis. In contrast, other clinical factors such as adiposity and liver enzyme levels do not affect the performance of CAP. Copyright © 2017 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.
Harrison-Woolrych, Mira; Ashton, Janelle; Herbison, Peter
2010-07-01
The cardiovascular safety of sibutramine is currently under review by medicines regulatory authorities worldwide after the SCOUT (Sibutramine Cardiovascular Outcome Trial) showed an increased risk of cardiovascular events in patients taking sibutramine. Further data regarding the cardiovascular safety of sibutramine in a general population are now required. To quantify the risk of fatal and non-fatal cardiovascular adverse events in a general population prescribed sibutramine in postmarketing use. Observational prospective cohort study of patients dispensed sibutramine during a 3-year period (2001-4) and followed up for at least 1 year after their last prescription. The study included record-linkage to national mortality datasets to identify fatal events. Postmarketing 'real-life' use of sibutramine in a general population in New Zealand. All New Zealand patients dispensed a prescription for sibutramine in a 3-year period (for whom a National Health Identification number could be validated). 15 686 patients were included in the record linkage study for fatal events. A subgroup of 9471 patients was followed up by intensive methods for non-fatal events. (i) Rate of death from all causes and from cardiovascular events; and (ii) rates of non-fatal cardiovascular adverse events. Total exposure to sibutramine for 15 686 patients in the validated cohort was 5431 treatment-years. The rate of death from all causes in this cohort was 0.13 (95% CI 0.05, 0.27) per 100 treatment-years exposure. The rate of death from a cardiovascular event was 0.07 (95% CI 0.02, 0.19) per 100 treatment-years exposure. The most frequent non-fatal cardiovascular events in the intensively followed up cohort were hypertension, palpitations, hypotensive events and tachycardia. Risk of death from a cardiovascular event in this general population of patients prescribed sibutramine was lower than has been reported in other overweight/obese populations. The results of this study suggest that further evaluation of the benefit-risk profile of sibutramine is now required.
Subarachnoid hemorrhage admissions retrospectively identified using a prediction model
McIntyre, Lauralyn; Fergusson, Dean; Turgeon, Alexis; dos Santos, Marlise P.; Lum, Cheemun; Chassé, Michaël; Sinclair, John; Forster, Alan; van Walraven, Carl
2016-01-01
Objective: To create an accurate prediction model using variables collected in widely available health administrative data records to identify hospitalizations for primary subarachnoid hemorrhage (SAH). Methods: A previously established complete cohort of consecutive primary SAH patients was combined with a random sample of control hospitalizations. Chi-square recursive partitioning was used to derive and internally validate a model to predict the probability that a patient had primary SAH (due to aneurysm or arteriovenous malformation) using health administrative data. Results: A total of 10,322 hospitalizations with 631 having primary SAH (6.1%) were included in the study (5,122 derivation, 5,200 validation). In the validation patients, our recursive partitioning algorithm had a sensitivity of 96.5% (95% confidence interval [CI] 93.9–98.0), a specificity of 99.8% (95% CI 99.6–99.9), and a positive likelihood ratio of 483 (95% CI 254–879). In this population, patients meeting criteria for the algorithm had a probability of 45% of truly having primary SAH. Conclusions: Routinely collected health administrative data can be used to accurately identify hospitalized patients with a high probability of having a primary SAH. This algorithm may allow, upon validation, an easy and accurate method to create validated cohorts of primary SAH from either ruptured aneurysm or arteriovenous malformation. PMID:27629096
Bullich, Gemma; Trujillano, Daniel; Santín, Sheila; Ossowski, Stephan; Mendizábal, Santiago; Fraga, Gloria; Madrid, Álvaro; Ariceta, Gema; Ballarín, José; Torra, Roser; Estivill, Xavier; Ars, Elisabet
2015-09-01
Genetic diagnosis of steroid-resistant nephrotic syndrome (SRNS) using Sanger sequencing is complicated by the high genetic heterogeneity and phenotypic variability of this disease. We aimed to improve the genetic diagnosis of SRNS by simultaneously sequencing 26 glomerular genes using massive parallel sequencing and to study whether mutations in multiple genes increase disease severity. High-throughput mutation analysis was performed in 50 SRNS and/or focal segmental glomerulosclerosis (FSGS) patients, a validation cohort of 25 patients with known pathogenic mutations, and a discovery cohort of 25 uncharacterized patients with probable genetic etiology. In the validation cohort, we identified the 42 previously known pathogenic mutations across NPHS1, NPHS2, WT1, TRPC6, and INF2 genes. In the discovery cohort, disease-causing mutations in SRNS/FSGS genes were found in nine patients. We detected three patients with mutations in an SRNS/FSGS gene and COL4A3. Two of them were familial cases and presented a more severe phenotype than family members with mutation in only one gene. In conclusion, our results show that massive parallel sequencing is feasible and robust for genetic diagnosis of SRNS/FSGS. Our results indicate that patients carrying mutations in an SRNS/FSGS gene and also in COL4A3 gene have increased disease severity.
Establishment and Validation of GV-SAPS II Scoring System for Non-Diabetic Critically Ill Patients
Liu, Wen-Yue; Lin, Shi-Gang; Zhu, Gui-Qi; Poucke, Sven Van; Braddock, Martin; Zhang, Zhongheng; Mao, Zhi; Shen, Fei-Xia
2016-01-01
Background and Aims Recently, glucose variability (GV) has been reported as an independent risk factor for mortality in non-diabetic critically ill patients. However, GV is not incorporated in any severity scoring system for critically ill patients currently. The aim of this study was to establish and validate a modified Simplified Acute Physiology Score II scoring system (SAPS II), integrated with GV parameters and named GV-SAPS II, specifically for non-diabetic critically ill patients to predict short-term and long-term mortality. Methods Training and validation cohorts were exacted from the Multiparameter Intelligent Monitoring in Intensive Care database III version 1.3 (MIMIC-III v1.3). The GV-SAPS II score was constructed by Cox proportional hazard regression analysis and compared with the original SAPS II, Sepsis-related Organ Failure Assessment Score (SOFA) and Elixhauser scoring systems using area under the curve of the receiver operator characteristic (auROC) curve. Results 4,895 and 5,048 eligible individuals were included in the training and validation cohorts, respectively. The GV-SAPS II score was established with four independent risk factors, including hyperglycemia, hypoglycemia, standard deviation of blood glucose levels (GluSD), and SAPS II score. In the validation cohort, the auROC values of the new scoring system were 0.824 (95% CI: 0.813–0.834, P< 0.001) and 0.738 (95% CI: 0.725–0.750, P< 0.001), respectively for 30 days and 9 months, which were significantly higher than other models used in our study (all P < 0.001). Moreover, Kaplan-Meier plots demonstrated significantly worse outcomes in higher GV-SAPS II score groups both for 30-day and 9-month mortality endpoints (all P< 0.001). Conclusions We established and validated a modified prognostic scoring system that integrated glucose variability for non-diabetic critically ill patients, named GV-SAPS II. It demonstrated a superior prognostic capability and may be an optimal scoring system for prognostic evaluation in this patient group. PMID:27824941
Knudsen, Vibeke K; Hatch, Elizabeth E; Cueto, Heidi; Tucker, Katherine L; Wise, Lauren; Christensen, Tue; Mikkelsen, Ellen M
2016-04-01
To assess the relative validity of a semi-quantitative, web-based FFQ completed by female pregnancy planners in the Danish 'Snart Forældre' study. We validated a web-based FFQ based on the FFQ used in the Danish National Birth Cohort against a 4 d food diary (FD) and assessed the relative validity of intakes of foods and nutrients. We compared means and medians of intakes, and calculated Pearson correlation coefficients and de-attenuated coefficients to assess agreement between the two methods. We also calculated the proportion correctly classified based on the same or adjacent quintile of intake and the proportion of grossly misclassified (extreme quintiles). Participants (n 128) in the 'Snart Forældre' study who had completed the web-based FFQ were invited to participate in the validation study. Participants in the 'Snart Forældre' study, in total ninety-seven women aged 20-42 years. Reported intakes of dairy products, vegetables and potatoes were higher in the FFQ compared with the FD, whereas reported intakes of fruit, meat, sugar and beverages were lower in the FFQ than in the FD. Overall the de-attenuated correlation coefficients were acceptable, ranging from 0·33 for energy to 0·93 for vitamin D. The majority of the women were classified in the same or adjacent quintile and few women were misclassified (extreme quintiles). The web-based FFQ performs well for ranking women of reproductive age according to high or low intake of foods and nutrients and, thus, provides a solid basis for investigating associations between diet and fertility.
Duan, Jun; Han, Xiaoli; Bai, Linfu; Zhou, Lintong; Huang, Shicong
2017-02-01
To develop and validate a scale using variables easily obtained at the bedside for prediction of failure of noninvasive ventilation (NIV) in hypoxemic patients. The test cohort comprised 449 patients with hypoxemia who were receiving NIV. This cohort was used to develop a scale that considers heart rate, acidosis, consciousness, oxygenation, and respiratory rate (referred to as the HACOR scale) to predict NIV failure, defined as need for intubation after NIV intervention. The highest possible score was 25 points. To validate the scale, a separate group of 358 hypoxemic patients were enrolled in the validation cohort. The failure rate of NIV was 47.8 and 39.4% in the test and validation cohorts, respectively. In the test cohort, patients with NIV failure had higher HACOR scores at initiation and after 1, 12, 24, and 48 h of NIV than those with successful NIV. At 1 h of NIV the area under the receiver operating characteristic curve was 0.88, showing good predictive power for NIV failure. Using 5 points as the cutoff value, the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for NIV failure were 72.6, 90.2, 87.2, 78.1, and 81.8%, respectively. These results were confirmed in the validation cohort. Moreover, the diagnostic accuracy for NIV failure exceeded 80% in subgroups classified by diagnosis, age, or disease severity and also at 1, 12, 24, and 48 h of NIV. Among patients with NIV failure with a HACOR score of >5 at 1 h of NIV, hospital mortality was lower in those who received intubation at ≤12 h of NIV than in those intubated later [58/88 (66%) vs. 138/175 (79%); p = 0.03). The HACOR scale variables are easily obtained at the bedside. The scale appears to be an effective way of predicting NIV failure in hypoxemic patients. Early intubation in high-risk patients may reduce hospital mortality.
Crook, Julia E.; Thomas, Colleen S.; Siersema, Peter D.; Rex, Douglas K.; Wallace, Michael B.
2017-01-01
Objective The adenoma detection rate (ADR) varies widely between physicians, possibly due to patient population differences, hampering direct ADR comparison. We developed and validated a prediction model for adenoma detection in an effort to determine if physicians’ ADRs should be adjusted for patient-related factors. Materials and methods Screening and surveillance colonoscopy data from the cross-sectional multicenter cluster-randomized Endoscopic Quality Improvement Program-3 (EQUIP-3) study (NCT02325635) was used. The dataset was split into two cohorts based on center. A prediction model for detection of ≥1 adenoma was developed using multivariable logistic regression and subsequently internally (bootstrap resampling) and geographically validated. We compared predicted to observed ADRs. Results The derivation (5 centers, 35 physicians, overall-ADR: 36%) and validation (4 centers, 31 physicians, overall-ADR: 40%) cohort included respectively 9934 and 10034 patients (both cohorts: 48% male, median age 60 years). Independent predictors for detection of ≥1 adenoma were: age (optimism-corrected odds ratio (OR): 1.02; 95%-confidence interval (CI): 1.02–1.03), male sex (OR: 1.73; 95%-CI: 1.60–1.88), body mass index (OR: 1.02; 95%-CI: 1.01–1.03), American Society of Anesthesiology physical status class (OR class II vs. I: 1.29; 95%-CI: 1.17–1.43, OR class ≥III vs. I: 1.57; 95%-CI: 1.32–1.86), surveillance versus screening (OR: 1.39; 95%-CI: 1.27–1.53), and Hispanic or Latino ethnicity (OR: 1.13; 95%-CI: 1.00–1.27). The model’s discriminative ability was modest (C-statistic in the derivation: 0.63 and validation cohort: 0.60). The observed ADR was considerably lower than predicted for 12/66 (18.2%) physicians and 2/9 (22.2%) centers, and considerably higher than predicted for 18/66 (27.3%) physicians and 4/9 (44.4%) centers. Conclusion The substantial variation in ADRs could only partially be explained by patient-related factors. These data suggest that ADR variation could likely also be due to other factors, e.g. physician or technical issues. PMID:28957445
Longitudinal construct validity of the minimum data set health status index.
Jones, Aaron; Feeny, David; Costa, Andrew P
2018-05-24
The Minimum Data Set Health Status Index (MDS-HSI) is a generic, preference-based health-related quality of life (HRQOL) measure derived by mapping items from the Resident Assessment Instrument - Minimum Data Set (RAI-MDS) assessment onto the Health Utilities Index Mark 2 classification system. While the validity of the MDS-HSI has been examined in cross-sectional settings, the longitudinal validity has not been explored. The objective of this study was to investigate the longitudinal construct validity of the MDS-HSI in a home care population. This study utilized a retrospective cohort of home care patients in the Hamilton-Niagara-Haldimand-Brant health region of Ontario, Canada with at least two RAI-MDS Home Care assessments between January 2010 and December 2014. Convergent validity was assessed by calculating Spearman rank correlations between the change in MDS-HSI and changes in six validated indices of health domains that can be calculated from the RAI-MDS assessment. Known-groups validity was investigated by fitting multivariable linear regression models to estimate the mean change in MDS-HSI associated with clinically important changes in the six health domain indices and 15 disease symptoms from the RAI-MDS Home Care assessment, controlling for age and sex. The cohort contained 25,182 patients with two RAI-MDS Home Care assessments. Spearman correlations between the MDS-HSI change and changes in the health domain indices were all statistically significant and in the hypothesized small to moderate range [0.1 < ρ < 0.5]. Clinically important changes in all of the health domain indices and 13 of the 15 disease symptoms were significantly associated with clinically important changes in the MDS-HSI. The findings of this study support the longitudinal construct validity of the MDS-HSI in home care populations. In addition to evaluating changes in HRQOL among home care patients in clinical research, economic evaluation, and health technology assessment, the MDS-HSI may be used in system-level applications using routinely collected population-level data.
Multicenter validation of a bedside antisaccade task as a measure of executive function
Hellmuth, J.; Mirsky, J.; Heuer, H.W.; Matlin, A.; Jafari, A.; Garbutt, S.; Widmeyer, M.; Berhel, A.; Sinha, L.; Miller, B.L.; Kramer, J.H.
2012-01-01
Objective: To create and validate a simple, standardized version of the antisaccade (AS) task that requires no specialized equipment for use as a measure of executive function in multicenter clinical studies. Methods: The bedside AS (BAS) task consisted of 40 pseudorandomized AS trials presented on a laptop computer. BAS performance was compared with AS performance measured using an infrared eye tracker in normal elders (NE) and individuals with mild cognitive impairment (MCI) or dementia (n = 33). The neuropsychological domain specificity of the BAS was then determined in a cohort of NE, MCI, and dementia (n = 103) at UCSF, and the BAS was validated as a measure of executive function in a 6-center cohort (n = 397) of normal adults and patients with a variety of brain diseases. Results: Performance on the BAS and laboratory AS task was strongly correlated and BAS performance was most strongly associated with neuropsychological measures of executive function. Even after controlling for disease severity and processing speed, BAS performance was associated with multiple assessments of executive function, most strongly the informant-based Frontal Systems Behavior Scale. Conclusions: The BAS is a simple, valid measure of executive function in aging and neurologic disease. PMID:22573640
Proposal and validation of a new model to estimate survival for hepatocellular carcinoma patients.
Liu, Po-Hong; Hsu, Chia-Yang; Hsia, Cheng-Yuan; Lee, Yun-Hsuan; Huang, Yi-Hsiang; Su, Chien-Wei; Lee, Fa-Yauh; Lin, Han-Chieh; Huo, Teh-Ia
2016-08-01
The survival of hepatocellular carcinoma (HCC) patients is heterogeneous. We aim to develop and validate a simple prognostic model to estimate survival for HCC patients (MESH score). A total of 3182 patients were randomised into derivation and validation cohort. Multivariate analysis was used to identify independent predictors of survival in the derivation cohort. The validation cohort was employed to examine the prognostic capabilities. The MESH score allocated 1 point for each of the following parameters: large tumour (beyond Milan criteria), presence of vascular invasion or metastasis, Child-Turcotte-Pugh score ≥6, performance status ≥2, serum alpha-fetoprotein level ≥20 ng/ml, and serum alkaline phosphatase ≥200 IU/L, with a maximal of 6 points. In the validation cohort, significant survival differences were found across all MESH scores from 0 to 6 (all p < 0.01). The MESH system was associated with the highest homogeneity and lowest corrected Akaike information criterion compared with Barcelona Clínic Liver Cancer, Hong Kong Liver Cancer (HKLC), Cancer of the Liver Italian Program, Taipei Integrated Scoring and model to estimate survival in ambulatory HCC Patients systems. The prognostic accuracy of the MESH scores remained constant in patients with hepatitis B- or hepatitis C-related HCC. The MESH score can also discriminate survival for patients from early to advanced stages of HCC. This newly proposed simple and accurate survival model provides enhanced prognostic accuracy for HCC. The MESH system is a useful supplement to the BCLC and HKLC classification schemes in refining treatment strategies. Copyright © 2016 Elsevier Ltd. All rights reserved.
Echevarria, C; Steer, J; Heslop-Marshall, K; Stenton, S C; Hughes, R; Wijesinghe, M; Harrison, R N; Steen, N; Simpson, A J; Gibson, G J; Bourke, S C
2017-01-01
Background One in three patients hospitalised due to acute exacerbation of COPD (AECOPD) is readmitted within 90 days. No tool has been developed specifically in this population to predict readmission or death. Clinicians are unable to identify patients at particular risk, yet resources to prevent readmission are allocated based on clinical judgement. Methods In participating hospitals, consecutive admissions of patients with AECOPD were identified by screening wards and reviewing coding records. A tool to predict 90-day readmission or death without readmission was developed in two hospitals (the derivation cohort) and validated in: (a) the same hospitals at a later timeframe (internal validation cohort) and (b) four further UK hospitals (external validation cohort). Performance was compared with ADO, BODEX, CODEX, DOSE and LACE scores. Results Of 2417 patients, 936 were readmitted or died within 90 days of discharge. The five independent variables in the final model were: Previous admissions, eMRCD score, Age, Right-sided heart failure and Left-sided heart failure (PEARL). The PEARL score was consistently discriminative and accurate with a c-statistic of 0.73, 0.68 and 0.70 in the derivation, internal validation and external validation cohorts. Higher PEARL scores were associated with a shorter time to readmission. Conclusions The PEARL score is a simple tool that can effectively stratify patients' risk of 90-day readmission or death, which could help guide readmission avoidance strategies within the clinical and research setting. It is superior to other scores that have been used in this population. Trial registration number UKCRN ID 14214. PMID:28235886
SMA-MAP: a plasma protein panel for spinal muscular atrophy.
Kobayashi, Dione T; Shi, Jing; Stephen, Laurie; Ballard, Karri L; Dewey, Ruth; Mapes, James; Chung, Brett; McCarthy, Kathleen; Swoboda, Kathryn J; Crawford, Thomas O; Li, Rebecca; Plasterer, Thomas; Joyce, Cynthia; Chung, Wendy K; Kaufmann, Petra; Darras, Basil T; Finkel, Richard S; Sproule, Douglas M; Martens, William B; McDermott, Michael P; De Vivo, Darryl C; Walker, Michael G; Chen, Karen S
2013-01-01
Spinal Muscular Atrophy (SMA) presents challenges in (i) monitoring disease activity and predicting progression, (ii) designing trials that allow rapid assessment of candidate therapies, and (iii) understanding molecular causes and consequences of the disease. Validated biomarkers of SMA motor and non-motor function would offer utility in addressing these challenges. Our objectives were (i) to discover additional markers from the Biomarkers for SMA (BforSMA) study using an immunoassay platform, and (ii) to validate the putative biomarkers in an independent cohort of SMA patients collected from a multi-site natural history study (NHS). BforSMA study plasma samples (N = 129) were analyzed by immunoassay to identify new analytes correlating to SMA motor function. These immunoassays included the strongest candidate biomarkers identified previously by chromatography. We selected 35 biomarkers to validate in an independent cohort SMA type 1, 2, and 3 samples (N = 158) from an SMA NHS. The putative biomarkers were tested for association to multiple motor scales and to pulmonary function, neurophysiology, strength, and quality of life measures. We implemented a Tobit model to predict SMA motor function scores. 12 of the 35 putative SMA biomarkers were significantly associated (p<0.05) with motor function, with a 13(th) analyte being nearly significant. Several other analytes associated with non-motor SMA outcome measures. From these 35 biomarkers, 27 analytes were selected for inclusion in a commercial panel (SMA-MAP) for association with motor and other functional measures. Discovery and validation using independent cohorts yielded a set of SMA biomarkers significantly associated with motor function and other measures of SMA disease activity. A commercial SMA-MAP biomarker panel was generated for further testing in other SMA collections and interventional trials. Future work includes evaluating the panel in other neuromuscular diseases, for pharmacodynamic responsiveness to experimental SMA therapies, and for predicting functional changes over time in SMA patients.
Genetic risk profiles for a childhood with severe overweight.
González, J R; Estévez, M N; Giralt, P S; Cáceres, A; Pérez, L M L; González-Carpio, M; Ballester, F; Sunyer, J; Rodríguez-López, R
2014-08-01
The objective of this study was the description of a valid genetic risk score (GRS) to predict individuals with high susceptibility to childhood overweight by their genetic profiles. Case-control study including a group of children with high-risk familial predisposition to morbid obesity. Birth cohort from general population constituted the validation sample. For the discovery sample, 218 children with non-syndromic obesity and 190 control individuals were included. The validation sample was 653 children from two birth cohorts belonging to the INMA (Infancia y Medio Ambiente [Environment and Childhood] )project. 109 SNPs located in the genes FTO, SEC16B, BDNF, ETV5, SH2B1, GNPDA2, LYPLAL1, MSRA, TFAP2, KCTD15, MTCH2 and NEGR1, previously reported in association to body mass index (BMI) were analysed. For the validation sample, association between genome-wide data and BMI measurements between 3.5 and 5 years of age, were evaluated. The GRS includes six SNPs in the genes FTO, TFAP2B, SEC16B, ETV5 and SH2B1. The score distribution differs among cases and controls (P = 9.2 × 10(-14) ) showing a significant linear association with obesity (odds ratio [OR] per allele = 1.69; confidence interval [CI] 95% = 1.46-1.97; P = 4.3 × 10(-1) and area under the receiver operating characteristic curve [AUC] = 0.727; CI 95% = 0.676-0.778). The results were validated by the INMA cohort (OR per allele = 1.23 CI 95% = 1.03-1.48 and AUC = 0.601 CI 95% = 0.522-0.680). The use of our proposed genetic score provides useful information to determine those children who are susceptible to obesity. To improve the efficiency of clinical prevention and treatment of obesity, it is essential to design individualized based protocols in advance knowledge of the molecular basis of inherited susceptibility. © 2013 The Authors. Pediatric Obesity © 2013 International Association for the Study of Obesity.
Gil, Víctor; Miró, Òscar; Schull, Michael J; Llorens, Pere; Herrero-Puente, Pablo; Jacob, Javier; Ríos, José; Lee, Douglas S; Martín-Sánchez, Francisco J
2018-06-01
The Emergency Heart Failure Mortality Risk Grade (EHMRG) scale, derived in 86 Canadian emergency departments (EDs), stratifies patients with acute-decompensated heart failure (ADHF) according to their 7-day mortality risk. We evaluated its external validity in a Spanish cohort. We applied the EHMRG scale to ADHF patients consecutively included in the Epidemiology of Acute Heart Failure in Emergency departments (EAHFE) registry (29 Spanish EDs) and measured its performance. Patients were distributed into quintiles according to the original and their self-defined score cutoffs. The 7-day mortality rates were compared internally among different categories and with categories of Canadian cohorts. The EAHFE group [n: 1553 patients; 80 (10) years; 55.6% women] had a 5.5% 7-day mortality rate and the EHMRG scale c-statistic was 0.741 (95% confidence interval: 0.688-0.793) compared with 0.807 (0.761-0.842) and 0.804 (0.763-0.840) obtained in the Canadian derivation and validation cohorts. The mortality rate of the EAHFE group mortality increased progressively as the quintile categories increased using intervals defined by either the Canadian or the Spanish EHMRG score cutoffs, although with more regular increments with the EAHFE-defined intervals; using the latter, patients at quintiles 2, 3, 4, 5a and 5b had (compared with quintile 1) odds ratios of 1.77, 3.36, 4.44, 9.39 and 16.19, respectively. The EHMRG scale stratified risk in an ADHF cohort that included both palliative and nonpalliative patients in Spanish EDs, showing an extrapolation to a higher mortality risk cohort than the original derivation sample. Stratification improved when the score was recalibrated in the Spanish cohort.
Two risk score models for predicting incident Type 2 diabetes in Japan.
Doi, Y; Ninomiya, T; Hata, J; Hirakawa, Y; Mukai, N; Iwase, M; Kiyohara, Y
2012-01-01
Risk scoring methods are effective for identifying persons at high risk of Type 2 diabetes mellitus, but such approaches have not yet been established in Japan. A total of 1935 subjects of a derivation cohort were followed up for 14 years from 1988 and 1147 subjects of a validation cohort independent of the derivation cohort were followed up for 5 years from 2002. Risk scores were estimated based on the coefficients (β) of Cox proportional hazards model in the derivation cohort and were verified in the validation cohort. In the derivation cohort, the non-invasive risk model was established using significant risk factors; namely, age, sex, family history of diabetes, abdominal circumference, body mass index, hypertension, regular exercise and current smoking. We also created another scoring risk model by adding fasting plasma glucose levels to the non-invasive model (plus-fasting plasma glucose model). The area under the curve of the non-invasive model was 0.700 and it increased significantly to 0.772 (P < 0.001) in the plus-fasting plasma glucose model. The ability of the non-invasive model to predict Type 2 diabetes was comparable with that of impaired glucose tolerance, and the plus-fasting plasma glucose model was superior to it. The cumulative incidence of Type 2 diabetes was significantly increased with elevating quintiles of the sum scores of both models in the validation cohort (P for trend < 0.001). We developed two practical risk score models for easily identifying individuals at high risk of incident Type 2 diabetes without an oral glucose tolerance test in the Japanese population. © 2011 The Authors. Diabetic Medicine © 2011 Diabetes UK.
Zhang, Chuanwu; Garrard, Lili; Keighley, John; Carlson, Susan; Gajewski, Byron
2017-01-10
Despite the widely recognized association between the severity of early preterm birth (ePTB) and its related severe diseases, little is known about the potential risk factors of ePTB and the sub-population with high risk of ePTB. Moreover, motivated by a future confirmatory clinical trial to identify whether supplementing pregnant women with docosahexaenoic acid (DHA) has a different effect on the risk subgroup population or not in terms of ePTB prevalence, this study aims to identify potential risk subgroups and risk factors for ePTB, defined as babies born less than 34 weeks of gestation. The analysis data (N = 3,994,872) were obtained from CDC and NCHS' 2014 Natality public data file. The sample was split into independent training and validation cohorts for model generation and model assessment, respectively. Logistic regression and CART models were used to examine potential ePTB risk predictors and their interactions, including mothers' age, nativity, race, Hispanic origin, marital status, education, pre-pregnancy smoking status, pre-pregnancy BMI, pre-pregnancy diabetes status, pre-pregnancy hypertension status, previous preterm birth status, infertility treatment usage status, fertility enhancing drug usage status, and delivery payment source. Both logistic regression models with either 14 or 10 ePTB risk factors produced the same C-index (0.646) based on the training cohort. The C-index of the logistic regression model based on 10 predictors was 0.645 for the validation cohort. Both C-indexes indicated a good discrimination and acceptable model fit. The CART model identified preterm birth history and race as the most important risk factors, and revealed that the subgroup with a preterm birth history and a race designation as Black had the highest risk for ePTB. The c-index and misclassification rate were 0.579 and 0.034 for the training cohort, and 0.578 and 0.034 for the validation cohort, respectively. This study revealed 14 maternal characteristic variables that reliably identified risk for ePTB through either logistic regression model and/or a CART model. Moreover, both models efficiently identify risk subgroups for further enrichment clinical trial design.
McLernon, David J; Dillon, John F; Sullivan, Frank M; Roderick, Paul; Rosenberg, William M; Ryder, Stephen D; Donnan, Peter T
2012-01-01
Although liver function tests (LFTs) are routinely measured in primary care, raised levels in patients with no obvious liver disease may trigger a range of subsequent expensive and unnecessary management plans. The aim of this study was to develop and validate a prediction model to guide decision-making by general practitioners, which estimates risk of one year all-cause mortality in patients with no obvious liver disease. In this population-based historical cohort study, biochemistry data from patients in Tayside, Scotland, with LFTs performed in primary care were record-linked to secondary care and prescription databases to ascertain baseline characteristics, and to mortality data. Using this derivation cohort a survival model was developed to predict mortality. The model was assessed for calibration, discrimination (using the C-statistic) and performance, and validated using a separate cohort of Scottish primary care practices. From the derivation cohort (n = 95 977), 2.7% died within one year. Predictors of mortality included: age; male gender; social deprivation; history of cancer, renal disease, stroke, ischaemic heart disease or respiratory disease; statin use; and LFTs (albumin, transaminase, alkaline phosphatase, bilirubin, and gamma-glutamyltransferase). The C-statistic for the final model was 0.82 (95% CI 0.80-0.84), and was similar in the validation cohort (n = 11 653) 0.86 (0.79-0.90). As an example of performance, for a 10% predicted probability cut-off, sensitivity = 52.8%, specificity = 94.0%, PPV = 21.0%, NPV = 98.5%. For the model without LFTs the respective values were 43.8%, 92.8%, 15.6%, 98.1%. The Algorithm for Liver Function Investigations (ALFI) is the first model to successfully estimate the probability of all-cause mortality in patients with no apparent liver disease having LFTs in primary care. While LFTs added to the model's discrimination and sensitivity, the clinical utility of ALFI remains to be established since LFTs did not improve an already high NPV for short term mortality and only modestly improved a very low PPV.
Clinical significance of somatic mutation in unexplained blood cytopenia
Gallì, Anna; Travaglino, Erica; Ambaglio, Ilaria; Rizzo, Ettore; Molteni, Elisabetta; Elena, Chiara; Ferretti, Virginia Valeria; Catricalà, Silvia; Bono, Elisa; Todisco, Gabriele; Bianchessi, Antonio; Rumi, Elisa; Zibellini, Silvia; Pietra, Daniela; Boveri, Emanuela; Camaschella, Clara; Toniolo, Daniela; Papaemmanuil, Elli; Ogawa, Seishi; Cazzola, Mario
2017-01-01
Unexplained blood cytopenias, in particular anemia, are often found in older persons. The relationship between these cytopenias and myeloid neoplasms like myelodysplastic syndromes is currently poorly defined. We studied a prospective cohort of patients with unexplained cytopenia with the aim to estimate the predictive value of somatic mutations for identifying subjects with, or at risk of, developing a myeloid neoplasm. The study included a learning cohort of 683 consecutive patients investigated for unexplained cytopenia, and a validation cohort of 190 patients referred for suspected myeloid neoplasm. Using granulocyte DNA, we looked for somatic mutations in 40 genes that are recurrently mutated in myeloid malignancies. Overall, 435/683 patients carried a somatic mutation in at least 1 of these genes. Carrying a somatic mutation with a variant allele frequency ≥0.10, or carrying 2 or more mutations, had a positive predictive value for diagnosis of myeloid neoplasm equal to 0.86 and 0.88, respectively. Spliceosome gene mutations and comutation patterns involving TET2, DNMT3A, or ASXL1 had positive predictive values for myeloid neoplasm ranging from 0.86 to 1.0. Within subjects with inconclusive diagnostic findings, carrying 1 or more somatic mutations was associated with a high probability of developing a myeloid neoplasm during follow-up (hazard ratio = 13.9, P < .001). The predictive values of mutation analysis were confirmed in the independent validation cohort. The findings of this study indicate that mutation analysis on peripheral blood granulocytes may significantly improve the current diagnostic approach to unexplained cytopenia and more generally the diagnostic accuracy of myeloid neoplasms. PMID:28424163
Wan, Eric Yuk Fai; Fong, Daniel Yee Tak; Fung, Colman Siu Cheung; Yu, Esther Yee Tak; Chin, Weng Yee; Chan, Anca Ka Chun; Lam, Cindy Lo Kuen
2017-11-10
Cardiovascular disease(CVD) is the leading cause of mortality among patients with type 2 diabetes mellitus(T2DM), and a risk classification model for CVD among primary care diabetic patients is pivotal for risk-based interventions and patient information. This study developed a simple tool for a 5-year CVD risk prediction for primary care Chinese patients with T2DM. A retrospective cohort study was conducted on 137,935 primary care Chinese T2DM patients aged 18-79 years without history of CVD between 1 January 2010 and 31 December 2010. New events of CVD of the cohort over a median follow up of 5 years were extracted from the medical records. A classification rule of 5-year CVD risk was obtained from the derivation cohort and validated in the validation cohort. Significant risk factors included in decision tree were age, gender, smoking status, diagnosis duration, obesity, unsatisfactory control on haemoglobin A1c and cholesterol, albuminuria and stage of chronic kidney disease, which categorized patients into five 5-year CVD risk groups(<5%; 5-9%; 10-14%; 15-19% and ≥20%). Taking the group with the lowest CVD risk, the hazard ratios varied from 1.92(1.77,2.08) to 8.46(7.75,9.24). The present prediction model performed comparable discrimination and better calibration from the plot compared to other current existing models.
Bax, Simon; Bredy, Charlene; Kempny, Aleksander; Dimopoulos, Konstantinos; Devaraj, Anand; Walsh, Simon; Jacob, Joseph; Nair, Arjun; Kokosi, Maria; Keir, Gregory; Kouranos, Vasileios; George, Peter M; McCabe, Colm; Wilde, Michael; Wells, Athol; Li, Wei; Wort, Stephen John; Price, Laura C
2018-04-01
European Respiratory Society (ERS) guidelines recommend the assessment of patients with interstitial lung disease (ILD) and severe pulmonary hypertension (PH), as defined by a mean pulmonary artery pressure (mPAP) ≥35 mmHg at right heart catheterisation (RHC). We developed and validated a stepwise echocardiographic score to detect severe PH using the tricuspid regurgitant velocity and right atrial pressure (right ventricular systolic pressure (RVSP)) and additional echocardiographic signs. Consecutive ILD patients with suspected PH underwent RHC between 2005 and 2015. Receiver operating curve analysis tested the ability of components of the score to predict mPAP ≥35 mmHg, and a score devised using a stepwise approach. The score was tested in a contemporaneous validation cohort. The score used "additional PH signs" where RVSP was unavailable, using a bootstrapping technique. Within the derivation cohort (n=210), a score ≥7 predicted severe PH with 89% sensitivity, 71% specificity, positive predictive value 68% and negative predictive value 90%, with similar performance in the validation cohort (n=61) (area under the curve (AUC) 84.8% versus 83.1%, p=0.8). Although RVSP could be estimated in 92% of studies, reducing this to 60% maintained a fair accuracy (AUC 74.4%). This simple stepwise echocardiographic PH score can predict severe PH in patients with ILD.
Bax, Simon; Bredy, Charlene; Kempny, Aleksander; Dimopoulos, Konstantinos; Devaraj, Anand; Walsh, Simon; Jacob, Joseph; Nair, Arjun; Kokosi, Maria; Keir, Gregory; Kouranos, Vasileios; George, Peter M.; McCabe, Colm; Wilde, Michael; Wells, Athol; Li, Wei; Wort, Stephen John; Price, Laura C.
