Predictive factors in patients with hepatocellular carcinoma receiving sorafenib therapy using time-dependent receiver operating characteristic analysis.

PubMed

Nishikawa, Hiroki; Nishijima, Norihiro; Enomoto, Hirayuki; Sakamoto, Azusa; Nasu, Akihiro; Komekado, Hideyuki; Nishimura, Takashi; Kita, Ryuichi; Kimura, Toru; Iijima, Hiroko; Nishiguchi, Shuhei; Osaki, Yukio

2017-01-01

To investigate variables before sorafenib therapy on the clinical outcomes in hepatocellular carcinoma (HCC) patients receiving sorafenib and to further assess and compare the predictive performance of continuous parameters using time-dependent receiver operating characteristics (ROC) analysis. A total of 225 HCC patients were analyzed. We retrospectively examined factors related to overall survival (OS) and progression free survival (PFS) using univariate and multivariate analyses. Subsequently, we performed time-dependent ROC analysis of continuous parameters which were significant in the multivariate analysis in terms of OS and PFS. Total sum of area under the ROC in all time points (defined as TAAT score) in each case was calculated. Our cohort included 175 male and 50 female patients (median age, 72 years) and included 158 Child-Pugh A and 67 Child-Pugh B patients. The median OS time was 0.68 years, while the median PFS time was 0.24 years. On multivariate analysis, gender, body mass index (BMI), Child-Pugh classification, extrahepatic metastases, tumor burden, aspartate aminotransferase (AST) and alpha-fetoprotein (AFP) were identified as significant predictors of OS and ECOG-performance status, Child-Pugh classification and extrahepatic metastases were identified as significant predictors of PFS. Among three continuous variables (i.e., BMI, AST and AFP), AFP had the highest TAAT score for the entire cohort. In subgroup analyses, AFP had the highest TAAT score except for Child-Pugh B and female among three continuous variables. In continuous variables, AFP could have higher predictive accuracy for survival in HCC patients undergoing sorafenib therapy.

Value of MR histogram analyses for prediction of microvascular invasion of hepatocellular carcinoma.

PubMed

Huang, Ya-Qin; Liang, He-Yue; Yang, Zhao-Xia; Ding, Ying; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-06-01

The objective is to explore the value of preoperative magnetic resonance (MR) histogram analyses in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC).Fifty-one patients with histologically confirmed HCC who underwent diffusion-weighted and contrast-enhanced MR imaging were included. Histogram analyses were performed and mean, variance, skewness, kurtosis, 1th, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared between HCCs with and without MVI. Receiver operating characteristics (ROC) analyses were generated to compare the diagnostic performance of tumor size, histogram analyses of apparent diffusion coefficient (ADC) maps, and MR enhancement.The mean, 1th, 10th, and 50th percentiles of ADC maps, and the mean, variance. 1th, 10th, 50th, 90th, and 99th percentiles of the portal venous phase (PVP) images were significantly different between the groups with and without MVI (P <0.05), with area under the ROC curves (AUCs) of 0.66 to 0.74 for ADC and 0.76 to 0.88 for PVP. The largest AUC of PVP (1th percentile) showed significantly higher accuracy compared with that of arterial phase (AP) or tumor size (P <0.001).MR histogram analyses-in particular for 1th percentile for PVP images-held promise for prediction of MVI of HCC.

Comparison of Paired ROC Curves through a Two-Stage Test.

PubMed

Yu, Wenbao; Park, Eunsik; Chang, Yuan-Chin Ivan

2015-01-01

The area under the receiver operating characteristic (ROC) curve (AUC) is a popularly used index when comparing two ROC curves. Statistical tests based on it for analyzing the difference have been well developed. However, this index is less informative when two ROC curves cross and have similar AUCs. In order to detect differences between ROC curves in such situations, a two-stage nonparametric test that uses a shifted area under the ROC curve (sAUC), along with AUCs, is proposed for paired designs. The new procedure is shown, numerically, to be effective in terms of power under a wide range of scenarios; additionally, it outperforms two conventional ROC-type tests, especially when two ROC curves cross each other and have similar AUCs. Larger sAUC implies larger partial AUC at the range of low false-positive rates in this case. Because high specificity is important in many classification tasks, such as medical diagnosis, this is an appealing characteristic. The test also implicitly analyzes the equality of two commonly used binormal ROC curves at every operating point. We also apply the proposed method to synthesized data and two real examples to illustrate its usefulness in practice.

Real-time Raman spectroscopy for automatic in vivo skin cancer detection: an independent validation.

PubMed

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.

PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R.

PubMed

Grau, Jan; Grosse, Ivo; Keilwagen, Jens

2015-08-01

Precision-recall (PR) and receiver operating characteristic (ROC) curves are valuable measures of classifier performance. Here, we present the R-package PRROC, which allows for computing and visualizing both PR and ROC curves. In contrast to available R-packages, PRROC allows for computing PR and ROC curves and areas under these curves for soft-labeled data using a continuous interpolation between the points of PR curves. In addition, PRROC provides a generic plot function for generating publication-quality graphics of PR and ROC curves. © The Author 2015. Published by Oxford University Press.

Recognition ROCS Are Curvilinear--Or Are They? On Premature Arguments against the Two-High-Threshold Model of Recognition

ERIC Educational Resources Information Center

Broder, Arndt; Schutz, Julia

2009-01-01

Recent reviews of recognition receiver operating characteristics (ROCs) claim that their curvilinear shape rules out threshold models of recognition. However, the shape of ROCs based on confidence ratings is not diagnostic to refute threshold models, whereas ROCs based on experimental bias manipulations are. Also, fitting predicted frequencies to…

Variations in Recollection: The Effects of Complexity on Source Recognition

ERIC Educational Resources Information Center

Parks, Colleen M.; Murray, Linda J.; Elfman, Kane; Yonelinas, Andrew P.

2011-01-01

Whether recollection is a threshold or signal detection process is highly controversial, and the controversy has centered in part on the shape of receiver operating characteristics (ROCs) and z-transformed ROCs (zROCs). U-shaped zROCs observed in tests thought to rely heavily on recollection, such as source memory tests, have provided evidence in…

Validating the Injury Severity Score (ISS) in different populations: ISS predicts mortality better among Hispanics and females.

PubMed

Bolorunduro, O B; Villegas, C; Oyetunji, T A; Haut, E R; Stevens, K A; Chang, D C; Cornwell, E E; Efron, D T; Haider, A H

2011-03-01

The Injury Severity Score (ISS) is the most commonly used measure of injury severity. The score has been shown to have excellent predictive capability for trauma mortality and has been validated in multiple data sets. However, the score has never been tested to see if its discriminatory ability is affected by differences in race and gender. This study is aimed at validating the ISS in men and women and in three different race/ethnic groups using a nationwide database. Retrospective analysis of patients age 18-64 y in the National Trauma Data Bank 7.0 with blunt trauma was performed. ISS was categorized as mild (<9,) moderate (9-15), severe (16-25), and profound (>25). Logistic regression was done to measure the relative odds of mortality associated with a change in ISS categories. The discriminatory ability was compared using the receiver operating characteristics curves (ROC). A P value testing the equality of the ROC curves was calculated. Age stratified analyses were also conducted. A total of 872,102 patients had complete data for the analysis on ethnicity, while 763,549 patients were included in the gender analysis. The overall mortality rate was 3.7%. ROC in Whites was 0.8617, in Blacks 0.8586, and in Hispanics 0.8869. Hispanics have a statistically significant higher ROC (P value < 0.001). Similar results were observed within each age category. ROC curves were also significantly higher in females than in males. The ISS possesses excellent discriminatory ability in all populations as indicated by the high ROCs. Copyright © 2011 Elsevier Inc. All rights reserved.

The average receiver operating characteristic curve in multireader multicase imaging studies

PubMed Central

Samuelson, F W

2014-01-01

Objective: In multireader, multicase (MRMC) receiver operating characteristic (ROC) studies for evaluating medical imaging systems, the area under the ROC curve (AUC) is often used as a summary metric. Owing to the limitations of AUC, plotting the average ROC curve to accompany the rigorous statistical inference on AUC is recommended. The objective of this article is to investigate methods for generating the average ROC curve from ROC curves of individual readers. Methods: We present both a non-parametric method and a parametric method for averaging ROC curves that produce a ROC curve, the area under which is equal to the average AUC of individual readers (a property we call area preserving). We use hypothetical examples, simulated data and a real-world imaging data set to illustrate these methods and their properties. Results: We show that our proposed methods are area preserving. We also show that the method of averaging the ROC parameters, either the conventional bi-normal parameters (a, b) or the proper bi-normal parameters (c, da), is generally not area preserving and may produce a ROC curve that is intuitively not an average of multiple curves. Conclusion: Our proposed methods are useful for making plots of average ROC curves in MRMC studies as a companion to the rigorous statistical inference on the AUC end point. The software implementing these methods is freely available from the authors. Advances in knowledge: Methods for generating the average ROC curve in MRMC ROC studies are formally investigated. The area-preserving criterion we defined is useful to evaluate such methods. PMID:24884728

Structural vascular disease in Africans: Performance of ethnic-specific waist circumference cut points using logistic regression and neural network analyses: The SABPA study.

PubMed

Botha, J; de Ridder, J H; Potgieter, J C; Steyn, H S; Malan, L

2013-10-01

A recently proposed model for waist circumference cut points (RPWC), driven by increased blood pressure, was demonstrated in an African population. We therefore aimed to validate the RPWC by comparing the RPWC and the Joint Statement Consensus (JSC) models via Logistic Regression (LR) and Neural Networks (NN) analyses. Urban African gender groups (N=171) were stratified according to the JSC and RPWC cut point models. Ultrasound carotid intima media thickness (CIMT), blood pressure (BP) and fasting bloods (glucose, high density lipoprotein (HDL) and triglycerides) were obtained in a well-controlled setting. The RPWC male model (LR ROC AUC: 0.71, NN ROC AUC: 0.71) was practically equal to the JSC model (LR ROC AUC: 0.71, NN ROC AUC: 0.69) to predict structural vascular -disease. Similarly, the female RPWC model (LR ROC AUC: 0.84, NN ROC AUC: 0.82) and JSC model (LR ROC AUC: 0.82, NN ROC AUC: 0.81) equally predicted CIMT as surrogate marker for structural vascular disease. Odds ratios supported validity where prediction of CIMT revealed -clinical -significance, well over 1, for both the JSC and RPWC models in African males and females (OR 3.75-13.98). In conclusion, the proposed RPWC model was substantially validated utilizing linear and non-linear analyses. We therefore propose ethnic-specific WC cut points (African males, ≥90 cm; -females, ≥98 cm) to predict a surrogate marker for structural vascular disease. © J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart · New York.