2018-01-01
European Respiratory Society (ERS) guidelines recommend the assessment of patients with interstitial lung disease (ILD) and severe pulmonary hypertension (PH), as defined by a mean pulmonary artery pressure (mPAP) ≥35 mmHg at right heart catheterisation (RHC). We developed and validated a stepwise echocardiographic score to detect severe PH using the tricuspid regurgitant velocity and right atrial pressure (right ventricular systolic pressure (RVSP)) and additional echocardiographic signs. Consecutive ILD patients with suspected PH underwent RHC between 2005 and 2015. Receiver operating curve analysis tested the ability of components of the score to predict mPAP ≥35 mmHg, and a score devised using a stepwise approach. The score was tested in a contemporaneous validation cohort. The score used “additional PH signs” where RVSP was unavailable, using a bootstrapping technique. Within the derivation cohort (n=210), a score ≥7 predicted severe PH with 89% sensitivity, 71% specificity, positive predictive value 68% and negative predictive value 90%, with similar performance in the validation cohort (n=61) (area under the curve (AUC) 84.8% versus 83.1%, p=0.8). Although RVSP could be estimated in 92% of studies, reducing this to 60% maintained a fair accuracy (AUC 74.4%). This simple stepwise echocardiographic PH score can predict severe PH in patients with ILD. PMID:29750141
Tian, Ying; Arai, Eri; Gotoh, Masahiro; Komiyama, Motokiyo; Fujimoto, Hiroyuki; Kanai, Yae
2014-10-20
The CpG island methylator phenotype (CIMP) of clear cell renal cell carcinomas (ccRCCs) is characterized by accumulation of DNA methylation at CpG islands and poorer patient outcome. The aim of this study was to establish criteria for prognostication of patients with ccRCCs using the ccRCC-specific CIMP marker genes. DNA methylation levels at 299 CpG sites in the 14 CIMP marker genes were evaluated quantitatively in tissue specimens of 88 CIMP-negative and 14 CIMP-positive ccRCCs in a learning cohort using the MassARRAY system. An additional 100 ccRCCs were also analyzed as a validation cohort. Receiver operating characteristic curve analysis showed that area under the curve values for the 23 CpG units including the 32 CpG sites in the 7 CIMP-marker genes, i.e. FAM150A, ZNF540, ZNF671, ZNF154, PRAC, TRH and SLC13A5, for discrimination of CIMP-positive from CIMP-negative ccRCCs were larger than 0.95. Criteria combining the 23 CpG units discriminated CIMP-positive from CIMP-negative ccRCCs with 100% sensitivity and specificity in the learning cohort. Cancer-free and overall survival rates of patients with CIMP-positive ccRCCs diagnosed using the criteria combining the 23 CpG units in a validation cohort were significantly lower than those of patients with CIMP-negative ccRCCs (P = 1.41 × 10-5 and 2.43 × 10-13, respectively). Patients with CIMP-positive ccRCCs in the validation cohort had a higher likelihood of disease-related death (hazard ratio, 75.8; 95% confidence interval, 7.81 to 735; P = 1.89 × 10-4) than those with CIMP-negative ccRCCs. The established criteria are able to reproducibly diagnose CIMP-positive ccRCCs and may be useful for personalized medicine for patients with ccRCCs.
Berger, Martin D; Stintzing, Sebastian; Heinemann, Volker; Cao, Shu; Yang, Dongyun; Sunakawa, Yu; Matsusaka, Satoshi; Ning, Yan; Okazaki, Satoshi; Miyamoto, Yuji; Suenaga, Mitsukuni; Schirripa, Marta; Hanna, Diana L; Soni, Shivani; Puccini, Alberto; Zhang, Wu; Cremolini, Chiara; Falcone, Alfredo; Loupakis, Fotios; Lenz, Heinz-Josef
2018-02-15
Purpose: Vitamin D exerts its inhibitory influence on colon cancer growth by inhibiting Wnt signaling and angiogenesis. We hypothesized that SNPs in genes involved in vitamin D transport, metabolism, and signaling are associated with outcome in metastatic colorectal cancer (mCRC) patients treated with first-line FOLFIRI and bevacizumab. Experimental Design: 522 mCRC patients enrolled in the FIRE-3 (discovery cohort) and TRIBE (validation set) trials treated with FOLFIRI/bevacizumab were included in this study. 278 patients receiving FOLFIRI and cetuximab (FIRE-3) served as a control cohort. Six SNPs in 6 genes ( GC, CYP24A1, CYP27B1, VDR, DKK1, CST5 ) were analyzed. Results: In the discovery cohort, AA carriers of the GC rs4588 SNP encoding for the vitamin D-binding protein, and treated with FOLFIRI/bevacizumab had a shorter overall survival (OS) than those harboring any C allele (15.9 vs. 25.1 months) in both univariable ( P = 0.001) and multivariable analyses ( P = 0.047). This association was confirmed in the validation cohort in multivariable analysis (OS 18.1 vs. 26.2 months, HR, 1.83; P = 0.037). Interestingly, AA carriers in the control set exhibited a longer OS (48.0 vs. 25.2 months, HR, 0.50; P = 0.021). This association was further confirmed in a second validation cohort comprising refractory mCRC patients treated with cetuximab ± irinotecan (PFS 8.7 vs. 3.7 months) in univariable ( P = 0.033) and multivariable analyses ( P = 0.046). Conclusions: GC rs4588 SNP might serve as a predictive marker in mCRC patients treated with FOLFIRI/bevacizumab or FOLFIRI/cetuximab. Whereas AA carriers derive a survival benefit with FOLFIRI/cetuximab, treatment with FOLFIRI/bevacizumab is associated with a worse outcome. Clin Cancer Res; 24(4); 784-93. ©2017 AACR . ©2017 American Association for Cancer Research.
Gevensleben, Heidrun; Holmes, Emily Eva; Goltz, Diane; Dietrich, Jörn; Sailer, Verena; Ellinger, Jörg; Dietrich, Dimo; Kristiansen, Glen
2016-11-29
The rapid development of programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) inhibitors has generated an urgent need for biomarkers assisting the selection of patients eligible for therapy. The use of PD-L1 immunohistochemistry, which has been suggested as a predictive biomarker, however, is confounded by multiple unresolved issues. The aim of this study therefore was to quantify PD-L1 DNA methylation (mPD-L1) in prostate tissue samples and to evaluate its potential as a biomarker in prostate cancer (PCa). In the training cohort, normal tissue showed significantly lower levels of mPD-L1 compared to tumor tissue. High mPD-L1 in PCa was associated with biochemical recurrence (BCR) in univariate Cox proportional hazards (hazard ratio (HR)=2.60 [95%CI: 1.50-4.51], p=0.001) and Kaplan-Meier analyses (p<0.001). These results were corroborated in an independent validation cohort in univariate Cox (HR=1.24 [95%CI: 1.08-1.43], p=0.002) and Kaplan-Meier analyses (p=0.029). Although mPD-L1 and PD-L1 protein expression did not correlate in the validation cohort, both parameters added significant prognostic information in bivariate Cox analysis (HR=1.22 [95%CI: 1.05-1.42], p=0.008 for mPD-L1 and HR=2.58 [95%CI: 1.43-4.63], p=0.002 for PD-L1 protein expression). mPD-L1 was analyzed in a training cohort from The Cancer Genome Atlas (n=498) and was subsequently measured in an independent validation cohort (n=299) by quantitative methylation-specific real-time PCR. All patients had undergone radical prostatectomy. mPD-L1 is a promising biomarker for the risk stratification of PCa patients and might offer additional relevant prognostic information to the implemented clinical parameters, particularly in the setting of immune checkpoint inhibition.
Stallmann, C; Ahrens, W; Kaaks, R; Pigeot, I; Swart, E; Jacobs, S
2015-02-01
Some German cohort studies have already linked secondary and registry data with primary data from interviews and medical examinations. This offers the opportunity to obtain more valid information by taking advantage of the strengths of these data synergistically and overcome their individual weaknesses at the same time. The potential and the requirements for linking secondary and registry data with primary data from cohort studies is described generally and illustrated by the example of the "German National Cohort" (GNC). The transfer and usage of secondary and registry data require that administrative and logistic efforts be made over the whole study period. In addition, rigid data protection regulations for using social data have to be observed. The particular strengths of secondary and registry data, namely their objectivity and independence from recall bias, add to the strengths of newly collected primary data and improve the assessment of morbidity endpoints, exposure history and need of patient care. Moreover, new insights on quality and on the added value of linking different data sources may be obtained. © Georg Thieme Verlag KG Stuttgart · New York.
Alvarez, Karina; Loehr, Laura; Folsom, Aaron R.; Newman, Anne B.; Weissfeld, Lisa A.; Wunderink, Richard G.; Kritchevsky, Stephen B.; Mukamal, Kenneth J.; London, Stephanie J.; Harris, Tamara B.; Bauer, Doug C.; Angus, Derek C.
2013-01-01
Background: Preventing pneumonia requires better understanding of incidence, mortality, and long-term clinical and biologic risk factors, particularly in younger individuals. Methods: This was a cohort study in three population-based cohorts of community-dwelling individuals. A derivation cohort (n = 16,260) was used to determine incidence and survival and develop a risk prediction model. The prediction model was validated in two cohorts (n = 8,495). The primary outcome was 10-year risk of pneumonia hospitalization. Results: The crude and age-adjusted incidences of pneumonia were 6.71 and 9.43 cases/1,000 person-years (10-year risk was 6.15%). The 30-day and 1-year mortality were 16.5% and 31.5%. Although age was the most important risk factor (range of crude incidence rates, 1.69-39.13 cases/1,000 person-years for each 5-year increment from 45-85 years), 38% of pneumonia cases occurred in adults < 65 years of age. The 30-day and 1-year mortality were 12.5% and 25.7% in those < 65 years of age. Although most comorbidities were associated with higher risk of pneumonia, reduced lung function was the most important risk factor (relative risk = 6.61 for severe reduction based on FEV1 by spirometry). A clinical risk prediction model based on age, smoking, and lung function predicted 10-year risk (area under curve [AUC] = 0.77 and Hosmer-Lemeshow [HL] C statistic = 0.12). Model discrimination and calibration were similar in the internal validation cohort (AUC = 0.77; HL C statistic, 0.65) but lower in the external validation cohort (AUC = 0.62; HL C statistic, 0.45). The model also calibrated well in blacks and younger adults. C-reactive protein and IL-6 were associated with higher pneumonia risk but did not improve model performance. Conclusions: Pneumonia hospitalization is common and associated with high mortality, even in younger healthy adults. Long-term risk of pneumonia can be predicted in community-dwelling adults with a simple clinical risk prediction model. PMID:23744106
Developing and validating a predictive model for stroke progression.
Craig, L E; Wu, O; Gilmour, H; Barber, M; Langhorne, P
2011-01-01
Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. Two patient cohorts were used for this study - the first cohort formed the training data set, which included consecutive patients admitted to an urban teaching hospital between 2000 and 2002, and the second cohort formed the test data set, which included patients admitted to the same hospital between 2003 and 2004. A standard definition of stroke progression was used. The first cohort (n = 863) was used to develop the model. Variables that were statistically significant (p < 0.1) on univariate analysis were included in the multivariate model. Logistic regression was the technique employed using backward stepwise regression to drop the least significant variables (p > 0.1) in turn. The second cohort (n = 216) was used to test the performance of the model. The performance of the predictive model was assessed in terms of both calibration and discrimination. Multiple imputation methods were used for dealing with the missing values. Variables shown to be significant predictors of stroke progression were conscious level, history of coronary heart disease, presence of hyperosmolarity, CT lesion, living alone on admission, Oxfordshire Community Stroke Project classification, presence of pyrexia and smoking status. The model appears to have reasonable discriminative properties [the median receiver-operating characteristic curve value was 0.72 (range 0.72-0.73)] and to fit well with the observed data, which is indicated by the high goodness-of-fit p value [the median p value from the Hosmer-Lemeshow test was 0.90 (range 0.50-0.92)]. The predictive model developed in this study contains variables that can be easily collected in practice therefore increasing its usability in clinical practice. Using this analysis approach, the discrimination and calibration of the predictive model appear sufficiently high to provide accurate predictions. This study also offers some discussion around the validation of predictive models for wider use in clinical practice.
Ni, Ai; Cai, Jianwen
2018-07-01
Case-cohort designs are commonly used in large epidemiological studies to reduce the cost associated with covariate measurement. In many such studies the number of covariates is very large. An efficient variable selection method is needed for case-cohort studies where the covariates are only observed in a subset of the sample. Current literature on this topic has been focused on the proportional hazards model. However, in many studies the additive hazards model is preferred over the proportional hazards model either because the proportional hazards assumption is violated or the additive hazards model provides more relevent information to the research question. Motivated by one such study, the Atherosclerosis Risk in Communities (ARIC) study, we investigate the properties of a regularized variable selection procedure in stratified case-cohort design under an additive hazards model with a diverging number of parameters. We establish the consistency and asymptotic normality of the penalized estimator and prove its oracle property. Simulation studies are conducted to assess the finite sample performance of the proposed method with a modified cross-validation tuning parameter selection methods. We apply the variable selection procedure to the ARIC study to demonstrate its practical use.
Pastor, Maria Delores; Nogal, Ana; Molina-Pinelo, Sonia; Quintanal-Villalonga, Álvaro; Meléndez, Ricardo; Ferrer, I; Romero-Romero, Beatrice; De Miguel, Maria José; López-Campos, José Luis; Corral, Jesús; García-Carboner, Rocío; Carnero, Amancio; Paz-Ares, Luis
2016-12-01
Lung cancer (LC) and chronic obstructive pulmonary disease (COPD) are smoking-related diseases, with the presence of COPD itself increasing the risk for development of LC, probably owing to underlying inflammation. LC is typically detected at late stages of the disease and carries a poor prognosis. There is an unmet need for methods to facilitate the early detection of LC in high-risk subjects such as smokers. The expression of inflammatory proteins in bronchoalveolar lavage fluid (BALF) samples was studied by antibody arrays in a prospective cohort of 60 smokers of more than 30 pack-years divided into four groups (control, patients with LC, patients with COPD, and patients with LC plus COPD). Relevant biomarkers were validated by Western blot. Additional validation with enzyme-linked immunosorbent assay (ELISA) was carried out on two independent controlled cohorts of 139 patients (control, patients with LC, patients with COPD, and patients with LC plus COPD) and 160 patients (control and patients with LC of all histological types). A total of 16 differentially expressed proteins in samples from patients with LC, COPD, and LC plus COPD were identified by antibody arrays and validated by Western blot and ELISA. C-C motif chemokine ligand 1 (CCL-1) and interleukin-11 (IL)-11 were selectively expressed in samples from patients with adenocarcinoma with or without COPD (p < 0.005). These proteins exhibited a remarkable diagnostic performance for lung adenocarcinoma in an independent cohort of 139 patients. Receiver operating characteristic curves showed that the optimum diagnostic cutoff value for IL-11 was 42 pg/mL (area under the curve = 0.93 [95% confidence interval: 0.896-0.975], sensitivity 90%, specificity 86%), whereas for CCL-1 it was 39.5 pg/mL (0.83 [95% confidence interval: 0.749-0.902], sensitivity 83%, and specificity 74%). Further validation of the ELISA biomarkers at the aforementioned cutoffs was performed in an additional cohort of 160 patients (20 controls, 66 patients with LC, and 74 patients with LC plus COPD). There was a significant correlation between BALF levels of IL-11 and CCL-1 (r 2 = 0.76, p < 0.001), and the use of both biomarkers increased the diagnostic accuracy to 96.1% in the two validation cohorts. Appropriate diagnostic performance was observed for all subgroups regardless of stage at diagnosis, involvement of the bronchial tract, pack-years smoked, and number of cells in BALF. IL-11 and CCL-1 are highly specific biomarkers with great accuracy for the diagnosis of lung adenocarcinoma in BALF specimens. Further study of these proteins as markers for the early diagnosis and screening of plasma and other biological materials is warranted. Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.
Challenges in translating endpoints from trials to observational cohort studies in oncology
Ording, Anne Gulbech; Cronin-Fenton, Deirdre; Ehrenstein, Vera; Lash, Timothy L; Acquavella, John; Rørth, Mikael; Sørensen, Henrik Toft
2016-01-01
Clinical trials are considered the gold standard for examining drug efficacy and for approval of new drugs. Medical databases and population surveillance registries are valuable resources for post-approval observational research, which are increasingly used in studies of benefits and risk of new cancer drugs. Here, we address the challenges in translating endpoints from oncology trials to observational studies. Registry-based cohort studies can investigate real-world safety issues – including previously unrecognized concerns – by examining rare endpoints or multiple endpoints at once. In contrast to clinical trials, observational cohort studies typically do not exclude real-world patients from clinical practice, such as old and frail patients with comorbidity. The observational cohort study complements the clinical trial by examining the effectiveness of interventions applied in clinical practice and by providing evidence on long-term clinical outcomes, which are often not feasible to study in a clinical trial. Various endpoints can be included in clinical trials, such as hard endpoints, soft endpoints, surrogate endpoints, and patient-reported endpoints. Each endpoint has it strengths and limitations for use in research studies. Endpoints used in oncology trials are often not applicable in observational cohort studies which are limited by the setting of standard clinical practice and by non-standardized endpoint determination. Observational studies can be more helpful moving research forward if they restrict focus to appropriate and valid endpoints. PMID:27354827
Predicting the Individual Risk of Acute Severe Colitis at Diagnosis
Cesarini, Monica; Collins, Gary S.; Rönnblom, Anders; Santos, Antonieta; Wang, Lai Mun; Sjöberg, Daniel; Parkes, Miles; Keshav, Satish
2017-01-01
Abstract Background and Aims: Acute severe colitis [ASC] is associated with major morbidity. We aimed to develop and externally validate an index that predicted ASC within 3 years of diagnosis. Methods: The development cohort included patients aged 16–89 years, diagnosed with ulcerative colitis [UC] in Oxford and followed for 3 years. Primary outcome was hospitalization for ASC, excluding patients admitted within 1 month of diagnosis. Multivariable logistic regression examined the adjusted association of seven risk factors with ASC. Backwards elimination produced a parsimonious model that was simplified to create an easy-to-use index. External validation occurred in separate cohorts from Cambridge, UK, and Uppsala, Sweden. Results: The development cohort [Oxford] included 34/111 patients who developed ASC within a median 14 months [range 1–29]. The final model applied the sum of 1 point each for extensive disease, C-reactive protein [CRP] > 10mg/l, or haemoglobin < 12g/dl F or < 14g/dl M at diagnosis, to give a score from 0/3 to 3/3. This predicted a 70% risk of developing ASC within 3 years [score 3/3]. Validation cohorts included different proportions with ASC [Cambridge = 25/96; Uppsala = 18/298]. Of those scoring 3/3 at diagnosis, 18/18 [Cambridge] and 12/13 [Uppsala] subsequently developed ASC. Discriminant ability [c-index, where 1.0 = perfect discrimination] was 0.81 [Oxford], 0.95 [Cambridge], 0.97 [Uppsala]. Internal validation using bootstrapping showed good calibration, with similar predicted risk across all cohorts. A nomogram predicted individual risk. Conclusions: An index applied at diagnosis reliably predicts the risk of ASC within 3 years in different populations. Patients with a score 3/3 at diagnosis may merit early immunomodulator therapy. PMID:27647858
Schmid, D; Kuo, H-W; Hell, M; Kasper, S; Lederer, I; Mikula, C; Springer, B; Allerberger, F
2011-03-01
An outbreak of norovirus GGII.4 2006b affected an Austrian 600-bed healthcare facility from 15 to 27 March 2009. A total of 204 patients, residents and staff fitted the outbreak case definition; 17 (8.3%) were laboratory-confirmed. Foodborne origin was suspected in the 114 patient and resident cases with onset 15-18 March. A case-cohort study was performed to test the hypothesis that consumption of dishes offered on 14, 15 and 16 March (risk days) was associated with increased risk of infection. Data on food exposure of 62% (317/510) of the patient and resident cohort were available for a simultaneous retrospective cohort study. The case-cohort analysis revealed that consumption of sliced cold sausage offered on 15 March [odds ratio (OR): 3.98; 95% confidence interval (CI): 1.18-14.1], a meat dish with salad (adjusted OR: 2.2; 95% CI: 1.19-4.08) and a rolled spinach pancake (adjusted OR: 2.17; 95% CI: 1.27-3.71) on 16 March were independent risk factors. It is likely that one of the five asymptomatic excretors among the kitchen staff on duty on the risk days was the source of food contamination. The case-cohort study design was found to be a valid alternative to the retrospective cohort study design for the investigation of a suspected foodborne outbreak in a large cohort. Copyright © 2010 The Hospital Infection Society. Published by Elsevier Ltd. All rights reserved.
Validity of the diagnosis of pre-eclampsia in the Medical Birth Registry of Norway.
Thomsen, Liv C V; Klungsøyr, Kari; Roten, Linda T; Tappert, Christian; Araya, Elisabeth; Baerheim, Gunhild; Tollaksen, Kjersti; Fenstad, Mona H; Macsali, Ferenc; Austgulen, Rigmor; Bjørge, Line
2013-08-01
Evaluating the validity of pre-eclampsia registration in the Medical Birth Registry of Norway (MBRN) according to both broader and restricted disease definitions. Retrospective nested cohort study. Multicenter study. In this study, two cohorts of women with pre-eclamptic pregnancies registered in the MBRN were selected. Study group 1 contained 966 pregnancies from 1967 to 2002. Concomitant participation in the Nord-Trøndelag Health Study 2 was required. Study group 2 comprised 1138 pregnancies recorded in 1967-2005, examined as a pre-eclampsia biobank was established. Diagnostic criteria vary. The broader criteria for pre-eclampsia, used by the MBRN, are one measurement of hypertension and proteinuria (Criterion A). Criteria used internationally today require two measurements of hypertension and proteinuria (Criterion B). The diagnostic validities in Study groups 1 and 2 were judged against medical records according to Criterion A and B, respectively. Positive predictive value (PPV) and trend analyses. The diagnosis was confirmed in 88.3% of pregnancies in Study group 1, and in 63.6% in Study group 2. PPV was high for Study group 1 throughout the period. For Study group 2, results improved significantly after 1986. This study ascertains high PPV of pre-eclampsia in the MBRN using broader traditional criteria, although the PPV decreases through assessment using restricted modern criteria. This illustrates how inclusion of direct measurements may improve registration of complex disorders defined by changing diagnostic criteria. © 2013 Nordic Federation of Societies of Obstetrics and Gynecology.
Prabhakaran, Shyam; Jovin, Tudor G.; Tayal, Ashis H.; Hussain, Muhammad S.; Nguyen, Thanh N.; Sheth, Kevin N.; Terry, John B.; Nogueira, Raul G.; Horev, Anat; Gandhi, Dheeraj; Wisco, Dolora; Glenn, Brenda A.; Ludwig, Bryan; Clemmons, Paul F.; Cronin, Carolyn A.; Tian, Melissa; Liebeskind, David; Zaidat, Osama O.; Castonguay, Alicia C.; Martin, Coleman; Mueller-Kronast, Nils; English, Joey D.; Linfante, Italo; Malisch, Timothy W.; Gupta, Rishi
2014-01-01
Background There are multiple clinical and radiographic factors that influence outcomes after endovascular reperfusion therapy (ERT) in acute ischemic stroke (AIS). We sought to derive and validate an outcome prediction score for AIS patients undergoing ERT based on readily available pretreatment and posttreatment factors. Methods The derivation cohort included 511 patients with anterior circulation AIS treated with ERT at 10 centers between September 2009 and July 2011. The prospective validation cohort included 223 patients with anterior circulation AIS treated in the North American Solitaire Acute Stroke registry. Multivariable logistic regression identified predictors of good outcome (modified Rankin score ≤2 at 3 months) in the derivation cohort; model β coefficients were used to assign points and calculate a risk score. Discrimination was tested using C statistics with 95% confidence intervals (CIs) in the derivation and validation cohorts. Calibration was assessed using the Hosmer-Lemeshow test and plots of observed to expected outcomes. We assessed the net reclassification improvement for the derived score compared to the Totaled Health Risks in Vascular Events (THRIVE) score. Subgroup analysis in patients with pretreatment Alberta Stroke Program Early CT Score (ASPECTS) and posttreatment final infarct volume measurements was also performed to identify whether these radiographic predictors improved the model compared to simpler models. Results Good outcome was noted in 186 (36.4%) and 100 patients (44.8%) in the derivation and validation cohorts, respectively. Combining readily available pretreatment and posttreatment variables, we created a score (acronym: SNARL) based on the following parameters: symptomatic hemorrhage [2 points: none, hemorrhagic infarction (HI)1–2 or parenchymal hematoma (PH) type 1; 0 points: PH2], baseline National Institutes of Health Stroke Scale score (3 points: 0–10; 1 point: 11–20; 0 points: >20), age (2 points: <60 years; 1 point: 60–79 years; 0 points: >79 years), reperfusion (3 points: Thrombolysis In Cerebral Ischemia score 2b or 3) and location of clot (1 point: M2; 0 points: M1 or internal carotid artery). The SNARL score demonstrated good discrimination in the derivation (C statistic 0.79, 95% CI 0.75–0.83) and validation cohorts (C statistic 0.74, 95% CI 0.68–0.81) and was superior to the THRIVE score (derivation cohort: C statistic 0.65, 95% CI 0.60–0.70; validation cohort: C-statistic 0.59, 95% CI 0.52–0.67; p < 0.01 in both cohorts) but was inferior to a score that included age, ASPECTS, reperfusion status and final infarct volume (C statistic 0.86, 95% CI 0.82–0.91; p = 0.04). Compared with the THRIVE score, the SNARL score resulted in a net reclassification improvement of 34.8%. Conclusions Among AIS patients treated with ERT, pretreatment scores such as the THRIVE score provide only fair prognostic information. Inclusion of posttreatment variables such as reperfusion and symptomatic hemorrhage greatly influences outcome and results in improved outcome prediction. PMID:24942008
Turusheva, Anna; Frolova, Elena; Korystina, Elena; Zelenukha, Dmitry; Tadjibaev, Pulodjon; Gurina, Natalia; Turkeshi, Eralda; Degryse, Jean-Marie
2016-05-09
Frailty prevalence differs across countries depending on the models used to assess it that are based on various conceptual and operational definitions. This study aims to assess the clinical validity of three frailty models among community-dwelling older adults in north-western Russia where there is a higher incidence of cardiovascular disease and lower life expectancy than in European countries. The Crystal study is a population-based prospective cohort study in Kolpino, St. Petersburg, Russia. A random sample of the population living in the district was stratified into two age groups: 65-75 (n = 305) and 75+ (n = 306) and had a baseline comprehensive health assessment followed by a second one after 33.4 +/-3 months. The total observation time was 47 +/-14.6 months. Frailty was assessed according to the models of Fried, Puts and Steverink-Slaets. Its association with mortality at 5 years follow-up as well as dependency, mental and physical decline at around 2.5 years follow up was explored by multivariable and time-to-event analyses. Mortality was predicted independently from age, sex and comorbidities only by the frail status of the Fried model in those over 75 years old [HR (95 % CI) = 2.50 (1.20-5.20)]. Mental decline was independently predicted only by pre-frail [OR (95 % CI) = 0.24 (0.10-0.55)] and frail [OR (95 % CI) = 0.196 (0.06-0.67)] status of Fried model in those 65-75 years old. The prediction of dependency and physical decline by pre-frail and frail status of any the three frailty models was not statistically significant in this cohort of older adults. None of the three frailty models was valid at predicting 5 years mortality and disability, mental and physical decline at 2.5 years in a cohort of older adults in north-west Russia. Frailty by the Fried model had only limited value for mortality in those 75 years old and mental decline in those 65-75 years old. Further research is needed to identify valid frailty markers for older adults in this population.
Mohaseb, Kam; Linder, Mark; Rootman, Jack; Wilkins, G E; Schechter, Martin T; Dolman, Peter J; Singer, Joel
2008-01-01
To construct a patient-based symptom questionnaire to facilitate early referral of thyroid-associated orbitopathy (TAO) in Graves' hyperthyroidism (GH). Phase I of our study involved developing a symptomatology-based questionnaire for the self-reporting of TAO symptoms in patients recently diagnosed with GH. Phase II involved administering the questionnaire along with a standard ophthalmic examination to a screening cohort of patients newly diagnosed with GH. Symptoms highly associated with the clinical diagnosis of TAO were used to construct a tool with the highest possible sensitivity. Phase III involved validation of this tool in a new cohort of patients recently diagnosed with GH. For each patient, the diagnosis of TAO was made by both a standardized orbital ophthalmic exam and the questionnaire. Results from the questionnaire were then compared to the clinical examination. The questionnaire was compared to the standardized examination and found to have a sensitivity of 0.76 and a specificity of 0.82 in the validation phase of the study. This questionnaire may be a useful tool in clinical practice to allow identification of patients with TAO secondary to GH. Future studies using this questionnaire are needed to determine whether earlier identification and management of these patients is associated with reduced morbidity from TAO.
Bennett, R J; Jayakody, D M P; Eikelboom, R H; Taljaard, D S; Atlas, M D
2016-02-01
To investigate the ability of cochlear implant (CI) recipients to physically handle and care for their hearing implant device(s) and to identify factors that may influence skills. To assess device management skills, a clinical survey was developed and validated on a clinical cohort of CI recipients. Survey development and validation. A prospective convenience cohort design study. Specialist hearing implant clinic. Forty-nine post-lingually deafened, adult CI recipients, at least 12 months postoperative. Survey test-retest reliability, interobserver reliability and responsiveness. Correlations between management skills and participant demographic, audiometric, clinical outcomes and device factors. The Cochlear Implant Management Skills survey was developed, demonstrating high test-retest reliability (0.878), interobserver reliability (0.972) and responsiveness to intervention (skills training) [t(20) = -3.913, P = 0.001]. Cochlear Implant Management Skills survey scores range from 54.69% to 100% (mean: 83.45%, sd: 12.47). No associations were found between handling skills and participant factors. This is the first study to demonstrate a range in cochlear implant device handling skills in CI recipients and offers clinicians and researchers a tool to systematically and objectively identify shortcomings in CI recipients' device handling skills. © 2015 John Wiley & Sons Ltd.
van den Bergen, Janneke C; Hiller, Monika; Böhringer, Stefan; Vijfhuizen, Linda; Ginjaar, Hendrika B; Chaouch, Amina; Bushby, Kate; Straub, Volker; Scoto, Mariacristina; Cirak, Sebahattin; Humbertclaude, Véronique; Claustres, Mireille; Scotton, Chiara; Passarelli, Chiara; Lochmüller, Hanns; Muntoni, Francesco; Tuffery-Giraud, Sylvie; Ferlini, Alessandra; Aartsma-Rus, Annemieke M; Verschuuren, Jan J G M; 't Hoen, Peter Ac; Spitali, Pietro
2015-10-01
Duchenne muscular dystrophy (DMD) is characterised by progressive muscle weakness. It has recently been reported that single nucleotide polymorphisms (SNPs) located in the SPP1 and LTBP4 loci can account for some of the inter-individual variability observed in the clinical disease course. The validation of genetic association in large independent cohorts is a key process for rare diseases in order to qualify prognostic biomarkers and stratify patients in clinical trials. Duchenne patients from five European neuromuscular centres were included. Information about age at wheelchair dependence and steroid use was gathered. Melting curve analysis of PCR fragments or Sanger sequencing were used to genotype SNP rs28357094 in the SPP1 gene in 336 patients. The genotype of SNPs rs2303729, rs1131620, rs1051303 and rs10880 in the LTBP4 locus was determined in 265 patients by mass spectrometry. For both loci, a multivariate analysis was performed, using genotype/haplotype, steroid use and cohort as covariates. We show that corticosteroid treatment and the IAAM haplotype of the LTBP4 gene are significantly associated with prolonged ambulation in patients with DMD. There was no significant association between the SNP rs28357094 in the SPP1 gene and the age of ambulation loss. This study underlines the importance of replicating genetic association studies for rare diseases in large independent cohorts to identify the most robust associations. We anticipate that genotyping of validated genetic associations will become important for the design and interpretation of clinical trials. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
2010-01-01
Background Surname lists are useful for identifying cohorts of ethnic minority patients from secondary data sources. This study sought to develop and validate lists to identify people of South Asian and Chinese origin. Methods Comprehensive lists of South Asian and Chinese surnames were reviewed to identify those that uniquely belonged to the ethnic minority group. Surnames that were common in other populations, communities or ethnic groups were specifically excluded. These surname lists were applied to the Registered Persons Database, a registry of the health card numbers assigned to all residents of the Canadian province of Ontario, so that all residents were assigned to South Asian ethnicity, Chinese ethnicity or the General Population. Ethnic assignment was validated against self-identified ethnicity through linkage with responses to the Canadian Community Health Survey. Results The final surname lists included 9,950 South Asian surnames and 1,133 Chinese surnames. All 16,688,384 current and former residents of Ontario were assigned to South Asian ethnicity, Chinese ethnicity or the General Population based on their surnames. Among 69,859 respondents to the Canadian Community Health Survey, both lists performed extremely well when compared against self-identified ethnicity: positive predictive value was 89.3% for the South Asian list, and 91.9% for the Chinese list. Because surnames shared with other ethnic groups were deliberately excluded from the lists, sensitivity was lower (50.4% and 80.2%, respectively). Conclusions These surname lists can be used to identify cohorts of people with South Asian and Chinese origins from secondary data sources with a high degree of accuracy. These cohorts could then be used in epidemiologic and health service research studies of populations with South Asian and Chinese origins. PMID:20470433
Shah, Baiju R; Chiu, Maria; Amin, Shubarna; Ramani, Meera; Sadry, Sharon; Tu, Jack V
2010-05-15
Surname lists are useful for identifying cohorts of ethnic minority patients from secondary data sources. This study sought to develop and validate lists to identify people of South Asian and Chinese origin. Comprehensive lists of South Asian and Chinese surnames were reviewed to identify those that uniquely belonged to the ethnic minority group. Surnames that were common in other populations, communities or ethnic groups were specifically excluded. These surname lists were applied to the Registered Persons Database, a registry of the health card numbers assigned to all residents of the Canadian province of Ontario, so that all residents were assigned to South Asian ethnicity, Chinese ethnicity or the General Population. Ethnic assignment was validated against self-identified ethnicity through linkage with responses to the Canadian Community Health Survey. The final surname lists included 9,950 South Asian surnames and 1,133 Chinese surnames. All 16,688,384 current and former residents of Ontario were assigned to South Asian ethnicity, Chinese ethnicity or the General Population based on their surnames. Among 69,859 respondents to the Canadian Community Health Survey, both lists performed extremely well when compared against self-identified ethnicity: positive predictive value was 89.3% for the South Asian list, and 91.9% for the Chinese list. Because surnames shared with other ethnic groups were deliberately excluded from the lists, sensitivity was lower (50.4% and 80.2%, respectively). These surname lists can be used to identify cohorts of people with South Asian and Chinese origins from secondary data sources with a high degree of accuracy. These cohorts could then be used in epidemiologic and health service research studies of populations with South Asian and Chinese origins.
Crude incidence in two-phase designs in the presence of competing risks.