A Three-Dimensional Receiver Operator Characteristic Surface Diagnostic Metric

NASA Technical Reports Server (NTRS)

Simon, Donald L.

2011-01-01

Receiver Operator Characteristic (ROC) curves are commonly applied as metrics for quantifying the performance of binary fault detection systems. An ROC curve provides a visual representation of a detection system s True Positive Rate versus False Positive Rate sensitivity as the detection threshold is varied. The area under the curve provides a measure of fault detection performance independent of the applied detection threshold. While the standard ROC curve is well suited for quantifying binary fault detection performance, it is not suitable for quantifying the classification performance of multi-fault classification problems. Furthermore, it does not provide a measure of diagnostic latency. To address these shortcomings, a novel three-dimensional receiver operator characteristic (3D ROC) surface metric has been developed. This is done by generating and applying two separate curves: the standard ROC curve reflecting fault detection performance, and a second curve reflecting fault classification performance. A third dimension, diagnostic latency, is added giving rise to 3D ROC surfaces. Applying numerical integration techniques, the volumes under and between the surfaces are calculated to produce metrics of the diagnostic system s detection and classification performance. This paper will describe the 3D ROC surface metric in detail, and present an example of its application for quantifying the performance of aircraft engine gas path diagnostic methods. Metric limitations and potential enhancements are also discussed

Validation of the German Diabetes Risk Score among the general adult population: findings from the German Health Interview and Examination Surveys

PubMed Central

Paprott, Rebecca; Mühlenbruch, Kristin; Mensink, Gert B M; Thiele, Silke; Schulze, Matthias B; Scheidt-Nave, Christa; Heidemann, Christin

2016-01-01

Objective To evaluate the German Diabetes Risk Score (GDRS) among the general adult German population for prediction of incident type 2 diabetes and detection of prevalent undiagnosed diabetes. Methods The longitudinal sample for prediction of incident diagnosed type 2 diabetes included 3625 persons who participated both in the examination survey in 1997–1999 and the examination survey in 2008–2011. Incident diagnosed type 2 diabetes was defined as first-time physician diagnosis or antidiabetic medication during 5 years of follow-up excluding potential incident type 1 and gestational diabetes. The cross-sectional sample for detection of prevalent undiagnosed diabetes included 6048 participants without diagnosed diabetes of the examination survey in 2008–2011. Prevalent undiagnosed diabetes was defined as glycated haemoglobin ≥6.5% (48 mmol/mol). We assessed discrimination as area under the receiver operating characteristic curve (ROC-AUC (95% CI)) and calibration through calibration plots. Results In longitudinal analyses, 82 subjects with incident diagnosed type 2 diabetes were identified after 5 years of follow-up. For prediction of incident diagnosed diabetes, the GDRS yielded an ROC-AUC of 0.87 (0.83 to 0.90). Calibration plots indicated excellent prediction for low diabetes risk and overestimation for intermediate and high diabetes risk. When considering the entire follow-up period of 11.9 years (ROC-AUC: 0.84 (0.82 to 0.86)) and including incident undiagnosed diabetes (ROC-AUC: 0.81 (0.78 to 0.84)), discrimination decreased somewhat. A previously simplified paper version of the GDRS yielded a similar predictive ability (ROC-AUC: 0.86 (0.82 to 0.89)). In cross-sectional analyses, 128 subjects with undiagnosed diabetes were identified. For detection of prevalent undiagnosed diabetes, the ROC-AUC was 0.84 (0.81 to 0.86). Again, the simplified version yielded a similar result (ROC-AUC: 0.83 (0.80 to 0.86)). Conclusions The GDRS might be applied for public health monitoring of diabetes risk in the German adult population. Future research needs to evaluate whether the GDRS is useful to improve diabetes risk awareness and prevention among the general population. PMID:27933187

Improvement of shallow landslide prediction accuracy using soil parameterisation for a granite area in South Korea

NASA Astrophysics Data System (ADS)

Kim, M. S.; Onda, Y.; Kim, J. K.

2015-01-01

SHALSTAB model applied to shallow landslides induced by rainfall to evaluate soil properties related with the effect of soil depth for a granite area in Jinbu region, Republic of Korea. Soil depth measured by a knocking pole test and two soil parameters from direct shear test (a and b) as well as one soil parameters from a triaxial compression test (c) were collected to determine the input parameters for the model. Experimental soil data were used for the first simulation (Case I) and, soil data represented the effect of measured soil depth and average soil depth from soil data of Case I were used in the second (Case II) and third simulations (Case III), respectively. All simulations were analysed using receiver operating characteristic (ROC) analysis to determine the accuracy of prediction. ROC analysis results for first simulation showed the low ROC values under 0.75 may be due to the internal friction angle and particularly the cohesion value. Soil parameters calculated from a stochastic hydro-geomorphological model were applied to the SHALSTAB model. The accuracy of Case II and Case III using ROC analysis showed higher accuracy values rather than first simulation. Our results clearly demonstrate that the accuracy of shallow landslide prediction can be improved when soil parameters represented the effect of soil thickness.

East London Modified-Broset as Decision-Making Tool to Predict Seclusion in Psychiatric Intensive Care Units.

PubMed

Loi, Felice; Marlowe, Karl

2017-01-01

Seclusion is a last resort intervention for management of aggressive behavior in psychiatric settings. There is no current objective and practical decision-making instrument for seclusion use on psychiatric wards. Our aim was to test the predictive and discriminatory characteristics of the East London Modified-Broset (ELMB), to delineate its decision-making profile for seclusion of adult psychiatric patients, and second to benchmark it against the psychometric properties of the Broset Violence Checklist (BVC). ELMB, an 8-item modified version of the 6-item BVC, was retrospectively employed to evaluate the seclusion decision-making process on two Psychiatric Intensive Care Units (patients n  = 201; incidents n  = 2,187). Data analyses were carried out using multivariate regression and Receiver Operating Characteristic (ROC) curves. Predictors of seclusion were: physical violence toward staff/patients OR = 24.2; non-compliance with PRN (pro re nata) medications OR = 9.8; and damage to hospital property OR = 2.9. ROC analyses indicated that ELMB was significantly more accurate that BVC, with higher sensitivity, specificity, and positive likelihood ratio. Results were similar across gender. The ELMB is a sensitive and specific instrument that can be used to guide the decision-making process when implementing seclusion.

East London Modified-Broset as Decision-Making Tool to Predict Seclusion in Psychiatric Intensive Care Units

PubMed Central

Loi, Felice; Marlowe, Karl

2017-01-01

Seclusion is a last resort intervention for management of aggressive behavior in psychiatric settings. There is no current objective and practical decision-making instrument for seclusion use on psychiatric wards. Our aim was to test the predictive and discriminatory characteristics of the East London Modified-Broset (ELMB), to delineate its decision-making profile for seclusion of adult psychiatric patients, and second to benchmark it against the psychometric properties of the Broset Violence Checklist (BVC). ELMB, an 8-item modified version of the 6-item BVC, was retrospectively employed to evaluate the seclusion decision-making process on two Psychiatric Intensive Care Units (patients n = 201; incidents n = 2,187). Data analyses were carried out using multivariate regression and Receiver Operating Characteristic (ROC) curves. Predictors of seclusion were: physical violence toward staff/patients OR = 24.2; non-compliance with PRN (pro re nata) medications OR = 9.8; and damage to hospital property OR = 2.9. ROC analyses indicated that ELMB was significantly more accurate that BVC, with higher sensitivity, specificity, and positive likelihood ratio. Results were similar across gender. The ELMB is a sensitive and specific instrument that can be used to guide the decision-making process when implementing seclusion. PMID:29046647

Validation of Thwaites Index for diagnosing tuberculous meningitis in a Colombian population.

PubMed

Saavedra, Juan Sebastián; Urrego, Sebastián; Toro, María Eugenia; Uribe, Carlos Santiago; García, Jenny; Hernández, Olga; Arango, Juan Carlos; Pérez, Ángela Beatriz; Franco, Andrés; Vélez, Isabel Cristina; Del Corral, Helena

2016-11-15

To determine the diagnostic accuracy of Thwaites Index (TI) in a Colombian population to distinguish meningeal tuberculosis (MTB) from bacterial meningitis (BM) and from non-tuberculous meningitis. Exploratory analyses were conducted to assess the TI's validity for patients with human immunodeficiency virus (HIV) and children above six-years-old. The study included 527 patients, the TI was calculated and results compared with those of a reference standard established by expert neurologists. Sensitivity, specificity, area under the curve of receiver-operator characteristics (AUC-ROC) and likelihood ratios were calculated. The AUC-ROC to distinguish MTB from non-tuberculous meningitis was 0.72 (95% CI: 0.67-0.77) for HIV negative adults. AUC-ROC was 0.62 (95% CI: 0.50-0.74) for HIV positive adults and 0.83 (95% CI: 0.68-0.97) for children. For distinguishing MTB from BM the AUC-ROC was 0.78 (95% CI: 0.73-0.83); furthermore, the AUC-ROC was 0.57 (95% CI: 0.31-0.83) for HIV positive adults and 0.86 (95% CI: 0.73-0.99) for children. The TI was sensitive but not specific when used to distinguish MTB from BM in HIV negative adults. In HIV positive adults the index had low diagnostic accuracy. Moreover, the TI showed discrimination capability for children over 6years; however, research with larger samples is required in these. Copyright © 2016 Elsevier B.V. All rights reserved.

Cerebrospinal fluid cytokines in the diagnosis of bacterial meningitis in infants.

PubMed

Srinivasan, Lakshmi; Kilpatrick, Laurie; Shah, Samir S; Abbasi, Soraya; Harris, Mary C

2016-10-01

Bacterial meningitis poses diagnostic challenges in infants. Antibiotic pretreatment and low bacterial density diminish cerebrospinal fluid (CSF) culture yield, while laboratory parameters do not reliably identify bacterial meningitis. Pro and anti-inflammatory cytokines are elevated in bacterial meningitis and may be useful diagnostic adjuncts when CSF cultures are negative. In a prospective cohort study of infants, we used cytometric bead arrays to measure tumor necrosis factor alpha (TNF-α), interleukin 1 (IL-1), IL-6, IL-8, IL-10, and IL-12 in CSF. Receiver operating characteristic (ROC) analyses and Principal component analysis (PCA) were used to determine cytokine combinations that identified bacterial meningitis. Six hundred and eighty four infants < 6 mo were included; 11 had culture-proven bacterial meningitis. IL-6 and IL-10 were the individual cytokines possessing greatest accuracy in diagnosis of culture proven bacterial meningitis (ROC analyses; area under the concentration-time curve (AUC) 0.91; 0.9103 respectively), and performed as well as, or better than combinations identified using ROC and PCA. CSF cytokines were highly correlated with each other and with CSF white blood cell count (WBC) counts in infants with meningitis. A subset of antibiotic pretreated culture-negative subjects demonstrated cytokine patterns similar to culture positive subjects. CSF cytokine levels may aid diagnosis of bacterial meningitis, and facilitate decision-making regarding treatment for culture negative meningitis.

Recollection is a continuous process: Evidence from plurality memory receiver operating characteristics.

PubMed

Slotnick, Scott D; Jeye, Brittany M; Dodson, Chad S

2016-01-01

Is recollection a continuous/graded process or a threshold/all-or-none process? Receiver operating characteristic (ROC) analysis can answer this question as the continuous model and the threshold model predict curved and linear recollection ROCs, respectively. As memory for plurality, an item's previous singular or plural form, is assumed to rely on recollection, the nature of recollection can be investigated by evaluating plurality memory ROCs. The present study consisted of four experiments. During encoding, words (singular or plural) or objects (single/singular or duplicate/plural) were presented. During retrieval, old items with the same plurality or different plurality were presented. For each item, participants made a confidence rating ranging from "very sure old", which was correct for same plurality items, to "very sure new", which was correct for different plurality items. Each plurality memory ROC was the proportion of same versus different plurality items classified as "old" (i.e., hits versus false alarms). Chi-squared analysis revealed that all of the plurality memory ROCs were adequately fit by the continuous unequal variance model, whereas none of the ROCs were adequately fit by the two-high threshold model. These plurality memory ROC results indicate recollection is a continuous process, which complements previous source memory and associative memory ROC findings.

Recognition errors suggest fast familiarity and slow recollection in rhesus monkeys

PubMed Central

Basile, Benjamin M.; Hampton, Robert R.

2013-01-01

One influential model of recognition posits two underlying memory processes: recollection, which is detailed but relatively slow, and familiarity, which is quick but lacks detail. Most of the evidence for this dual-process model in nonhumans has come from analyses of receiver operating characteristic (ROC) curves in rats, but whether ROC analyses can demonstrate dual processes has been repeatedly challenged. Here, we present independent converging evidence for the dual-process model from analyses of recognition errors made by rhesus monkeys. Recognition choices were made in three different ways depending on processing duration. Short-latency errors were disproportionately false alarms to familiar lures, suggesting control by familiarity. Medium-latency responses were less likely to be false alarms and were more accurate, suggesting onset of a recollective process that could correctly reject familiar lures. Long-latency responses were guesses. A response deadline increased false alarms, suggesting that limiting processing time weakened the contribution of recollection and strengthened the contribution of familiarity. Together, these findings suggest fast familiarity and slow recollection in monkeys, that monkeys use a “recollect to reject” strategy to countermand false familiarity, and that primate recognition performance is well-characterized by a dual-process model consisting of recollection and familiarity. PMID:23864646

The influence of averaging and noisy decision strategies on the recognition memory ROC.

PubMed

Malmberg, Kenneth J; Xu, Jing

2006-02-01

Many single- and dual-process models of recognition memory predict that the ratings and remember-know receiver operating characteristics (ROCs) are the same, but Rotello, Macmillan, and Reeder (2004) reported that the slopes of the remember-know and ratings z-transformed ROCs (zROCs) are different The authors show that averaging introduces nonlinearities to the form of the zROC and that ratings and remember-know zROCs are indistinguishable when constructed in a conventional manner. The authors show, further, that some nonoptimal decision strategies have a distinctive, nonlinear effect on the form of the single-process continuous-state zROC. The conclusion is that many factors having nothing to do with the nature of recognition memory can affect the shape of zROCs, and that therefore, the shape of the zROC does not, alone, characterize different memory models.

Value of MR histogram analyses for prediction of microvascular invasion of hepatocellular carcinoma

PubMed Central

Huang, Ya-Qin; Liang, He-Yue; Yang, Zhao-Xia; Ding, Ying; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-01-01

Abstract The objective is to explore the value of preoperative magnetic resonance (MR) histogram analyses in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Fifty-one patients with histologically confirmed HCC who underwent diffusion-weighted and contrast-enhanced MR imaging were included. Histogram analyses were performed and mean, variance, skewness, kurtosis, 1th, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared between HCCs with and without MVI. Receiver operating characteristics (ROC) analyses were generated to compare the diagnostic performance of tumor size, histogram analyses of apparent diffusion coefficient (ADC) maps, and MR enhancement. The mean, 1th, 10th, and 50th percentiles of ADC maps, and the mean, variance. 1th, 10th, 50th, 90th, and 99th percentiles of the portal venous phase (PVP) images were significantly different between the groups with and without MVI (P <0.05), with area under the ROC curves (AUCs) of 0.66 to 0.74 for ADC and 0.76 to 0.88 for PVP. The largest AUC of PVP (1th percentile) showed significantly higher accuracy compared with that of arterial phase (AP) or tumor size (P <0.001). MR histogram analyses—in particular for 1th percentile for PVP images—held promise for prediction of MVI of HCC. PMID:27368028

Multicategory reclassification statistics for assessing improvements in diagnostic accuracy

PubMed Central

Li, Jialiang; Jiang, Binyan; Fine, Jason P.

2013-01-01

In this paper, we extend the definitions of the net reclassification improvement (NRI) and the integrated discrimination improvement (IDI) in the context of multicategory classification. Both measures were proposed in Pencina and others (2008. Evaluating the added predictive ability of a new marker: from area under the receiver operating characteristic (ROC) curve to reclassification and beyond. Statistics in Medicine 27, 157–172) as numeric characterizations of accuracy improvement for binary diagnostic tests and were shown to have certain advantage over analyses based on ROC curves or other regression approaches. Estimation and inference procedures for the multiclass NRI and IDI are provided in this paper along with necessary asymptotic distributional results. Simulations are conducted to study the finite-sample properties of the proposed estimators. Two medical examples are considered to illustrate our methodology. PMID:23197381

Binary ROCs in Perception and Recognition Memory Are Curved

ERIC Educational Resources Information Center

Dube, Chad; Rotello, Caren M.

2012-01-01

In recognition memory, a classic finding is that receiver operating characteristics (ROCs) are curvilinear. This has been taken to support the fundamental assumptions of signal detection theory (SDT) over discrete-state models such as the double high-threshold model (2HTM), which predicts linear ROCs. Recently, however, Broder and Schutz (2009)…

Verification of a model for the detection of intrauterine growth restriction (IUGR) by receiver operating characteristics (ROC)

NASA Astrophysics Data System (ADS)

Liu, Pengbo; Mongelli, Max; Mondry, Adrian

2004-07-01

The purpose of this study is to verify by Receiver Operating Characteristics (ROC) a mathematical model supporting the hypothesis that IUGR can be diagnosed by estimating growth velocity. The ROC compare computerized simulation results with clinical data from 325 pregnant British women. Each patient had 6 consecutive ultrasound examinations for fetal abdominal circumference (fac). Customized and un-customized fetal weights were calculated according to Hadlock"s formula. IUGR was diagnosed by the clinical standard, i.e. estimated weight below the tenth percentile. Growth velocity was estimated by calculating the changes of fac (Dzfac/dt) at various time intervals from 3 to 10 weeks. Finally, ROC was used to compare the methods. At 3~4 weeks scan interval, the area under the ROC curve is 0.68 for customized data and 0.66 for the uncustomized data with 95% confidence interval. Comparison between simulation data and real pregnancies verified that the model is clinically acceptable.

Impact of signal scattering and parametric uncertainties on receiver operating characteristics

NASA Astrophysics Data System (ADS)

Wilson, D. Keith; Breton, Daniel J.; Hart, Carl R.; Pettit, Chris L.

2017-05-01

The receiver operating characteristic (ROC curve), which is a plot of the probability of detection as a function of the probability of false alarm, plays a key role in the classical analysis of detector performance. However, meaningful characterization of the ROC curve is challenging when practically important complications such as variations in source emissions, environmental impacts on the signal propagation, uncertainties in the sensor response, and multiple sources of interference are considered. In this paper, a relatively simple but realistic model for scattered signals is employed to explore how parametric uncertainties impact the ROC curve. In particular, we show that parametric uncertainties in the mean signal and noise power substantially raise the tails of the distributions; since receiver operation with a very low probability of false alarm and a high probability of detection is normally desired, these tails lead to severely degraded performance. Because full a priori knowledge of such parametric uncertainties is rarely available in practice, analyses must typically be based on a finite sample of environmental states, which only partially characterize the range of parameter variations. We show how this effect can lead to misleading assessments of system performance. For the cases considered, approximately 64 or more statistically independent samples of the uncertain parameters are needed to accurately predict the probabilities of detection and false alarm. A connection is also described between selection of suitable distributions for the uncertain parameters, and Bayesian adaptive methods for inferring the parameters.