Rebora, Paola; Antolini, Laura; Glidden, David V; Valsecchi, Maria Grazia
2016-01-11
In many studies, some information might not be available for the whole cohort, some covariates, or even the outcome, might be ascertained in selected subsamples. These studies are part of a broad category termed two-phase studies. Common examples include the nested case-control and the case-cohort designs. For two-phase studies, appropriate weighted survival estimates have been derived; however, no estimator of cumulative incidence accounting for competing events has been proposed. This is relevant in the presence of multiple types of events, where estimation of event type specific quantities are needed for evaluating outcome. We develop a non parametric estimator of the cumulative incidence function of events accounting for possible competing events. It handles a general sampling design by weights derived from the sampling probabilities. The variance is derived from the influence function of the subdistribution hazard. The proposed method shows good performance in simulations. It is applied to estimate the crude incidence of relapse in childhood acute lymphoblastic leukemia in groups defined by a genotype not available for everyone in a cohort of nearly 2000 patients, where death due to toxicity acted as a competing event. In a second example the aim was to estimate engagement in care of a cohort of HIV patients in resource limited setting, where for some patients the outcome itself was missing due to lost to follow-up. A sampling based approach was used to identify outcome in a subsample of lost patients and to obtain a valid estimate of connection to care. A valid estimator for cumulative incidence of events accounting for competing risks under a general sampling design from an infinite target population is derived.
Lindholm, Daniel; Lindbäck, Johan; Armstrong, Paul W; Budaj, Andrzej; Cannon, Christopher P; Granger, Christopher B; Hagström, Emil; Held, Claes; Koenig, Wolfgang; Östlund, Ollie; Stewart, Ralph A H; Soffer, Joseph; White, Harvey D; de Winter, Robbert J; Steg, Philippe Gabriel; Siegbahn, Agneta; Kleber, Marcus E; Dressel, Alexander; Grammer, Tanja B; März, Winfried; Wallentin, Lars
2017-08-15
Currently, there is no generally accepted model to predict outcomes in stable coronary heart disease (CHD). This study evaluated and compared the prognostic value of biomarkers and clinical variables to develop a biomarker-based prediction model in patients with stable CHD. In a prospective, randomized trial cohort of 13,164 patients with stable CHD, we analyzed several candidate biomarkers and clinical variables and used multivariable Cox regression to develop a clinical prediction model based on the most important markers. The primary outcome was cardiovascular (CV) death, but model performance was also explored for other key outcomes. It was internally bootstrap validated, and externally validated in 1,547 patients in another study. During a median follow-up of 3.7 years, there were 591 cases of CV death. The 3 most important biomarkers were N-terminal pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT), and low-density lipoprotein cholesterol, where NT-proBNP and hs-cTnT had greater prognostic value than any other biomarker or clinical variable. The final prediction model included age (A), biomarkers (B) (NT-proBNP, hs-cTnT, and low-density lipoprotein cholesterol), and clinical variables (C) (smoking, diabetes mellitus, and peripheral arterial disease). This "ABC-CHD" model had high discriminatory ability for CV death (c-index 0.81 in derivation cohort, 0.78 in validation cohort), with adequate calibration in both cohorts. This model provided a robust tool for the prediction of CV death in patients with stable CHD. As it is based on a small number of readily available biomarkers and clinical factors, it can be widely employed to complement clinical assessment and guide management based on CV risk. (The Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy Trial [STABILITY]; NCT00799903). Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Chen, Yu-Wei Roy; Chen, Virginia; Hollander, Zsuzsanna; Leipsic, Jonathon A; Hague, Cameron J; DeMarco, Mari L; FitzGerald, J Mark; McManus, Bruce M; Ng, Raymond T; Sin, Don D
2017-01-01
There are currently no accepted and validated blood tests available for diagnosing acute exacerbations of chronic obstructive pulmonary disease (AECOPD). In this study, we sought to determine the discriminatory power of blood C-reactive protein (CRP) and N-terminal prohormone brain natriuretic peptide (NT-proBNP) in the diagnosis of AECOPD requiring hospitalizations. The study cohort consisted of 468 patients recruited in the COPD Rapid Transition Program who were hospitalized with a primary diagnosis of AECOPD, and 110 stable COPD patients who served as controls. Logistic regression was used to build a classification model to separate AECOPD from convalescent or stable COPD patients. Performance was assessed using an independent validation set of patients who were not included in the discovery set. Serum CRP and whole blood NT-proBNP concentrations were highest at the time of hospitalization and progressively decreased over time. Of the 3 classification models, the one with both CRP and NT-proBNP had the highest AUC in discriminating AECOPD (cross-validated AUC of 0.80). These data were replicated in a validation cohort with an AUC of 0.88. A combination of CRP and NT-proBNP can reasonably discriminate AECOPD requiring hospitalization versus clinical stability and can be used to rapidly diagnose patients requiring hospitalization for AECOPD.
Afshar, Majid; Press, Valerie G; Robison, Rachel G; Kho, Abel N; Bandi, Sindhura; Biswas, Ashvini; Avila, Pedro C; Kumar, Harsha Vardhan Madan; Yu, Byung; Naureckas, Edward T; Nyenhuis, Sharmilee M; Codispoti, Christopher D
2017-10-13
Comprehensive, rapid, and accurate identification of patients with asthma for clinical care and engagement in research efforts is needed. The original development and validation of a computable phenotype for asthma case identification occurred at a single institution in Chicago and demonstrated excellent test characteristics. However, its application in a diverse payer mix, across different health systems and multiple electronic health record vendors, and in both children and adults was not examined. The objective of this study is to externally validate the computable phenotype across diverse Chicago institutions to accurately identify pediatric and adult patients with asthma. A cohort of 900 asthma and control patients was identified from the electronic health record between January 1, 2012 and November 30, 2014. Two physicians at each site independently reviewed the patient chart to annotate cases. The inter-observer reliability between the physician reviewers had a κ-coefficient of 0.95 (95% CI 0.93-0.97). The accuracy, sensitivity, specificity, negative predictive value, and positive predictive value of the computable phenotype were all above 94% in the full cohort. The excellent positive and negative predictive values in this multi-center external validation study establish a useful tool to identify asthma cases in in the electronic health record for research and care. This computable phenotype could be used in large-scale comparative-effectiveness trials.
Suarez, Ralph O; Taimouri, Vahid; Boyer, Katrina; Vega, Clemente; Rotenberg, Alexander; Madsen, Joseph R; Loddenkemper, Tobias; Duffy, Frank H; Prabhu, Sanjay P; Warfield, Simon K
2014-12-01
In this study we validate passive language fMRI protocols designed for clinical application in pediatric epilepsy surgical planning as they do not require overt participation from patients. We introduced a set of quality checks that assess reliability of noninvasive fMRI mappings utilized for clinical purposes. We initially compared two fMRI language mapping paradigms, one active in nature (requiring participation from the patient) and the other passive in nature (requiring no participation from the patient). Group-level analysis in a healthy control cohort demonstrated similar activation of the putative language centers of the brain in the inferior frontal (IFG) and temporoparietal (TPG) regions. Additionally, we showed that passive language fMRI produced more left-lateralized activation in TPG (LI=+0.45) compared to the active task; with similarly robust left-lateralized IFG (LI=+0.24) activations using the passive task. We validated our recommended fMRI mapping protocols in a cohort of 15 pediatric epilepsy patients by direct comparison against the invasive clinical gold-standards. We found that language-specific TPG activation by fMRI agreed to within 9.2mm to subdural localizations by invasive functional mapping in the same patients, and language dominance by fMRI agreed with Wada test results at 80% congruency in TPG and 73% congruency in IFG. Lastly, we tested the recommended passive language fMRI protocols in a cohort of very young patients and confirmed reliable language-specific activation patterns in that challenging cohort. We concluded that language activation maps can be reliably achieved using the passive language fMRI protocols we proposed even in very young (average 7.5 years old) or sedated pediatric epilepsy patients. Copyright © 2014 Elsevier B.V. All rights reserved.
Development and validation of a surgical-pathologic staging and scoring system for cervical cancer
Zhou, Hang; Tang, Fangxu; Jia, Yao; Hu, Ting; Sun, Haiying; Yang, Ru; Chen, Yile; Cheng, Xiaodong; Lv, Weiguo; Wu, Li; Zhou, Jin; Wang, Shaoshuai; Huang, Kecheng; Wang, Lin; Yao, Yuan; Yang, Qifeng; Yang, Xingsheng; Zhang, Qinghua; Han, Xiaobing; Lin, Zhongqiu; Xing, Hui; Qu, Pengpeng; Cai, Hongbing; Song, Xiaojie; Tian, Xiaoyu; Shen, Jian; Xi, Ling; Li, Kezhen; Deng, Dongrui; Wang, Hui; Wang, Changyu; Wu, Mingfu; Zhu, Tao; Chen, Gang; Gao, Qinglei; Wang, Shixuan; Hu, Junbo; Kong, Beihua; Xie, Xing; Ma, Ding
2016-01-01
Background Most cervical cancer patients worldwide receive surgical treatments, and yet the current International Federation of Gynecology and Obstetrics (FIGO) staging system do not consider surgical-pathologic data. We propose a more comprehensive and prognostically valuable surgical-pathologic staging and scoring system (SPSs). Methods Records from 4,220 eligible cervical cancer cases (Cohort 1) were screened for surgical-pathologic risk factors. We constructed a surgical-pathologic staging and SPSs, which was subsequently validated in a prospective study of 1,104 cervical cancer patients (Cohort 2). Results In Cohort 1, seven independent risk factors were associated with patient outcome: lymph node metastasis (LNM), parametrial involvement, histological type, grade, tumor size, stromal invasion, and lymph-vascular space invasion (LVSI). The FIGO staging system was revised and expanded into a surgical-pathologic staging system by including additional criteria of LNM, stromal invasion, and LVSI. LNM was subdivided into three categories based on number and location of metastases. Inclusion of all seven prognostic risk factors improves practical applicability. Patients were stratified into three SPSs risk categories: zero-, low-, and high-score with scores of 0, 1 to 3, and ≥4 (P=1.08E-45; P=6.15E-55). In Cohort 2, 5-year overall survival (OS) and disease-free survival (DFS) outcomes decreased with increased SPSs scores (P=9.04E-15; P=3.23E-16), validating the approach. Surgical-pathologic staging and SPSs show greater homogeneity and discriminatory utility than FIGO staging. Conclusions Surgical-pathologic staging and SPSs improve characterization of tumor severity and disease invasion, which may more accurately predict outcome and guide postoperative therapy. PMID:27014971
Carbone, Marco; Sharp, Stephen J; Flack, Steve; Paximadas, Dimitrios; Spiess, Kelly; Adgey, Carolyn; Griffiths, Laura; Lim, Reyna; Trembling, Paul; Williamson, Kate; Wareham, Nick J; Aldersley, Mark; Bathgate, Andrew; Burroughs, Andrew K; Heneghan, Michael A; Neuberger, James M; Thorburn, Douglas; Hirschfield, Gideon M; Cordell, Heather J; Alexander, Graeme J; Jones, David E J; Sandford, Richard N; Mells, George F
2016-03-01
The biochemical response to ursodeoxycholic acid (UDCA)--so-called "treatment response"--strongly predicts long-term outcome in primary biliary cholangitis (PBC). Several long-term prognostic models based solely on the treatment response have been developed that are widely used to risk stratify PBC patients and guide their management. However, they do not take other prognostic variables into account, such as the stage of the liver disease. We sought to improve existing long-term prognostic models of PBC using data from the UK-PBC Research Cohort. We performed Cox's proportional hazards regression analysis of diverse explanatory variables in a derivation cohort of 1,916 UDCA-treated participants. We used nonautomatic backward selection to derive the best-fitting Cox model, from which we derived a multivariable fractional polynomial model. We combined linear predictors and baseline survivor functions in equations to score the risk of a liver transplant or liver-related death occurring within 5, 10, or 15 years. We validated these risk scores in an independent cohort of 1,249 UDCA-treated participants. The best-fitting model consisted of the baseline albumin and platelet count, as well as the bilirubin, transaminases, and alkaline phosphatase, after 12 months of UDCA. In the validation cohort, the 5-, 10-, and 15-year risk scores were highly accurate (areas under the curve: >0.90). The prognosis of PBC patients can be accurately evaluated using the UK-PBC risk scores. They may be used to identify high-risk patients for closer monitoring and second-line therapies, as well as low-risk patients who could potentially be followed up in primary care. © 2015 by the American Association for the Study of Liver Diseases.
An administrative claims model for profiling hospital 30-day mortality rates for pneumonia patients.
Bratzler, Dale W; Normand, Sharon-Lise T; Wang, Yun; O'Donnell, Walter J; Metersky, Mark; Han, Lein F; Rapp, Michael T; Krumholz, Harlan M
2011-04-12
Outcome measures for patients hospitalized with pneumonia may complement process measures in characterizing quality of care. We sought to develop and validate a hierarchical regression model using Medicare claims data that produces hospital-level, risk-standardized 30-day mortality rates useful for public reporting for patients hospitalized with pneumonia. Retrospective study of fee-for-service Medicare beneficiaries age 66 years and older with a principal discharge diagnosis of pneumonia. Candidate risk-adjustment variables included patient demographics, administrative diagnosis codes from the index hospitalization, and all inpatient and outpatient encounters from the year before admission. The model derivation cohort included 224,608 pneumonia cases admitted to 4,664 hospitals in 2000, and validation cohorts included cases from each of years 1998-2003. We compared model-derived state-level standardized mortality estimates with medical record-derived state-level standardized mortality estimates using data from the Medicare National Pneumonia Project on 50,858 patients hospitalized from 1998-2001. The final model included 31 variables and had an area under the Receiver Operating Characteristic curve of 0.72. In each administrative claims validation cohort, model fit was similar to the derivation cohort. The distribution of standardized mortality rates among hospitals ranged from 13.0% to 23.7%, with 25(th), 50(th), and 75(th) percentiles of 16.5%, 17.4%, and 18.3%, respectively. Comparing model-derived risk-standardized state mortality rates with medical record-derived estimates, the correlation coefficient was 0.86 (Standard Error = 0.032). An administrative claims-based model for profiling hospitals for pneumonia mortality performs consistently over several years and produces hospital estimates close to those using a medical record model.
An Administrative Claims Model for Profiling Hospital 30-Day Mortality Rates for Pneumonia Patients
Bratzler, Dale W.; Normand, Sharon-Lise T.; Wang, Yun; O'Donnell, Walter J.; Metersky, Mark; Han, Lein F.; Rapp, Michael T.; Krumholz, Harlan M.
2011-01-01
Background Outcome measures for patients hospitalized with pneumonia may complement process measures in characterizing quality of care. We sought to develop and validate a hierarchical regression model using Medicare claims data that produces hospital-level, risk-standardized 30-day mortality rates useful for public reporting for patients hospitalized with pneumonia. Methodology/Principal Findings Retrospective study of fee-for-service Medicare beneficiaries age 66 years and older with a principal discharge diagnosis of pneumonia. Candidate risk-adjustment variables included patient demographics, administrative diagnosis codes from the index hospitalization, and all inpatient and outpatient encounters from the year before admission. The model derivation cohort included 224,608 pneumonia cases admitted to 4,664 hospitals in 2000, and validation cohorts included cases from each of years 1998–2003. We compared model-derived state-level standardized mortality estimates with medical record-derived state-level standardized mortality estimates using data from the Medicare National Pneumonia Project on 50,858 patients hospitalized from 1998–2001. The final model included 31 variables and had an area under the Receiver Operating Characteristic curve of 0.72. In each administrative claims validation cohort, model fit was similar to the derivation cohort. The distribution of standardized mortality rates among hospitals ranged from 13.0% to 23.7%, with 25th, 50th, and 75th percentiles of 16.5%, 17.4%, and 18.3%, respectively. Comparing model-derived risk-standardized state mortality rates with medical record-derived estimates, the correlation coefficient was 0.86 (Standard Error = 0.032). Conclusions/Significance An administrative claims-based model for profiling hospitals for pneumonia mortality performs consistently over several years and produces hospital estimates close to those using a medical record model. PMID:21532758
Yamaguchi, Motoko; Suzuki, Ritsuro; Kim, Seok Jin; Ko, Young Hyeh; Oguchi, Masahiko; Asano, Naoko; Miyazaki, Kana; Terui, Yasuhiko; Kubota, Nobuko; Maeda, Takeshi; Kobayashi, Yukio; Amaki, Jun; Soejima, Toshinori; Saito, Bungo; Shimoda, Emiko; Fukuhara, Noriko; Tsukamoto, Norifumi; Shimada, Kazuyuki; Choi, Ilseung; Utsumi, Takahiko; Ejima, Yasuo; Kim, Won Seog; Katayama, Naoyuki
2018-03-30
Prognosis of patients with localized nasal extranodal natural killer/T-cell lymphoma, nasal type (ENKL) has been improved by non-anthracycline-containing treatments such as concurrent chemoradiotherapy (CCRT). However, some patients experience early disease progression. To clarify the clinical features and outcomes of these patients, data from 165 patients with localized nasal ENKL who were diagnosed between 2000 and 2013 at 31 institutes in Japan and who received radiotherapy with dexamethasone, etoposide, ifosfamide, and carboplatin (RT-DeVIC) were retrospectively analyzed. Progression of disease within 2 years after diagnosis (POD24) was used as the definition of early progression. An independent dataset of 60 patients with localized nasal ENKL who received CCRT at Samsung Medical Center was used in the validation analysis. POD24 was documented in 23% of patients who received RT-DeVIC and in 25% of patients in the validation cohort. Overall survival (OS) from risk-defining events of the POD24 group was inferior to that of the reference group in both cohorts (P < .00001). In the RT-DeVIC cohort, pretreatment elevated levels of serum soluble interleukin-2 receptor (sIL-2R), lactate dehydrogenase, C-reactive protein, and detectable Epstein-Barr virus DNA in peripheral blood were associated with POD24. In the validation cohort, no pretreatment clinical factor associated with POD24 was identified. Our study indicates that POD24 is a strong indicator of survival in localized ENKL, despite the different CCRT regimens adopted. In the treatment of localized nasal ENKL, POD24 is useful for identifying patients who have unmet medical needs. © 2018 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.
Ferreira, Wasney de Almeida; Giatti, Luana; Figueiredo, Roberta Carvalho de; Mello, Heliana Ribeiro de; Barreto, Sandhi Maria
2018-04-01
This work assessed the concurrent and face validity of the MacArthur scale, which attempts to capture subjective social status in society, neighborhood and work contexts. The study population comprised a convenience sample made up of 159 adult participants of the ELSA-Brasil cohort study conducted in Minas Gerais between 2012 and 2014. The analysis was conducted drawing on Conceptual Metaphor Theory and using corpus linguistic methods. Concurrent validity was shown to be moderate for the society ladder (Kappaw = 0.55) and good for the neighborhood (Kappaw = 0.60) and work (Kappaw = 0,67) ladders. Face validity indicated that the MacArthur scale really captures subjective social status across indicators of socioeconomic position, thus confirming that it is a valuable tool for the study of social inequalities in health Brazil.
Borsi, John P.
2016-01-01
We have sought to replicate and extend the Season-wide Association Study (SeaWAS) of Boland, et al.1 in identifying birth month-disease associations from electronic health records (EHRs). We used methodology similar to that implemented by Boland on three geographically distinct cohorts, for a total of 11.8 million individuals derived from multiple data sources. We were able to identify eleven out of sixteen literature-supported birth month associations as compared to seven of sixteen for SeaWAS. Of the nine novel cardiovascular birth month associations discovered by SeaWAS, we were able to replicate four. None of the novel non-cardiovascular associations discovered by SeaWAS emerged as significant relations in our study. We identified thirty birth month disease associations not previously reported; of those, only six associations were validated in more than one cohort. These results suggest that differences in cohort composition and location can cause consequential variation in results of hypothesis-free searches. PMID:28269826
The Subjective Visual Vertical: Validation of a Simple Test
ERIC Educational Resources Information Center
Tesio, Luigi; Longo, Stefano; Rota, Viviana
2011-01-01
The study sought to provide norms for a simple test of visual perception of verticality (subjective visual vertical). The study was designed as a cohort study with a balanced design. The setting was the Rehabilitation Department of a University Hospital. Twenty-two healthy adults, of 23-58 years, 11 men (three left handed) and 11 women (three left…
Jochems, Arthur; El-Naqa, Issam; Kessler, Marc; Mayo, Charles S; Jolly, Shruti; Matuszak, Martha; Faivre-Finn, Corinne; Price, Gareth; Holloway, Lois; Vinod, Shalini; Field, Matthew; Barakat, Mohamed Samir; Thwaites, David; de Ruysscher, Dirk; Dekker, Andre; Lambin, Philippe
2018-02-01
Early death after a treatment can be seen as a therapeutic failure. Accurate prediction of patients at risk for early mortality is crucial to avoid unnecessary harm and reducing costs. The goal of our work is two-fold: first, to evaluate the performance of a previously published model for early death in our cohorts. Second, to develop a prognostic model for early death prediction following radiotherapy. Patients with NSCLC treated with chemoradiotherapy or radiotherapy alone were included in this study. Four different cohorts from different countries were available for this work (N = 1540). The previous model used age, gender, performance status, tumor stage, income deprivation, no previous treatment given (yes/no) and body mass index to make predictions. A random forest model was developed by learning on the Maastro cohort (N = 698). The new model used performance status, age, gender, T and N stage, total tumor volume (cc), total tumor dose (Gy) and chemotherapy timing (none, sequential, concurrent) to make predictions. Death within 4 months of receiving the first radiotherapy fraction was used as the outcome. Early death rates ranged from 6 to 11% within the four cohorts. The previous model performed with AUC values ranging from 0.54 to 0.64 on the validation cohorts. Our newly developed model had improved AUC values ranging from 0.62 to 0.71 on the validation cohorts. Using advanced machine learning methods and informative variables, prognostic models for early mortality can be developed. Development of accurate prognostic tools for early mortality is important to inform patients about treatment options and optimize care.
Reproducibility and validity of the Shanghai Women's Health Study physical activity questionnaire.
Matthews, Charles E; Shu, Xiao-Ou; Yang, Gong; Jin, Fan; Ainsworth, Barbara E; Liu, Dake; Gao, Yu-Tang; Zheng, Wei
2003-12-01
In this investigation, the authors evaluated the reproducibility and validity of the Shanghai Women's Health Study (SWHS) physical activity questionnaire (PAQ), which was administered in a cohort study of approximately 75,000 Chinese women aged 40-70 years. Reproducibility (2-year test-retest) was evaluated using kappa statistics and intraclass correlation coefficients (ICCs). Validity was evaluated by comparing Spearman correlations (r) for the SWHS PAQ with two criterion measures administered over a period of 12 months: four 7-day physical activity logs and up to 28 7-day PAQs. Women were recruited from the SWHS cohort (n = 200). Results indicated that the reproducibility of adolescent and adult exercise participation (kappa = 0.85 and kappa = 0.64, respectively) and years of adolescent exercise and adult exercise energy expenditure (ICC = 0.83 and ICC = 0.70, respectively) was reasonable. Reproducibility values for adult lifestyle activities were lower (ICC = 0.14-0.54). Significant correlations between the PAQ and criterion measures of adult exercise were observed for the first PAQ administration (physical activity log, r = 0.50; 7-day PAQ, r = 0.62) and the second PAQ administration (physical activity log, r = 0.74; 7-day PAQ, r = 0.80). Significant correlations between PAQ lifestyle activities and the 7-day PAQ were also noted (r = 0.33-0.88). These data indicate that the SWHS PAQ is a reproducible and valid measure of exercise behaviors and that it demonstrates utility in stratifying women by levels of important lifestyle activities (e.g., housework, walking, cycling).
Tumusiime, David K; Musabeyezu, Emmanuel; Mutimurah, Eugene; Hoover, Donald R; Shi, Qiuhu; Rudakemwa, Emmanuel; Ndacyayisenga, Victorien; Dusingize, Jean Claude; Sinayobye, Jean D'Amour; Stewart, Aimee; Venter, Francois W D; Anastos, Kathryn
2014-06-01
Peripheral neuropathy symptoms (PNS) are commonly manifested in HIV-infected (HIV+) individuals, although data are limited on the prevalence and predictors of PNS in HIV+ patients from sub-Saharan Africa. To determine the prevalence and predictors of PNS in HIV+ and HIV-uninfected (HIV-) Rwandan women. Data were analysed from 936 (710 HIV+ and 226 HIV-) women from the Rwanda Women Interassociation Study and Assessment (RWISA), an observational prospective cohort study investigating the effectiveness and toxicity of ART in HIV+ women. Of 936 enrolled, 920 (98.3%) were included in this analysis with 44% of HIV- and 52% of the HIV+ women reporting PNS (p=0.06). CD4+ count was not associated with PNS, although there was a non-significant trend towards higher prevalence in those with lower CD4+ counts. For the HIV- women, only alcohol and co-trimoxazole use were independently associated with PNS. WHO HIV stage IV illness and albumin ≤ 3.5 were associated with PNS in HIV+ women. The rate of peripheral neuropathy symptoms reported in this cohort of HIV-infected African women seems implausible, and rather suggests that the screening tool for peripheral neuropathy in culturally diverse African settings be locally validated.
Armand, P; Deeg, H J; Kim, H T; Lee, H; Armistead, P; de Lima, M; Gupta, V; Soiffer, R J
2010-05-01
Cytogenetics is an important prognostic factor for patients with myelodysplastic syndromes (MDS). However, existing cytogenetics grouping schemes are based on patients treated with supportive care, and may not be optimal for patients undergoing allo-SCT. We proposed earlier an SCT-specific cytogenetics grouping scheme for patients with MDS and AML arising from MDS, based on an analysis of patients transplanted at the Dana-Farber Cancer Institute/Brigham and Women's Hospital. Under this scheme, abnormalities of chromosome 7 and complex karyotype are considered adverse risk, whereas all others are considered standard risk. In this retrospective study, we validated this scheme on an independent multicenter cohort of 546 patients. Adverse cytogenetics was the strongest prognostic factor for outcome in this cohort. The 4-year relapse-free survival and OS were 42 and 46%, respectively, in the standard-risk group, vs 21 and 23% in the adverse group (P<0.0001 for both comparisons). This grouping scheme retained its prognostic significance irrespective of patient age, disease type, earlier leukemogenic therapy and conditioning intensity. Therapy-related disease was not associated with increased mortality in this cohort, after taking cytogenetics into account. We propose that this SCT-specific cytogenetics grouping scheme be used for patients with MDS or AML arising from MDS who are considering or undergoing SCT.
Kaihan, Ahmad Baseer; Yasuda, Yoshinari; Katsuno, Takayuki; Kato, Sawako; Imaizumi, Takahiro; Ozeki, Takaya; Hishida, Manabu; Nagata, Takanobu; Ando, Masahiko; Tsuboi, Naotake; Maruyama, Shoichi
2017-12-01
The Oxford Classification is utilized globally, but has not been fully validated. In this study, we conducted a comparative analysis between the Oxford Classification and Japanese Histologic Classification (JHC) to predict renal outcome in Japanese patients with IgA nephropathy (IgAN). A retrospective cohort study including 86 adult IgAN patients was conducted. The Oxford Classification and the JHC were evaluated by 7 independent specialists. The JHC, MEST score in the Oxford Classification, and crescents were analyzed in association with renal outcome, defined as a 50% increase in serum creatinine. In multivariate analysis without the JHC, only the T score was significantly associated with renal outcome. While, a significant association was revealed only in the JHC on multivariate analysis with JHC. The JHC and T score in the Oxford Classification were associated with renal outcome among Japanese patients with IgAN. Superiority of the JHC as a predictive index should be validated with larger study population and cohort studies in different ethnicities.
2013-01-01
Background A prospective study of a cohort of nursing staff from nursing homes was undertaken to validate the Nurse-Work Instability Scale (Nurse-WIS). Baseline investigation data was used to test reliability, construct validity and criterion validity. Method A survey of nursing staff from nursing homes was conducted using a questionnaire containing the Nurse-WIS along with other survey instruments (including SF-12, WAI, SPE). The self-reported number of days’ sick leave taken and if a pension for reduced work capacity was drawn were recorded. The reliability of the scale was checked by item difficulty (P), item discrimination (rjt) and by internal consistency according to Cronbach’s coefficient. The hypotheses for checking construct validity were tested on the basis of correlations. Pearson’s chi-square was used to test concurrent criterion validity; discriminant validity was tested by means of binary logistic regression. Results 396 persons answered the questionnaire (21.3% response rate). More than 80% were female and mostly work full-time in a rotating shift pattern. Following the test for item discrimination, two items were removed from the Nurse-WIS test. According to Cronbach’s (0.927) the scale provides a high degree of measuring accuracy. All hypotheses and assumptions used to test validity were confirmed: As the Nurse-WIS risk increases, health-related quality of life, work ability and job satisfaction decline. Depressive symptoms and a poor subjective prognosis of earning capacity are also more frequent. Musculoskeletal disorders and impairments of psychological well-being are more frequent. Age also influences the Nurse-WIS result. While 12.0% of those below the age of 35 had an increased risk, the figure for those aged over 55 was 50%. Conclusion This study is the first validation study of the Nurse-WIS to date. The Nurse-WIS shows good reliability, good validity and a good level of measuring accuracy. It appears to be suitable for recording prevention and rehabilitation needs among health care workers. If, in the follow-up, the Nurse-WIS likewise proves to be a reliable screening instrument with good predictive validity, it could ensure that suitable action is taken at an early stage, thereby helping to counteract early retirement and the anticipated shortage of health care workers. PMID:24330532
Hellwig, Birte; Madjar, Katrin; Edlund, Karolina; Marchan, Rosemarie; Cadenas, Cristina; Heimes, Anne-Sophie; Almstedt, Katrin; Lebrecht, Antje; Sicking, Isabel; Battista, Marco J; Micke, Patrick; Schmidt, Marcus; Hengstler, Jan G; Rahnenführer, Jörg
2016-01-01
In breast cancer, gene signatures that predict the risk of metastasis after surgical tumor resection are mainly indicative of early events. The purpose of this study was to identify genes linked to metastatic recurrence more than three years after surgery. Affymetrix HG U133A and Plus 2.0 array datasets with information on metastasis-free, disease-free or overall survival were accessed via public repositories. Time restricted Cox regression models were used to identify genes associated with metastasis during or after the first three years post-surgery (early- and late-type genes). A sequential validation study design, with two non-adjuvantly treated discovery cohorts (n = 409) and one validation cohort (n = 169) was applied and identified genes were further evaluated in tamoxifen-treated breast cancer patients (n = 923), as well as in patients with non-small cell lung (n = 1779), colon (n = 893) and ovarian (n = 922) cancer. Ten late- and 243 early-type genes were identified in adjuvantly untreated breast cancer. Adjustment to clinicopathological factors and an established proliferation-related signature markedly reduced the number of early-type genes to 16, whereas nine late-type genes still remained significant. These nine genes were associated with metastasis-free survival (MFS) also in a non-time restricted model, but not in the early period alone, stressing that their prognostic impact was primarily based on MFS more than three years after surgery. Four of the ten late-type genes, the ribosome-related factors EIF4B, RPL5, RPL3, and the tumor angiogenesis modifier EPN3 were significantly associated with MFS in the late period also in a meta-analysis of tamoxifen-treated breast cancer cohorts. In contrast, only one late-type gene (EPN3) showed consistent survival associations in more than one cohort in the other cancer types, being associated with worse outcome in two non-small cell lung cancer cohorts. No late-type gene was validated in ovarian and colon cancer. Ribosome-related genes were associated with decreased risk of late metastasis in both adjuvantly untreated and tamoxifen-treated breast cancer patients. In contrast, high expression of epsin (EPN3) was associated with increased risk of late metastasis. This is of clinical relevance considering the well-understood role of epsins in tumor angiogenesis and the ongoing development of epsin antagonizing therapies.
Intergrated Systems Biology Approach for Ovarian Cancer Biomarker Discovery — EDRN Public Portal
The overall objective is to validate serum protein markers for early diagnosis of ovarian cancer with the ultimate goal being to develop a multiparametric panel consisting of 2-4 novel markers with 10 known markers for phase 3 analysis. In phase 1, we will screen for markers able to pass a threshold of 98% specificity and 30% sensitivity in a cohort of 300 women. Markers that pass phase 1 validation will be investigated in a phase 2 PRoBE cohort with a 98% specificity and 70% sensitivity cut-off. Finally, markers that pass phase 2 validation will be evaluated in EDRN CVC laboratory specimens with a cut-off of > 98% specificity and 90% sensitivity.
Burbach, J P M; Kurk, S A; Coebergh van den Braak, R R J; Dik, V K; May, A M; Meijer, G A; Punt, C J A; Vink, G R; Los, M; Hoogerbrugge, N; Huijgens, P C; Ijzermans, J N M; Kuipers, E J; de Noo, M E; Pennings, J P; van der Velden, A M T; Verhoef, C; Siersema, P D; van Oijen, M G H; Verkooijen, H M; Koopman, M
2016-11-01
Systematic evaluation and validation of new prognostic and predictive markers, technologies and interventions for colorectal cancer (CRC) is crucial for optimizing patients' outcomes. With only 5-15% of patients participating in clinical trials, generalizability of results is poor. Moreover, current trials often lack the capacity for post-hoc subgroup analyses. For this purpose, a large observational cohort study, serving as a multiple trial and biobanking facility, was set up by the Dutch Colorectal Cancer Group (DCCG). The Prospective Dutch ColoRectal Cancer cohort is a prospective multidisciplinary nationwide observational cohort study in the Netherlands (yearly CRC incidence of 15 500). All CRC patients (stage I-IV) are eligible for inclusion, and longitudinal clinical data are registered. Patients give separate consent for the collection of blood and tumor tissue, filling out questionnaires, and broad randomization for studies according to the innovative cohort multiple randomized controlled trial design (cmRCT), serving as an alternative study design for the classic RCT. Objectives of the study include: 1) systematically collected long-term clinical data, patient-reported outcomes and biomaterials from daily CRC practice; and 2) to facilitate future basic, translational and clinical research including interventional and cost-effectiveness studies for both national and international research groups with short inclusion periods, even for studies with stringent inclusion criteria. Seven months after initiation 650 patients have been enrolled, eight centers participate, 15 centers await IRB approval and nine embedded cohort- or cmRCT-designed studies are currently recruiting patients. This cohort provides a unique multidisciplinary data, biobank, and patient-reported outcomes collection initiative, serving as an infrastructure for various kinds of research aiming to improve treatment outcomes in CRC patients. This comprehensive design may serve as an example for other tumor types.
The QT Scale: A Weight Scale Measuring the QTc Interval.
Couderc, Jean-Philippe; Beshaw, Connor; Niu, Xiaodan; Serrano-Finetti, Ernesto; Casas, Oscar; Pallas-Areny, Ramon; Rosero, Spencer; Zareba, Wojciech
2017-01-01
Despite the strong evidence of the clinical utility of QTc prolongation as a surrogate marker of cardiac risk, QTc measurement is not part of clinical routine either in hospital or in physician offices. We evaluated a novel device ("the QT scale") to measure heart rate (HR) and QTc interval. The QT scale is a weight scale embedding an ECG acquisition system with four limb sensors (feet and hands: lead I, II, and III). We evaluated the reliability of QT scale in healthy subjects (cohort 1) and cardiac patients (cohorts 2 and 3) considering a learning (cohort 2) and two validation cohorts. The QT scale and the standard 12-lead recorder were compared using intraclass correlation coefficient (ICC) in cohorts 2 and 3. Absolute value of heart rate and QTc intervals between manual and automatic measurements using ECGs from the QT scale and a clinical device were compared in cohort 1. We enrolled 16 subjects in cohort 1 (8 w, 8 m; 32 ± 8 vs 34 ± 10 years, P = 0.7), 51 patients in cohort 2 (13 w, 38 m; 61 ± 16 vs 58 ± 18 years, P = 0.6), and 13 AF patients in cohort 3 (4 w, 9 m; 63 ± 10 vs 64 ± 10 years, P = 0.9). Similar automatic heart rate and QTc were delivered by the scale and the clinical device in cohort 1: paired difference in RR and QTc were -7 ± 34 milliseconds (P = 0.37) and 3.4 ± 28.6 milliseconds (P = 0.64), respectively. The measurement of stability was slightly lower in ECG from the QT scale than from the clinical device (ICC: 91% vs 80%) in cohort 3. The "QT scale device" delivers valid heart rate and QTc interval measurements. © 2016 Wiley Periodicals, Inc.
Wild, Marcus G; Wallston, Kenneth A; Green, Jamie A; Beach, Lauren B; Umeukeje, Ebele; Wright Nunes, Julie A; Ikizler, T Alp; Steed, Julia; Cavanaugh, Kerri L
2017-10-01
Chronic Kidney Disease (CKD) is a major burden on patients and the health care system. Treatment of CKD requires dedicated involvement from both caretakers and patients. Self-efficacy, also known as perceived competence, contributes to successful maintenance of patient's CKD self-management behaviors such as medication adherence and dietary regulations. Despite a clear association between self-efficacy and improved CKD outcomes, there remains a lack of validated self-report measures of CKD self-efficacy. To address this gap, the Perceived Kidney/Dialysis Self-Management Scale (PKDSMS) was adapted from the previously validated Perceived Medical Condition Self-Management Scale. We then sought to validate this using data from two separate cohorts: a cross-sectional investigation of 146 patients with end-stage renal disease receiving maintenance hemodialysis and a longitudinal study of 237 patients with CKD not receiving dialysis. The PKDSMS was found to be positively and significantly correlated with self-management behaviors and medication adherence in both patient cohorts. The PKDSMS had acceptable reliability, was internally consistent, and exhibited predictive validity between baseline PKDSMS scores and self-management behaviors across multiple time points. Thus, the PKDSMS is a valid and reliable measure of CKD patient self-efficacy and supports the development of interventions enhancing perceived competence to improve CKD self-management. Copyright © 2017 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.
Lerche, L; Olsen, A; Petersen, K E N; Rostgaard-Hansen, A L; Dragsted, L O; Nordsborg, N B; Tjønneland, A; Halkjaer, J
2017-12-01
Valid assessments of physical activity (PA) and cardiorespiratory fitness (CRF) are essential in epidemiological studies to define dose-response relationship for formulating thorough recommendations of an appropriate pattern of PA to maintain good health. The aim of this study was to validate the Danish step test, the physical activity questionnaire Active-Q, and self-rated fitness against directly measured maximal oxygen uptake (VO 2 max). A population-based subsample (n=125) was included from the "Diet, Cancer and Health-Next Generations" (DCH-NG) cohort which is under establishment. Validity coefficients, which express the correlation between measured and "true" exposure, were calculated, and misclassification across categories was evaluated. The validity of the Danish step test was moderate (women: r=.66, and men: r=.56); however, men were systematically underestimated (43% misclassification). When validating the questionnaire-derived measures of PA, leisure-time physical activity was not correlated with VO 2 max. Positive correlations were found for sports overall, but these were only significant for men: total hours per week of sports (r=.26), MET-hours per week of sports (r=.28) and vigorous sports (0.28) alone were positively correlated with VO 2 max. Finally, the percentage of misclassification was low for self-rated fitness (women: 9% and men: 13%). Thus, self-rated fitness was found to be a superior method to the Danish step test, as well as being less cost prohibitive and more practical than the VO 2 max method. Finally, even if correlations were low, they support the potential for questionnaire outcomes, particularly sports, vigorous sports, and self-rated fitness to be used to estimate CRF. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Ely, E Wesley; Truman, Brenda; Shintani, Ayumi; Thomason, Jason W W; Wheeler, Arthur P; Gordon, Sharon; Francis, Joseph; Speroff, Theodore; Gautam, Shiva; Margolin, Richard; Sessler, Curtis N; Dittus, Robert S; Bernard, Gordon R
2003-06-11
Goal-directed delivery of sedative and analgesic medications is recommended as standard care in intensive care units (ICUs) because of the impact these medications have on ventilator weaning and ICU length of stay, but few of the available sedation scales have been appropriately tested for reliability and validity. To test the reliability and validity of the Richmond Agitation-Sedation Scale (RASS). Prospective cohort study. Adult medical and coronary ICUs of a university-based medical center. Thirty-eight medical ICU patients enrolled for reliability testing (46% receiving mechanical ventilation) from July 21, 1999, to September 7, 1999, and an independent cohort of 275 patients receiving mechanical ventilation were enrolled for validity testing from February 1, 2000, to May 3, 2001. Interrater reliability of the RASS, Glasgow Coma Scale (GCS), and Ramsay Scale (RS); validity of the RASS correlated with reference standard ratings, assessments of content of consciousness, GCS scores, doses of sedatives and analgesics, and bispectral electroencephalography. In 290-paired observations by nurses, results of both the RASS and RS demonstrated excellent interrater reliability (weighted kappa, 0.91 and 0.94, respectively), which were both superior to the GCS (weighted kappa, 0.64; P<.001 for both comparisons). Criterion validity was tested in 411-paired observations in the first 96 patients of the validation cohort, in whom the RASS showed significant differences between levels of consciousness (P<.001 for all) and correctly identified fluctuations within patients over time (P<.001). In addition, 5 methods were used to test the construct validity of the RASS, including correlation with an attention screening examination (r = 0.78, P<.001), GCS scores (r = 0.91, P<.001), quantity of different psychoactive medication dosages 8 hours prior to assessment (eg, lorazepam: r = - 0.31, P<.001), successful extubation (P =.07), and bispectral electroencephalography (r = 0.63, P<.001). Face validity was demonstrated via a survey of 26 critical care nurses, which the results showed that 92% agreed or strongly agreed with the RASS scoring scheme, and 81% agreed or strongly agreed that the instrument provided a consensus for goal-directed delivery of medications. The RASS demonstrated excellent interrater reliability and criterion, construct, and face validity. This is the first sedation scale to be validated for its ability to detect changes in sedation status over consecutive days of ICU care, against constructs of level of consciousness and delirium, and correlated with the administered dose of sedative and analgesic medications.
Prediction models for successful external cephalic version: a systematic review.
Velzel, Joost; de Hundt, Marcella; Mulder, Frederique M; Molkenboer, Jan F M; Van der Post, Joris A M; Mol, Ben W; Kok, Marjolein
2015-12-01
To provide an overview of existing prediction models for successful ECV, and to assess their quality, development and performance. We searched MEDLINE, EMBASE and the Cochrane Library to identify all articles reporting on prediction models for successful ECV published from inception to January 2015. We extracted information on study design, sample size, model-building strategies and validation. We evaluated the phases of model development and summarized their performance in terms of discrimination, calibration and clinical usefulness. We collected different predictor variables together with their defined significance, in order to identify important predictor variables for successful ECV. We identified eight articles reporting on seven prediction models. All models were subjected to internal validation. Only one model was also validated in an external cohort. Two prediction models had a low overall risk of bias, of which only one showed promising predictive performance at internal validation. This model also completed the phase of external validation. For none of the models their impact on clinical practice was evaluated. The most important predictor variables for successful ECV described in the selected articles were parity, placental location, breech engagement and the fetal head being palpable. One model was assessed using discrimination and calibration using internal (AUC 0.71) and external validation (AUC 0.64), while two other models were assessed with discrimination and calibration, respectively. We found one prediction model for breech presentation that was validated in an external cohort and had acceptable predictive performance. This model should be used to council women considering ECV. Copyright © 2015. Published by Elsevier Ireland Ltd.
Franklin, Jessica M; Donneyong, Macarius M; Desai, Rishi J; Markson, Leona; Girman, Cynthia J; McKay, Caroline; Patel, Mehul D; Mavros, Panagiotis; Schneeweiss, Sebastian
2017-10-01
To assess heterogeneity in adherence to medications in two example comparative effectiveness research studies. We analyzed data from commercially insured patients initiating a statin or anticoagulant during 2005-2012. We calculated the cross-validated R 2 from a series of hierarchical linear models to assess variation in 1-year adherence. There was less heterogeneity in adherence in the statin cohort compared with the anticoagulant cohort, where patient characteristics explained 7.2% of variation in adherence, and adding therapy and provider characteristics increased the proportion of variation explained to 8.0 and 8.5%, cumulatively. Random effects provided essentially no explanatory power, even in the statin cohort with large numbers of patients clustered within each pharmacy, prescriber and provider. The dependence of adherence on the healthcare system was stronger when the healthcare system influenced treatment choice and patient access to medication and when indications for treatment were strong.
van Montfort, Pim; Willemse, Jessica Ppm; Dirksen, Carmen D; van Dooren, Ivo Ma; Meertens, Linda Je; Spaanderman, Marc Ea; Zelis, Maartje; Zwaan, Iris M; Scheepers, Hubertina Cj; Smits, Luc Jm
2018-05-04
Recently, validated risk models predicting adverse obstetric outcomes combined with risk-dependent care paths have been made available for early antenatal care in the southeastern part of the Netherlands. This study will evaluate implementation progress and impact of the new approach in obstetric care. The objective of this paper is to describe the design of a study evaluating the impact of implementing risk-dependent care. Validated first-trimester prediction models are embedded in daily clinical practice and combined with risk-dependent obstetric care paths. A multicenter prospective cohort study consisting of women who receive risk-dependent care is being performed from April 2017 to April 2018 (Expect Study II). Obstetric risk profiles will be calculated using a Web-based tool, the Expect prediction tool. The primary outcomes are the adherence of health care professionals and compliance of women. Secondary outcomes are patient satisfaction and cost-effectiveness. Outcome measures will be established using Web-based questionnaires. The secondary outcomes of the risk-dependent care cohort (Expect II) will be compared with the outcomes of a similar prospective cohort (Expect I). Women of this similar cohort received former care-as-usual and were prospectively included between July 1, 2013 and December 31, 2015 (Expect I). Currently, women are being recruited for the Expect Study II, and a total of 300 women are enrolled. This study will provide information about the implementation and impact of a new approach in obstetric care using prediction models and risk-dependent obstetric care paths. Netherlands Trial Register NTR4143; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4143 (Archived by WebCite at http://www.webcitation.org/6t8ijtpd9). ©Pim van Montfort, Jessica PPM Willemse, Carmen D Dirksen, Ivo MA van Dooren, Linda JE Meertens, Marc EA Spaanderman, Maartje Zelis, Iris M Zwaan, Hubertina CJ Scheepers, Luc JM Smits. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 04.05.2018.
Poirier, Anne-Lise; Kwiatkowski, Fabrice; Commer, Jean-Marie; D'Aillières, Bénédicte; Berger, Virginie; Mercier, Mariette; Bonnetain, Franck
2012-04-20
The end of life for cancer patients is the ultimate stage of the disease, and care in this setting is important as it can improve the wellbeing not only of patients, but also the patients' family and close friends. As it is a matter of profoundly personal concerns, patients' perception of this phase of the disease is difficult to assess and has thus been insufficiently studied. Nonetheless, caregivers are required to provide specific care to help patients and to treat them in order to improve their wellbeing during this period.While tools to assess health-related quality of life (QoL) in cancer patients at the end of life exist in English, to our knowledge, no validated tools are available in French. This randomized multicenter cohort study will be carried out to cross-culturally adapt and validate a French version of the English QUAL-E and the Missoula Vitas Quality Of Life Index (MVQOLI) questionnaires for advanced cancer patients in a palliative setting. A randomized clinical trial component in addition to a cohort study is implemented in order to test psychometric hypotheses: order effect and improvement of sensibility to change.The validation procedure will ensure that the psychometric properties are maintained.The main criterion to assess the reliability of the questionnaires will be reproducibility (test-retest method) using intraclass correlation coefficients. It will be necessary to include 372 patients. The sensitivity to change, discriminant capability as well as convergent validity will be also investigated. If the cross-cultural validation of the MVQOLI and QUAL-E questionnaires for advanced cancer patients in a palliative setting have satisfactory psychometric properties, it will allow us to assess the specific dimensions of QoL at the end of life. Current Controlled Trials NCT01545921.
Nelson, Jennifer C.; Marsh, Tracey; Lumley, Thomas; Larson, Eric B.; Jackson, Lisa A.; Jackson, Michael
2014-01-01
Objective Estimates of treatment effectiveness in epidemiologic studies using large observational health care databases may be biased due to inaccurate or incomplete information on important confounders. Study methods that collect and incorporate more comprehensive confounder data on a validation cohort may reduce confounding bias. Study Design and Setting We applied two such methods, imputation and reweighting, to Group Health administrative data (full sample) supplemented by more detailed confounder data from the Adult Changes in Thought study (validation sample). We used influenza vaccination effectiveness (with an unexposed comparator group) as an example and evaluated each method’s ability to reduce bias using the control time period prior to influenza circulation. Results Both methods reduced, but did not completely eliminate, the bias compared with traditional effectiveness estimates that do not utilize the validation sample confounders. Conclusion Although these results support the use of validation sampling methods to improve the accuracy of comparative effectiveness findings from healthcare database studies, they also illustrate that the success of such methods depends on many factors, including the ability to measure important confounders in a representative and large enough validation sample, the comparability of the full sample and validation sample, and the accuracy with which data can be imputed or reweighted using the additional validation sample information. PMID:23849144
Interpreting SF-12 mental component score: an investigation of its convergent validity with CESD-10.
Yu, Doris S F; Yan, Elsie C W; Chow, Choi Kai
2015-09-01
To examine the convergent validity of Mental Component Scale of the Short-Form 12 (SF-12 MCS) with the Center for Epidemiologic Studies Depression Scale (CESD-10). The CESD-10 is a screening tool for probably clinically significant depression in the Chinese population. Data were obtained from a household survey carried out in Hong Kong. A two-stage stratified sampling method successfully interviewed 1795 adult subjects from 1239 households. Data on SF-12 MCS and the CESD-10 were extracted. Receiver operating characteristics (ROC) analyses were performed to examine the convergent validity of SF-12 MCS against the CESD-10 threshold for probably clinically significant depression for the younger to middle-aged, late middle-aged and older population cohorts. ROC analysis indicated the excellent convergent validity of SF-12 MCS with the CESD-10 threshold for identifying probably clinically significant depression, with the area under curve ranged from 0.81 to 0.85. The optimal cutoff scores for depression among the younger to middle age group, late middle age group and older age group were 48.1, 50.2 and 50.2, respectively, with sensitivities ranged from 77 to 83 % and specificities ranged from 73 to 78 %. Bootstrapping estimates of the mean difference indicated no significant difference in the optimal cutoff scores between these age cohorts. SF-12 is a widely adopted measure to capture the health profile of Chinese population. The study findings indicated the satisfactory performance of the SF-12 MCS in identifying probably clinical depression. Future study is warrant to examine the diagnostic validity of the SF-12 MCS by using gold standard to assess clinical depression.
Jalan, Rajiv; Saliba, Faouzi; Pavesi, Marco; Amoros, Alex; Moreau, Richard; Ginès, Pere; Levesque, Eric; Durand, Francois; Angeli, Paolo; Caraceni, Paolo; Hopf, Corinna; Alessandria, Carlo; Rodriguez, Ezequiel; Solis-Muñoz, Pablo; Laleman, Wim; Trebicka, Jonel; Zeuzem, Stefan; Gustot, Thierry; Mookerjee, Rajeshwar; Elkrief, Laure; Soriano, German; Cordoba, Joan; Morando, Filippo; Gerbes, Alexander; Agarwal, Banwari; Samuel, Didier; Bernardi, Mauro; Arroyo, Vicente
2014-11-01
Acute-on-chronic liver failure (ACLF) is a frequent syndrome (30% prevalence), characterized by acute decompensation of cirrhosis, organ failure(s) and high short-term mortality. This study develops and validates a specific prognostic score for ACLF patients. Data from 1349 patients included in the CANONIC study were used. First, a simplified organ function scoring system (CLIF Consortium Organ Failure score, CLIF-C OFs) was developed to diagnose ACLF using data from all patients. Subsequently, in 275 patients with ACLF, CLIF-C OFs and two other independent predictors of mortality (age and white blood cell count) were combined to develop a specific prognostic score for ACLF (CLIF Consortium ACLF score [CLIF-C ACLFs]). A concordance index (C-index) was used to compare the discrimination abilities of CLIF-C ACLF, MELD, MELD-sodium (MELD-Na), and Child-Pugh (CPs) scores. The CLIF-C ACLFs was validated in an external cohort and assessed for sequential use. The CLIF-C ACLFs showed a significantly higher predictive accuracy than MELDs, MELD-Nas, and CPs, reducing (19-28%) the corresponding prediction error rates at all main time points after ACLF diagnosis (28, 90, 180, and 365 days) in both the CANONIC and the external validation cohort. CLIF-C ACLFs computed at 48 h, 3-7 days, and 8-15 days after ACLF diagnosis predicted the 28-day mortality significantly better than at diagnosis. The CLIF-C ACLFs at ACLF diagnosis is superior to the MELDs and MELD-Nas in predicting mortality. The CLIF-C ACLFs is a clinically relevant, validated scoring system that can be used sequentially to stratify the risk of mortality in ACLF patients. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.
Janković, Slavenka; Vukićević, Jelica; Djordjević, Sanja; Janković, Janko; Marinković, Jelena; Erić, Miloš
2013-01-01
The Children's Dermatology Life Quality Index (CDLQI) evaluates the impact of skin diseases on the patient's quality of life. The purpose of the study was to translate and to validate the CDLQI into Serbian. The CDLQI was translated into Serbian following international recommendations for translation and cultural adaptation. The validation study was carried out on a large cohort of secondary schoolchildren who self-reported acne. Translating the CDLQI consisted of forward translation, reconciliation, back translation, back-translation review, and cognitive debriefing. The good internal consistency of the scale was demonstrated with a Cronbach alpha coefficient of 0.87. A Spearman correlation coefficient of 0.66 between the CDLQI and the Cardiff Acne Disability Index (CADI) was deemed satisfactory to demonstrate concurrent validity. The translation, cross-cultural adaptation, and psychometric qualities of the CDLQI were satisfactory, enabling its application in clinical practice and future studies.
Using microRNA profiling in urine samples to develop a non-invasive test for bladder cancer.
Mengual, Lourdes; Lozano, Juan José; Ingelmo-Torres, Mercedes; Gazquez, Cristina; Ribal, María José; Alcaraz, Antonio
2013-12-01
Current standard methods used to detect and monitor bladder urothelial cell carcinoma (UCC) are invasive or have low sensitivity. The incorporation into clinical practice of a non-invasive tool for UCC assessment would enormously improve patients' quality of life and outcome. This study aimed to examine the microRNA (miRNA) expression profiles in urines of UCC patients in order to develop a non-invasive accurate and reliable tool to diagnose and provide information on the aggressiveness of the tumor. We performed a global miRNA expression profiling analysis of the urinary cells from 40 UCC patients and controls using TaqMan Human MicroRNA Array followed by validation of 22 selected potentially diagnostic and prognostic miRNAs in a separate cohort of 277 samples using a miRCURY LNA qPCR system. miRNA-based signatures were developed by multivariate logistic regression analysis and internally cross-validated. In the initial cohort of patients, we identified 40 and 30 aberrantly expressed miRNA in UCC compared with control urines and in high compared with low grade tumors, respectively. Quantification of 22 key miRNAs in an independent cohort resulted in the identification of a six miRNA diagnostic signature with a sensitivity of 84.8% and specificity of 86.5% (AUC = 0.92) and a two miRNA prognostic model with a sensitivity of 84.95% and a specificity of 74.14% (AUC = 0.83). Internal cross-validation analysis confirmed the accuracy rates of both models, reinforcing the strength of our findings. Although the data needs to be externally validated, miRNA analysis in urine appears to be a valuable tool for the non-invasive assessment of UCC. Copyright © 2013 UICC.
Ong, Chin-Ann J.; Shapiro, Joel; Nason, Katie S.; Davison, Jon M.; Liu, Xinxue; Ross-Innes, Caryn; O'Donovan, Maria; Dinjens, Winand N.M.; Biermann, Katharina; Shannon, Nicholas; Worster, Susannah; Schulz, Laura K.E.; Luketich, James D.; Wijnhoven, Bas P.L.; Hardwick, Richard H.; Fitzgerald, Rebecca C.
2013-01-01
Purpose Esophageal adenocarcinoma (EAC) is a highly aggressive disease with poor long-term survival. Despite growing knowledge of its biology, no molecular biomarkers are currently used in routine clinical practice to determine prognosis or aid clinical decision making. Hence, this study set out to identify and validate a small, clinically applicable immunohistochemistry (IHC) panel for prognostication in patients with EAC. Patients and Methods We recently identified eight molecular prognostic biomarkers using two different genomic platforms. IHC scores of these biomarkers from a UK multicenter cohort (N = 374) were used in univariate Cox regression analysis to determine the smallest biomarker panel with the greatest prognostic power with potential therapeutic relevance. This new panel was validated in two independent cohorts of patients with EAC who had undergone curative esophagectomy from the United States and Europe (N = 666). Results Three of the eight previously identified prognostic molecular biomarkers (epidermal growth factor receptor [EGFR], tripartite motif-containing 44 [TRIM44], and sirtuin 2 [SIRT2]) had the strongest correlation with long-term survival in patients with EAC. Applying these three biomarkers as an IHC panel to the validation cohort segregated patients into two different prognostic groups (P < .01). Adjusting for known survival covariates, including clinical staging criteria, the IHC panel remained an independent predictor, with incremental adverse overall survival (OS) for each positive biomarker (hazard ratio, 1.20; 95% CI, 1.03 to 1.40 per biomarker; P = .02). Conclusion We identified and validated a clinically applicable IHC biomarker panel, consisting of EGFR, TRIM44, and SIRT2, that is independently associated with OS and provides additional prognostic information to current survival predictors such as stage. PMID:23509313
Seisen, Thomas; Colin, Pierre; Hupertan, Vincent; Yates, David R; Xylinas, Evanguelos; Nison, Laurent; Cussenot, Olivier; Neuzillet, Yann; Bensalah, Karim; Novara, Giacomo; Montorsi, Francesco; Zigeuner, Richard; Remzi, Mesut; Shariat, Shahrokh F; Rouprêt, Morgan
2014-11-01
To propose and validate a nomogram to predict cancer-specific survival (CSS) after radical nephroureterectomy (RNU) in patients with pT1-3/N0-x upper tract urothelial carcinoma (UTUC). The international and the French national collaborative groups on UTUC pooled data from 3387 patients treated with RNU. Only 2233 chemotherapy naïve pT1-3/N0-x patients were included in the present study. The population was randomly split into the development cohort (1563) and the external validation cohort (670). To build the nomogram, logistic regressions were used for univariable and multivariable analyses. Different models were generated. The most accurate model was assessed using Harrell's concordance index and decision curve analysis (DCA). Internal validation was then performed by bootstrapping. Finally, the nomogram was calibrated and externally validated in the external dataset. Of the 1563 patients in the nomogram development cohort, 309 (19.7%) died during follow-up from UTUC. The actuarial CSS probability at 5 years was 75.7% (95% confidence interval [CI] 73.2-78.6%). DCA revealed that the use of the best model was associated with benefit gains relative to prediction of CSS. The optimised nomogram included only six variables associated with CSS in multivariable analysis: age (P < 0.001), pT stage (P < 0.001), grade (P < 0.02), location (P < 0.001), architecture (P < 0.001) and lymphovascular invasion (P < 0.001). The accuracy of the nomogram was 0.81 (95% CI, 0.78-0.85). Limitations included the retrospective study design and the lack of a central pathological review. An accurate postoperative nomogram was developed to predict CSS after RNU only in locally and/or locally advanced UTUC without metastasis, where the decision for adjuvant treatment is controversial but crucial for the oncological outcome. © 2014 The Authors. BJU International © 2014 BJU International.
Eaton, John E; Vesterhus, Mette; McCauley, Bryan M; Atkinson, Elizabeth J; Schlicht, Erik M; Juran, Brian D; Gossard, Andrea A; LaRusso, Nicholas F; Gores, Gregory J; Karlsen, Tom H; Lazaridis, Konstantinos N
2018-05-09
Improved methods are needed to risk stratify and predict outcomes in patients with primary sclerosing cholangitis (PSC). Therefore, we sought to derive and validate a new prediction model and compare its performance to existing surrogate markers. The model was derived using 509 subjects from a multicenter North American cohort and validated in an international multicenter cohort (n=278). Gradient boosting, a machine based learning technique, was used to create the model. The endpoint was hepatic decompensation (ascites, variceal hemorrhage or encephalopathy). Subjects with advanced PSC or cholangiocarcinoma at baseline were excluded. The PSC risk estimate tool (PREsTo) consists of 9 variables: bilirubin, albumin, serum alkaline phosphatase (SAP) times the upper limit of normal (ULN), platelets, AST, hemoglobin, sodium, patient age and the number of years since PSC was diagnosed. Validation in an independent cohort confirms PREsTo accurately predicts decompensation (C statistic 0.90, 95% confidence interval (CI) 0.84-0.95) and performed well compared to MELD score (C statistic 0.72, 95% CI 0.57-0.84), Mayo PSC risk score (C statistic 0.85, 95% CI 0.77-0.92) and SAP < 1.5x ULN (C statistic 0.65, 95% CI 0.55-0.73). PREsTo continued to be accurate among individuals with a bilirubin < 2.0 mg/dL (C statistic 0.90, 95% CI 0.82-0.96) and when the score was re-applied at a later course in the disease (C statistic 0.82, 95% CI 0.64-0.95). PREsTo accurately predicts hepatic decompensation in PSC and exceeds the performance among other widely available, noninvasive prognostic scoring systems. This article is protected by copyright. All rights reserved. © 2018 by the American Association for the Study of Liver Diseases.
The Minimum Data Set 3.0 Cognitive Function Scale.
Thomas, Kali S; Dosa, David; Wysocki, Andrea; Mor, Vincent
2017-09-01
The Minimum Data Set (MDS) 3.0 introduced the Brief Interview for Mental Status (BIMS), a short performance-based cognitive screener for nursing home (NH) residents. Not all residents are able to complete the BIMS and are consequently assessed by staff. We designed a Cognitive Function Scale (CFS) integrating self-report and staff-report data and present evidence of the scale's construct validity. A retrospective cohort study. The subjects consisted of 3 cohorts: (1) long-stay NH residents (N=941,077) and (2) new admissions (N=2,066,580) during 2011-2012, and (3) residents with the older MDS 2.0 assessment in 2010 and the newer MDS 3.0 assessment (n=688,511). MDS 3.0 items were used to create a single, integrated 4-category hierarchical CFS that was compared with residents' prior MDS 2.0 Cognitive Performance Scale scores and other concurrent MDS 3.0 measures of construct validity. The new CFS suggests that 28% of the long-stay cohort in 2011-2012 were cognitively intact, 22% were mildly impaired, 33% were moderately impaired, and 17% were severely impaired. For the admission cohort, the CFS noted 56% as cognitively intact, 23% as mildly impaired, 17% as moderately impaired, and 4% as severely impaired. The CFS corresponded closely with residents' prior MDS 2.0 Cognitive Performance Scale scores and with performance of Activities of Daily Living, and nurses' judgments of function and behavior in both the admission and long-stay cohorts. The new CFS is valuable to researchers as it provides a single, integrated measure of NH residents' cognitive function, regardless of the mode of assessment.
Wong, E T; Lok, E; Gautam, S; Swanson, K D
2015-01-01
Background: Patients with recurrent glioblastoma have a poor outcome. Data from the phase III registration trial comparing tumour-treating alternating electric fields (TTFields) vs chemotherapy provided a unique opportunity to study dexamethasone effects on patient outcome unencumbered by the confounding immune and myeloablative side effects of chemotherapy. Methods: Using an unsupervised binary partitioning algorithm, we segregated both cohorts of the trial based on the dexamethasone dose that yielded the greatest statistical difference in overall survival (OS). The results were validated in a separate cohort treated in a single institution with TTFields and their T lymphocytes were correlated with OS. Results: Patients who used dexamethasone doses >4.1 mg per day had a significant reduction in OS when compared with those who used ⩽4.1 mg per day, 4.8 vs 11.0 months respectively (χ2=34.6, P<0.0001) in the TTField-treated cohort and 6.0 vs 8.9 months respectively (χ2=10.0, P<0.0015) in the chemotherapy-treated cohort. In a single institution validation cohort treated with TTFields, the median OS of patients who used dexamethasone >4.1 mg per day was 3.2 months compared with those who used ⩽4.1 mg per day was 8.7 months (χ2=11.1, P=0.0009). There was a significant correlation between OS and T-lymphocyte counts. Conclusions: Dexamethasone exerted profound effects on both TTFields and chemotherapy efficacy resulting in lower patient OS. Therefore, global immunosuppression by dexamethasone likely interferes with immune functions that are necessary for the treatment of glioblastoma. PMID:26125449
Okazaki, Satoshi; Schirripa, Marta; Loupakis, Fotios; Cao, Shu; Zhang, Wu; Yang, Dongyun; Ning, Yan; Berger, Martin D; Miyamoto, Yuji; Suenaga, Mitsukuni; Iqubal, Syma; Barzi, Afsaneh; Cremolini, Chiara; Falcone, Alfredo; Battaglin, Francesca; Salvatore, Lisa; Borelli, Beatrice; Helentjaris, Timothy G; Lenz, Heinz-Josef
2017-11-15
The hypermethylated in cancer 1/sirtuin 1 (HIC1/SIRT1) axis plays an important role in regulating the nucleotide excision repair pathway, which is the main oxaliplatin-induced damage-repair system. On the basis of prior evidence that the variable number of tandem repeat (VNTR) sequence located near the promoter lesion of HIC1 is associated with HIC1 gene expression, the authors tested the hypothesis that this VNTR is associated with clinical outcome in patients with metastatic colorectal cancer who receive oxaliplatin-based chemotherapy. Four independent cohorts were tested. Patients who received oxaliplatin-based chemotherapy served as the training cohort (n = 218), and those who received treatment without oxaliplatin served as the control cohort (n = 215). Two cohorts of patients who received oxaliplatin-based chemotherapy were used for validation studies (n = 176 and n = 73). The VNTR sequence near HIC1 was analyzed by polymerase chain reaction analysis and gel electrophoresis and was tested for associations with the response rate, progression-free survival, and overall survival. In the training cohort, patients who harbored at least 5 tandem repeats (TRs) in both alleles had a significantly shorter PFS compared with those who had fewer than 4 TRs in at least 1 allele (9.5 vs 11.6 months; hazard ratio, 1.93; P = .012), and these findings remained statistically significant after multivariate analysis (hazard ratio, 2.00; 95% confidence interval, 1.13-3.54; P = .018). This preliminary association was confirmed in the validation cohort, and patients who had at least 5 TRs in both alleles had a worse PFS compared with the other cohort (7.9 vs 9.8 months; hazard ratio, 1.85; P = .044). The current findings suggest that the VNTR sequence near HIC1 could be a predictive marker for oxaliplatin-based chemotherapy in patients with metastatic colorectal cancer. Cancer 2017;123:4506-14. © 2017 American Cancer Society. © 2017 American Cancer Society.
Olivares, Josefina; Wang, Jack; Yu, Wen; Pereg, Vicente; Weil, Richard; Kovacs, Betty; Gallagher, Dympna; Pi-Sunyer, F. Xavier
2007-01-01
Background We studied whether significant differences exist between Hispanic-Americans (H-A) and Caucasian-Americans (C-A) in body dimensions using a newly validated three-dimensional photonic scanner (3DPS). Methods We compared two cohorts of 34 adult U.S.-based H-A (19 females) and 40 adult C-A (25 females) of similar age and body mass index (BMI, kg/m2). We measured total body volume (TBV), trunk volume (TV), and other body dimensions, including waist and hip circumferences, estimated percentage body fat (%fat), calculated TV/TBV, and waist-to-hip ratio. Results For female cohorts, there were no significant differences in age, weight, height, and 3DPS-measured variables between the two ethnic cohorts. For male cohorts, C-A had greater height (p = 0.014), but there were no significant differences in absolute or proportional volumes or dimensions between the two cohorts. Conclusions Results demonstrate that, in these H-A and C-A cohorts of similar age and BMI, total and regional body volumes and dimensions, as well as their proportions, approximate each other very closely in both sexes; these variables also show similar relationships with %fat in each sex. This is in contradistinction to previous study reports using other measurement techniques. PMID:19885167
Choo, Min Soo; Yoo, Changwon; Cho, Sung Yong; Jeong, Seong Jin; Jeong, Chang Wook; Ku, Ja Hyeon; Oh, Seung-June
2017-04-01
As the elderly population increases, a growing number of patients have lower urinary tract symptom (LUTS)/benign prostatic hyperplasia (BPH). The aim of this study was to develop decision support formulas and nomograms for the prediction of bladder outlet obstruction (BOO) and for BOO-related surgical decision-making, and to validate them in patients with LUTS/BPH. Patient with LUTS/BPH between October 2004 and May 2014 were enrolled as a development cohort. The available variables included age, International Prostate Symptom Score, free uroflowmetry, postvoid residual volume, total prostate volume, and the results of a pressure-flow study. A causal Bayesian network analysis was used to identify relevant parameters. Using multivariate logistic regression analysis, formulas were developed to calculate the probabilities of having BOO and requiring prostatic surgery. Patients between June 2014 and December 2015 were prospectively enrolled for internal validation. Receiver operating characteristic curve analysis, calibration plots, and decision curve analysis were performed. A total of 1,179 male patients with LUTS/BPH, with a mean age of 66.1 years, were included as a development cohort. Another 253 patients were enrolled as an internal validation cohort. Using multivariate logistic regression analysis, 2 and 4 formulas were established to estimate the probabilities of having BOO and requiring prostatic surgery, respectively. Our analysis of the predictive accuracy of the model revealed area under the curve values of 0.82 for BOO and 0.87 for prostatic surgery. The sensitivity and specificity were 53.6% and 87.0% for BOO, and 91.6% and 50.0% for prostatic surgery, respectively. The calibration plot indicated that these prediction models showed a good correspondence. In addition, the decision curve analysis showed a high net benefit across the entire spectrum of probability thresholds. We established nomograms for the prediction of BOO and BOO-related prostatic surgery in patients with LUTS/BPH. Internal validation of the nomograms demonstrated that they predicted both having BOO and requiring prostatic surgery very well.
Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights.
Pasolli, Edoardo; Truong, Duy Tin; Malik, Faizan; Waldron, Levi; Segata, Nicola
2016-07-01
Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction tasks using quantitative microbiome profiles, including species-level relative abundances and presence of strain-specific markers. A comprehensive meta-analysis, with particular emphasis on generalization across cohorts, was performed in a collection of 2424 publicly available metagenomic samples from eight large-scale studies. Cross-validation revealed good disease-prediction capabilities, which were in general improved by feature selection and use of strain-specific markers instead of species-level taxonomic abundance. In cross-study analysis, models transferred between studies were in some cases less accurate than models tested by within-study cross-validation. Interestingly, the addition of healthy (control) samples from other studies to training sets improved disease prediction capabilities. Some microbial species (most notably Streptococcus anginosus) seem to characterize general dysbiotic states of the microbiome rather than connections with a specific disease. Our results in modelling features of the "healthy" microbiome can be considered a first step toward defining general microbial dysbiosis. The software framework, microbiome profiles, and metadata for thousands of samples are publicly available at http://segatalab.cibio.unitn.it/tools/metaml.