Reliability of cone beam computed tomography as a biopsy-independent tool in differential diagnosis of periapical cysts and granulomas: An In vivo Study.

PubMed

Chanani, Ankit; Adhikari, Haridas Das

2017-01-01

Differential diagnosis of periapical cysts and granulomas is required as their treatment modalities are different. The aim of this study was to evaluate the efficacy of cone beam computed tomography (CBCT) in the differential diagnosis of periapical cysts from granulomas. A single-centered observational study was carried out in the Department of Conservative Dentistry and Endodontics, Dr. R. Ahmed Dental College and Hospital, using CBCT and dental operating microscope. Forty-five lesions were analyzed using CBCT scans. One evaluator analyzed each CBCT scan for the presence of the following six characteristic radiological features: cyst like-location, shape, periphery, internal structure, effect on the surrounding structures, and cortical plate perforation. Another independent evaluator analyzed the CBCT scans. This process was repeated after 6 months, and inter- and intrarater reliability of CBCT diagnoses was evaluated. Periapical surgeries were performed and tissue samples were obtained for histopathological analysis. To evaluate the efficacy, CBCT diagnoses were compared with histopathological diagnoses, and six receiver operating characteristic (ROC) curve analyses were conducted. ROC curve, Cronbach's alpha (α) test, and Cohen Kappa (κ) test were used for statistical analysis. Both inter- and intrarater reliability were excellent (α = 0.94, κ = 0.75 and 0.77, respectively). ROC curve with regard to ≥4 positive findings revealed the highest area under curve (0.66). CBCT is moderately accurate in the differential diagnosis of periapical cysts and granulomas.

pROC: an open-source package for R and S+ to analyze and compare ROC curves.

PubMed

Robin, Xavier; Turck, Natacha; Hainard, Alexandre; Tiberti, Natalia; Lisacek, Frédérique; Sanchez, Jean-Charles; Müller, Markus

2011-03-17

Receiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often reached through inconsistent use or insufficient statistical analysis. To support researchers in their ROC curves analysis we developed pROC, a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface. With data previously imported into the R or S+ environment, the pROC package builds ROC curves and includes functions for computing confidence intervals, statistical tests for comparing total or partial area under the curve or the operating points of different classifiers, and methods for smoothing ROC curves. Intermediary and final results are visualised in user-friendly interfaces. A case study based on published clinical and biomarker data shows how to perform a typical ROC analysis with pROC. pROC is a package for R and S+ specifically dedicated to ROC analysis. It proposes multiple statistical tests to compare ROC curves, and in particular partial areas under the curve, allowing proper ROC interpretation. pROC is available in two versions: in the R programming language or with a graphical user interface in the S+ statistical software. It is accessible at http://expasy.org/tools/pROC/ under the GNU General Public License. It is also distributed through the CRAN and CSAN public repositories, facilitating its installation.

Transformation-invariant and nonparametric monotone smooth estimation of ROC curves.

PubMed

Du, Pang; Tang, Liansheng

2009-01-30

When a new diagnostic test is developed, it is of interest to evaluate its accuracy in distinguishing diseased subjects from non-diseased subjects. The accuracy of the test is often evaluated by receiver operating characteristic (ROC) curves. Smooth ROC estimates are often preferable for continuous test results when the underlying ROC curves are in fact continuous. Nonparametric and parametric methods have been proposed by various authors to obtain smooth ROC curve estimates. However, there are certain drawbacks with the existing methods. Parametric methods need specific model assumptions. Nonparametric methods do not always satisfy the inherent properties of the ROC curves, such as monotonicity and transformation invariance. In this paper we propose a monotone spline approach to obtain smooth monotone ROC curves. Our method ensures important inherent properties of the underlying ROC curves, which include monotonicity, transformation invariance, and boundary constraints. We compare the finite sample performance of the newly proposed ROC method with other ROC smoothing methods in large-scale simulation studies. We illustrate our method through a real life example. Copyright (c) 2008 John Wiley & Sons, Ltd.

The Belief Bias Effect Is Aptly Named: A Reply to Klauer and Kellen (2011)

ERIC Educational Resources Information Center

Dube, Chad; Rotello, Caren M.; Heit, Evan

2011-01-01

In "Assessing the Belief Bias Effect With ROCs: It's a Response Bias Effect," Dube, Rotello, and Heit (2010) examined the form of receiver operating characteristic (ROC) curves for reasoning and the effects of belief bias on measurement indices that differ in whether they imply a curved or linear ROC function. We concluded that the ROC…

The receiver operational characteristic for binary classification with multiple indices and its application to the neuroimaging study of Alzheimer's disease.

PubMed

Wu, Xia; Li, Juan; Ayutyanont, Napatkamon; Protas, Hillary; Jagust, William; Fleisher, Adam; Reiman, Eric; Yao, Li; Chen, Kewei

2013-01-01

Given a single index, the receiver operational characteristic (ROC) curve analysis is routinely utilized for characterizing performances in distinguishing two conditions/groups in terms of sensitivity and specificity. Given the availability of multiple data sources (referred to as multi-indices), such as multimodal neuroimaging data sets, cognitive tests, and clinical ratings and genomic data in Alzheimer’s disease (AD) studies, the single-index-based ROC underutilizes all available information. For a long time, a number of algorithmic/analytic approaches combining multiple indices have been widely used to simultaneously incorporate multiple sources. In this study, we propose an alternative for combining multiple indices using logical operations, such as “AND,” “OR,” and “at least n” (where n is an integer), to construct multivariate ROC (multiV-ROC) and characterize the sensitivity and specificity statistically associated with the use of multiple indices. With and without the “leave-one-out” cross-validation, we used two data sets from AD studies to showcase the potentially increased sensitivity/specificity of the multiV-ROC in comparison to the single-index ROC and linear discriminant analysis (an analytic way of combining multi-indices). We conclude that, for the data sets we investigated, the proposed multiV-ROC approach is capable of providing a natural and practical alternative with improved classification accuracy as compared to univariate ROC and linear discriminant analysis.

The Receiver Operational Characteristic for Binary Classification with Multiple Indices and Its Application to the Neuroimaging Study of Alzheimer’s Disease

PubMed Central

Wu, Xia; Li, Juan; Ayutyanont, Napatkamon; Protas, Hillary; Jagust, William; Fleisher, Adam; Reiman, Eric; Yao, Li; Chen, Kewei

2014-01-01

Given a single index, the receiver operational characteristic (ROC) curve analysis is routinely utilized for characterizing performances in distinguishing two conditions/groups in terms of sensitivity and specificity. Given the availability of multiple data sources (referred to as multi-indices), such as multimodal neuroimaging data sets, cognitive tests, and clinical ratings and genomic data in Alzheimer’s disease (AD) studies, the single-index-based ROC underutilizes all available information. For a long time, a number of algorithmic/analytic approaches combining multiple indices have been widely used to simultaneously incorporate multiple sources. In this study, we propose an alternative for combining multiple indices using logical operations, such as “AND,” “OR,” and “at least n” (where n is an integer), to construct multivariate ROC (multiV-ROC) and characterize the sensitivity and specificity statistically associated with the use of multiple indices. With and without the “leave-one-out” cross-validation, we used two data sets from AD studies to showcase the potentially increased sensitivity/specificity of the multiV-ROC in comparison to the single-index ROC and linear discriminant analysis (an analytic way of combining multi-indices). We conclude that, for the data sets we investigated, the proposed multiV-ROC approach is capable of providing a natural and practical alternative with improved classification accuracy as compared to univariate ROC and linear discriminant analysis. PMID:23702553

Receiver operating characteristic analysis. Application to the study of quantum fluctuation effects in optic nerve of Rana pipiens

PubMed Central

1975-01-01

Receiver operating characteristic (ROC) analysis of nerve messages is described. The hypothesis that quantum fluctuations provide the only limit to the ability of frog ganglion cells to signal luminance change information is examined using ROC analysis. In the context of ROC analysis, the quantum fluctuation hypothesis predicts (a) the detectability of a luminance change signal should rise proportionally to the size of the change, (b) detectability should decrease as the square root of background, an implication of which is the deVries-Rose law, and (c) ROC curves should exhibit a shape particular to underlying Poisson distributions. Each of these predictions is confirmed for the responses of dimming ganglion cells to brief luminance decrements at scotopic levels, but none could have been tested using classical nerve message analysis procedures. PMID:172597

Some interesting examples of binormal degeneracy and analysis using a contaminated binormal ROC model

NASA Astrophysics Data System (ADS)

Berbaum, Kevin S.; Dorfman, Donald D.

2001-06-01

Receiver operating characteristic (ROC) data with false positive fractions of zero are often difficult to fit with standard ROC methodology, and are sometimes discarded. Some extreme examples of such data were analyzed. A new ROC model is proposed that assumes that for a proportion of abnormalities, no signal information is captured and that those abnormalities have the same distribution as noise along the latent decision axis. Rating reports of fracture for single view ankle radiographs were also analyzed with the binormal ROC model and two proper ROC models. The conventional models gave ROC area close to one, implying a true positive fraction close to one. The data contained no such fractions. When all false positive fractions were zero, conventional ROC areas gave little or no hint of unmistakable differences in true positive fractions. In contrast, the new model can fit ROC data in which some or all of the ROC points have false positive fractions of zero and true positive fractions less than one without concluding perfect performance. These data challenge the validity and robustness of conventional ROC models, but the contaminated binormal model accounts for these data. This research has been published for a different audience.

To t-Test or Not to t-Test? A p-Values-Based Point of View in the Receiver Operating Characteristic Curve Framework.