The BioFIND study: Characteristics of a clinically typical Parkinson's disease biomarker cohort
Goldman, Jennifer G.; Alcalay, Roy N.; Xie, Tao; Tuite, Paul; Henchcliffe, Claire; Hogarth, Penelope; Amara, Amy W.; Frank, Samuel; Rudolph, Alice; Casaceli, Cynthia; Andrews, Howard; Gwinn, Katrina; Sutherland, Margaret; Kopil, Catherine; Vincent, Lona; Frasier, Mark
2016-01-01
ABSTRACT Background Identifying PD‐specific biomarkers in biofluids will greatly aid in diagnosis, monitoring progression, and therapeutic interventions. PD biomarkers have been limited by poor discriminatory power, partly driven by heterogeneity of the disease, variability of collection protocols, and focus on de novo, unmedicated patients. Thus, a platform for biomarker discovery and validation in well‐characterized, clinically typical, moderate to advanced PD cohorts is critically needed. Methods BioFIND (Fox Investigation for New Discovery of Biomarkers in Parkinson's Disease) is a cross‐sectional, multicenter biomarker study that established a repository of clinical data, blood, DNA, RNA, CSF, saliva, and urine samples from 118 moderate to advanced PD and 88 healthy control subjects. Inclusion criteria were designed to maximize diagnostic specificity by selecting participants with clinically typical PD symptoms, and clinical data and biospecimen collection utilized standardized procedures to minimize variability across sites. Results We present the study methodology and data on the cohort's clinical characteristics. Motor scores and biospecimen samples including plasma are available for practically defined off and on states and thus enable testing the effects of PD medications on biomarkers. Other biospecimens are available from off state PD assessments and from controls. Conclusion Our cohort provides a valuable resource for biomarker discovery and validation in PD. Clinical data and biospecimens, available through The Michael J. Fox Foundation for Parkinson's Research and the National Institute of Neurological Disorders and Stroke, can serve as a platform for discovering biomarkers in clinically typical PD and comparisons across PD's broad and heterogeneous spectrum. © 2016 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society PMID:27113479
Fridell, Mats; Hesse, Morten; Jaeger, Mads Meier; Kühlhorn, Eckart
2008-06-01
Mixed findings have been made with regard to the long-term predictive validity of antisocial personality disorder (ASPD) on criminal behaviour in samples of substance abusers. A longitudinal record-linkage study of a cohort of 1052 drug abusers admitted 1977-1995 was undertaken. Subjects were recruited from a detoxification and short-term rehabilitation unit in Lund, Sweden, and followed through criminal justice registers from their first treatment episode to death or to the year 2004. In a ML multinomial random effects regression, subjects diagnosed with antisocial personality disorders were 2.16 times more likely to be charged with theft only (p<0.001), and 2.44 times more likely to be charged committing multiple types of crime during an observation year (p<0.001). The findings of the current study support the predictive validity of the DSM-III-R diagnosis of ASPD. ASPD should be taken seriously in drug abusers, and be targeted in treatment to prevent crime in society.
A nomogram to predict the survival of stage IIIA-N2 non-small cell lung cancer after surgery.
Mao, Qixing; Xia, Wenjie; Dong, Gaochao; Chen, Shuqi; Wang, Anpeng; Jin, Guangfu; Jiang, Feng; Xu, Lin
2018-04-01
Postoperative survival of patients with stage IIIA-N2 non-small cell lung cancer (NSCLC) is highly heterogeneous. Here, we aimed to identify variables associated with postoperative survival and develop a tool for survival prediction. A retrospective review was performed in the Surveillance, Epidemiology, and End Results database from January 2004 to December 2009. Significant variables were selected by use of the backward stepwise method. The nomogram was constructed with multivariable Cox regression. The model's performance was evaluated by concordance index and calibration curve. The model was validated via an independent cohort from the Jiangsu Cancer Hospital Lung Cancer Center. A total of 1809 patients with stage IIIA-N2 NSCLC who underwent surgery were included in the training cohort. Age, sex, grade, histology, tumor size, visceral pleural invasion, positive lymph nodes, lymph nodes examined, and surgery type (lobectomy vs pneumonectomy) were identified as significant prognostic variables using backward stepwise method. A nomogram was developed from the training cohort and validated using an independent Chinese cohort. The concordance index of the model was 0.673 (95% confidence interval, 0.654-0.692) in training cohort and 0.664 in validation cohort (95% confidence interval, 0.614-0.714). The calibration plot showed optimal consistency between nomogram predicted survival and observed survival. Survival analyses demonstrated significant differences between different subgroups stratified by prognostic scores. This nomogram provided the individual survival prediction for patients with stage IIIA-N2 NSCLC after surgery, which might benefit survival counseling for patients and clinicians, clinical trial design and follow-up, as well as postoperative strategy-making. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.
Serum microRNAs as biomarkers for recurrence in melanoma
2012-01-01
Background Identification of melanoma patients at high risk for recurrence and monitoring for recurrence are critical for informed management decisions. We hypothesized that serum microRNAs (miRNAs) could provide prognostic information at the time of diagnosis unaccounted for by the current staging system and could be useful in detecting recurrence after resection. Methods We screened 355 miRNAs in sera from 80 melanoma patients at primary diagnosis (discovery cohort) using a unique quantitative reverse transcription-PCR (qRT-PCR) panel. Cox proportional hazard models and Kaplan-Meier recurrence-free survival (RFS) curves were used to identify a miRNA signature with prognostic potential adjusting for stage. We then tested the miRNA signature in an independent cohort of 50 primary melanoma patients (validation cohort). Logistic regression analysis was performed to determine if the miRNA signature can determine risk of recurrence in both cohorts. Selected miRNAs were measured longitudinally in subsets of patients pre-/post-operatively and pre-/post-recurrence. Results A signature of 5 miRNAs successfully classified melanoma patients into high and low recurrence risk groups with significant separation of RFS in both discovery and validation cohorts (p = 0.0036, p = 0.0093, respectively). Significant separation of RFS was maintained when a logistic model containing the same signature set was used to predict recurrence risk in both discovery and validation cohorts (p < 0.0001, p = 0.033, respectively). Longitudinal expression of 4 miRNAs in a subset of patients was dynamic, suggesting miRNAs can be associated with tumor burden. Conclusion Our data demonstrate that serum miRNAs can improve accuracy in identifying primary melanoma patients with high recurrence risk and in monitoring melanoma tumor burden over time. PMID:22857597
Validity of the Medical College Admission Test for predicting MD-PhD student outcomes.
Bills, James L; VanHouten, Jacob; Grundy, Michelle M; Chalkley, Roger; Dermody, Terence S
2016-03-01
The Medical College Admission Test (MCAT) is a quantitative metric used by MD and MD-PhD programs to evaluate applicants for admission. This study assessed the validity of the MCAT in predicting training performance measures and career outcomes for MD-PhD students at a single institution. The study population consisted of 153 graduates of the Vanderbilt Medical Scientist Training Program (combined MD-PhD program) who matriculated between 1963 and 2003 and completed dual-degree training. This population was divided into three cohorts corresponding to the version of the MCAT taken at the time of application. Multivariable regression (logistic for binary outcomes and linear for continuous outcomes) was used to analyze factors associated with outcome measures. The MCAT score and undergraduate GPA (uGPA) were treated as independent variables; medical and graduate school grades, time-to-PhD defense, USMLE scores, publication number, and career outcome were dependent variables. For cohort 1 (1963-1977), MCAT score was not associated with any assessed outcome, although uGPA was associated with medical school preclinical GPA and graduate school GPA (gsGPA). For cohort 2 (1978-1991), MCAT score was associated with USMLE Step II score and inversely correlated with publication number, and uGPA was associated with preclinical GPA (mspGPA) and clinical GPA (mscGPA). For cohort 3 (1992-2003), the MCAT score was associated with mscGPA, and uGPA was associated with gsGPA. Overall, MCAT score and uGPA were inconsistent or weak predictors of training metrics and career outcomes for this population of MD-PhD students.
Ma, Xu; He, Zhijuan; Li, Ling; Yang, Daping; Liu, Guofeng
2017-09-29
Recent advancements in cancer biology have identified a large number of lncRNAs that are dysregulated expression in the development and tumorigenesis of cancers, highlighting the importance of lncRNAs as a key player for human cancers. However, the prognostic value of lncRNAs still remains unclear and needs to be further investigated. In the present study, we aim to assess the prognostic value of lncRNAs in cutaneous melanoma by integrated lncRNA expression profiles from TCGA database and matched clinical information from a large cohort of patients with cutaneous melanoma. We finally identified a set of six lncRNAs that are significantly associated with survival of patients with cutaneous melanoma. A linear combination of six lncRNAs ( LINC01260, HCP5, PIGBOS1, RP11-247L20.4, CTA-292E10.6 and CTB-113P19.5 ) was constructed as a six-lncRNA signature which classified patients of training cohort into the high-risk group and low-risk group with significantly different survival time. The prognostic value of the six-lncRNA signature was validated in both the validation cohort and entire TCGA cohort. Moreover, the six-lncRNA signature is independent of known clinic-pathological factors by multivariate Cox regression analysis and demonstrated good performance for predicting three- and five-year overall survival by time-dependent receiver operating characteristic (ROC) analysis. Our study provides novel insights into the molecular heterogeneity of cutaneous melanoma and also shows potentially important implications of lncRNAs for prognosis and therapy for cutaneous melanoma.
Cox, Zachary L; Lai, Pikki; Lewis, Connie M; Lindenfeld, JoAnn; Collins, Sean P; Lenihan, Daniel J
2018-05-28
Nationally-derived models predicting 30-day readmissions following heart failure (HF) hospitalizations yield insufficient discrimination for institutional use. Develop a customized readmission risk model from Medicare-employed and institutionally-customized risk factors and compare the performance against national models in a medical center. Medicare patients age ≥ 65 years hospitalized for HF (n = 1,454) were studied in a derivation cohort and in a separate validation cohort (n = 243). All 30-day hospital readmissions were documented. The primary outcome was risk discrimination (c-statistic) compared to national models. A customized model demonstrated improved discrimination (c-statistic 0.72; 95% CI 0.69 - 0.74) compared to national models (c-statistics of 0.60 and 0.61) with a c-statistic of 0.63 in the validation cohort. Compared to national models, a customized model demonstrated superior readmission risk profiling by distinguishing a high-risk (38.3%) from a low-risk (9.4%) quartile. A customized model improved readmission risk discrimination from HF hospitalizations compared to national models. Copyright © 2018 Elsevier Inc. All rights reserved.
External Validation of the Updated Partin Tables in a Cohort of French and Italian Men
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bhojani, Naeem; Department of Urology, University of Montreal, Montreal, PQ; Salomon, Laurent
2009-02-01
Purpose: To test the discrimination and calibration properties of the newly developed 2007 Partin Tables in two European cohorts with localized prostate cancer. Methods: Data on clinical and pathologic characteristics were obtained for 1,064 men treated with radical prostatectomy at the Creteil University Health Center in France (n = 839) and at the Milan University Vita-Salute in Italy (n = 225). Overall discrimination was assessed with receiver operating characteristic curve analysis, which quantified the accuracy of stage predictions for each center. Calibration plots graphically explored the relationship between predicted and observed rates of extracapsular extension (ECE), seminal vesicle invasion (SVI)more » and lymph node invasion (LNI). Results: The rates of ECE, SVI, and LNI were 28%, 14%, and 2% in the Creteil cohort vs. 11%, 5%, and 5% in the Milan cohort. In the Creteil cohort, the accuracy of ECE, SVI, and LNI prediction was 61%, 71%, and 82% vs. 66%, 92% and 75% for the Milan cohort. Important departures were recorded between Partin Tables' predicted and observed rates of ECE, SVI, and LNI within both cohorts. Conclusions: The 2007 Partin Tables demonstrated worse performance in European men than they originally did in North American men. This indicates that predictive models need to be externally validated before their implementation into clinical practice.« less
Ban, Jong-Wook; Emparanza, José Ignacio; Urreta, Iratxe; Burls, Amanda
2016-01-01
Background Many new clinical prediction rules are derived and validated. But the design and reporting quality of clinical prediction research has been less than optimal. We aimed to assess whether design characteristics of validation studies were associated with the overestimation of clinical prediction rules’ performance. We also aimed to evaluate whether validation studies clearly reported important methodological characteristics. Methods Electronic databases were searched for systematic reviews of clinical prediction rule studies published between 2006 and 2010. Data were extracted from the eligible validation studies included in the systematic reviews. A meta-analytic meta-epidemiological approach was used to assess the influence of design characteristics on predictive performance. From each validation study, it was assessed whether 7 design and 7 reporting characteristics were properly described. Results A total of 287 validation studies of clinical prediction rule were collected from 15 systematic reviews (31 meta-analyses). Validation studies using case-control design produced a summary diagnostic odds ratio (DOR) 2.2 times (95% CI: 1.2–4.3) larger than validation studies using cohort design and unclear design. When differential verification was used, the summary DOR was overestimated by twofold (95% CI: 1.2 -3.1) compared to complete, partial and unclear verification. The summary RDOR of validation studies with inadequate sample size was 1.9 (95% CI: 1.2 -3.1) compared to studies with adequate sample size. Study site, reliability, and clinical prediction rule was adequately described in 10.1%, 9.4%, and 7.0% of validation studies respectively. Conclusion Validation studies with design shortcomings may overestimate the performance of clinical prediction rules. The quality of reporting among studies validating clinical prediction rules needs to be improved. PMID:26730980
Ban, Jong-Wook; Emparanza, José Ignacio; Urreta, Iratxe; Burls, Amanda
2016-01-01
Many new clinical prediction rules are derived and validated. But the design and reporting quality of clinical prediction research has been less than optimal. We aimed to assess whether design characteristics of validation studies were associated with the overestimation of clinical prediction rules' performance. We also aimed to evaluate whether validation studies clearly reported important methodological characteristics. Electronic databases were searched for systematic reviews of clinical prediction rule studies published between 2006 and 2010. Data were extracted from the eligible validation studies included in the systematic reviews. A meta-analytic meta-epidemiological approach was used to assess the influence of design characteristics on predictive performance. From each validation study, it was assessed whether 7 design and 7 reporting characteristics were properly described. A total of 287 validation studies of clinical prediction rule were collected from 15 systematic reviews (31 meta-analyses). Validation studies using case-control design produced a summary diagnostic odds ratio (DOR) 2.2 times (95% CI: 1.2-4.3) larger than validation studies using cohort design and unclear design. When differential verification was used, the summary DOR was overestimated by twofold (95% CI: 1.2 -3.1) compared to complete, partial and unclear verification. The summary RDOR of validation studies with inadequate sample size was 1.9 (95% CI: 1.2 -3.1) compared to studies with adequate sample size. Study site, reliability, and clinical prediction rule was adequately described in 10.1%, 9.4%, and 7.0% of validation studies respectively. Validation studies with design shortcomings may overestimate the performance of clinical prediction rules. The quality of reporting among studies validating clinical prediction rules needs to be improved.
Haile, Sarah R; Guerra, Beniamino; Soriano, Joan B; Puhan, Milo A
2017-12-21
Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them. Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC) which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD) arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined. We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small. We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties of clinical scores. Our large-scale external validation indicates that the scores with the best discriminative properties to predict 3 year mortality in patients with COPD are ADO and eBODE.
Prediction of prostate cancer in unscreened men: external validation of a risk calculator.
van Vugt, Heidi A; Roobol, Monique J; Kranse, Ries; Määttänen, Liisa; Finne, Patrik; Hugosson, Jonas; Bangma, Chris H; Schröder, Fritz H; Steyerberg, Ewout W
2011-04-01
Prediction models need external validation to assess their value beyond the setting where the model was derived from. To assess the external validity of the European Randomized study of Screening for Prostate Cancer (ERSPC) risk calculator (www.prostatecancer-riskcalculator.com) for the probability of having a positive prostate biopsy (P(posb)). The ERSPC risk calculator was based on data of the initial screening round of the ERSPC section Rotterdam and validated in 1825 and 531 men biopsied at the initial screening round in the Finnish and Swedish sections of the ERSPC respectively. P(posb) was calculated using serum prostate specific antigen (PSA), outcome of digital rectal examination (DRE), transrectal ultrasound and ultrasound assessed prostate volume. The external validity was assessed for the presence of cancer at biopsy by calibration (agreement between observed and predicted outcomes), discrimination (separation of those with and without cancer), and decision curves (for clinical usefulness). Prostate cancer was detected in 469 men (26%) of the Finnish cohort and in 124 men (23%) of the Swedish cohort. Systematic miscalibration was present in both cohorts (mean predicted probability 34% versus 26% observed, and 29% versus 23% observed, both p<0.001). The areas under the curves were 0.76 and 0.78, and substantially lower for the model with PSA only (0.64 and 0.68 respectively). The model proved clinically useful for any decision threshold compared with a model with PSA only, PSA and DRE, or biopsying all men. A limitation is that the model is based on sextant biopsies results. The ERSPC risk calculator discriminated well between those with and without prostate cancer among initially screened men, but overestimated the risk of a positive biopsy. Further research is necessary to assess the performance and applicability of the ERSPC risk calculator when a clinical setting is considered rather than a screening setting. Copyright © 2010 Elsevier Ltd. All rights reserved.
Karstoft, Karen-Inge; Andersen, Søren B; Nielsen, Anni B S
2017-06-01
Since 1998, soldiers deployed to war zones with the Danish Defense (≈31,000) have been invited to fill out a questionnaire on post-mission reactions. This provides a unique data source for studying the psychological toll of war. Here, we validate a measure of PTSD-symptoms from the questionnaire. Soldiers from two cohorts deployed to Afghanistan with the International Security Assistance Force (ISAF) in 2009 (ISAF7, N = 334) and 2013 (ISAF15, N = 278) filled out a standard questionnaire (Psychological Reactions following International Missions, PRIM) concerning a range of post-deployment reactions including symptoms of PTSD (PRIM-PTSD). They also filled out a validated measure of PTSD-symptoms in DSM-IV, the PTSD-checklist (PCL). We tested reliability of PRIM-PTSD by estimating Cronbach's alpha, and tested validity by correlating items, clusters, and overall scale with corresponding items in the PCL. Furthermore, we conducted two confirmatory factor analytic models to test the factor structure of PRIM-PTSD, and tested measurement invariance of the selected model. Finally, we established a screening and a clinical cutoff score by application of ROC analysis. We found high internal consistency of the PRIM-PTSD (Cronbach's alpha = 0.88; both cohorts), strong item-item (0.48-0.83), item-cluster (0.43-0.72), cluster-cluster (0.71-0.82) and full-scale (0.86-0.88) correlations between PRIM-PTSD and PCL. The factor analyses showed adequate fit of a one-factor model, which was also found to display strong measurement invariance across cohorts. ROC curve analysis established cutoff scores for screening (sensitivity = 1, specificity = 0.93) and clinical use (sensitivity = 0.71, specificity = 0.98). In conclusion, we find that PRIM-PTSD is a valid measure for assessing PTSD-symptoms in Danish soldiers following deployment. © 2017 Scandinavian Psychological Associations and John Wiley & Sons Ltd.
Nelson, Jennifer Clark; Marsh, Tracey; Lumley, Thomas; Larson, Eric B; Jackson, Lisa A; Jackson, Michael L
2013-08-01
Estimates of treatment effectiveness in epidemiologic studies using large observational health care databases may be biased owing to inaccurate or incomplete information on important confounders. Study methods that collect and incorporate more comprehensive confounder data on a validation cohort may reduce confounding bias. We applied two such methods, namely imputation and reweighting, to Group Health administrative data (full sample) supplemented by more detailed confounder data from the Adult Changes in Thought study (validation sample). We used influenza vaccination effectiveness (with an unexposed comparator group) as an example and evaluated each method's ability to reduce bias using the control time period before influenza circulation. Both methods reduced, but did not completely eliminate, the bias compared with traditional effectiveness estimates that do not use the validation sample confounders. Although these results support the use of validation sampling methods to improve the accuracy of comparative effectiveness findings from health care database studies, they also illustrate that the success of such methods depends on many factors, including the ability to measure important confounders in a representative and large enough validation sample, the comparability of the full sample and validation sample, and the accuracy with which the data can be imputed or reweighted using the additional validation sample information. Copyright © 2013 Elsevier Inc. All rights reserved.
HbA1c Outcomes in Patients Treated With Canagliflozin Versus Sitagliptin in US Health Plans.
Thayer, Sarah; Aguilar, Richard; Korrer, Stephanie; Chow, Wing
2017-10-01
Clinical trial evidence supports greater glycemic control with canagliflozin than with sitagliptin. The objective of this study was to provide real-world evidence comparing outcomes in routine clinical practice among patients initiating each medication. With the use of a health care administrative database, patients initiating canagliflozin were compared with patients initiating sitagliptin (first prescription fill as index date). Baseline (6 months before index date) demographic and clinical (eg, comorbidities and diabetes-related complications) characteristics were compared, and propensity score matching was used to control for baseline differences between cohorts. Outcomes included change in glycosylated hemoglobin (HbA 1c ) and persistence with medication over a 9-month period after index date. Before matching, the canagliflozin cohort (N = 3993) was younger than the sitagliptin cohort (N = 12,153) and was composed of fewer women and Medicare Advantage enrollees, with lower mean baseline comorbidity scores (all p < 0.001). Before matching, the canagliflozin cohort (valid n = 1482) had a significantly (p < 0.001) higher baseline HbA 1c (8.60) than the sitagliptin cohort (valid n = 3697; HbA 1c , 8.32). After matching (n = 1472 per cohort), patients were well balanced on baseline characteristics, and HbA 1c values were not significantly different (p = 0.634) between the cohorts. Patients initiating canagliflozin had greater reductions in HbA 1c than patients in the sitagliptin cohort (-0.93% versus -0.57%, respectively; p = 0.004), with similar mean (median) time from index date to follow-up HbA 1c of 185.4 (199.0) and 184.3 (190.5) days, respectively (p = 0.802). Only 29.8% of canagliflozin patients discontinued during follow-up compared with 41.5% of sitagliptin patients (p < 0.001); the average days of persistence on index therapy was longer for canagliflozin patients (152 days) than for sitagliptin patients (139 days; p < 0.001). In this observational study, patients initiating canagliflozin had greater reduction in HbA 1c and longer persistence with medication than did patients who initiated sitagliptin, over a 9-month period. Better understanding of antihyperglycemic treatment, HbA 1c results, and differences among patients in demographic/clinical characteristics as well as persistence with treatment will inform optimal diabetes treatment choice in routine practice. Copyright © 2017 Elsevier HS Journals, Inc. All rights reserved.
Validation of a brief form of the Perceived Neighborhood Social Cohesion questionnaire.
Dupuis, Marc; Baggio, Stéphanie; Gmel, Gerhard
2017-02-01
The aim of this study was the validation of a brief form of the Perceived Neighborhood Social Cohesion questionnaire using data from 5065 men from the "Cohort Study on Substance-Use Risk Factors." A 9-item scale covering three factors was proposed. Excellent indices of internal consistency were measured (α = .93). The confirmatory factor analyses resulted in acceptable fit indices supporting measurement invariance across French and German forms. Significant correlations were found between the brief form of the Perceived Neighborhood Social Cohesion questionnaire, and satisfaction and self-reported health, providing evidence of the concurrent validity of the scale. Perceived neighborhood social cohesion, and depression and suicide attempts were negatively associated, sustaining the protective effect of perceived social cohesion.
Application of Large-Scale Aptamer-Based Proteomic Profiling to Planned Myocardial Infarctions.
Jacob, Jaison; Ngo, Debby; Finkel, Nancy; Pitts, Rebecca; Gleim, Scott; Benson, Mark D; Keyes, Michelle J; Farrell, Laurie A; Morgan, Thomas; Jennings, Lori L; Gerszten, Robert E
2018-03-20
Emerging proteomic technologies using novel affinity-based reagents allow for efficient multiplexing with high-sample throughput. To identify early biomarkers of myocardial injury, we recently applied an aptamer-based proteomic profiling platform that measures 1129 proteins to samples from patients undergoing septal alcohol ablation for hypertrophic cardiomyopathy, a human model of planned myocardial injury. Here, we examined the scalability of this approach using a markedly expanded platform to study a far broader range of human proteins in the context of myocardial injury. We applied a highly multiplexed, expanded proteomic technique that uses single-stranded DNA aptamers to assay 4783 human proteins (4137 distinct human gene targets) to derivation and validation cohorts of planned myocardial injury, individuals with spontaneous myocardial infarction, and at-risk controls. We found 376 target proteins that significantly changed in the blood after planned myocardial injury in a derivation cohort (n=20; P <1.05E-05, 1-way repeated measures analysis of variance, Bonferroni threshold). Two hundred forty-seven of these proteins were validated in an independent planned myocardial injury cohort (n=15; P <1.33E-04, 1-way repeated measures analysis of variance); >90% were directionally consistent and reached nominal significance in the validation cohort. Among the validated proteins that were increased within 1 hour after planned myocardial injury, 29 were also elevated in patients with spontaneous myocardial infarction (n=63; P <6.17E-04). Many of the novel markers identified in our study are intracellular proteins not previously identified in the peripheral circulation or have functional roles relevant to myocardial injury. For example, the cardiac LIM protein, cysteine- and glycine-rich protein 3, is thought to mediate cardiac mechanotransduction and stress responses, whereas the mitochondrial ATP synthase F 0 subunit component is a vasoactive peptide on its release from cells. Last, we performed aptamer-affinity enrichment coupled with mass spectrometry to technically verify aptamer specificity for a subset of the new biomarkers. Our results demonstrate the feasibility of large-scale aptamer multiplexing at a level that has not previously been reported and with sample throughput that greatly exceeds other existing proteomic methods. The expanded aptamer-based proteomic platform provides a unique opportunity for biomarker and pathway discovery after myocardial injury. © 2017 American Heart Association, Inc.
VALIDATION AND EVALUATION OF BIOMARKERS IN WORKERS EXPOSED TO BENZENE IN CHINA
Qu and colleagues recruited 181 healthy workers in several factories in the Tianjin region of China. These subjects formed part of a cohort of thousands identified by the U.S. National Cancer Institute (NCI) and the China Academy of Preventive Medicine for a study to evalua...
Goodenough, Christopher J; Ko, Tien C; Kao, Lillian S; Nguyen, Mylan T; Holihan, Julie L; Alawadi, Zeinab; Nguyen, Duyen H; Flores, Juan R; Arita, Nestor T; Roth, J Scott; Liang, Mike K
2015-04-01
Ventral incisional hernias (VIH) develop in up to 20% of patients after abdominal surgery. No widely applicable preoperative risk-assessment tool exists. We aimed to develop and validate a risk-assessment tool to predict VIH after abdominal surgery. A prospective study of all patients undergoing abdominal surgery was conducted at a single institution from 2008 to 2010. Variables were defined in accordance with the National Surgical Quality Improvement Project, and VIH was determined through clinical and radiographic evaluation. A multivariate Cox proportional hazard model was built from a development cohort (2008 to 2009) to identify predictors of VIH. The HERNIAscore was created by converting the hazards ratios (HR) to points. The predictive accuracy was assessed on the validation cohort (2010) using a receiver operator characteristic curve and calculating the area under the curve (AUC). Of 625 patients followed for a median of 41 months (range 0.3 to 64 months), 93 (13.9%) developed a VIH. The training cohort (n = 428, VIH = 70, 16.4%) identified 4 independent predictors: laparotomy (HR 4.77, 95% CI 2.61 to 8.70) or hand-assisted laparoscopy (HAL, HR 4.00, 95% CI 2.08 to 7.70), COPD (HR 2.35; 95% CI 1.44 to 3.83), and BMI ≥ 25 kg/m(2) (HR1.74; 95% CI 1.04 to 2.91). Factors that were not predictive included age, sex, American Society of Anesthesiologists (ASA) score, albumin, immunosuppression, previous surgery, and suture material or technique. The predictive score had an AUC = 0.77 (95% CI 0.68 to 0.86) using the validation cohort (n = 197, VIH = 23, 11.6%). Using the HERNIAscore: HERNIAscore = 4(∗)Laparotomy+3(∗)HAL+1(∗)COPD+1(∗) BMI ≥ 25, 3 classes stratified the risk of VIH: class I (0 to 3 points),5.2%; class II (4 to 5 points),19.6%; and class III (6 points), 55.0%. The HERNIAscore accurately identifies patients at increased risk for VIH. Although external validation is needed, this provides a starting point to counsel patients and guide clinical decisions. Increasing the use of laparoscopy, weight-loss programs, community smoking prevention programs, and incisional reinforcement may help reduce rates of VIH. Copyright © 2015 American College of Surgeons. Published by Elsevier Inc. All rights reserved.
Suenaga, Mitsukuni; Schirripa, Marta; Cao, Shu; Zhang, Wu; Yang, Dongyun; Ning, Yan; Cremolini, Chiara; Antoniotti, Carlotta; Borelli, Beatrice; Mashima, Tetsuo; Okazaki, Satoshi; Berger, Martin D; Miyamoto, Yuji; Gopez, Roel; Barzi, Afsaneh; Lonardi, Sara; Yamaguchi, Toshiharu; Falcone, Alfredo; Loupakis, Fotios; Lenz, Heinz-Josef
2018-06-01
The C-C motif chemokine ligand 5/C-C motif chemokine receptor 5 (CCL5/CCR5) pathway has been shown to induce endothelial progenitor cell migration, resulting in increased vascular endothelial growth factor A expression. We hypothesized that genetic polymorphisms in the CCL5/CCR5 pathway predict efficacy and toxicity in patients with metastatic colorectal cancer (mCRC) treated with regorafenib. We analyzed genomic DNA extracted from 229 tumor samples from 2 different cohorts of patients who received regorafenib: an evaluation cohort of 79 Japanese patients and a validation cohort of 150 Italian patients. Single nucleotide polymorphisms of CCL5/CCR5 pathway-related genes were analyzed by PCR-based direct sequencing. CCL4 rs1634517 and CCL3 rs1130371 were associated with progression-free survival in the evaluation cohort (hazard ratio [HR] 1.54, P = .043; HR 1.48, P = .064), and progression-free survival (HR 1.74, P < .001; HR 1.66, P = .002) and overall survival (HR 1.65, P = .004; HR 1.65, P = .004) in the validation cohort. The allelic frequencies of CCL5 single nucleotide polymorphisms varied between the evaluation and validation cohorts (G/G variant in rs2280789, 21.5% vs. 1.3%, P < .001; T/T variant in rs3817655, 22.8% vs. 2.7%, P < .001). In the evaluation cohort, patients with the G/G variant in rs2280789 had a higher incidence of grade 3+ hand-foot skin reaction compared to any A allele (53% vs. 27%, P = .078), and similarly to the T/T variant in rs3817655 compared to any A allele (56% vs. 26%, P = .026). Genetic variants in the CCL5/CCR5 pathway may serve as prognostic markers and may predict severe hand-foot skin reaction in mCRC patients receiving regorafenib therapy. Copyright © 2018 Elsevier Inc. All rights reserved.
Risk of thyroid cancer in patients with thyroiditis: a population-based cohort study.
Liu, Chien-Liang; Cheng, Shih-Ping; Lin, Hui-Wen; Lai, Yuen-Liang
2014-03-01
The causative relationship between autoimmune thyroiditis and thyroid cancer remains a controversial issue. The aim of this population-based study was to investigate the risk of thyroid cancer in patients with thyroiditis. From the Longitudinal Health Insurance Database 2005 (LHID2005) of Taiwan, we identified adult patients newly diagnosed with thyroiditis between 2004 and 2009 (n = 1,654). The comparison cohort (n = 8,270) included five randomly selected age- and sex-matched controls for each patient in the study cohort. All patients were followed up from the date of cohort entry until they developed thyroid cancer or to the end of 2010. Multivariate Cox regression was used to assess the risk of developing thyroid cancer. A total of 1,000 bootstrap replicates were created for internal validation. A total of 35 patients developed thyroid cancer during the study period, of whom 24 were from the thyroiditis cohort and 11 were from the comparison cohort (incidence 353 and 22 per 100,000 person-years, respectively). After adjusting for potential confounding factors, the hazard ratio (HR) for thyroid cancer in patients with thyroiditis was 13.24 (95 % CI 6.40-27.39). Excluding cancers occurring within 1 year of follow-up, the HR remained significantly increased (6.64; 95 % CI 2.35-18.75). Hypothyroidism was not an independent factor associated with the occurrence of thyroid cancer. We found an increased risk for the development of thyroid cancer after a diagnosis of thyroiditis, independent of comorbidities.
Cross-cultural comparisons of the Mini-mental State Examination between Japanese and U.S. cohorts
Meguro, Kenichi; Ishii, Hiroshi; Yamaguchi, Satoshi; Saxton, Judith A.; Ganguli, Mary
2009-01-01
Background The Mini-mental State Examination (MMSE) is widely used in Japan and the U.S.A. for cognitive screening in the clinical setting and in epidemiological studies. A previous Japanese community study reported distributions of the MMSE total score very similar to that of the U.S.A. Methods Data were obtained from the Monongahela Valley Independent Elder's Study (MoVIES), a representative sample of community-dwelling elderly people aged 65 and older living near Pittsburgh, U.S.A., and from the Tajiri Project, with similar aims in Tajiri, Japan. We examined item-by-item distributions of the MMSE between two cohorts, comparing (1) percentage of correct answers for each item within each cohort, and (2) relative difficulty of each item measured by Item Characteristic Curve analysis (ICC), which estimates log odds of obtaining a correct answer adjusted for the remaining MMSE items, demographic variables (age, gender, education) and interactions of demographic variables and cohort. Results Median MMSE scores were very similar between the two samples within the same education groups. However, the relative difficulty of each item differed substantially between the two cohorts. Specifically, recall and auditory comprehension were easier for the Tajiri group, but reading comprehension and sentence construction were easier for the MoVIES group. Conclusions Our results reaffirm the importance of validation and examination of thresholds in each cohort to be studied when a common instrument is used as a dementia screening tool or for defining cognitive impairment. PMID:18925977
Monteiro, Márcia S; Barros, António S; Pinto, Joana; Carvalho, Márcia; Pires-Luís, Ana S; Henrique, Rui; Jerónimo, Carmen; Bastos, Maria de Lourdes; Gil, Ana M; Guedes de Pinho, Paula
2016-11-18
RCC usually develops and progresses asymptomatically and, when detected, it is frequently at advanced stages and metastatic, entailing a dismal prognosis. Therefore, there is an obvious demand for new strategies enabling an earlier diagnosis. The importance of metabolic rearrangements for carcinogenesis unlocked a new approach for cancer research, catalyzing the increased use of metabolomics. The present study aimed the NMR metabolic profiling of RCC in urine samples from a cohort of RCC patients (n = 42) and controls (n = 49). The methodology entailed variable selection of the spectra in tandem with multivariate analysis and validation procedures. The retrieval of a disease signature was preceded by a systematic evaluation of the impacts of subject age, gender, BMI, and smoking habits. The impact of confounders on the urine metabolomics profile of this population is residual compared to that of RCC. A 32-metabolite/resonance signature descriptive of RCC was unveiled, successfully distinguishing RCC patients from controls in principal component analysis. This work demonstrates the value of a systematic metabolomics workflow for the identification of robust urinary metabolic biomarkers of RCC. Future studies should entail the validation of the 32-metabolite/resonance signature found for RCC in independent cohorts, as well as biological validation of the putative hypotheses advanced.
She, Yunlang; Zhao, Lilan; Dai, Chenyang; Ren, Yijiu; Jiang, Gening; Xie, Huikang; Zhu, Huiyuan; Sun, Xiwen; Yang, Ping; Chen, Yongbing; Shi, Shunbin; Shi, Weirong; Yu, Bing; Xie, Dong; Chen, Chang
2017-11-01
To develop and validate a nomogram to estimate the pretest probability of malignancy in Chinese patients with solid solitary pulmonary nodule (SPN). A primary cohort of 1798 patients with pathologically confirmed solid SPNs after surgery was retrospectively studied at five institutions from January 2014 to December 2015. A nomogram based on independent prediction factors of malignant solid SPN was developed. Predictive performance also was evaluated using the calibration curve and the area under the receiver operating characteristic curve (AUC). The mean age of the cohort was 58.9 ± 10.7 years. In univariate and multivariate analysis, age; history of cancer; the log base 10 transformations of serum carcinoembryonic antigen value; nodule diameter; the presence of spiculation, pleural indentation, and calcification remained the predictive factors of malignancy. A nomogram was developed, and the AUC value (0.85; 95%CI, 0.83-0.88) was significantly higher than other three models. The calibration cure showed optimal agreement between the malignant probability as predicted by nomogram and the actual probability. We developed and validated a nomogram that can estimate the pretest probability of malignant solid SPNs, which can assist clinical physicians to select and interpret the results of subsequent diagnostic tests. © 2017 Wiley Periodicals, Inc.
Herr, Raphael M; Li, Jian; Bosch, Jos A; Schmidt, Burkhard; DeJoy, David M; Fischer, Joachim E; Loerbroks, Adrian
2014-01-01
The objective of the present study was to validate a German 11-item organizational justice questionnaire (G-OJQ) that consists of two subscales, referred to as "procedural justice" (PJ) and "interactional justice" (IJ) adapted from Moorman's organizational justice (OJ) questionnaire. A second objective was to determine associations of the G-OJQ with self-rated health. This study used cross-sectional data from an occupational cohort of 1518 factory workers from Germany (87.7 % male; mean age = 38.8 with SD = 11.9). After splitting the sample in two random subsamples, we assessed structural validity by exploratory factor analyses in one subsample and by confirmatory factor analysis in the other subsample. Internal validity was assessed by Cronbach's α. Associations with self-reported poor health were estimated by logistic regression. The full scale and its subscales yielded Cronbach's α's of ≥0.9, and item-total correlations were ≥0.5. Factor analyses confirmed the expected 2-factor structure, labeled "interactional justice" (IJ, 4 items, λ 0.43-0.94) and "procedural justice" (PJ, 7 items, λ 0.46-0.83), respectively, and showed an acceptable fit to the data (χ (2) = 61; p = .001; CFI = 0.995; RMSEA = 0.037). The OJ total score as well as subscale scores in the lowest quartile, when compared to the highest quartile, was associated with an ≥2.3 increased odds of reporting poor health. The G-OJQ seems to be a valid and useful tool for observational and intervention studies in occupational settings. Future studies may additionally explore longitudinal associations and test the generalizability of the present findings to other populations and health outcomes.
Improving the Validity of Activity of Daily Living Dependency Risk Assessment
Clark, Daniel O.; Stump, Timothy E.; Tu, Wanzhu; Miller, Douglas K.
2015-01-01
Objectives Efforts to prevent activity of daily living (ADL) dependency may be improved through models that assess older adults’ dependency risk. We evaluated whether cognition and gait speed measures improve the predictive validity of interview-based models. Method Participants were 8,095 self-respondents in the 2006 Health and Retirement Survey who were aged 65 years or over and independent in five ADLs. Incident ADL dependency was determined from the 2008 interview. Models were developed using random 2/3rd cohorts and validated in the remaining 1/3rd. Results Compared to a c-statistic of 0.79 in the best interview model, the model including cognitive measures had c-statistics of 0.82 and 0.80 while the best fitting gait speed model had c-statistics of 0.83 and 0.79 in the development and validation cohorts, respectively. Conclusion Two relatively brief models, one that requires an in-person assessment and one that does not, had excellent validity for predicting incident ADL dependency but did not significantly improve the predictive validity of the best fitting interview-based models. PMID:24652867
Amsallem, Myriam; Boulate, David; Kooreman, Zoe; Zamanian, Roham T; Fadel, Guillaume; Schnittger, Ingela; Fadel, Elie; McConnell, Michael V; Dhillon, Gundeep; Mercier, Olaf; Haddad, François
2017-06-01
This study determined whether novel right heart echocardiography metrics help to detect pulmonary hypertension (PH) in patients with advanced lung disease (ALD). We reviewed echocardiography and catheterization data of 192 patients from the Stanford ALD registry and echocardiograms of 50 healthy controls. Accuracy of echocardiographic right heart metrics to detect PH was assessed using logistic regression and area under the ROC curves (AUC) analysis. Patients were divided into a derivation (n = 92) and validation cohort (n = 100). Experimental validation was assessed in a piglet model of mild PH followed longitudinally. Tricuspid regurgitation (TR) was not interpretable in 52% of patients. In the derivation cohort, right atrial maximal volume index (RAVI), ventricular end-systolic area index (RVESAI), free-wall longitudinal strain and tricuspid annular plane systolic excursion (TAPSE) differentiated patients with and without PH; 20% of patients without PH had moderate to severe RV enlargement by RVESAI. On multivariate analysis, RAVI and TAPSE were independently associated with PH (AUC = 0.77, p < 0.001), which was confirmed in the validation cohort (0.78, p < 0.001). Presence of right heart metrics abnormalities did not improve detection of PH in patients with interpretable TR (p > 0.05) and provided moderate detection value in patients without TR. Only two patients with more severe PH (mean pulmonary pressure 35 and 36 mmHg) were missed. The animal model confirmed that right heart enlargement discriminated best pigs with PH from shams. This study highlights the frequency of right heart enlargement and dysfunction in ALD irrespectively from presence of PH, therefore limiting their use for detection of PH.
Muller, David C; Johansson, Mattias; Brennan, Paul
2017-03-10
Purpose Several lung cancer risk prediction models have been developed, but none to date have assessed the predictive ability of lung function in a population-based cohort. We sought to develop and internally validate a model incorporating lung function using data from the UK Biobank prospective cohort study. Methods This analysis included 502,321 participants without a previous diagnosis of lung cancer, predominantly between 40 and 70 years of age. We used flexible parametric survival models to estimate the 2-year probability of lung cancer, accounting for the competing risk of death. Models included predictors previously shown to be associated with lung cancer risk, including sex, variables related to smoking history and nicotine addiction, medical history, family history of lung cancer, and lung function (forced expiratory volume in 1 second [FEV1]). Results During accumulated follow-up of 1,469,518 person-years, there were 738 lung cancer diagnoses. A model incorporating all predictors had excellent discrimination (concordance (c)-statistic [95% CI] = 0.85 [0.82 to 0.87]). Internal validation suggested that the model will discriminate well when applied to new data (optimism-corrected c-statistic = 0.84). The full model, including FEV1, also had modestly superior discriminatory power than one that was designed solely on the basis of questionnaire variables (c-statistic = 0.84 [0.82 to 0.86]; optimism-corrected c-statistic = 0.83; p FEV1 = 3.4 × 10 -13 ). The full model had better discrimination than standard lung cancer screening eligibility criteria (c-statistic = 0.66 [0.64 to 0.69]). Conclusion A risk prediction model that includes lung function has strong predictive ability, which could improve eligibility criteria for lung cancer screening programs.
Chiò, Adriano; Calvo, Andrea; Bovio, Giacomo; Canosa, Antonio; Bertuzzo, Davide; Galmozzi, Francesco; Cugnasco, Paolo; Clerico, Marinella; De Mercanti, Stefania; Bersano, Enrica; Cammarosano, Stefania; Ilardi, Antonio; Manera, Umberto; Moglia, Cristina; Sideri, Riccardo; Marinou, Kalliopi; Bottacchi, Edo; Pisano, Fabrizio; Cantello, Roberto; Mazzini, Letizia; Mora, Gabriele
2014-09-01
There is an urgent need to identify reliable biomarkers of amyotrophic lateral sclerosis (ALS) progression for clinical practice and pharmacological trials. To correlate several hematological markers evaluated at diagnosis with ALS outcome in a population-based series of patients (discovery cohort) and replicate the findings in an independent validation cohort from an ALS tertiary center. The discovery cohort included 712 patients with ALS from the Piemonte and Valle d'Aosta Register for Amyotrophic Lateral Sclerosis from January 1, 2007, to December 31, 2011. The validation cohort comprised 122 patients with ALS at different stages of disease consecutively seen at an ALS tertiary center between January 1, 2007, and January 1, 2009. The following hematological factors were investigated and correlated with survival: total leukocytes, neutrophils, lymphocytes, monocytes, glucose, creatinine, uric acid, albumin, bilirubin, total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, creatine kinase, thyroid-stimulating hormones, and erythrocyte sedimentation rate; all analyses were performed separately by sex. The patient of the validation cohort also underwent bioelectrical impedance analysis for the calculation of fat-free mass. Of the 712 patients in the examined period in Piemonte and Valle d'Aosta, 638 (89.6%) were included in the study. Only serum albumin (men: ≤ 4.3 vs >4.3 mg/dL, P < .001; women: ≤ 4.3 vs >4.3 mg/dL, P < .001) and creatinine levels (men: ≤ 0.82 vs >0.82 mg/dL, P = .004; women: ≤ 0.65 vs >0.05 mg/dL, P = .004) and lymphocyte count (men: ≤ 1700 vs >1700/μL, P = .04; women: ≤ 1700 vs >1700/μL, P = .02) were significantly associated with ALS outcome in both sexes with a dose-response effect (better survival with increasing levels). These findings were confirmed in the validation cohort. Multivariable analysis showed that serum albumin (men: hazard ratio [HR], 1.39; 95% CI, 1.05-1.90; P = .02; women: HR, 1.73; 95 % CI, 1.35-2.39; P = .001) and creatinine (men: HR, 1.47; 95% CI, 1.11-1.95; P = .007; women: HR, 1.49; 95% CI, 1.07-2.05; P = .02) were independent predictors of survival in both sexes; no other hematological factor was retained in the model. In patients with ALS, serum albumin was correlated with markers of inflammatory state while serum creatinine was correlated with fat-free mass, which is a marker of muscle mass. In ALS, serum albumin and creatinine are independent markers of outcome in both sexes. Creatinine reflects the muscle waste whereas albumin is connected with inflammatory state. Both creatinine and albumin are reliable markers of the severity of clinical status in patients with ALS and can be used in defining prognosis at the time of diagnosis.
ERIC Educational Resources Information Center
Patterson, Brian F.; Mattern, Krista D.
2013-01-01
The continued accumulation of validity evidence for the core uses of educational assessments is critical to ensure that proper inferences will be made for those core purposes. To that end, the College Board has continued to follow previous cohorts of college students and this report provides updated validity evidence for using the SAT to predict…
Shao, Hui; Fonseca, Vivian; Stoecker, Charles; Liu, Shuqian; Shi, Lizheng
2018-05-03
There is an urgent need to update diabetes prediction, which has relied on the United Kingdom Prospective Diabetes Study (UKPDS) that dates back to 1970 s' European populations. The objective of this study was to develop a risk engine with multiple risk equations using a recent patient cohort with type 2 diabetes mellitus reflective of the US population. A total of 17 risk equations for predicting diabetes-related microvascular and macrovascular events, hypoglycemia, mortality, and progression of diabetes risk factors were estimated using the data from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (n = 10,251). Internal and external validation processes were used to assess performance of the Building, Relating, Assessing, and Validating Outcomes (BRAVO) risk engine. One-way sensitivity analysis was conducted to examine the impact of risk factors on mortality at the population level. The BRAVO risk engine added several risk factors including severe hypoglycemia and common US racial/ethnicity categories compared with the UKPDS risk engine. The BRAVO risk engine also modeled mortality escalation associated with intensive glycemic control (i.e., glycosylated hemoglobin < 6.5%). External validation showed a good prediction power on 28 endpoints observed from other clinical trials (slope = 1.071, R 2 = 0.86). The BRAVO risk engine for the US diabetes cohort provides an alternative to the UKPDS risk engine. It can be applied to assist clinical and policy decision making such as cost-effective resource allocation in USA.
Tramm, Trine; Mohammed, Hayat; Myhre, Simen; Kyndi, Marianne; Alsner, Jan; Børresen-Dale, Anne-Lise; Sørlie, Therese; Frigessi, Arnoldo; Overgaard, Jens
2014-10-15
To identify genes predicting benefit of radiotherapy in patients with high-risk breast cancer treated with systemic therapy and randomized to receive or not receive postmastectomy radiotherapy (PMRT). The study was based on the Danish Breast Cancer Cooperative Group (DBCG82bc) cohort. Gene-expression analysis was performed in a training set of frozen tumor tissue from 191 patients. Genes were identified through the Lasso method with the endpoint being locoregional recurrence (LRR). A weighted gene-expression index (DBCG-RT profile) was calculated and transferred to quantitative real-time PCR (qRT-PCR) in corresponding formalin-fixed, paraffin-embedded (FFPE) samples, before validation in FFPE from 112 additional patients. Seven genes were identified, and the derived DBCG-RT profile divided the 191 patients into "high LRR risk" and "low LRR risk" groups. PMRT significantly reduced risk of LRR in "high LRR risk" patients, whereas "low LRR risk" patients showed no additional reduction in LRR rate. Technical transfer of the DBCG-RT profile to FFPE/qRT-PCR was successful, and the predictive impact was successfully validated in another 112 patients. A DBCG-RT gene profile was identified and validated, identifying patients with very low risk of LRR and no benefit from PMRT. The profile may provide a method to individualize treatment with PMRT. ©2014 American Association for Cancer Research.
Reisner, Sari L; Conron, Kerith J; Tardiff, Laura Anatale; Jarvi, Stephanie; Gordon, Allegra R; Austin, S Bryn
2014-11-26
A barrier to monitoring the health of gender minority (transgender) populations is the lack of brief, validated tools with which to identify participants in surveillance systems. We used the Growing Up Today Study (GUTS), a prospective cohort study of U.S. young adults (mean age = 20.7 years in 2005), to assess the validity of self-report measures and implement a two-step method to measure gender minority status (step 1: assigned sex at birth, step 2: current gender identity). A mixed-methods study was conducted in 2013. Construct validity was evaluated in secondary data analysis of the 2010 wave (n = 7,831). Cognitive testing interviews of close-ended measures were conducted with a subsample of participants (n = 39). Compared to cisgender (non-transgender) participants, transgender participants had higher levels of recalled childhood gender nonconformity age < 11 years and current socially assigned gender nonconformity and were more likely to have ever identified as not completely heterosexual (p < 0.001). No problems with item comprehension were found for cisgender or gender minority participants. Assigned sex at birth was interpreted as sex designated on a birth certificate; transgender was understood to be a difference between a person's natal sex and gender identity. Participants were correctly classified as male, female, or transgender. The survey items performed well in this sample and are recommended for further evaluation in languages other than English and with diverse samples in terms of age, race/ethnicity, and socioeconomic status.
Bahl, Gautam; Cruite, Irene; Wolfson, Tanya; Gamst, Anthony C.; Collins, Julie M.; Chavez, Alyssa D.; Barakat, Fatma; Hassanein, Tarek; Sirlin, Claude B.
2016-01-01
Purpose To demonstrate a proof of concept that quantitative texture feature analysis of double contrast-enhanced magnetic resonance imaging (MRI) can classify fibrosis noninvasively, using histology as a reference standard. Materials and Methods A Health Insurance Portability and Accountability Act (HIPAA)-compliant Institutional Review Board (IRB)-approved retrospective study of 68 patients with diffuse liver disease was performed at a tertiary liver center. All patients underwent double contrast-enhanced MRI, with histopathology-based staging of fibrosis obtained within 12 months of imaging. The MaZda software program was used to compute 279 texture parameters for each image. A statistical regularization technique, generalized linear model (GLM)-path, was used to develop a model based on texture features for dichotomous classification of fibrosis category (F ≤2 vs. F ≥3) of the 68 patients, with histology as the reference standard. The model's performance was assessed and cross-validated. There was no additional validation performed on an independent cohort. Results Cross-validated sensitivity, specificity, and total accuracy of the texture feature model in classifying fibrosis were 91.9%, 83.9%, and 88.2%, respectively. Conclusion This study shows proof of concept that accurate, noninvasive classification of liver fibrosis is possible by applying quantitative texture analysis to double contrast-enhanced MRI. Further studies are needed in independent cohorts of subjects. PMID:22851409
Aspirin exposure reveals novel genes associated with platelet function and cardiovascular events.
Voora, Deepak; Cyr, Derek; Lucas, Joseph; Chi, Jen-Tsan; Dungan, Jennifer; McCaffrey, Timothy A; Katz, Richard; Newby, L Kristin; Kraus, William E; Becker, Richard C; Ortel, Thomas L; Ginsburg, Geoffrey S
2013-10-01
The aim of this study was to develop ribonucleic acid (RNA) profiles that could serve as novel biomarkers for the response to aspirin. Aspirin reduces death and myocardial infarction (MI), suggesting that aspirin interacts with biological pathways that may underlie these events. Aspirin was administered, followed by whole-blood RNA microarray profiling, in a discovery cohort of healthy volunteers (HV1) (n = 50) and 2 validation cohorts of healthy volunteers (HV2) (n = 53) and outpatient cardiology patients (OPC) (n = 25). Platelet function was assessed using the platelet function score (PFS) in HV1 and HV2 and the VerifyNow Aspirin Test (Accumetrics, Inc., San Diego, California) in OPC. Bayesian sparse factor analysis identified sets of coexpressed transcripts, which were examined for associations with PFS in HV1 and validated in HV2 and OPC. Proteomic analysis confirmed the association of validated transcripts in platelet proteins. Validated gene sets were tested for association with death or MI in 2 patient cohorts (n = 587 total) from RNA samples collected at cardiac catheterization. A set of 60 coexpressed genes named the "aspirin response signature" (ARS) was associated with PFS in HV1 (r = -0.31, p = 0.03), HV2 (r = -0.34, Bonferroni p = 0.03), and OPC (p = 0.046). Corresponding proteins for the 17 ARS genes were identified in the platelet proteome, of which 6 were associated with PFS. The ARS was associated with death or MI in both patient cohorts (odds ratio: 1.2 [p = 0.01]; hazard ratio: 1.5 [p = 0.001]), independent of cardiovascular risk factors. Compared with traditional risk factors, reclassification (net reclassification index = 31% to 37%, p ≤ 0.0002) was improved by including the ARS or 1 of its genes, ITGA2B. RNA profiles of platelet-specific genes are novel biomarkers for identifying patients who do not respond adequately to aspirin and who are at risk for death or MI. Copyright © 2013 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Shen, P; Zhao, J; Sun, G; Chen, N; Zhang, X; Gui, H; Yang, Y; Liu, J; Shu, K; Wang, Z; Zeng, H
2017-05-01
The aim of this study was to develop nomograms for predicting prostate cancer and its zonal location using prostate-specific antigen density, prostate volume, and their zone-adjusted derivatives. A total of 928 consecutive patients with prostate-specific antigen (PSA) less than 20.0 ng/mL, who underwent transrectal ultrasound-guided transperineal 12-core prostate biopsy at West China Hospital between 2011 and 2014, were retrospectively enrolled. The patients were randomly split into training cohort (70%, n = 650) and validation cohort (30%, n = 278). Predicting models and the associated nomograms were built using the training cohort, while the validations of the models were conducted using the validation cohort. Univariate and multivariate logistic regression was performed. Then, new nomograms were generated based on multivariate regression coefficients. The discrimination power and calibration of these nomograms were validated using the area under the ROC curve (AUC) and the calibration curve. The potential clinical effects of these models were also tested using decision curve analysis. In total, 285 (30.7%) patients were diagnosed with prostate cancer. Among them, 131 (14.1%) and 269 (29.0%) had transition zone prostate cancer and peripheral zone prostate cancer. Each of zone-adjusted derivatives-based nomogram had an AUC more than 0.75. All nomograms had higher calibration and much better net benefit than the scenarios in predicting patients with or without different zones prostate cancer. Prostate-specific antigen density, prostate volume, and their zone-adjusted derivatives have important roles in detecting prostate cancer and its zonal location for patients with PSA 2.5-20.0 ng/mL. To the best of our knowledge, this is the first nomogram using these parameters to predict outcomes of 12-core prostate biopsy. These instruments can help clinicians to increase the accuracy of prostate cancer screening and to avoid unnecessary prostate biopsy. © 2017 American Society of Andrology and European Academy of Andrology.
Rudd, Kristina E; Seymour, Christopher W; Aluisio, Adam R; Augustin, Marc E; Bagenda, Danstan S; Beane, Abi; Byiringiro, Jean Claude; Chang, Chung-Chou H; Colas, L Nathalie; Day, Nicholas P J; De Silva, A Pubudu; Dondorp, Arjen M; Dünser, Martin W; Faiz, M Abul; Grant, Donald S; Haniffa, Rashan; Van Hao, Nguyen; Kennedy, Jason N; Levine, Adam C; Limmathurotsakul, Direk; Mohanty, Sanjib; Nosten, François; Papali, Alfred; Patterson, Andrew J; Schieffelin, John S; Shaffer, Jeffrey G; Thuy, Duong Bich; Thwaites, C Louise; Urayeneza, Olivier; White, Nicholas J; West, T Eoin; Angus, Derek C
2018-05-20
The quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA) score has not been well-evaluated in low- and middle-income countries (LMICs). To assess the association of qSOFA with excess hospital death among patients with suspected infection in LMICs and to compare qSOFA with the systemic inflammatory response syndrome (SIRS) criteria. Retrospective secondary analysis of 8 cohort studies and 1 randomized clinical trial from 2003 to 2017. This study included 6569 hospitalized adults with suspected infection in emergency departments, inpatient wards, and intensive care units of 17 hospitals in 10 LMICs across sub-Saharan Africa, Asia, and the Americas. Low (0), moderate (1), or high (≥2) qSOFA score (range, 0 [best] to 3 [worst]) or SIRS criteria (range, 0 [best] to 4 [worst]) within 24 hours of presentation to study hospital. Predictive validity (measured as incremental hospital mortality beyond that predicted by baseline risk factors, as a marker of sepsis or analogous severe infectious course) of the qSOFA score (primary) and SIRS criteria (secondary). The cohorts were diverse in enrollment criteria, demographics (median ages, 29-54 years; males range, 36%-76%), HIV prevalence (range, 2%-43%), cause of infection, and hospital mortality (range, 1%-39%). Among 6218 patients with nonmissing outcome status in the combined cohort, 643 (10%) died. Compared with a low or moderate score, a high qSOFA score was associated with increased risk of death overall (19% vs 6%; difference, 13% [95% CI, 11%-14%]; odds ratio, 3.6 [95% CI, 3.0-4.2]) and across cohorts (P < .05 for 8 of 9 cohorts). Compared with a low qSOFA score, a moderate qSOFA score was also associated with increased risk of death overall (8% vs 3%; difference, 5% [95% CI, 4%-6%]; odds ratio, 2.8 [95% CI, 2.0-3.9]), but not in every cohort (P < .05 in 2 of 7 cohorts). High, vs low or moderate, SIRS criteria were associated with a smaller increase in risk of death overall (13% vs 8%; difference, 5% [95% CI, 3%-6%]; odds ratio, 1.7 [95% CI, 1.4-2.0]) and across cohorts (P < .05 for 4 of 9 cohorts). qSOFA discrimination (area under the receiver operating characteristic curve [AUROC], 0.70 [95% CI, 0.68-0.72]) was superior to that of both the baseline model (AUROC, 0.56 [95% CI, 0.53-0.58; P < .001) and SIRS (AUROC, 0.59 [95% CI, 0.57-0.62]; P < .001). When assessed among hospitalized adults with suspected infection in 9 LMIC cohorts, the qSOFA score identified infected patients at risk of death beyond that explained by baseline factors. However, the predictive validity varied among cohorts and settings, and further research is needed to better understand potential generalizability.
Shi, Min; Movius, James; Dator, Romel; Aro, Patrick; Zhao, Yanchun; Pan, Catherine; Lin, Xiangmin; Bammler, Theo K.; Stewart, Tessandra; Zabetian, Cyrus P.; Peskind, Elaine R.; Hu, Shu-Ching; Quinn, Joseph F.; Galasko, Douglas R.; Zhang, Jing
2015-01-01
Finding robust biomarkers for Parkinson disease (PD) is currently hampered by inherent technical limitations associated with imaging or antibody-based protein assays. To circumvent the challenges, we adapted a staged pipeline, starting from our previous proteomic profiling followed by high-throughput targeted mass spectrometry (MS), to identify peptides in human cerebrospinal fluid (CSF) for PD diagnosis and disease severity correlation. In this multicenter study consisting of training and validation sets, a total of 178 subjects were randomly selected from a retrospective cohort, matching age and sex between PD patients, healthy controls, and neurological controls with Alzheimer disease (AD). From ∼14,000 unique peptides displaying differences between PD and healthy control in proteomic investigations, 126 peptides were selected based on relevance and observability in CSF using bioinformatic analysis and MS screening, and then quantified by highly accurate and sensitive selected reaction monitoring (SRM) in the CSF of 30 PD patients versus 30 healthy controls (training set), followed by diagnostic (receiver operating characteristics) and disease severity correlation analyses. The most promising candidates were further tested in an independent cohort of 40 PD patients, 38 AD patients, and 40 healthy controls (validation set). A panel of five peptides (derived from SPP1, LRP1, CSF1R, EPHA4, and TIMP1) was identified to provide an area under curve (AUC) of 0.873 (sensitivity = 76.7%, specificity = 80.0%) for PD versus healthy controls in the training set. The performance was essentially confirmed in the validation set (AUC = 0.853, sensitivity = 82.5%, specificity = 82.5%). Additionally, this panel could also differentiate the PD and AD groups (AUC = 0.990, sensitivity = 95.0%, specificity = 97.4%). Furthermore, a combination of two peptides belonging to proteins TIMP1 and APLP1 significantly correlated with disease severity as determined by the Unified Parkinson's Disease Rating Scale motor scores in both the training (r = 0.381, p = 0.038)j and the validation (r = 0.339, p = 0.032) sets. The novel panel of CSF peptides, if validated in independent cohorts, could be used to assist in clinical diagnosis of PD and has the potential to help monitoring or predicting disease progression. PMID:25556233
Dowell, Jon; Lumsden, Mary Ann; Powis, David; Munro, Don; Bore, Miles; Makubate, Boikanyo; Kumwenda, Ben
2011-01-01
The Personal Qualities Assessment (PQA) was developed to enhance medical student selection by measuring a range of non-cognitive attributes in the applicants to medical school. Applicants to the five Scottish medical schools were invited to pilot the test in 2001 and 2002. To evaluate the predictive validity of PQA for selecting medical students. A longitudinal cohort study was conducted in which PQA scores were compared with senior year medical school performance. Consent to access performance markers was obtained from 626 students (61.6% of 1017 entrants in 2002-2003). Linkable Foundation Year (4th) rankings were available for 411 (66%) students and objective structured clinical examination (OSCE) rankings for 335 (54%) of those consenting. Both samples were representative of the original cohort. No significant correlations were detected between separate elements of the PQA assessment and student performance. However, using the algorithm advocated by Powis et al. those defined as 'non-extreme' (<±1.5 SD from the cohort mean scores; SD, standard deviation) character types on the involved-detached and on the libertarian-communitarian moral orientation scales were ranked higher in OSCEs (average of 7.5% or 25 out of 335, p = 0.049). This study was limited by high attrition and basic outcome markers which are insensitive to relevant non-cognitive characteristics. However, it is the largest currently available study of predictive validity for the PQA assessment. There was one finding of significance: that those students who were identified by PQA as 'not extreme' on the two personal characteristics scales performed better in an OSCE measure of professionalism. Futures studies are required since psychometric testing for both cognitive and non-cognitive attributes are increasingly used in admission process and these should include more and better measures of professionalism against which to correlate non-cognitive traits.
O'Mahony, Constantinos; Jichi, Fatima; Ommen, Steve R; Christiaans, Imke; Arbustini, Eloisa; Garcia-Pavia, Pablo; Cecchi, Franco; Olivotto, Iacopo; Kitaoka, Hiroaki; Gotsman, Israel; Carr-White, Gerald; Mogensen, Jens; Antoniades, Loizos; Mohiddin, Saidi A; Maurer, Mathew S; Tang, Hak Chiaw; Geske, Jeffrey B; Siontis, Konstantinos C; Mahmoud, Karim D; Vermeer, Alexa; Wilde, Arthur; Favalli, Valentina; Guttmann, Oliver P; Gallego-Delgado, Maria; Dominguez, Fernando; Tanini, Ilaria; Kubo, Toru; Keren, Andre; Bueser, Teofila; Waters, Sarah; Issa, Issa F; Malcolmson, James; Burns, Tom; Sekhri, Neha; Hoeger, Christopher W; Omar, Rumana Z; Elliott, Perry M
2018-03-06
Identification of people with hypertrophic cardiomyopathy (HCM) who are at risk of sudden cardiac death (SCD) and require a prophylactic implantable cardioverter defibrillator is challenging. In 2014, the European Society of Cardiology proposed a new risk stratification method based on a risk prediction model (HCM Risk-SCD) that estimates the 5-year risk of SCD. The aim was to externally validate the 2014 European Society of Cardiology recommendations in a geographically diverse cohort of patients recruited from the United States, Europe, the Middle East, and Asia. This was an observational, retrospective, longitudinal cohort study. The cohort consisted of 3703 patients. Seventy three (2%) patients reached the SCD end point within 5 years of follow-up (5-year incidence, 2.4% [95% confidence interval {CI}, 1.9-3.0]). The validation study revealed a calibration slope of 1.02 (95% CI, 0.93-1.12), C-index of 0.70 (95% CI, 0.68-0.72), and D-statistic of 1.17 (95% CI, 1.05-1.29). In a complete case analysis (n= 2147; 44 SCD end points at 5 years), patients with a predicted 5-year risk of <4% (n=1524; 71%) had an observed 5-year SCD incidence of 1.4% (95% CI, 0.8-2.2); patients with a predicted risk of ≥6% (n=297; 14%) had an observed SCD incidence of 8.9% (95% CI, 5.96-13.1) at 5 years. For every 13 (297/23) implantable cardioverter defibrillator implantations in patients with an estimated 5-year SCD risk ≥6%, 1 patient can potentially be saved from SCD. This study confirms that the HCM Risk-SCD model provides accurate prognostic information that can be used to target implantable cardioverter defibrillator therapy in patients at the highest risk of SCD. © 2017 American Heart Association, Inc.
Cardesa-Salzmann, Teresa M.; Colomo, Luis; Gutierrez, Gonzalo; Chan, Wing C.; Weisenburger, Dennis; Climent, Fina; González-Barca, Eva; Mercadal, Santiago; Arenillas, Leonor; Serrano, Sergio; Tubbs, Ray; Delabie, Jan; Gascoyne, Randy D.; Connors, Joseph M; Mate, Jose L.; Rimsza, Lisa; Braziel, Rita; Rosenwald, Andreas; Lenz, Georg; Wright, George; Jaffe, Elaine S.; Staudt, Louis; Jares, Pedro; López-Guillermo, Armando; Campo, Elias
2011-01-01
Background Diffuse large B-cell lymphoma is a clinically and molecularly heterogeneous disease. Gene expression profiling studies have shown that the tumor microenvironment affects survival and that the angiogenesis-related signature is prognostically unfavorable. The contribution of histopathological microvessel density to survival in diffuse large B-cell lymphomas treated with immunochemotherapy remains unknown. The purpose of this study is to assess the prognostic impact of histopathological microvessel density in two independent series of patients with diffuse large B-cell lymphoma treated with immunochemotherapy. Design and Methods One hundred and forty-seven patients from the Leukemia Lymphoma Molecular Profiling Project (training series) and 118 patients from the Catalan Lymphoma-Study group-GELCAB (validation cohort) were included in the study. Microvessels were immunostained with CD31 and quantified with a computerized image analysis system. The stromal scores previously defined in 110 Leukemia Lymphoma Molecular Profiling Project cases were used to analyze correlations with microvessel density data. Results Microvessel density significantly correlated with the stromal score (r=0.3209; P<0.001). Patients with high microvessel density showed significantly poorer overall survival than those with low microvessel density both in the training series (4-year OS 54% vs. 78%; P=0.004) and in the validation cohort (57% vs. 81%; P=0.006). In multivariate analysis, in both groups high microvessel density was a statistically significant unfavorable prognostic factor independent of international prognostic index [training series: international prognostic index (relative risk 2.7; P=0.003); microvessel density (relative risk 1.96; P=0.002); validation cohort: international prognostic index (relative risk 4.74; P<0.001); microvessel density (relative risk 2.4; P=0.016)]. Conclusions These findings highlight the impact of angiogenesis in the outcome of patients with diffuse large B-cell lymphoma and the interest of evaluating antiangiogenic drugs in clinical trials. PMID:21546504
Janssen, Daniël M C; van Kuijk, Sander M J; d'Aumerie, Boudewijn B; Willems, Paul C
2018-05-16
A prediction model for surgical site infection (SSI) after spine surgery was developed in 2014 by Lee et al. This model was developed to compute an individual estimate of the probability of SSI after spine surgery based on the patient's comorbidity profile and invasiveness of surgery. Before any prediction model can be validly implemented in daily medical practice, it should be externally validated to assess how the prediction model performs in patients sampled independently from the derivation cohort. We included 898 consecutive patients who underwent instrumented thoracolumbar spine surgery. To quantify overall performance using Nagelkerke's R 2 statistic, the discriminative ability was quantified as the area under the receiver operating characteristic curve (AUC). We computed the calibration slope of the calibration plot, to judge prediction accuracy. Sixty patients developed an SSI. The overall performance of the prediction model in our population was poor: Nagelkerke's R 2 was 0.01. The AUC was 0.61 (95% confidence interval (CI) 0.54-0.68). The estimated slope of the calibration plot was 0.52. The previously published prediction model showed poor performance in our academic external validation cohort. To predict SSI after instrumented thoracolumbar spine surgery for the present population, a better fitting prediction model should be developed.
Overby, Nina Cecilie; Johannesen, Elisabeth; Jensen, Grete; Skjaevesland, Anne-Kirsti; Haugen, Margaretha
2014-01-01
The assessment of food intake is challenging and prone to errors; it is therefore important to consider the reliability and validity of the assessment methods. The aim of this study was to analyze the reproducibility and validity of a developed food-frequency questionnaire (FFQ) for use among adolescents. In total, 58 students (aged 13-14) from four different schools in the southern part of Norway participated in the reproducibility study of filling out the FFQ 4 weeks apart. In addition, 93 students participated in the relative validity study where the FFQ was compared to 2×24-hour dietary recalls, while 92 students participated in the absolute validity study where the intakes of fatty acids and vitamin D from the FFQ were compared to fatty acids and 25-hydroxy-vitamin D3 in whole blood. The median Spearman correlation coefficient for all nutrients in the test-retest reliability study was 0.57. The median Spearman correlation for all nutrients in the relative validity study was 0.26, while the correlations coefficients were low in the absolute validity study with n-3 fatty acid coefficients ranging from 0.05 to 0.25, and absent for vitamin D (r=0.000). The test-retest reproducibility was considered good, the relative validity was considered poor to good, and the absolute validity was considered poor. However, the results are comparable to other studies among adolescents.
Ramaswamy, Vidya; Piskorowski, Wilhelm; Fitzgerald, Mark; Hamerink, Howard A; Stefanac, Stephen; Greene, Rachel; Lantz, Marilyn S
2016-10-01
Since 2006, the University of Michigan School of Dentistry has used a 13-point measure of overall competence instrument to assess fourth-year dental students' end-rotation performance at community clinics. The aim of this study was to assess the reliability and validity of this instrument used by preceptors to rate students' overall competence during community-based dental education experiences. The measure was analyzed using performance ratings for all fourth-year DDS students in the graduating classes of 2012 and 2013 (combined n=201). The results were that interrater agreement was satisfactory and the measure scored high for internal consistency; also, the measure loaded highly on a single overall competence factor. Ratings on this measure did not correlate with students' final cumulative dental school GPA, but showed a significant positive correlation with their fourth-year fall patient management grades (which signify students' conscientiousness in managing patients and their families in a professional and ethical manner). There were differences in grading systems between the 2012 cohort (which used a pass/fail system) and the 2013 cohort (which used a letter grade system) and the mean ratings they received (higher for the 2013 cohort). Overall, the study found that the 13-point measure demonstrated excellent reliability and validity, suggesting it is useful in determining a student's clinical competence in these settings.