PubMed

Vexler, Albert; Yu, Jihnhee

2018-04-13

A common statistical doctrine supported by many introductory courses and textbooks is that t-test type procedures based on normally distributed data points are anticipated to provide a standard in decision-making. In order to motivate scholars to examine this convention, we introduce a simple approach based on graphical tools of receiver operating characteristic (ROC) curve analysis, a well-established biostatistical methodology. In this context, we propose employing a p-values-based method, taking into account the stochastic nature of p-values. We focus on the modern statistical literature to address the expected p-value (EPV) as a measure of the performance of decision-making rules. During the course of our study, we extend the EPV concept to be considered in terms of the ROC curve technique. This provides expressive evaluations and visualizations of a wide spectrum of testing mechanisms' properties. We show that the conventional power characterization of tests is a partial aspect of the presented EPV/ROC technique. We desire that this explanation of the EPV/ROC approach convinces researchers of the usefulness of the EPV/ROC approach for depicting different characteristics of decision-making procedures, in light of the growing interest regarding correct p-values-based applications.

Clinical evaluation of JPEG2000 compression for digital mammography

NASA Astrophysics Data System (ADS)

Sung, Min-Mo; Kim, Hee-Joung; Kim, Eun-Kyung; Kwak, Jin-Young; Yoo, Jae-Kyung; Yoo, Hyung-Sik

2002-06-01

Medical images, such as computed radiography (CR), and digital mammographic images will require large storage facilities and long transmission times for picture archiving and communications system (PACS) implementation. American College of Radiology and National Equipment Manufacturers Association (ACR/NEMA) group is planning to adopt a JPEG2000 compression algorithm in digital imaging and communications in medicine (DICOM) standard to better utilize medical images. The purpose of the study was to evaluate the compression ratios of JPEG2000 for digital mammographic images using peak signal-to-noise ratio (PSNR), receiver operating characteristic (ROC) analysis, and the t-test. The traditional statistical quality measures such as PSNR, which is a commonly used measure for the evaluation of reconstructed images, measures how the reconstructed image differs from the original by making pixel-by-pixel comparisons. The ability to accurately discriminate diseased cases from normal cases is evaluated using ROC curve analysis. ROC curves can be used to compare the diagnostic performance of two or more reconstructed images. The t test can be also used to evaluate the subjective image quality of reconstructed images. The results of the t test suggested that the possible compression ratios using JPEG2000 for digital mammographic images may be as much as 15:1 without visual loss or with preserving significant medical information at a confidence level of 99%, although both PSNR and ROC analyses suggest as much as 80:1 compression ratio can be achieved without affecting clinical diagnostic performance.

Influencing clinicians and healthcare managers: can ROC be more persuasive?

NASA Astrophysics Data System (ADS)

Taylor-Phillips, S.; Wallis, M. G.; Duncan, A.; Gale, A. G.

2010-02-01

Receiver Operating Characteristic analysis provides a reliable and cost effective performance measurement tool, without using full clinical trials. However, when ROC analysis shows that performance is statistically superior in one condition than another it is difficult to relate this result to effects in practice, or even to determine whether it is clinically significant. In this paper we present two concurrent analyses: using ROC methods alongside single threshold recall rate data, and suggest that reporting both provides complimentary data. Four mammographers read 160 difficult cases (41% malignant) twice, with and without prior mammograms. Lesion location and probability of malignancy was reported for each case and analyzed using JAFROC. Concurrently each participant chose recall or return to screen for each case. JAFROC analysis showed that the presence of prior mammograms improved performance (p<.05). Single threshold data showed a trend towards a 26% increase in the number of false positive recalls without prior mammograms (p=.056). If this trend were present throughout the NHS Breast Screening Programme then discarding prior mammograms would correspond to an increase in recall rate from 4.6% to 5.3%, and 12,414 extra women recalled annually for assessment. Whilst ROC methods account for all possible thresholds of recall and have higher power, providing a single threshold example of false positive, false negative, and recall rates when reporting results could be more influential for clinicians. This paper discusses whether this is a useful additional method of presenting data, or whether it is misleading and inaccurate.

Improving the prediction of pathologic outcomes in patients undergoing radical prostatectomy: the value of prostate cancer antigen 3 (PCA3), prostate health index (phi) and sarcosine.

PubMed

Ferro, Matteo; Lucarelli, Giuseppe; Bruzzese, Dario; Perdonà, Sisto; Mazzarella, Claudia; Perruolo, Giuseppe; Marino, Ada; Cosimato, Vincenzo; Giorgio, Emilia; Tagliamonte, Virginia; Bottero, Danilo; De Cobelli, Ottavio; Terracciano, Daniela

2015-02-01

Several efforts have been made to find biomarkers that could help clinicians to preoperatively determine prostate cancer (PCa) pathological characteristics and choose the best therapeutic approach, avoiding over-treatment. On this effort, prostate cancer antigen 3 (PCA3), prostate health index (phi) and sarcosine have been presented as promising tools. We evaluated the ability of these biomarkers to predict the pathologic PCa characteristics within a prospectively collected contemporary cohort of patients who underwent radical prostatectomy (RP) for clinically localized PCa at a single high-volume Institution. The prognostic performance of PCA3, phi and sarcosine were evaluated in 78 patients undergoing RP for biopsy-proven PCa. Receiver operating characteristic (ROC) curve analyses tested the accuracy (area under the curve (AUC)) in predicting PCa pathological characteristics. Decision curve analyses (DCA) were used to assess the clinical benefit of the three biomarkers. We found that PCA3, phi and sarcosine levels were significantly higher in patients with tumor volume (TV)≥0.5 ml, pathologic Gleason sum (GS)≥7 and pT3 disease (all p-values≤0.01). ROC curve analysis showed that phi is an accurate predictor of high-stage (AUC 0.85 [0.77-0.93]), high-grade (AUC 0.83 [0.73-0.93]) and high-volume disease (AUC 0.94 [0.88-0.99]). Sarcosine showed a comparable AUC (0.85 [0.76-0.94]) only for T3 stage prediction, whereas PCA3 score showed lower AUCs, ranging from 0.74 (for GS) to 0.86 (for TV). PCA3, phi and sarcosine are predictors of PCa characteristics at final pathology. Successful clinical translation of these findings would reduce the frequency of surveillance biopsies and may enhance acceptance of active surveillance (AS). Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Investigating strength and frequency effects in recognition memory using type-2 signal detection theory.

PubMed

Higham, Philip A; Perfect, Timothy J; Bruno, Davide

2009-01-01

Criterion- versus distribution-shift accounts of frequency and strength effects in recognition memory were investigated with Type-2 signal detection receiver operating characteristic (ROC) analysis, which provides a measure of metacognitive monitoring. Experiment 1 demonstrated a frequency-based mirror effect, with a higher hit rate and lower false alarm rate, for low frequency words compared with high frequency words. In Experiment 2, the authors manipulated item strength with repetition, which showed an increased hit rate but no effect on the false alarm rate. Whereas Type-1 indices were ambiguous as to whether these effects were based on a criterion- or distribution-shift model, the two models predict opposite effects on Type-2 distractor monitoring under some assumptions. Hence, Type-2 ROC analysis discriminated between potential models of recognition that could not be discriminated using Type-1 indices alone. In Experiment 3, the authors manipulated Type-1 response bias by varying the number of old versus new response categories to confirm the assumptions made in Experiments 1 and 2. The authors conclude that Type-2 analyses are a useful tool for investigating recognition memory when used in conjunction with more traditional Type-1 analyses.

Analysis of glottal source parameters in Parkinsonian speech.

PubMed

Hanratty, Jane; Deegan, Catherine; Walsh, Mary; Kirkpatrick, Barry

2016-08-01

Diagnosis and monitoring of Parkinson's disease has a number of challenges as there is no definitive biomarker despite the broad range of symptoms. Research is ongoing to produce objective measures that can either diagnose Parkinson's or act as an objective decision support tool. Recent research on speech based measures have demonstrated promising results. This study aims to investigate the characteristics of the glottal source signal in Parkinsonian speech. An experiment is conducted in which a selection of glottal parameters are tested for their ability to discriminate between healthy and Parkinsonian speech. Results for each glottal parameter are presented for a database of 50 healthy speakers and a database of 16 speakers with Parkinsonian speech symptoms. Receiver operating characteristic (ROC) curves were employed to analyse the results and the area under the ROC curve (AUC) values were used to quantify the performance of each glottal parameter. The results indicate that glottal parameters can be used to discriminate between healthy and Parkinsonian speech, although results varied for each parameter tested. For the task of separating healthy and Parkinsonian speech, 2 out of the 7 glottal parameters tested produced AUC values of over 0.9.

Proposing a Tentative Cut Point for the Compulsive Sexual Behavior Inventory

PubMed Central

Storholm, Erik David; Fisher, Dennis G.; Napper, Lucy E.; Reynolds, Grace L.

2015-01-01

Bivariate analyses were utilized in order to identify the relations between scores on the Compulsive Sexual Behavior Inventory (CSBI) and self-report of risky sexual behavior and drug abuse among 482 racially and ethnically diverse men and women. CSBI scores were associated with both risky sexual behavior and drug abuse among a diverse non-clinical sample, thereby providing evidence of criterion-related validity. The variables that demonstrated a high association with the CSBI were subsequently entered into a multiple regression model. Four variables (number of sexual partners in the last 30 days, self-report of trading drugs for sex, having paid for sex, and perceived chance of acquiring HIV) were retained as variables with good model fit. Receiver operating characteristic (ROC) curve analyses were conducted in order to determine the optimal tentative cut point for the CSBI. The four variables retained in the multiple regression model were utilized as exploratory gold standards in order to construct ROC curves. The ROC curves were then compared to one another in order to determine the point that maximized both sensitivity and specificity in the identification of compulsive sexual behavior with the CSBI scale. The current findings suggest that a tentative cut point of 40 may prove clinically useful in discriminating between persons who exhibit compulsive sexual behavior and those who do not. Because of the association between compulsive sexual behavior and HIV, STIs, and drug abuse, it is paramount that a psychometrically sound measure of compulsive sexual behavior is made available to all healthcare professionals working in disease prevention and other areas. PMID:21203814

Siemens Immulite Aspergillus-specific IgG assay for chronic pulmonary aspergillosis diagnosis.