Leger, Stefan; Zwanenburg, Alex; Pilz, Karoline; Lohaus, Fabian; Linge, Annett; Zöphel, Klaus; Kotzerke, Jörg; Schreiber, Andreas; Tinhofer, Inge; Budach, Volker; Sak, Ali; Stuschke, Martin; Balermpas, Panagiotis; Rödel, Claus; Ganswindt, Ute; Belka, Claus; Pigorsch, Steffi; Combs, Stephanie E; Mönnich, David; Zips, Daniel; Krause, Mechthild; Baumann, Michael; Troost, Esther G C; Löck, Steffen; Richter, Christian
2017-10-16
Radiomics applies machine learning algorithms to quantitative imaging data to characterise the tumour phenotype and predict clinical outcome. For the development of radiomics risk models, a variety of different algorithms is available and it is not clear which one gives optimal results. Therefore, we assessed the performance of 11 machine learning algorithms combined with 12 feature selection methods by the concordance index (C-Index), to predict loco-regional tumour control (LRC) and overall survival for patients with head and neck squamous cell carcinoma. The considered algorithms are able to deal with continuous time-to-event survival data. Feature selection and model building were performed on a multicentre cohort (213 patients) and validated using an independent cohort (80 patients). We found several combinations of machine learning algorithms and feature selection methods which achieve similar results, e.g. C-Index = 0.71 and BT-COX: C-Index = 0.70 in combination with Spearman feature selection. Using the best performing models, patients were stratified into groups of low and high risk of recurrence. Significant differences in LRC were obtained between both groups on the validation cohort. Based on the presented analysis, we identified a subset of algorithms which should be considered in future radiomics studies to develop stable and clinically relevant predictive models for time-to-event endpoints.
Measurement of COPD Severity Using a Survey-Based Score
Omachi, Theodore A.; Katz, Patricia P.; Yelin, Edward H.; Iribarren, Carlos; Blanc, Paul D.
2010-01-01
Background: A comprehensive survey-based COPD severity score has usefulness for epidemiologic and health outcomes research. We previously developed and validated the survey-based COPD Severity Score without using lung function or other physiologic measurements. In this study, we aimed to further validate the severity score in a different COPD cohort and using a combination of patient-reported and objective physiologic measurements. Methods: Using data from the Function, Living, Outcomes, and Work cohort study of COPD, we evaluated the concurrent and predictive validity of the COPD Severity Score among 1,202 subjects. The survey instrument is a 35-point score based on symptoms, medication and oxygen use, and prior hospitalization or intubation for COPD. Subjects were systemically assessed using structured telephone survey, spirometry, and 6-min walk testing. Results: We found evidence to support concurrent validity of the score. Higher COPD Severity Score values were associated with poorer FEV1 (r = −0.38), FEV1% predicted (r = −0.40), Body mass, Obstruction, Dyspnea, Exercise Index (r = 0.57), and distance walked in 6 min (r = −0.43) (P < .0001 in all cases). Greater COPD severity was also related to poorer generic physical health status (r = −0.49) and disease-specific health-related quality of life (r = 0.57) (P < .0001). The score also demonstrated predictive validity. It was also associated with a greater prospective risk of acute exacerbation of COPD defined as ED visits (hazard ratio [HR], 1.31; 95% CI, 1.24-1.39), hospitalizations (HR, 1.59; 95% CI, 1.44-1.75), and either measure of hospital-based care for COPD (HR, 1.34; 95% CI, 1.26-1.41) (P < .0001 in all cases). Conclusion: The COPD Severity Score is a valid survey-based measure of disease-specific severity, both in terms of concurrent and predictive validity. The score is a psychometrically sound instrument for use in epidemiologic and outcomes research in COPD. PMID:20040611
Pichler, Martin; Stiegelbauer, Verena; Vychytilova-Faltejskova, Petra; Ivan, Cristina; Ling, Hui; Winter, Elke; Zhang, Xinna; Goblirsch, Matthew; Wulf-Goldenberg, Annika; Ohtsuka, Masahisa; Haybaeck, Johannes; Svoboda, Marek; Okugawa, Yoshinaga; Gerger, Armin; Hoefler, Gerald; Goel, Ajay; Slaby, Ondrej; Calin, George Adrian
2017-01-01
Purpose Characterization of colorectal cancer transcriptome by high-throughput techniques has enabled the discovery of several differentially expressed genes involving previously unreported miRNA abnormalities. Here, we followed a systematic approach on a global scale to identify miRNAs as clinical outcome predictors and further validated them in the clinical and experimental setting. Experimental Design Genome-wide miRNA sequencing data of 228 colorectal cancer patients from The Cancer Genome Atlas dataset were analyzed as a screening cohort to identify miRNAs significantly associated with survival according to stringent prespecified criteria. A panel of six miRNAs was further validated for their prognostic utility in a large independent validation cohort (n = 332). In situ hybridization and functional experiments in a panel of colorectal cancer cell lines and xenografts further clarified the role of clinical relevant miRNAs. Results Six miRNAs (miR-92b-3p, miR-188-3p, miR-221-5p, miR-331-3p, miR-425-3p, and miR-497-5p) were identified as strong predictors of survival in the screening cohort. High miR-188-3p expression proves to be an independent prognostic factor [screening cohort: HR = 4.137; 95% confidence interval (CI), 1.568–10.917; P = 0.004; validation cohort: HR = 1.538; 95% CI, 1.107–2.137; P = 0.010, respectively]. Forced miR-188-3p expression increased migratory behavior of colorectal cancer cells in vitro and metastases formation in vivo (P < 0.05). The promigratory role of miR-188-3p is mediated by direct interaction with MLLT4, a novel identified player involved in colorectal cancer cell migration. Conclusions miR-188-3p is a novel independent prognostic factor in colorectal cancer patients, which can be partly explained by its effect on MLLT4 expression and migration of cancer cells. PMID:27601590
Predicting the Individual Risk of Acute Severe Colitis at Diagnosis.
Cesarini, Monica; Collins, Gary S; Rönnblom, Anders; Santos, Antonieta; Wang, Lai Mun; Sjöberg, Daniel; Parkes, Miles; Keshav, Satish; Travis, Simon P L
2017-03-01
Acute severe colitis [ASC] is associated with major morbidity. We aimed to develop and externally validate an index that predicted ASC within 3 years of diagnosis. The development cohort included patients aged 16-89 years, diagnosed with ulcerative colitis [UC] in Oxford and followed for 3 years. Primary outcome was hospitalization for ASC, excluding patients admitted within 1 month of diagnosis. Multivariable logistic regression examined the adjusted association of seven risk factors with ASC. Backwards elimination produced a parsimonious model that was simplified to create an easy-to-use index. External validation occurred in separate cohorts from Cambridge, UK, and Uppsala, Sweden. The development cohort [Oxford] included 34/111 patients who developed ASC within a median 14 months [range 1-29]. The final model applied the sum of 1 point each for extensive disease, C-reactive protein [CRP] > 10mg/l, or haemoglobin < 12g/dl F or < 14g/dl M at diagnosis, to give a score from 0/3 to 3/3. This predicted a 70% risk of developing ASC within 3 years [score 3/3]. Validation cohorts included different proportions with ASC [Cambridge = 25/96; Uppsala = 18/298]. Of those scoring 3/3 at diagnosis, 18/18 [Cambridge] and 12/13 [Uppsala] subsequently developed ASC. Discriminant ability [c-index, where 1.0 = perfect discrimination] was 0.81 [Oxford], 0.95 [Cambridge], 0.97 [Uppsala]. Internal validation using bootstrapping showed good calibration, with similar predicted risk across all cohorts. A nomogram predicted individual risk. An index applied at diagnosis reliably predicts the risk of ASC within 3 years in different populations. Patients with a score 3/3 at diagnosis may merit early immunomodulator therapy. Copyright © 2016 European Crohn’s and Colitis Organisation (ECCO). Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com
Dinglin, Xiao-Xiao; Ma, Shu-Xiang; Wang, Fang; Li, De-Lan; Liang, Jian-Zhong; Chen, Xin-Ru; Liu, Qing; Zeng, Yin-Duo; Chen, Li-Kun
2017-05-01
The current published prognosis models for brain metastases (BMs) from cancer have not addressed the issue of either newly diagnosed non-small-cell lung cancer (NSCLC) with BMs or the lung cancer genotype. We sought to build an adjusted prognosis analysis (APA) model, a new prognosis model specifically for NSCLC patients with BMs at the initial diagnosis using adjusted prognosis analysis (APA). The model was derived using data from 1158 consecutive patients, with 837 in the derivation cohort and 321 in the validation cohort. The patients had initially received a diagnosis of BMs from NSCLC at Sun Yat-Sen University Cancer Center from 1994 to 2015. The prognostic factors analyzed included patient characteristics, disease characteristics, and treatments. The APA model was built according to the numerical score derived from the hazard ratio of each independent prognostic variable. The predictive accuracy of the APA model was determined using a concordance index and was compared with current prognosis models. The results were validated using bootstrap resampling and a validation cohort. We established 2 prognostic models (APA 1 and 2) for the whole group of patients and for those with known epidermal growth factor receptor (EGFR) genotype, respectively. Six factors were independently associated with survival time: Karnofsky performance status, age, smoking history (replaced by EGFR mutation in APA 2), local treatment of intracranial metastases, EGFR-tyrosine kinase inhibitor treatment, and chemotherapy. Patients in the derivation cohort were stratified into low- (score, 0-2), moderate- (score, 3-5), and high-risk (score 6-7) groups according to the median survival time (16.6, 10.3, and 5.2 months, respectively; P < .001). The results were further confirmed in the validation cohort. Compared with recursive partition analysis and graded prognostic assessment, APA seems to be more suitable for initially diagnosed NSCLC with BMs. Copyright © 2017 Elsevier Inc. All rights reserved.
Yen, Jennifer; Van Arendonk, Kyle J.; Streiff, Michael B.; McNamara, LeAnn; Stewart, F. Dylan; Conner G, Kim G; Thompson, Richard E.; Haut, Elliott R.; Takemoto, Clifford M.
2017-01-01
OBJECTIVES Identify risk factors for venous thromboembolism (VTE) and develop a VTE risk assessment model for pediatric trauma patients. DESIGN, SETTING, AND PATIENTS We performed a retrospective review of patients 21 years and younger who were hospitalized following traumatic injuries at the John Hopkins level 1 adult and pediatric trauma center (1987-2011). The clinical characteristics of patients with and without VTE were compared, and multivariable logistic regression analysis was used to identify independent risk factors for VTE. Weighted risk assessment scoring systems were developed based on these and previously identified factors from patients in the National Trauma Data Bank (NTDB 2008-2010); the scoring systems were validated in this cohort from Johns Hopkins as well as a cohort of pediatric admissions from the NTDB (2011-2012). MAIN RESULTS Forty-nine of 17,366 pediatric trauma patients (0.28%) were diagnosed with VTE after admission to our trauma center. After adjusting for potential confounders, VTE was independently associated with older age, surgery, blood transfusion, higher Injury Severity Score (ISS), and lower Glasgow Coma Scale (GCS) score. These and additional factors were identified in 402,329 pediatric patients from the NTDB from 2008-2010; independent risk factors from the logistic regression analysis of this NTDB cohort were selected and incorporated into weighted risk assessment scoring systems. Two models were developed and were cross-validated in 2 separate pediatric trauma cohorts: 1) 282,535 patients in the NTDB from 2011 to 2012 2) 17,366 patients from Johns Hopkins. The receiver operator curve using these models in the validation cohorts had area under the curves that ranged 90% to 94%. CONCLUSIONS VTE is infrequent after trauma in pediatric patients. We developed weighted scoring systems to stratify pediatric trauma patients at risk for VTE. These systems may have potential to guide risk-appropriate VTE prophylaxis in children after trauma. PMID:26963757
Developing and Validating a Predictive Model for Stroke Progression
Craig, L.E.; Wu, O.; Gilmour, H.; Barber, M.; Langhorne, P.
2011-01-01
Background Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. Methods Two patient cohorts were used for this study – the first cohort formed the training data set, which included consecutive patients admitted to an urban teaching hospital between 2000 and 2002, and the second cohort formed the test data set, which included patients admitted to the same hospital between 2003 and 2004. A standard definition of stroke progression was used. The first cohort (n = 863) was used to develop the model. Variables that were statistically significant (p < 0.1) on univariate analysis were included in the multivariate model. Logistic regression was the technique employed using backward stepwise regression to drop the least significant variables (p > 0.1) in turn. The second cohort (n = 216) was used to test the performance of the model. The performance of the predictive model was assessed in terms of both calibration and discrimination. Multiple imputation methods were used for dealing with the missing values. Results Variables shown to be significant predictors of stroke progression were conscious level, history of coronary heart disease, presence of hyperosmolarity, CT lesion, living alone on admission, Oxfordshire Community Stroke Project classification, presence of pyrexia and smoking status. The model appears to have reasonable discriminative properties [the median receiver-operating characteristic curve value was 0.72 (range 0.72–0.73)] and to fit well with the observed data, which is indicated by the high goodness-of-fit p value [the median p value from the Hosmer-Lemeshow test was 0.90 (range 0.50–0.92)]. Conclusion The predictive model developed in this study contains variables that can be easily collected in practice therefore increasing its usability in clinical practice. Using this analysis approach, the discrimination and calibration of the predictive model appear sufficiently high to provide accurate predictions. This study also offers some discussion around the validation of predictive models for wider use in clinical practice. PMID:22566988
Sysol, Justin R.; Abbasi, Taimur; Patel, Amit R.; Lang, Roberto M.; Gupta, Akash; Garcia, Joe G. N.; Gordeuk, Victor R.; Machado, Roberto F.
2016-01-01
Background Diastolic dysfunction is common in sickle cell disease (SCD), and is associated with an increased risk of mortality. However, the molecular pathogenesis underlying this development is poorly understood. The aim of this study was to identify a gene expression profile that is associated with diastolic function in SCD, potentially elucidating molecular mechanisms behind diastolic dysfunction development. Methods Diastolic function was measured via echocardiography in 65 patients with SCD from two independent study populations. Gene expression microarray data was compared with diastolic function in both study cohorts. Candidate genes that associated in both analyses were tested for validation in a murine SCD model. Lastly, genotyping array data from the replication cohort was used to derive cis-expression quantitative trait loci (cis-eQTLs) and genetic associations within the candidate gene regions. Results Transcriptome data from both patient cohorts implicated 7 genes associated with diastolic function, and mouse SCD myocardial expression validated 3 of these genes. Genetic associations and eQTLs were detected in 2 of the 3 genes, FUCA2 and IL18. Conclusions FUCA2 and IL18 are associated with diastolic function in SCD patients, and may be involved in the pathogenesis of the disease. Genetic polymorphisms within the FUCA2 and IL18 gene regions are also associated with diastolic function in SCD, likely by affecting expression levels of the genes. PMID:27636371
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cui, Yi; Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo; Song, Jie
Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT {sup 18}F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162more » robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6). Conclusion: Quantitative analysis identified novel {sup 18}F-fluorodeoxyglucose positron emission tomography image features that showed improved prognostic value over conventional imaging metrics. If validated in large, prospective cohorts, the new prognostic signature might be used to identify patients for individualized risk-adaptive therapy.« less
Risk prediction model for knee pain in the Nottingham community: a Bayesian modelling approach.
Fernandes, G S; Bhattacharya, A; McWilliams, D F; Ingham, S L; Doherty, M; Zhang, W
2017-03-20
Twenty-five percent of the British population over the age of 50 years experiences knee pain. Knee pain can limit physical ability and cause distress and bears significant socioeconomic costs. The objectives of this study were to develop and validate the first risk prediction model for incident knee pain in the Nottingham community and validate this internally within the Nottingham cohort and externally within the Osteoarthritis Initiative (OAI) cohort. A total of 1822 participants from the Nottingham community who were at risk for knee pain were followed for 12 years. Of this cohort, two-thirds (n = 1203) were used to develop the risk prediction model, and one-third (n = 619) were used to validate the model. Incident knee pain was defined as pain on most days for at least 1 month in the past 12 months. Predictors were age, sex, body mass index, pain elsewhere, prior knee injury and knee alignment. A Bayesian logistic regression model was used to determine the probability of an OR >1. The Hosmer-Lemeshow χ 2 statistic (HLS) was used for calibration, and ROC curve analysis was used for discrimination. The OAI cohort from the United States was also used to examine the performance of the model. A risk prediction model for knee pain incidence was developed using a Bayesian approach. The model had good calibration, with an HLS of 7.17 (p = 0.52) and moderate discriminative ability (ROC 0.70) in the community. Individual scenarios are given using the model. However, the model had poor calibration (HLS 5866.28, p < 0.01) and poor discriminative ability (ROC 0.54) in the OAI cohort. To our knowledge, this is the first risk prediction model for knee pain, regardless of underlying structural changes of knee osteoarthritis, in the community using a Bayesian modelling approach. The model appears to work well in a community-based population but not in individuals with a higher risk for knee osteoarthritis, and it may provide a convenient tool for use in primary care to predict the risk of knee pain in the general population.
Extending the Research on the Tests of Early Numeracy: Longitudinal Analyses over Two School Years
ERIC Educational Resources Information Center
Baglici, Stephanie Petreshock; Codding, Robin; Tryon, Georgiana
2010-01-01
The purpose of this study was to extend the research on the "Tests of Early Numeracy" (TEN) by following a cohort of 61 students from kindergarten through first grade. Specifically, this study examined the relationship between kindergarten and first-grade TEN measures built within and across school years and their predictive validity of a math…
Williams, Brent A; Chagin, Kevin M; Bash, Lori D; Boden, William E; Duval, Sue; Fowkes, F Gerry R; Mahaffey, Kenneth W; Patel, Mehul D; D'Agostino, Ralph B; Peterson, Eric D; Kattan, Michael W; Bhatt, Deepak L; Bonaca, Marc P
2018-05-01
Risk stratification of patients with recent myocardial infarction (MI) for subsequent cardiovascular (CV) events helps identify patients most likely to benefit from secondary prevention therapies. This study externally validated a new risk score (TRS2˚P) for secondary events derived from the TRA2°P-TIMI 50 trial among post-MI patients from two large health care systems. This retrospective cohort study included 9618 patients treated for acute MI at either the Cleveland Clinic (CC) or Geisinger Health System (GHS) between 2008 and 2013. Patients with a clinic visit within 2-52 weeks of MI were included and followed for CV death, repeat MI, and ischemic stroke through electronic medical records (EMR). The TRS2˚P is based on nine factors determined through EMR documentation. Discrimination and calibration of the TRS2˚P were quantified in both patient populations. MI patients at CC and GHS were older, had more comorbidities, received fewer medications, and had higher 3-year event rates compared to subjects in the TRA2°P trial: 31% (CC), 33% (GHS), and 10% (TRA2°P-TIMI 50). The proposed risk score had similar discrimination across the three cohorts with c-statistics of 0.66 (CC), 0.66 (GHS), and 0.67 (TRA2°P-TIMI 50). A strong graded relationship between the risk score and event rates was observed in all cohorts, though 3-year event rates were consistently higher within TRS2°P strata in the CC and GHS cohorts relative to TRA2˚P-TIMI 50. The TRS2˚P demonstrated consistent risk discrimination across trial and non-trial patients with recent MI, but event rates were consistently higher in the non-trial cohorts. Copyright © 2018. Published by Elsevier B.V.
Stratton, Alexandra; Faris, Peter; Thomas, Kenneth
2018-05-01
Retrospective cohort study. To test the external validity of the 2 published prediction criteria for failure of medical management in patients with spinal epidural abscess (SEA). Patients with SEA over a 10-year period at a tertiary care center were identified using ICD-10 (International Classification of Diseases, 10th Revision) diagnostic codes; electronic and paper charts were reviewed. The incidence of SEA and the proportion of patients with SEA that were treated medically were calculated. The rate of failure of medical management was determined. The published prediction models were applied to our data to determine how predictive they were of failure in our cohort. A total of 550 patients were identified using ICD-10 codes, 160 of whom had a magnetic resonance imaging-confirmed diagnosis of SEA. The incidence of SEA was 16 patients per year. Seventy-five patients were found to be intentionally managed medically and were included in the analysis. Thirteen of these 75 patients failed medical management (17%). Based on the published prediction criteria, 26% (Kim et al) and 45% (Patel et al) of our patients were expected to fail. Published prediction models for failure of medical management of SEA were not valid in our cohort. However, once calibrated to our cohort, Patel's model consisting of positive blood culture, presence of diabetes, white blood cells >12.5, and C-reactive protein >115 was the better model for our data.
HLA-DQA1 and PLA2R1 polymorphisms and risk of idiopathic membranous nephropathy.
Bullich, Gemma; Ballarín, José; Oliver, Artur; Ayasreh, Nadia; Silva, Irene; Santín, Sheila; Díaz-Encarnación, Montserrat M; Torra, Roser; Ars, Elisabet
2014-02-01
Single nucleotide polymorphisms (SNPs) within HLA complex class II HLA-DQ α-chain 1 (HLA-DQA1) and M-type phospholipase A2 receptor (PLA2R1) genes were identified as strong risk factors for idiopathic membranous nephropathy (IMN) development in a recent genome-wide association study. Copy number variants (CNVs) within the Fc gamma receptor III (FCGR3) locus have been associated with several autoimmune diseases, but their role in IMN has not been studied. This study aimed to validate the association of HLA-DQA1 and PLA2R1 risk alleles with IMN in a Spanish cohort, test the putative association of FCGR3A and FCGR3B CNVs with IMN, and assess the use of these genetic factors to predict the clinical outcome of the disease. A Spanish cohort of 89 IMN patients and 286 matched controls without nephropathy was recruited between October of 2009 and July of 2012. Case-control studies for SNPs within HLA-DQA1 (rs2187668) and PLA2R1 (rs4664308) genes and CNVs for FCGR3A and FCGR3B genes were performed. The contribution of these polymorphisms to predict clinical outcome and renal function decline was analyzed. This study validated the association of these HLA-DQA1 and PLA2R1 SNPs with IMN in a Spanish cohort and its increased risk when combining both risk genotypes. No significant association was found between FCGR3 CNVs and IMN. These results revealed that HLA-DQA1 and PLA2R1 genotype combination adjusted for baseline proteinuria strongly predicted response to immunosuppressive therapy. HLA-DQA1 genotype adjusted for proteinuria was also linked with renal function decline. This study confirms that HLA-DQA1 and PLA2R1 genotypes are risk factors for IMN, whereas no association was identified for FCGR3 CNVs. This study provides, for the first time, evidence of the contribution of these HLA-DQA1 and PLA2R1 polymorphisms in predicting IMN response to immunosuppressors and disease progression. Future studies are needed to validate and identify prognostic markers.
Validation of intermediate end points in cancer research.
Schatzkin, A; Freedman, L S; Schiffman, M H; Dawsey, S M
1990-11-21
Investigations using intermediate end points as cancer surrogates are quicker, smaller, and less expensive than studies that use malignancy as the end point. We present a strategy for determining whether a given biomarker is a valid intermediate end point between an exposure and incidence of cancer. Candidate intermediate end points may be selected from case series, ecologic studies, and animal experiments. Prospective cohort and sometimes case-control studies may be used to quantify the intermediate end point-cancer association. The most appropriate measure of this association is the attributable proportion. The intermediate end point is a valid cancer surrogate if the attributable proportion is close to 1.0, but not if it is close to 0. Usually, the attributable proportion is close to neither 1.0 nor 0; in this case, valid surrogacy requires that the intermediate end point mediate an established exposure-cancer relation. This would in turn imply that the exposure effect would vanish if adjusted for the intermediate end point. We discuss the relative advantages of intervention and observational studies for the validation of intermediate end points. This validation strategy also may be applied to intermediate end points for adverse reproductive outcomes and chronic diseases other than cancer.
Mohey, Hesham; Laurent, Blandine; Mariat, Christophe; Berthoux, Francois
2013-08-01
We established earlier the absolute renal risk (ARR) of dialysis/death (D/D) in primary IgA nephropathy (IgAN) which permitted accurate prospective prediction of final prognosis. This ARR was based on the potential presence at initial diagnosis of three major, independent, and equipotent risk factors such as hypertension, quantitative proteinuria≥1 g per day, and severe pathological lesions appreciated by our local classification scoring≥8 (range 0-20). We studied the validity of this ARR concept in secondary IgAN to predict future outcome and focused on Henoch-Schönlein purpura (HSP) nephritis. Our cohort of adults IgAN concerned 1064 patients with 101 secondary IgAN and was focused on 74 HSP (59 men) with a mean age of 38.6 at initial diagnosis and a mean follow-up of 11.8 years. Three major risk factors: hypertension, proteinuria≥1 g/d, and severe pathological lesions appreciated by our global optical score≥8 (GOS integrated all elementary histological lesions), were studied at biopsy-proven diagnosis and their presence defined the ARR scoring: 0 for none present, 3 for all present, 1 or 2 for the presence of any 1 or 2 risk factors. The primary end-point was composite with occurrence of dialysis or death before (D/D). We used classical statistics and both time-dependent Cox regression and Kaplan-Meier survival curve methods. The cumulative rate of D/D at 10 and 20 years post-onset was respectively 0 and 14% for ARR=0 (23 patients); 10 and 23% for ARR=1 (N=19); 27 and 33% for ARR=2 (N=24); and 81 and 100% (before 20 y) in the 8 patients with ARR=3 (P=0.0007). Prediction at time of diagnosis (time zero) of 10y cumulative rate of D/D event was 0% for ARR=0, 10% for ARR=1, 33% for ARR=2, and 100% by 8.5y for ARR=3 (P=0.0003) in this adequately treated cohort. This study clearly validates the Absolute Renal Risk of Dialysis/Death concept in a new cohort of HSP-IgAN with utility to individual management and in future clinical trials.
Lewis, Gregory D; Ngo, Debby; Hemnes, Anna R; Farrell, Laurie; Domos, Carly; Pappagianopoulos, Paul P; Dhakal, Bishnu P; Souza, Amanda; Shi, Xu; Pugh, Meredith E; Beloiartsev, Arkadi; Sinha, Sumita; Clish, Clary B; Gerszten, Robert E
2016-01-19
Pulmonary hypertension and associated right ventricular (RV) dysfunction are important determinants of morbidity and mortality, which are optimally characterized by invasive hemodynamic measurements. This study sought to determine whether metabolite profiling could identify plasma signatures of right ventricular-pulmonary vascular (RV-PV) dysfunction. We measured plasma concentrations of 105 metabolites using targeted mass spectrometry in 71 individuals (discovery cohort) who underwent comprehensive physiological assessment with right-sided heart catheterization and radionuclide ventriculography at rest and during exercise. Our findings were validated in a second cohort undergoing invasive hemodynamic evaluations (n = 71), as well as in an independent cohort with or without known pulmonary arterial (PA) hypertension (n = 30). In the discovery cohort, 21 metabolites were associated with 2 or more hemodynamic indicators of RV-PV function (i.e., resting right atrial pressure, mean PA pressure, pulmonary vascular resistance [PVR], and PVR and PA pressure-flow response [ΔPQ] during exercise). We identified novel associations of RV-PV dysfunction with circulating indoleamine 2,3-dioxygenase (IDO)-dependent tryptophan metabolites (TMs), tricarboxylic acid intermediates, and purine metabolites and confirmed previously described associations with arginine-nitric oxide metabolic pathway constituents. IDO-TM levels were inversely related to RV ejection fraction and were particularly well correlated with exercise PVR and ΔPQ. Multisite sampling demonstrated transpulmonary release of IDO-TMs. IDO-TMs also identified RV-PV dysfunction in a validation cohort with known risk factors for pulmonary hypertension and in patients with established PA hypertension. Metabolic profiling identified reproducible signatures of RV-PV dysfunction, highlighting both new biomarkers and pathways for further functional characterization. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Syed, Zeeshan; Moscucci, Mauro; Share, David; Gurm, Hitinder S
2015-01-01
Background Clinical tools to stratify patients for emergency coronary artery bypass graft (ECABG) after percutaneous coronary intervention (PCI) create the opportunity to selectively assign patients undergoing procedures to hospitals with and without onsite surgical facilities for dealing with potential complications while balancing load across providers. The goal of our study was to investigate the feasibility of a computational model directly optimised for cohort-level performance to predict ECABG in PCI patients for this application. Methods Blue Cross Blue Shield of Michigan Cardiovascular Consortium registry data with 69 pre-procedural and angiographic risk variables from 68 022 PCI procedures in 2004–2007 were used to develop a support vector machine (SVM) model for ECABG. The SVM model was optimised for the area under the receiver operating characteristic curve (AUROC) at the level of the training cohort and validated on 42 310 PCI procedures performed in 2008–2009. Results There were 87 cases of ECABG (0.21%) in the validation cohort. The SVM model achieved an AUROC of 0.81 (95% CI 0.76 to 0.86). Patients in the predicted top decile were at a significantly increased risk relative to the remaining patients (OR 9.74, 95% CI 6.39 to 14.85, p<0.001) for ECABG. The SVM model optimised for the AUROC on the training cohort significantly improved discrimination, net reclassification and calibration over logistic regression and traditional SVM classification optimised for univariate performance. Conclusions Computational risk stratification directly optimising cohort-level performance holds the potential of high levels of discrimination for ECABG following PCI. This approach has value in selectively referring PCI patients to hospitals with and without onsite surgery. PMID:26688738
Street, J T; Thorogood, N P; Cheung, A; Noonan, V K; Chen, J; Fisher, C G; Dvorak, M F
2013-06-01
Observational cohort comparison. To compare the previously validated Spine Adverse Events Severity system (SAVES) with International Classification of Diseases, Tenth Revision codes (ICD-10) codes for identifying adverse events (AEs) in patients with traumatic spinal cord injury (TSCI). Quaternary Care Spine Program. Patients discharged between 2006 and 2010 were identified from our prospective registry. Two consecutive cohorts were created based on the system used to record acute care AEs; one used ICD-10 coding by hospital coders and the other used SAVES data prospectively collected by a multidisciplinary clinical team. The ICD-10 codes were appropriately mapped to the SAVES. There were 212 patients in the ICD-10 cohort and 173 patients in the SAVES cohort. Analyses were adjusted to account for the different sample sizes, and the two cohorts were comparable based on age, gender and motor score. The SAVES system identified twice as many AEs per person as ICD-10 coding. Fifteen unique AEs were more reliably identified using SAVES, including neuropathic pain (32 × more; P<0.001), urinary tract infections (1.4 × ; P<0.05), pressure sores (2.9 × ; P<0.001) and intra-operative AEs (2.3 × ; P<0.05). Eight of these 15 AEs more frequently identified by SAVES significantly impacted length of stay (P<0.05). Risk factors such as patient age and severity of paralysis were more reliably correlated to AEs collected through SAVES than ICD-10. Implementation of the SAVES system for patients with TSCI captured more individuals experiencing AEs and more AEs per person compared with ICD-10 codes. This study demonstrates the utility of prospectively collecting AE data using validated tools.
Huber, J; Hüsler, J; Dieppe, P; Günther, K P; Dreinhöfer, K; Judge, A
2016-03-01
To validate a new method to identify responders (relative effect per patient (REPP) >0.2) using the OMERACT-OARSI criteria as gold standard in a large multicentre sample. The REPP ([score before - after treatment]/score before treatment) was calculated for 845 patients of a large multicenter European cohort study for THR. The patients with a REPP >0.2 were defined as responders. The responder rate was compared to the gold standard (OMERACT-OARSI criteria) using receiver operator characteristic (ROC) curve analysis for sensitivity, specificity and percentage of appropriately classified patients. With the criterion REPP>0.2 85.4% of the patients were classified as responders, applying the OARSI-OMERACT criteria 85.7%. The new method had 98.8% sensitivity, 94.2% specificity and 98.1% of the patients were correctly classified compared to the gold standard. The external validation showed a high sensitivity and also specificity of a new criterion to identify a responder compared to the gold standard method. It is simple and has no uncertainties due to a single classification criterion. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Brunckhorst, Oliver; Shahid, Shahab; Aydin, Abdullatif; McIlhenny, Craig; Khan, Shahid; Raza, Syed Johar; Sahai, Arun; Brewin, James; Bello, Fernando; Kneebone, Roger; Khan, Muhammad Shamim; Dasgupta, Prokar; Ahmed, Kamran
2015-09-01
Current training modalities within ureteroscopy have been extensively validated and must now be integrated within a comprehensive curriculum. Additionally, non-technical skills often cause surgical error and little research has been conducted to combine this with technical skills teaching. This study therefore aimed to develop and validate a curriculum for semi-rigid ureteroscopy, integrating both technical and non-technical skills teaching within the programme. Delphi methodology was utilised for curriculum development and content validation, with a randomised trial then conducted (n = 32) for curriculum evaluation. The developed curriculum consisted of four modules; initially developing basic technical skills and subsequently integrating non-technical skills teaching. Sixteen participants underwent the simulation-based curriculum and were subsequently assessed, together with the control cohort (n = 16) within a full immersion environment. Both technical (Time to completion, OSATS and a task specific checklist) and non-technical (NOTSS) outcome measures were recorded with parametric and non-parametric analyses used depending on the distribution of our data as evaluated by a Shapiro-Wilk test. Improvements within the intervention cohort demonstrated educational value across all technical and non-technical parameters recorded, including time to completion (p < 0.01), OSATS scores (p < 0.001), task specific checklist scores (p = 0.011) and NOTSS scores (p < 0.001). Content validity, feasibility and acceptability were all demonstrated through curriculum development and post-study questionnaire results. The current developed curriculum demonstrates that integrating both technical and non-technical skills teaching is both educationally valuable and feasible. Additionally, the curriculum offers a validated simulation-based training modality within ureteroscopy and a framework for the development of other simulation-based programmes.
Graff, Lesley A; Sexton, Kathryn A; Walker, John R; Clara, Ian; Targownik, Laura E; Bernstein, Charles N
2016-09-01
Self-efficacy describes a person's confidence in their ability to manage demands, and is predictive of health outcomes in chronic disease such as hospitalization and health status. However, meaningful measurement must be domain (e.g., disease) specific. This study aims to provide validation of the Inflammatory Bowel Disease Self-Efficacy scale (IBD-SE), using a population-based IBD sample. Manitoba IBD Cohort Study participants completed a survey and clinical interview at a mean of 12 years postdiagnosis (n = 121 Crohn's disease; n = 108 ulcerative colitis), which included validated measures of psychological functioning, disability, disease-specific quality of life, perceived health, and current and recent disease activity, in addition to the IBD-SE. The IBD-SE had high internal consistency (Cronbach's α = 0.97), and a 4-factor structure was confirmed. Construct validity was demonstrated as follows: the IBD-SE was strongly correlated with mastery (r = 0.53), highly correlated in the expected directions with measures of psychological well-being (r = 0.70), stress (r = -0.78), distress (r = -0.71), disability (r = -0.48), disease-specific quality of life (r = 0.68), and overall perceived health (r = 0.52) (all P < 0.001). Those with currently inactive disease had higher self-efficacy than the active disease group (Crohn's disease: mean = 232 versus 195, P < 0.001; ulcerative colitis: mean = 233 versus 202, P < 0.01), with similar findings for recent symptomatic disease activity. The IBD-SE is a reliable, valid, and sensitive measure as demonstrated in this population-based sample, supporting its utility in IBD. Because self-efficacy is a modifiable psychological characteristic that can contribute to positive health outcomes, the IBD-SE may prove to be a valuable instrument for research and in targeted intervention with IBD patients.
Émond, Marcel; Guimont, Chantal; Chauny, Jean-Marc; Daoust, Raoul; Bergeron, Éric; Vanier, Laurent; Moore, Lynne; Plourde, Miville; Kuimi, Batomen; Boucher, Valérie; Allain-Boulé, Nadine; Le Sage, Natalie
2017-01-01
Background: About 75% of patients with minor thoracic injury are discharged after an emergency department visit. However, complications such as delayed hemothorax can occur. We sought to derive and validate a clinical decision rule to predict hemothorax in patients discharged from the emergency department. Methods: We conducted a 6-year prospective cohort study in 4 university-affiliated emergency departments. Patients aged 16 years or older presenting with a minor thoracic injury were assessed at 5 time points (initial visit and 7, 14, 30 and 90 d after the injury). Radiologists' reports were reviewed for the presence of hemothorax. We used log-binomial regression models to identify predictors of hemothorax. Results: A total of 1382 patients were included: 830 in the derivation phase and 552 in the validation phase. Of these, 151 (10.9%) had hemothorax at the 14-day follow-up. Patients 65 years of age or older represented 25.3% (210/830) and 23.7% (131/552) of the derivation and validation cohorts, respectively. The final clinical decision rule included a combination of age (> 70 yr, 2 points; 45-70 yr, 1 point), fracture of any high to mid thorax rib (ribs 3-9, 2 points) and presence of 3 or more rib fractures (1 point). Twenty (30.8%) of the 65 high-risk patients (score ≥ 4) experienced hemothorax during the follow-up period. The clinical decision rule had a high specificity (90.7%, 95% confidence interval 87.7%-93.1%) in this high-risk group, thus guiding appropriate post-emergency care. Interpretation: One patient out of every 10 presented with delayed hemothorax after discharge from the emergency department. Implementation of this validated clinical decision rule for minor thoracic injury could guide emergency discharge plans. PMID:28611156
Herrmann, Wolfram J; Weikert, Cornelia; Bergmann, Manuela; Boeing, Heiner; Katzke, Verena A; Kaaks, Rudolf; Tiller, Daniel; Greiser, Karin Halina; Heier, Margit; Meisinger, Christa; Schmidt, Carsten Oliver; Neuhauser, Hannelore; Heidemann, Christin; Jünger, Claus; Wild, Philipp S; Schramm, Sara Helena; Jöckel, Karl-Heinz; Dörr, Marcus; Pischon, Tobias
2018-04-01
Cardiovascular and metabolic diseases are a major cause of mortality and loss of quality of life in Germany. Research into risk factors of these diseases requires large population-based cohort studies. Complete and accurate assessment of the incidence of cardiovascular and metabolic diseases is a key element for valid interpretation of the results from such studies. Our aim was to identify population-based cohort studies with incidence of cardiovascular and metabolic diseases in Germany and to summarize their methods for assessment and classification of disease endpoints, including myocardial infarction, type 2 diabetes, stroke, heart failure, and arterial hypertension. Within the framework of a workshop, representatives of the ascertained population-based cohort studies in Germany with incidence of cardiovascular or metabolic diseases were invited to present and to systematically provide information on their methods of endpoint identification. We identified eight studies from different regions in Germany with a total of 100,571 participants, aged 18-83 years at baseline. Self-reporting by study participants is the major source for further inquiries to assess disease endpoints in these studies. Most studies use additional data sources to verify the incidence of diseases, such as documents provided by the treating physician or hospital. Our results highlight the central role of self-reporting and the efforts associated with identification and verification of disease endpoints in cohort studies. They also provide a basis for future population-based studies that aim for standardized assessment of the incidence of cardiovascular and metabolic diseases.
The Measurement and Evaluation of Social Attitudes in Two British Cohort Studies
ERIC Educational Resources Information Center
Cheng, Helen; Bynner, John; Wiggins, Richard; Schoon, Ingrid
2012-01-01
This paper presents an empirical evaluation of the internal consistency and validity of six attitudes scales assessing left-right beliefs, political cynicism, antiracism, libertarian-authoritarian views, and gender equality (two versions) in two large nationally representative samples of the British population born in 1958 and 1970. In the 1958…
Are Fluency Measures Accurate Predictors of Reading Achievement?
ERIC Educational Resources Information Center
Schilling, Stephen G.; Carlisle, Joanne F.; Scott, Sarah E.; Zeng, Ji
2007-01-01
This study focused on the predictive validity of fluency measures that comprise Dynamic Indicators of Basic Early Literacy Skills (DIBELS). Data were gathered from first through third graders attending 44 schools in 9 districts or local educational agencies that made up the first Reading First cohort in Michigan. Students were administered DIBELS…
Moojen, Wouter A; Arts, Mark P; Bartels, Ronald H M A; Jacobs, Wilco C H; Peul, Wilco C
2011-10-01
Despite an increasing implantation rate of interspinous process distraction (IPD) devices in the treatment of intermittent neurogenic claudication (INC), definitive evidence on the clinical effectiveness of implants is lacking. The main objective of this review was to perform a meta-analysis of all systematic reviews, randomized clinical trials and prospective cohort series to quantify the effectiveness of IPDs and to evaluate the potential side-effects. Data from all studies prospectively describing clinical results based on validated outcome scales and reporting complications of treatment of patients with INC with IPD placement. We searched MEDLINE, EMBASE, Web of Science, Cochrane (CENTRAL), CINAHL, Academic Search Premier, Science Direct up to July 2010. Studies describing patients with INC caused by lumbar stenosis, reporting complication rate and reporting based on validated outcome scores, were eligible. Studies with only instrumented IPD results were excluded. Eleven studies eligible studies were identified. Two independently RCTs and eight prospective cohorts were available. In total 563 patients were treated with IPDs. All studies showed improvement in validated outcome scores after 6 weeks and 1 year. Pooled data based on the Zurich Claudication Questionnaire of the RCTs were more in favor of IPD treatment compared with conservative treatment (pooled estimate 23.2, SD 18.5-27.8). Statistical heterogeneity after pooled data was low (I-squared 0.0, p = 0.930). Overall complication rate was 7%. As the evidence is relatively low and the costs are high, more thorough (cost-) effectiveness studies should be performed before worldwide implementation is introduced.
Cerebral palsy in Victoria: motor types, topography and gross motor function.
Howard, Jason; Soo, Brendan; Graham, H Kerr; Boyd, Roslyn N; Reid, Sue; Lanigan, Anna; Wolfe, Rory; Reddihough, Dinah S
2005-01-01
To study the relationships between motor type, topographical distribution and gross motor function in a large, population-based cohort of children with cerebral palsy (CP), from the State of Victoria, and compare this cohort to similar cohorts from other countries. An inception cohort was generated from the Victorian Cerebral Palsy Register (VCPR) for the birth years 1990-1992. Demographic information, motor types and topographical distribution were obtained from the register and supplemented by grading gross motor function according to the Gross Motor Function Classification System (GMFCS). Complete data were obtained on 323 (86%) of 374 children in the cohort. Gross motor function varied from GMFCS level I (35%) to GMFCS level V (18%) and was similar in distribution to a contemporaneous Swedish cohort. There was a fairly even distribution across the topographical distributions of hemiplegia (35%), diplegia (28%) and quadriplegia (37%) with a large majority of young people having the spastic motor type (86%). The VCPR is ideal for population-based studies of gross motor function in children with CP. Gross motor function is similar in populations of children with CP in developed countries but the comparison of motor types and topographical distribution is difficult because of lack of consensus with classification systems. Use of the GMFCS provides a valid and reproducible method for clinicians to describe gross motor function in children with CP using a universal language.
Self-selection and bias in a large prospective pregnancy cohort in Norway.
Nilsen, Roy M; Vollset, Stein Emil; Gjessing, Håkon K; Skjaerven, Rolv; Melve, Kari K; Schreuder, Patricia; Alsaker, Elin R; Haug, Kjell; Daltveit, Anne Kjersti; Magnus, Per
2009-11-01
Self-selection in epidemiological studies may introduce selection bias and influence the validity of study results. To evaluate potential bias due to self-selection in a large prospective pregnancy cohort in Norway, the authors studied differences in prevalence estimates and association measures between study participants and all women giving birth in Norway. Women who agreed to participate in the Norwegian Mother and Child Cohort Study (43.5% of invited; n = 73 579) were compared with all women giving birth in Norway (n = 398 849) using data from the population-based Medical Birth Registry of Norway in 2000-2006. Bias in the prevalence of 23 exposure and outcome variables was measured as the ratio of relative frequencies, whereas bias in exposure-outcome associations of eight relationships was measured as the ratio of odds ratios. Statistically significant relative differences in prevalence estimates between the cohort participants and the total population were found for all variables, except for maternal epilepsy, chronic hypertension and pre-eclampsia. There was a strong under-representation of the youngest women (<25 years), those living alone, mothers with more than two previous births and with previous stillbirths (relative deviation 30-45%). In addition, smokers, women with stillbirths and neonatal death were markedly under-represented in the cohort (relative deviation 22-43%), while multivitamin and folic acid supplement users were over-represented (relative deviation 31-43%). Despite this, no statistically relative differences in association measures were found between participants and the total population regarding the eight exposure-outcome associations. Using data from the Medical Birth Registry of Norway, this study suggests that prevalence estimates of exposures and outcomes, but not estimates of exposure-outcome associations are biased due to self-selection in the Norwegian Mother and Child Cohort Study.
Söderqvist, Fredrik; Carlberg, Michael; Hardell, Lennart
2012-01-01
Since the International Agency for Research on Cancer recently classified radiofrequency electromagnetic fields, such as those emanating from mobile and cordless phones, as possibly carcinogenic to humans (group 2B), two additional reports relevant to the topic have been published. Both articles were new updates of a Danish cohort on mobile phone subscribers and concern the possible association between assumed use of mobile phones and risk of brain tumors. The aim of the present review is to reexamine all four publications on this cohort. In brief, publications were scrutinized, and in particular, if the authors made explicit claims to have either proved or disproved their hypothesis, such claims were reviewed in light of applied methods and study design, and in principle, the stronger the claims, the more careful our review. The nationwide Danish cohort study on mobile phone subscribers and risk of brain tumors, including at best 420,095 persons (58% of the initial cohort), is the only one of its kind. In comparison with previous investigations, i.e., case-control studies, its strength lies in the possibility to eliminate non-response, selection, and recall bias. Although at least non-response and recall bias can be excluded, the study has serious limitations related to exposure assessment. In fact, these limitations cloud the findings of the four reports to such an extent that render them uninformative at best. At worst, they may be used in a seemingly solid argument against an increased risk--as reassuring results from a large nationwide cohort study, which rules out not only non-response and recall bias but also an increased risk as indicated by tight confidence intervals. Although two of the most comprehensive case-control studies on the matter both have methodological limitations that need to be carefully considered, type I errors are not the only threats to the validity of studies on this topic--the Danish cohort study is a textbook example of that.
O’Connell, Grant C; Petrone, Ashley B; Treadway, Madison B; Tennant, Connie S; Lucke-Wold, Noelle; Chantler, Paul D; Barr, Taura L
2016-01-01
Early and accurate diagnosis of stroke improves the probability of positive outcome. The objective of this study was to identify a pattern of gene expression in peripheral blood that could potentially be optimised to expedite the diagnosis of acute ischaemic stroke (AIS). A discovery cohort was recruited consisting of 39 AIS patients and 24 neurologically asymptomatic controls. Peripheral blood was sampled at emergency department admission, and genome-wide expression profiling was performed via microarray. A machine-learning technique known as genetic algorithm k-nearest neighbours (GA/kNN) was then used to identify a pattern of gene expression that could optimally discriminate between groups. This pattern of expression was then assessed via qRT-PCR in an independent validation cohort, where it was evaluated for its ability to discriminate between an additional 39 AIS patients and 30 neurologically asymptomatic controls, as well as 20 acute stroke mimics. GA/kNN identified 10 genes (ANTXR2, STK3, PDK4, CD163, MAL, GRAP, ID3, CTSZ, KIF1B and PLXDC2) whose coordinate pattern of expression was able to identify 98.4% of discovery cohort subjects correctly (97.4% sensitive, 100% specific). In the validation cohort, the expression levels of the same 10 genes were able to identify 95.6% of subjects correctly when comparing AIS patients to asymptomatic controls (92.3% sensitive, 100% specific), and 94.9% of subjects correctly when comparing AIS patients with stroke mimics (97.4% sensitive, 90.0% specific). The transcriptional pattern identified in this study shows strong diagnostic potential, and warrants further evaluation to determine its true clinical efficacy. PMID:29263821
Guo, Ping; Dzingina, Mendwas; Firth, Alice M; Davies, Joanna M; Douiri, Abdel; O’Brien, Suzanne M; Pinto, Cathryn; Pask, Sophie; Higginson, Irene J; Eagar, Kathy; Murtagh, Fliss E M
2018-01-01
Introduction Provision of palliative care is inequitable with wide variations across conditions and settings in the UK. Lack of a standard way to classify by case complexity is one of the principle obstacles to addressing this. We aim to develop and validate a casemix classification to support the prediction of costs of specialist palliative care provision. Methods and analysis Phase I: A cohort study to determine the variables and potential classes to be included in a casemix classification. Data are collected from clinicians in palliative care services across inpatient hospice, hospital and community settings on: patient demographics, potential complexity/casemix criteria and patient-level resource use. Cost predictors are derived using multivariate regression and then incorporated into a classification using classification and regression trees. Internal validation will be conducted by bootstrapping to quantify any optimism in the predictive performance (calibration and discrimination) of the developed classification. Phase II: A mixed-methods cohort study across settings for external validation of the classification developed in phase I. Patient and family caregiver data will be collected longitudinally on demographics, potential complexity/casemix criteria and patient-level resource use. This will be triangulated with data collected from clinicians on potential complexity/casemix criteria and patient-level resource use, and with qualitative interviews with patients and caregivers about care provision across difference settings. The classification will be refined on the basis of its performance in the validation data set. Ethics and dissemination The study has been approved by the National Health Service Health Research Authority Research Ethics Committee. The results are expected to be disseminated in 2018 through papers for publication in major palliative care journals; policy briefs for clinicians, commissioning leads and policy makers; and lay summaries for patients and public. Trial registration number ISRCTN90752212. PMID:29550781
Guo, Ping; Dzingina, Mendwas; Firth, Alice M; Davies, Joanna M; Douiri, Abdel; O'Brien, Suzanne M; Pinto, Cathryn; Pask, Sophie; Higginson, Irene J; Eagar, Kathy; Murtagh, Fliss E M
2018-03-17
Provision of palliative care is inequitable with wide variations across conditions and settings in the UK. Lack of a standard way to classify by case complexity is one of the principle obstacles to addressing this. We aim to develop and validate a casemix classification to support the prediction of costs of specialist palliative care provision. Phase I: A cohort study to determine the variables and potential classes to be included in a casemix classification. Data are collected from clinicians in palliative care services across inpatient hospice, hospital and community settings on: patient demographics, potential complexity/casemix criteria and patient-level resource use. Cost predictors are derived using multivariate regression and then incorporated into a classification using classification and regression trees. Internal validation will be conducted by bootstrapping to quantify any optimism in the predictive performance (calibration and discrimination) of the developed classification. Phase II: A mixed-methods cohort study across settings for external validation of the classification developed in phase I. Patient and family caregiver data will be collected longitudinally on demographics, potential complexity/casemix criteria and patient-level resource use. This will be triangulated with data collected from clinicians on potential complexity/casemix criteria and patient-level resource use, and with qualitative interviews with patients and caregivers about care provision across difference settings. The classification will be refined on the basis of its performance in the validation data set. The study has been approved by the National Health Service Health Research Authority Research Ethics Committee. The results are expected to be disseminated in 2018 through papers for publication in major palliative care journals; policy briefs for clinicians, commissioning leads and policy makers; and lay summaries for patients and public. ISRCTN90752212. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Jayaram, Natalie; Spertus, John A; Kennedy, Kevin F; Vincent, Robert; Martin, Gerard R; Curtis, Jeptha P; Nykanen, David; Moore, Phillip M; Bergersen, Lisa
2017-11-21
Risk standardization for adverse events after congenital cardiac catheterization is needed to equitably compare patient outcomes among different hospitals as a foundation for quality improvement. The goal of this project was to develop a risk-standardization methodology to adjust for patient characteristics when comparing major adverse outcomes in the NCDR's (National Cardiovascular Data Registry) IMPACT Registry (Improving Pediatric and Adult Congenital Treatment). Between January 2011 and March 2014, 39 725 consecutive patients within IMPACT undergoing cardiac catheterization were identified. Given the heterogeneity of interventional procedures for congenital heart disease, new procedure-type risk categories were derived with empirical data and expert opinion, as were markers of hemodynamic vulnerability. A multivariable hierarchical logistic regression model to identify patient and procedural characteristics predictive of a major adverse event or death after cardiac catheterization was derived in 70% of the cohort and validated in the remaining 30%. The rate of major adverse event or death was 7.1% and 7.2% in the derivation and validation cohorts, respectively. Six procedure-type risk categories and 6 independent indicators of hemodynamic vulnerability were identified. The final risk adjustment model included procedure-type risk category, number of hemodynamic vulnerability indicators, renal insufficiency, single-ventricle physiology, and coagulation disorder. The model had good discrimination, with a C-statistic of 0.76 and 0.75 in the derivation and validation cohorts, respectively. Model calibration in the validation cohort was excellent, with a slope of 0.97 (standard error, 0.04; P value [for difference from 1] =0.53) and an intercept of 0.007 (standard error, 0.12; P value [for difference from 0] =0.95). The creation of a validated risk-standardization model for adverse outcomes after congenital cardiac catheterization can support reporting of risk-adjusted outcomes in the IMPACT Registry as a foundation for quality improvement. © 2017 American Heart Association, Inc.
Risk score to predict hospital-acquired pneumonia after spontaneous intracerebral hemorrhage.
Ji, Ruijun; Shen, Haipeng; Pan, Yuesong; Du, Wanliang; Wang, Penglian; Liu, Gaifen; Wang, Yilong; Li, Hao; Zhao, Xingquan; Wang, Yongjun
2014-09-01
We aimed to develop a risk score (intracerebral hemorrhage-associated pneumonia score, ICH-APS) for predicting hospital-acquired stroke-associated pneumonia (SAP) after ICH. The ICH-APS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Variables routinely collected at presentation were used for predicting SAP after ICH. For testing the added value of hematoma volume measure, we separately developed 2 models with (ICH-APS-B) and without (ICH-APS-A) hematoma volume included. Multivariable logistic regression was performed to identify independent predictors. The area under the receiver operating characteristic curve (AUROC), Hosmer-Lemeshow goodness-of-fit test, and integrated discrimination index were used to assess model discrimination, calibration, and reclassification, respectively. The SAP was 16.4% and 17.7% in the overall derivation (n=2998) and validation (n=2000) cohorts, respectively. A 23-point ICH-APS-A was developed based on a set of predictors and showed good discrimination in the overall derivation (AUROC, 0.75; 95% confidence interval, 0.72-0.77) and validation (AUROC, 0.76; 95% confidence interval, 0.71-0.79) cohorts. The ICH-APS-A was more sensitive for patients with length of stay >48 hours (AUROC, 0.78; 95% confidence interval, 0.75-0.81) than those with length of stay <48 hours (AUROC, 0.64; 95% confidence interval, 0.55-0.73). The ICH-APS-A was well calibrated (Hosmer-Lemeshow test) in the derivation (P=0.20) and validation (P=0.66) cohorts. Similarly, a 26-point ICH-APS-B was established. The ICH-APS-A and ICH-APS-B were not significantly different in discrimination and reclassification for SAP after ICH. The ICH-APSs are valid risk scores for predicting SAP after ICH, especially for patients with length of stay >48 hours. © 2014 American Heart Association, Inc.
Derivation and validation of the prolonged length of stay score in acute stroke patients.
Koton, S; Bornstein, N M; Tsabari, R; Tanne, D
2010-05-11
Length of stay (LOS) is the main cost-determining factor of hospitalization of stroke patients. Our aim was to derive and validate a simple score for the assessment of the risk of prolonged LOS for acute stroke patients in a national setting. Ischemic stroke (IS) and intracerebral hemorrhage (ICH) patients in the National Acute Stroke Israeli Surveys (NASIS 2004 and 2007) were included. Predictors of prolonged LOS (LOS > or =7 days) in the NASIS 2004 (n = 1,700) were identified with logistic regression analysis and used for the derivation of the Prolonged Length of Stay (PLOS) score. The score was validated in the NASIS 2007 (n = 1,648). Median (interquartile range) LOS was 6 (3-10) days in the derivation cohort (42.3% prolonged LOS) and 5 (3-8) in the validation cohort (35.7% prolonged LOS). The derivation cohort included 54.8% men, 90.8% IS and 9.2% ICH, with a mean (SD) age of 71.2 (12.5) years. Stroke severity was the strongest multivariable predictor of prolonged LOS: odds ratio (95% confidence interval [CI]) increased from 2.6 (2.0-3.3) for NIH Stroke Scale score (NIHSS) 6-10 to 4.9 (3.0-8.0) for NIHSS 16-20, compared with NIHSS < or =5. Stroke severity and type, decreased level of consciousness on admission, history of congestive heart failure, and prior atrial fibrillation were used for the derivation of the PLOS score (c statistics 0.692, 95% CI 0.666-0.718). The score performed similarly well in the validation cohort (c statistics 0.680, 95% CI 0.653-0.707). A simple prolonged length of stay score, based on available baseline information, may be useful for tailoring policy aimed at better use of resources and optimal discharge planning of acute stroke patients.
Development and Validation of a Novel Pediatric Appendicitis Risk Calculator (pARC).
Kharbanda, Anupam B; Vazquez-Benitez, Gabriela; Ballard, Dustin W; Vinson, David R; Chettipally, Uli K; Kene, Mamata V; Dehmer, Steven P; Bachur, Richard G; Dayan, Peter S; Kuppermann, Nathan; O'Connor, Patrick J; Kharbanda, Elyse O
2018-04-01
We sought to develop and validate a clinical calculator that can be used to quantify risk for appendicitis on a continuous scale for patients with acute abdominal pain. The pediatric appendicitis risk calculator (pARC) was developed and validated through secondary analyses of 3 distinct cohorts. The derivation sample included visits to 9 pediatric emergency departments between March 2009 and April 2010. The validation sample included visits to a single pediatric emergency department from 2003 to 2004 and 2013 to 2015. Variables evaluated were as follows: age, sex, temperature, nausea and/or vomiting, pain duration, pain location, pain with walking, pain migration, guarding, white blood cell count, and absolute neutrophil count. We used stepwise regression to develop and select the best model. Test performance of the pARC was compared with the Pediatric Appendicitis Score (PAS). The derivation sample included 2423 children, 40% of whom had appendicitis. The validation sample included 1426 children, 35% of whom had appendicitis. The final pARC model included the following variables: sex, age, duration of pain, guarding, pain migration, maximal tenderness in the right-lower quadrant, and absolute neutrophil count. In the validation sample, the pARC exhibited near perfect calibration and a high degree of discrimination (area under the curve: 0.85; 95% confidence interval: 0.83 to 0.87) and outperformed the PAS (area under the curve: 0.77; 95% confidence interval: 0.75 to 0.80). By using the pARC, almost half of patients in the validation cohort could be accurately classified as at <15% risk or ≥85% risk for appendicitis, whereas only 23% would be identified as having a comparable PAS of <3 or >8. In our validation cohort of patients with acute abdominal pain, the pARC accurately quantified risk for appendicitis. Copyright © 2018 by the American Academy of Pediatrics.
Pajulo, Marjukka; Tolvanen, Mimmi; Karlsson, Linnea; Halme-Chowdhury, Elina; Öst, Camilla; Luyten, Patrick; Mayes, Linda; Karlsson, Hasse
2015-01-01
Parental reflective functioning (PRF) is the capacity to focus on experience and feelings in oneself and in the child. Individual differences in PRF reportedly affect child attachment and socioemotional development. In this study, we report work on developing a questionnaire to assess PRF during pregnancy (Prenatal Parental Reflective Functioning Questionnaire; P-PRFQ). The factor structure of the 33-item version of the P-PRFQ was explored using pilot study data from the Finn Brain Birth Cohort Study (n = 124 mothers, n = 82 fathers). Construct validity was assessed against the Pregnancy Interview (PI; A. Slade, L. Grunebaum, L. Huganir, & M. Reeves, 1987, 2002, 2011) in a subsample of 29 mothers from the same pilot sample. Exploratory and confirmatory factor analysis resulted in a 14-item P-PRFQ, with three factors which seem to capture relevant aspects of prenatal parental mentalization-F1: "Opacity of mental states," F2: "Reflecting on the fetus-child," and F3: "The dynamic nature of the mental states." Functioning of the factor structure was further tested in the large cohort with 600 mothers and 600 fathers. Correlations with the PI result were high, both regarding total and factor scores of the P-PRFQ. Cost-effective tools to assess key areas of early parenting are needed for both research and clinical purposes. The 14-item P-PRFQ seems to be an applicable and promising new tool for assessing very early parental mentalizing capacity. © 2015 Michigan Association for Infant Mental Health.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Caine, Hannah; Whalley, Deborah; Kneebone, Andrew
If a prostate intensity-modulated radiation therapy (IMRT) or volumetric-modulated arc therapy (VMAT) plan has protocol violations, it is often a challenge knowing whether this is due to unfavorable anatomy or suboptimal planning. This study aimed to create a model to predict protocol violations based on patient anatomical variables and their potential relationship to target and organ at risk (OAR) end points in the setting of definitive, dose-escalated IMRT/VMAT prostate planning. Radiotherapy plans from 200 consecutive patients treated with definitive radiation for prostate cancer using IMRT or VMAT were analyzed. The first 100 patient plans (hypothesis-generating cohort) were examined to identifymore » anatomical variables that predict for dosimetric outcome, in particular OAR end points. Variables that scored significance were further assessed for their ability to predict protocol violations using a Classification and Regression Tree (CART) analysis. These results were then validated in a second group of 100 patients (validation cohort). In the initial analysis of the hypothesis-generating cohort, percentage of rectum overlap in the planning target volume (PTV) (%OR) and percentage of bladder overlap in the PTV (%OB) were highlighted as significant predictors of rectal and bladder dosimetry. Lymph node treatment was also significant for bladder outcomes. For the validation cohort, CART analysis showed that %OR of < 6%, 6% to 9% and > 9% predicted a 13%, 63%, and 100% rate of rectal protocol violations respectively. For the bladder, %OB of < 9% vs > 9% is associated with 13% vs 88% rate of bladder constraint violations when lymph nodes were not treated. If nodal irradiation was delivered, plans with a %OB of < 9% had a 59% risk of violations. Percentage of rectum and bladder within the PTV can be used to identify individual plan potential to achieve dose-volume histogram (DVH) constraints. A model based on these factors could be used to reduce planning time, improve work flow, and strengthen plan quality and consistency.« less
Zhang, Yang; Zheng, Difan; Xie, Juntao; Li, Yuan; Wang, Yiyang; Li, Chenguang; Xiang, Jiaqing; Zhang, Yawei; Hu, Hong; Sun, Yihua; Chen, Haiquan
2018-06-15
There is currently no consensus regarding the optimal postoperative follow-up strategy for patients with completely resected non-small cell lung cancer (NSCLC). We aimed to develop web-based nomograms to precisely predict site-specific postoperative recurrence in patients with NSCLC and to guide individual surveillance strategies including when to follow up and what diagnostic tests to perform. We investigated the pattern of recurrence in a series of 2,017 patients with NSCLC (squamous cell carcinoma and nonlepidic invasive adenocarcinoma) who underwent complete surgical resection at Fudan University Shanghai Cancer Center (development cohort), and developed web-based clinicopathologic prediction models for conditional risk of site-specific recurrence based on Cox regression. The variables used in the analysis included sex, age, smoking history, tumor size, tumor histology, lymphovascular invasion, visceral pleural invasion, and pathologic TNM stage. A separate cohort of 3,308 patients with NSCLC from Shanghai Chest Hospital was used for external validation. In the development cohort and the external validation cohort for the established nomograms to predict overall recurrence, thorax recurrence, abdomen recurrence, neck recurrence, brain recurrence, and bone recurrence, the C-statistics of Harrell et al were 0.743 and 0.748, 0.728 and 0.703, 0.760 and 0.749, 0.779 and 0.757, 0.787 and 0.784, and 0.777 and 0.739, respectively. The calibration plots showed optimal agreement between nomogram-predicted 3-year recurrence-free survival and actual 3-year recurrence-free survival. These user-friendly nomograms can precisely predict site-specific recurrence in patients with completely resected NSCLC, based on clinicopathologic features. They may help physicians to make individual postoperative follow-up plans. Copyright © 2018 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.
O’Neill, Sadhbh; Larsen, Mette Bohl; Gregersen, Søren; Hermansen, Kjeld; O’Driscoll, Lorraine
2018-01-01
Due to increasing prevalence of obesity, a simple method or methods for the diagnosis of metabolic syndrome are urgently required to reduce the risk of associated cardiovascular disease, diabetes and cancer. This study aimed to identify a miRNA biomarker that may distinguish metabolic syndrome from obesity and to investigate if such a miRNA may have functional relevance for metabolic syndrome. 52 adults with clinical obesity (n=26) or metabolic syndrome (n=26) were recruited. Plasma specimens were procured from all and were randomly designated to discovery and validation cohorts. miRNA discovery profiling was performed, using array technology, on plasma RNA. Validation was performed by quantitative polymerase chain reaction. The functional effect of miR-758-3p on its predicted target, cholesterol efflux regulatory protein/ATP-binding cassette transporter, was investigated using HepG2 liver cells. Custom miRNA profiling of 25 miRNAs in the discovery cohort found miR-758-3p to be detected in the obese cohort but undetected in the metabolic syndrome cohort. miR-758-3p was subsequently validated as a potential biomarker for metabolic syndrome by quantitative polymerase chain reaction. Bioinformatics analysis identified cholesterol efflux regulatory protein/ATP-binding cassette transporter as miR-758-3p’s predicted target. Specifically, mimicking miR-758-3p in HepG2 cells suppressed cholesterol efflux regulatory protein/ATP-binding cassette transporter protein expression; conversely, inhibiting miR-758-3p increased cholesterol efflux regulatory protein/ATP-binding cassette transporter protein expression. miR-758-3p holds potential as a blood-based biomarker for distinguishing progression from obesity to metabolic syndrome and as a driver in controlling cholesterol efflux regulatory protein/ATP-binding cassette transporter expression, indicating it potential role in cholesterol control in metabolic syndrome. PMID:29507696
Vanacker, Peter; Heldner, Mirjam R; Amiguet, Michael; Faouzi, Mohamed; Cras, Patrick; Ntaios, George; Arnold, Marcel; Mattle, Heinrich P; Gralla, Jan; Fischer, Urs; Michel, Patrik
2016-06-01
Endovascular treatment for acute ischemic stroke with a large vessel occlusion was recently shown to be effective. We aimed to develop a score capable of predicting large vessel occlusion eligible for endovascular treatment in the early hospital management. Retrospective, cohort study. Two tertiary, Swiss stroke centers. Consecutive acute ischemic stroke patients (1,645 patients; Acute STroke Registry and Analysis of Lausanne registry), who had CT angiography within 6 and 12 hours of symptom onset, were categorized according to the occlusion site. Demographic and clinical information was used in logistic regression analysis to derive predictors of large vessel occlusion (defined as intracranial carotid, basilar, and M1 segment of middle cerebral artery occlusions). Based on logistic regression coefficients, an integer score was created and validated internally and externally (848 patients; Bernese Stroke Registry). None. Large vessel occlusions were present in 316 patients (21%) in the derivation and 566 (28%) in the external validation cohort. Five predictors added significantly to the score: National Institute of Health Stroke Scale at admission, hemineglect, female sex, atrial fibrillation, and no history of stroke and prestroke handicap (modified Rankin Scale score, < 2). Diagnostic accuracy in internal and external validation cohorts was excellent (area under the receiver operating characteristic curve, 0.84 both). The score performed slightly better than National Institute of Health Stroke Scale alone regarding prediction error (Wilcoxon signed rank test, p < 0.001) and regarding discriminatory power in derivation and pooled cohorts (area under the receiver operating characteristic curve, 0.81 vs 0.80; DeLong test, p = 0.02). Our score accurately predicts the presence of emergent large vessel occlusions, which are eligible for endovascular treatment. However, incorporation of additional demographic and historical information available on hospital arrival provides minimal incremental predictive value compared with the National Institute of Health Stroke Scale alone.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ahmed, Kamran A.; Fulp, William J.; Berglund, Anders E.
2015-07-15
Purpose: We previously developed a multigene expression model of tumor radiation sensitivity index (RSI) with clinical validation in multiple independent cohorts (breast, rectal, esophageal, and head and neck patients). The purpose of this study was to assess differences between RSI scores in primary colon cancer and metastases. Methods and Materials: Patients were identified from our institutional review board–approved prospective observational protocol. A total of 704 metastatic and 1362 primary lesions were obtained from a de-identified metadata pool. RSI was calculated using the previously published rank-based algorithm. An independent cohort of 29 lung or liver colon metastases treated with 60 Gy in 5more » fractions stereotactic body radiation therapy (SBRT) was used for validation. Results: The most common sites of metastases included liver (n=374; 53%), lung (n=116; 17%), and lymph nodes (n=40; 6%). Sixty percent of metastatic tumors, compared with 54% of primaries, were in the RSI radiation-resistant peak, suggesting metastatic tumors may be slightly more radiation resistant than primaries (P=.01). In contrast, when we analyzed metastases based on anatomical site, we uncovered large differences in RSI. The median RSIs for metastases in descending order of radiation resistance were ovary (0.48), abdomen (0.47), liver (0.43), brain (0.42), lung (0.32), and lymph nodes (0.31) (P<.0001). These findings were confirmed when the analysis was restricted to lesions from the same patient (n=139). In our independent cohort of treated lung and liver metastases, lung metastases had an improved local control rate compared to that in patients with liver metastases (2-year local control rate of 100% vs 73.0%, respectively; P=.026). Conclusions: Assessment of radiation sensitivity between primary and metastatic tissues of colon cancer histology revealed significant differences based on anatomical location of metastases. These initial results warrant validation in a larger clinical cohort.« less
O'Neill, Sadhbh; Larsen, Mette Bohl; Gregersen, Søren; Hermansen, Kjeld; O'Driscoll, Lorraine
2018-02-06
Due to increasing prevalence of obesity, a simple method or methods for the diagnosis of metabolic syndrome are urgently required to reduce the risk of associated cardiovascular disease, diabetes and cancer. This study aimed to identify a miRNA biomarker that may distinguish metabolic syndrome from obesity and to investigate if such a miRNA may have functional relevance for metabolic syndrome. 52 adults with clinical obesity (n=26) or metabolic syndrome (n=26) were recruited. Plasma specimens were procured from all and were randomly designated to discovery and validation cohorts. miRNA discovery profiling was performed, using array technology, on plasma RNA. Validation was performed by quantitative polymerase chain reaction. The functional effect of miR-758-3p on its predicted target, cholesterol efflux regulatory protein/ATP-binding cassette transporter, was investigated using HepG2 liver cells. Custom miRNA profiling of 25 miRNAs in the discovery cohort found miR-758-3p to be detected in the obese cohort but undetected in the metabolic syndrome cohort. miR-758-3p was subsequently validated as a potential biomarker for metabolic syndrome by quantitative polymerase chain reaction. Bioinformatics analysis identified cholesterol efflux regulatory protein/ATP-binding cassette transporter as miR-758-3p's predicted target. Specifically, mimicking miR-758-3p in HepG2 cells suppressed cholesterol efflux regulatory protein/ATP-binding cassette transporter protein expression; conversely, inhibiting miR-758-3p increased cholesterol efflux regulatory protein/ATP-binding cassette transporter protein expression. miR-758-3p holds potential as a blood-based biomarker for distinguishing progression from obesity to metabolic syndrome and as a driver in controlling cholesterol efflux regulatory protein/ATP-binding cassette transporter expression, indicating it potential role in cholesterol control in metabolic syndrome.