PubMed

Page, Iain D; Richardson, Malcolm D; Denning, David W

2018-05-14

Chronic pulmonary aspergillosis (CPA) complicates underlying lung disease, including treated tuberculosis. Measurement of Aspergillus-specific immunoglobulin G (IgG) is a key diagnostic step. Cutoffs have been proposed based on receiver operating characteristic (ROC) curve analyses comparing CPA cases to healthy controls, but performance in at-risk populations with underlying lung disease is unclear. We evaluated optimal cutoffs for the Siemens Immulite Aspergillus-specific IgG assay for CPA diagnosis in relation to large groups of healthy and diseased controls with treated pulmonary tuberculosis. Sera from 241 patients with CPA attending the UK National Aspergillosis Centre, 299 Ugandan blood donors (healthy controls), and 398 Ugandans with treated pulmonary tuberculosis (diseased controls) were tested. Radiological screening removed potential CPA cases from diseased controls (234 screened diseased controls). ROC curve analyses were performed and optimal cutoffs identified by Youden J statistic. CPA versus control ROC area under curve (AUC) results were: healthy controls 0.984 (95% confidence interval 0.972-0.997), diseased controls 0.972 (0.959-0.985), screened diseased controls 0.979 (0.967-0.992). Optimal cutoffs were: healthy controls 15 mg/l (94.6% sensitivity, 98% specificity), unscreened diseased controls 15 mg/l (94.6% sensitivity, 94.5% specificity), screened diseased controls 25 mg/l (92.9% sensitivity, 98.7% specificity). Results were similar in healthy and diseased controls. We advocate a cutoff of 20 mg/l as this is the midpoint of the range of optimal cutoffs. Cutoffs calculated in relation to healthy controls for other assays are likely to remain valid for use in a treated tuberculosis population.

Proposing a tentative cut point for the Compulsive Sexual Behavior Inventory.

PubMed

Storholm, Erik David; Fisher, Dennis G; Napper, Lucy E; Reynolds, Grace L; Halkitis, Perry N

2011-12-01

Bivariate analyses were utilized in order to identify the relations between scores on the Compulsive Sexual Behavior Inventory (CSBI) and self-report of risky sexual behavior and drug abuse among 482 racially and ethnically diverse men and women. CSBI scores were associated with both risky sexual behavior and drug abuse among a diverse non-clinical sample, thereby providing evidence of criterion-related validity. The variables that demonstrated a high association with the CSBI were subsequently entered into a multiple regression model. Four variables (number of sexual partners in the last 30 days, self-report of trading drugs for sex, having paid for sex, and perceived chance of acquiring HIV) were retained as variables with good model fit. Receiver operating characteristic (ROC) curve analyses were conducted in order to determine the optimal tentative cut point for the CSBI. The four variables retained in the multiple regression model were utilized as exploratory gold standards in order to construct ROC curves. The ROC curves were then compared to one another in order to determine the point that maximized both sensitivity and specificity in the identification of compulsive sexual behavior with the CSBI scale. The current findings suggest that a tentative cut point of 40 may prove clinically useful in discriminating between persons who exhibit compulsive sexual behavior and those who do not. Because of the association between compulsive sexual behavior and HIV, STIs, and drug abuse, it is paramount that a psychometrically sound measure of compulsive sexual behavior is made available to all healthcare professionals working in disease prevention and other areas.

Benign and malignant skull-involved lesions: discriminative value of conventional CT and MRI combined with diffusion-weighted MRI.

PubMed

Tu, Zhanhai; Xiao, Zebin; Zheng, Yingyan; Huang, Hongjie; Yang, Libin; Cao, Dairong

2018-01-01

Background Little is known about the value of computed tomography (CT) and magnetic resonance imaging (MRI) combined with diffusion-weighted imaging (DWI) in distinguishing malignant from benign skull-involved lesions. Purpose To evaluate the discriminative value of DWI combined with conventional CT and MRI for differentiating between benign and malignant skull-involved lesions. Material and Methods CT and MRI findings of 58 patients with pathologically proven skull-involved lesions (43 benign and 15 malignant) were retrospectively reviewed. Conventional CT and MRI characteristics and apparent diffusion coefficient (ADC) value of the two groups were evaluated and compared. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the differential performance of each parameter separately and together. Results The presence of cortical defects or break-through and ill-defined margins were associated with malignant skull-involved lesions (both P < 0.05). Malignant skull-involved lesions demonstrated a significantly lower ADC ( P = 0.016) than benign lesions. ROC curve analyses indicated that a combination of CT, MRI, and DWI with an ADC ≤ 0.703 × 10 -3 mm 2 /s showed optimal sensitivity, while DWI along showed optimal specificity of 88.4% in differentiating between benign and malignant skull-involved lesions. Conclusion The combination of CT, MRI, and DWI can help to differentiate malignant from benign skull-involved lesions. CT + MRI + DWI offers optimal sensitivity, while DWI offers optimal specificity.

Reliability of cone beam computed tomography as a biopsy-independent tool in differential diagnosis of periapical cysts and granulomas: An In vivo Study

PubMed Central

Chanani, Ankit; Adhikari, Haridas Das

2017-01-01

Background: Differential diagnosis of periapical cysts and granulomas is required as their treatment modalities are different. Aim: The aim of this study was to evaluate the efficacy of cone beam computed tomography (CBCT) in the differential diagnosis of periapical cysts from granulomas. Settings and Design: A single-centered observational study was carried out in the Department of Conservative Dentistry and Endodontics, Dr. R. Ahmed Dental College and Hospital, using CBCT and dental operating microscope. Methods: Forty-five lesions were analyzed using CBCT scans. One evaluator analyzed each CBCT scan for the presence of the following six characteristic radiological features: cyst like-location, shape, periphery, internal structure, effect on the surrounding structures, and cortical plate perforation. Another independent evaluator analyzed the CBCT scans. This process was repeated after 6 months, and inter- and intrarater reliability of CBCT diagnoses was evaluated. Periapical surgeries were performed and tissue samples were obtained for histopathological analysis. To evaluate the efficacy, CBCT diagnoses were compared with histopathological diagnoses, and six receiver operating characteristic (ROC) curve analyses were conducted. Statistical Analysis Used: ROC curve, Cronbach's alpha (α) test, and Cohen Kappa (κ) test were used for statistical analysis. Results: Both inter- and intrarater reliability were excellent (α = 0.94, κ = 0.75 and 0.77, respectively). ROC curve with regard to ≥4 positive findings revealed the highest area under curve (0.66). Conclusion: CBCT is moderately accurate in the differential diagnosis of periapical cysts and granulomas. PMID:29386780

[Resistant Obsessive Compulsive disorder (ROC): clinical picture, predictive factors and influence of affective temperaments].

PubMed

Hantouche, E G; Demonfaucon, C

2008-12-01

Despite significant advances in clinical research, Obsessive Compulsive Disorder, OCD represents a difficult to treat condition. The French Association of patients suffering from OCD, "AFTOC" is highly concerned by this issue. A new survey was implemented with the aim of exploring Resistant Obsessive Compulsive disorder "ROC". Patients with OCD and members of the "AFTOC" were included in the survey. A self-rated file was elaborated in order to get the maximum of information on the clinical and therapeutic aspects and conditions of OCD. The full version of "TEMPS-A" was also included for assessment of affective temperaments. Statistical analyses were performed for inter-group comparison between "ROC" (resistant OCD) and good responders. Logistic regression analyses with "ROC" method were used to search for independent predictive factors to "ROC". The new survey of "AFTOC", "TOC & ROC" selected a sample of 360 patients, who are members of the association. The rate of "ROC" was 44.2%, 25.3% of Good Responders (GR), and 30.5% in between. Inter-group comparisons ("ROC" versus GR) showed significant higher rates of psychiatric admissions (49% versus 28%), and suicide attempts (26% versus 13%), greater numbers of doctors consulted (5.5 versus. 3.2), compulsions (4.6 versus 3.4), and psychiatric comorbidity (2.8 disorders versus. 2.0; notably agoraphobia, social anxiety and worry about appearance) in the "ROC" group. Assessment by full "TEMPS-A" scale revealed, significantly higher rates of Cyclothymic Temperament (63% versus 43%; p: 0.0003), Depressive Temperament (72% versus 53%; p: 0.004), and Irritable Temperament (21% versus 9%; p: 0.02) in the ROC group. Moreover, the mean global score on each of these temperaments was significantly higher in the "ROC" group. No difference was obtained in the rate or the mean score on the hyperthymic temperament scale. The most predictive factors of "ROC" were represented by "slow continuous course", "worsening under SRI", "worry about appearance", current age above 40 years and psychiatric admission. Our data provides a more precise clinical picture of "ROC", which should be initially explored through baseline severity, compulsive dominance, hoarding, special comorbidity such as recurrent depression, obsession of appearance, agoraphobia, social anxiety, and complex mixture of unstable affective temperament (cyclothymic, irritable, and depressive), and course of illness. Furthermore, vigilance towards the notion of worsening linked to drug therapy, and the increased suicide risk is warranted in the clinical management of "ROC".

Asymptotic Properties of the Sequential Empirical ROC, PPV and NPV Curves Under Case-Control Sampling.

PubMed

Koopmeiners, Joseph S; Feng, Ziding

2011-01-01

The receiver operating characteristic (ROC) curve, the positive predictive value (PPV) curve and the negative predictive value (NPV) curve are three measures of performance for a continuous diagnostic biomarker. The ROC, PPV and NPV curves are often estimated empirically to avoid assumptions about the distributional form of the biomarkers. Recently, there has been a push to incorporate group sequential methods into the design of diagnostic biomarker studies. A thorough understanding of the asymptotic properties of the sequential empirical ROC, PPV and NPV curves will provide more flexibility when designing group sequential diagnostic biomarker studies. In this paper we derive asymptotic theory for the sequential empirical ROC, PPV and NPV curves under case-control sampling using sequential empirical process theory. We show that the sequential empirical ROC, PPV and NPV curves converge to the sum of independent Kiefer processes and show how these results can be used to derive asymptotic results for summaries of the sequential empirical ROC, PPV and NPV curves.

Asymptotic Properties of the Sequential Empirical ROC, PPV and NPV Curves Under Case-Control Sampling

PubMed Central

Koopmeiners, Joseph S.; Feng, Ziding

2013-01-01

The receiver operating characteristic (ROC) curve, the positive predictive value (PPV) curve and the negative predictive value (NPV) curve are three measures of performance for a continuous diagnostic biomarker. The ROC, PPV and NPV curves are often estimated empirically to avoid assumptions about the distributional form of the biomarkers. Recently, there has been a push to incorporate group sequential methods into the design of diagnostic biomarker studies. A thorough understanding of the asymptotic properties of the sequential empirical ROC, PPV and NPV curves will provide more flexibility when designing group sequential diagnostic biomarker studies. In this paper we derive asymptotic theory for the sequential empirical ROC, PPV and NPV curves under case-control sampling using sequential empirical process theory. We show that the sequential empirical ROC, PPV and NPV curves converge to the sum of independent Kiefer processes and show how these results can be used to derive asymptotic results for summaries of the sequential empirical ROC, PPV and NPV curves. PMID:24039313

Optimal joint detection and estimation that maximizes ROC-type curves

PubMed Central

Wunderlich, Adam; Goossens, Bart; Abbey, Craig K.

2017-01-01

Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation. PMID:27093544

Optimal Joint Detection and Estimation That Maximizes ROC-Type Curves.

PubMed

Wunderlich, Adam; Goossens, Bart; Abbey, Craig K

2016-09-01

Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation.

Diagnostic accuracy and receiver-operating characteristics curve analysis in surgical research and decision making.

PubMed

Søreide, Kjetil; Kørner, Hartwig; Søreide, Jon Arne

2011-01-01

In surgical research, the ability to correctly classify one type of condition or specific outcome from another is of great importance for variables influencing clinical decision making. Receiver-operating characteristic (ROC) curve analysis is a useful tool in assessing the diagnostic accuracy of any variable with a continuous spectrum of results. In order to rule a disease state in or out with a given test, the test results are usually binary, with arbitrarily chosen cut-offs for defining disease versus health, or for grading of disease severity. In the postgenomic era, the translation from bench-to-bedside of biomarkers in various tissues and body fluids requires appropriate tools for analysis. In contrast to predetermining a cut-off value to define disease, the advantages of applying ROC analysis include the ability to test diagnostic accuracy across the entire range of variable scores and test outcomes. In addition, ROC analysis can easily examine visual and statistical comparisons across tests or scores. ROC is also favored because it is thought to be independent from the prevalence of the condition under investigation. ROC analysis is used in various surgical settings and across disciplines, including cancer research, biomarker assessment, imaging evaluation, and assessment of risk scores.With appropriate use, ROC curves may help identify the most appropriate cutoff value for clinical and surgical decision making and avoid confounding effects seen with subjective ratings. ROC curve results should always be put in perspective, because a good classifier does not guarantee the expected clinical outcome. In this review, we discuss the fundamental roles, suggested presentation, potential biases, and interpretation of ROC analysis in surgical research.

Class-specific Error Bounds for Ensemble Classifiers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prenger, R; Lemmond, T; Varshney, K

2009-10-06

The generalization error, or probability of misclassification, of ensemble classifiers has been shown to be bounded above by a function of the mean correlation between the constituent (i.e., base) classifiers and their average strength. This bound suggests that increasing the strength and/or decreasing the correlation of an ensemble's base classifiers may yield improved performance under the assumption of equal error costs. However, this and other existing bounds do not directly address application spaces in which error costs are inherently unequal. For applications involving binary classification, Receiver Operating Characteristic (ROC) curves, performance curves that explicitly trade off false alarms and missedmore » detections, are often utilized to support decision making. To address performance optimization in this context, we have developed a lower bound for the entire ROC curve that can be expressed in terms of the class-specific strength and correlation of the base classifiers. We present empirical analyses demonstrating the efficacy of these bounds in predicting relative classifier performance. In addition, we specify performance regions of the ROC curve that are naturally delineated by the class-specific strengths of the base classifiers and show that each of these regions can be associated with a unique set of guidelines for performance optimization of binary classifiers within unequal error cost regimes.« less

Clinical value of the neutrophil/lymphocyte ratio in diagnosing adult strangulated inguinal hernia.

PubMed

Zhou, Huanhao; Ruan, Xiaojiao; Shao, Xia; Huang, Xiaming; Fang, Guan; Zheng, Xiaofeng

2016-12-01

Diagnosis of incarcerated inguinal hernia (IIH) is not difficult, but currently, there are no diagnostic criteria that can be used to differentiate it from strangulated inguinal hernia (SIH). This research aimed to evaluate the clinical value of the neutrophil/lymphocyte ratio (NLR) in diagnosing SIH. We retrospectively analyzed 263 patients with IIH who had undergone emergency operation. The patients were divided into two groups according to IIH severity: group A, patients with pure IIH validated during operation as having no bowel ischemia; group B, patients with SIH validated during operation as having obvious bowel ischemia, including bowel necrosis. We statistically evaluated the relation between several clinical features and SIH. The accuracy of different indices was then evaluated and compared using receiver operating characteristic (ROC) curve analyses, and the corresponding cutoff values were calculated. Univariate analysis showed eight clinical features that were significantly different between the two groups. They were then subjected to multivariate analysis, which showed that the NLR, type of hernia, and incarcerated organ were significantly related to SIH. ROC curve analysis showed that the NLR had the largest area under the ROC curve. Among the different clinical features, the NLR appears to be the best index in diagnosing SIH. Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Potential of MR histogram analyses for prediction of response to chemotherapy in patients with colorectal hepatic metastases.

PubMed

Liang, He-Yue; Huang, Ya-Qin; Yang, Zhao-Xia; Ying-Ding; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-07-01

To determine if magnetic resonance imaging (MRI) histogram analyses can help predict response to chemotherapy in patients with colorectal hepatic metastases by using response evaluation criteria in solid tumours (RECIST1.1) as the reference standard. Standard MRI including diffusion-weighted imaging (b=0, 500 s/mm(2)) was performed before chemotherapy in 53 patients with colorectal hepatic metastases. Histograms were performed for apparent diffusion coefficient (ADC) maps, arterial, and portal venous phase images; thereafter, mean, percentiles (1st, 10th, 50th, 90th, 99th), skewness, kurtosis, and variance were generated. Quantitative histogram parameters were compared between responders (partial and complete response, n=15) and non-responders (progressive and stable disease, n=38). Receiver operator characteristics (ROC) analyses were further analyzed for the significant parameters. The mean, 1st percentile, 10th percentile, 50th percentile, 90th percentile, 99th percentile of the ADC maps were significantly lower in responding group than that in non-responding group (p=0.000-0.002) with area under the ROC curve (AUCs) of 0.76-0.82. The histogram parameters of arterial and portal venous phase showed no significant difference (p>0.05) between the two groups. Histogram-derived parameters for ADC maps seem to be a promising tool for predicting response to chemotherapy in patients with colorectal hepatic metastases. • ADC histogram analyses can potentially predict chemotherapy response in colorectal liver metastases. • Lower histogram-derived parameters (mean, percentiles) for ADC tend to have good response. • MR enhancement histogram analyses are not reliable to predict response.

Bayesian multivariate hierarchical transformation models for ROC analysis.

PubMed

O'Malley, A James; Zou, Kelly H

2006-02-15

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayesian multivariate hierarchical transformation models for ROC analysis

PubMed Central

O'Malley, A. James; Zou, Kelly H.

2006-01-01

SUMMARY A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box–Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial. PMID:16217836

CombiROC: an interactive web tool for selecting accurate marker combinations of omics data.

PubMed

Mazzara, Saveria; Rossi, Riccardo L; Grifantini, Renata; Donizetti, Simone; Abrignani, Sergio; Bombaci, Mauro

2017-03-30

Diagnostic accuracy can be improved considerably by combining multiple markers, whose performance in identifying diseased subjects is usually assessed via receiver operating characteristic (ROC) curves. The selection of multimarker signatures is a complicated process that requires integration of data signatures with sophisticated statistical methods. We developed a user-friendly tool, called CombiROC, to help researchers accurately determine optimal markers combinations from diverse omics methods. With CombiROC data from different domains, such as proteomics and transcriptomics, can be analyzed using sensitivity/specificity filters: the number of candidate marker panels rising from combinatorial analysis is easily optimized bypassing limitations imposed by the nature of different experimental approaches. Leaving to the user full control on initial selection stringency, CombiROC computes sensitivity and specificity for all markers combinations, performances of best combinations and ROC curves for automatic comparisons, all visualized in a graphic interface. CombiROC was designed without hard-coded thresholds, allowing a custom fit to each specific data: this dramatically reduces the computational burden and lowers the false negative rates given by fixed thresholds. The application was validated with published data, confirming the marker combination already originally described or even finding new ones. CombiROC is a novel tool for the scientific community freely available at http://CombiROC.eu.

Rocker: Open source, easy-to-use tool for AUC and enrichment calculations and ROC visualization.

PubMed

Lätti, Sakari; Niinivehmas, Sanna; Pentikäinen, Olli T

2016-01-01

Receiver operating characteristics (ROC) curve with the calculation of area under curve (AUC) is a useful tool to evaluate the performance of biomedical and chemoinformatics data. For example, in virtual drug screening ROC curves are very often used to visualize the efficiency of the used application to separate active ligands from inactive molecules. Unfortunately, most of the available tools for ROC analysis are implemented into commercially available software packages, or are plugins in statistical software, which are not always the easiest to use. Here, we present Rocker, a simple ROC curve visualization tool that can be used for the generation of publication quality images. Rocker also includes an automatic calculation of the AUC for the ROC curve and Boltzmann-enhanced discrimination of ROC (BEDROC). Furthermore, in virtual screening campaigns it is often important to understand the early enrichment of active ligand identification, for this Rocker offers automated calculation routine. To enable further development of Rocker, it is freely available (MIT-GPL license) for use and modifications from our web-site (http://www.jyu.fi/rocker).

Reliability, Validity, and Clinical Utility of the Dominic Interactive for Adolescents-RevisedA DSM-5-Based Self-Report Screen for Mental Disorders, Borderline Personality Traits, and Suicidality.

PubMed

Bergeron, Lise; Smolla, Nicole; Berthiaume, Claude; Renaud, Johanne; Breton, Jean-Jacques; St-Georges, Marie; Morin, Pauline; Zavaglia, Elissa; Labelle, Réal

2017-03-01

The Dominic Interactive for Adolescents-Revised (DIA-R) is a multimedia self-report screen for 9 mental disorders, borderline personality traits, and suicidality defined by the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders ( DSM-5). This study aimed to examine the reliability and the validity of this instrument. French- and English-speaking adolescents aged 12 to 15 years ( N = 447) were recruited from schools and clinical settings in Montreal and were evaluated twice. The internal consistency was estimated by Cronbach alpha coefficients and the test-retest reliability by intraclass correlation coefficients. Cutoff points on the DIA-R scales were determined by using clinically relevant measures for defining external validation criteria: the Schedule for Affective Disorders and Schizophrenia for School-Aged Children, the Beck Hopelessness Scale, and the Abbreviated-Diagnostic Interview for Borderlines. Receiver operating characteristic (ROC) analyses provided accuracy estimates (area under the ROC curve, sensitivity, specificity, likelihood ratio) to evaluate the ability of the DIA-R scales to predict external criteria. For most of the DIA-R scales, reliability coefficients were excellent or moderate. High or moderate accuracy estimates from ROC analyses demonstrated the ability of the DIA-R thresholds to predict psychopathological conditions. These thresholds were generally capable to discriminate between clinical and school subsamples. However, the validity of the obsessions/compulsions scale was too low. Findings clearly support the reliability and the validity of the DIA-R. This instrument may be useful to assess a wide range of adolescents' mental health problems in the continuum of services. This conclusion applies to all scales, except the obsessions/compulsions one.

A global goodness-of-fit test for receiver operating characteristic curve analysis via the bootstrap method.

PubMed

Zou, Kelly H; Resnic, Frederic S; Talos, Ion-Florin; Goldberg-Zimring, Daniel; Bhagwat, Jui G; Haker, Steven J; Kikinis, Ron; Jolesz, Ferenc A; Ohno-Machado, Lucila

2005-10-01

Medical classification accuracy studies often yield continuous data based on predictive models for treatment outcomes. A popular method for evaluating the performance of diagnostic tests is the receiver operating characteristic (ROC) curve analysis. The main objective was to develop a global statistical hypothesis test for assessing the goodness-of-fit (GOF) for parametric ROC curves via the bootstrap. A simple log (or logit) and a more flexible Box-Cox normality transformations were applied to untransformed or transformed data from two clinical studies to predict complications following percutaneous coronary interventions (PCIs) and for image-guided neurosurgical resection results predicted by tumor volume, respectively. We compared a non-parametric with a parametric binormal estimate of the underlying ROC curve. To construct such a GOF test, we used the non-parametric and parametric areas under the curve (AUCs) as the metrics, with a resulting p value reported. In the interventional cardiology example, logit and Box-Cox transformations of the predictive probabilities led to satisfactory AUCs (AUC=0.888; p=0.78, and AUC=0.888; p=0.73, respectively), while in the brain tumor resection example, log and Box-Cox transformations of the tumor size also led to satisfactory AUCs (AUC=0.898; p=0.61, and AUC=0.899; p=0.42, respectively). In contrast, significant departures from GOF were observed without applying any transformation prior to assuming a binormal model (AUC=0.766; p=0.004, and AUC=0.831; p=0.03), respectively. In both studies the p values suggested that transformations were important to consider before applying any binormal model to estimate the AUC. Our analyses also demonstrated and confirmed the predictive values of different classifiers for determining the interventional complications following PCIs and resection outcomes in image-guided neurosurgery.

The cyclophosphamide equivalent dose as an approach for quantifying alkylating agent exposure: a report from the Childhood Cancer Survivor Study.

PubMed

Green, Daniel M; Nolan, Vikki G; Goodman, Pamela J; Whitton, John A; Srivastava, DeoKumar; Leisenring, Wendy M; Neglia, Joseph P; Sklar, Charles A; Kaste, Sue C; Hudson, Melissa M; Diller, Lisa R; Stovall, Marilyn; Donaldson, Sarah S; Robison, Leslie L

2014-01-01

Estimation of the risk of adverse long-term outcomes such as second malignant neoplasms and infertility often requires reproducible quantification of exposures. The method for quantification should be easily utilized and valid across different study populations. The widely used Alkylating Agent Dose (AAD) score is derived from the drug dose distribution of the study population and thus cannot be used for comparisons across populations as each will have a unique distribution of drug doses. We compared the performance of the Cyclophosphamide Equivalent Dose (CED), a unit for quantifying alkylating agent exposure independent of study population, to the AAD. Comparisons included associations from three Childhood Cancer Survivor Study (CCSS) outcome analyses, receiver operator characteristic (ROC) curves and goodness of fit based on the Akaike's Information Criterion (AIC). The CED and AAD performed essentially identically in analyses of risk for pregnancy among the partners of male CCSS participants, risk for adverse dental outcomes among all CCSS participants and risk for premature menopause among female CCSS participants, based on similar associations, lack of statistically significant differences between the areas under the ROC curves and similar model fit values for the AIC between models including the two measures of exposure. The CED is easily calculated, facilitating its use for patient counseling. It is independent of the drug dose distribution of a particular patient population, a characteristic that will allow direct comparisons of outcomes among epidemiological cohorts. We recommend the use of the CED in future research assessing cumulative alkylating agent exposure. © 2013 Wiley Periodicals, Inc.

Scoring the DSM-IV personality disorders using the Five-Factor Model: development and validation of normative scores for North American, French, and Dutch-Flemish samples.

PubMed

Miller, Joshua D; Lynam, Donald R; Rolland, Jean-Pierre; De Fruyt, Filip; Reynolds, Sarah K; Pham-Scottez, Alexandra; Baker, Spencer R; Bagby, R Michael

2008-10-01

Five-Factor Model (FFM) personality disorder (PD) counts have demonstrated significant convergent and discriminant validity with DSM-IV PD symptoms. However, these FFM PD counts are of limited clinical use without normative data because it is difficult to determine what a specific score means with regard to the relative level of elevation. The current study presents data from three large normative samples that can be used as norms for the FFM PD counts in the respective countries: United States (N = 1,000), France (N = 801), and Belgium-Netherlands (N = 549). The present study also examines the performance, with regard to diagnostic efficiency, of statistically-defined cut-offs at 1.5 standard deviations above the mean (T > or = 65) versus previously identified cut-offs using receiver-operator characteristics (ROC) analyses. These cut-offs are tested in three clinical samples-one from each of the aforementioned countries. In general, the T > or = 65 cut-offs performed similarly to those identified using ROC analyses and manifested properties relevant to a screening instrument. These normative data allow FFM data to be used in a flexible and comprehensive manner, which may include scoring this type of personality data in order to screen for DSM-IV PD constructs.

Association Between Aerobic Fitness And High Blood Pressure in Adolescents in Brazil: Evidence for Criterion-Referenced Cut-Points.

PubMed

Silva, Diego Augusto; Tremblay, Mark; Pelegrini, Andreia; Dos Santos Silva, Roberto Jeronimo; Cabral de Oliveira, Antonio Cesar; Petroski, Edio Luiz

2016-05-01

Criterion-referenced cut-points for health-related fitness measures are lacking. This study aimed to determine the associations between aerobic fitness and high blood pressure levels (HBP) to determine the cut-points that best predict HBP among adolescents. This cross-sectional school-based study with sample of 875 adolescents aged 14-19 years was conducted in southern Brazil. Aerobic fitness was assessed using the modified Canadian Aerobic Fitness Test (mCAFT). Systolic and diastolic blood pressure were measured by the oscillometric method with a digital sphygmomanometer. Analyses controlled for sociodemographic variables, physical activity, body mass and biological maturation. Receiver Operating Characteristic (ROC) curves demonstrated that mCAFT measures could discriminate HBP in both sexes (female: AUC = 0.70; male: AUC = 0.63). The cut-points with the best discriminatory power for HBP were 32 mL·kg-1·min-1 for females and 40 mL·kg-1·min-1 for males. Females (OR = 8.4; 95% CI: 2.1, 33.7) and males (OR: 2.5; CI 95%: 1.2, 5.2) with low aerobic fitness levels were more likely to have HBP. mCAFT measures are inversely associated with BP and cut-points from ROC analyses have good discriminatory power for HBP.

Design of a receiver operating characteristic (ROC) study of 10:1 lossy image compression

NASA Astrophysics Data System (ADS)

Collins, Cary A.; Lane, David; Frank, Mark S.; Hardy, Michael E.; Haynor, David R.; Smith, Donald V.; Parker, James E.; Bender, Gregory N.; Kim, Yongmin

1994-04-01

The digital archiving system at Madigan Army Medical Center (MAMC) uses a 10:1 lossy data compression algorithm for most forms of computed radiography. A systematic study on the potential effect of lossy image compression on patient care has been initiated with a series of studies focused on specific diagnostic tasks. The studies are based upon the receiver operating characteristic (ROC) method of analysis for diagnostic systems. The null hypothesis is that observer performance with approximately 10:1 compressed and decompressed images is not different from using original, uncompressed images for detecting subtle pathologic findings seen on computed radiographs of bone, chest, or abdomen, when viewed on a high-resolution monitor. Our design involves collecting cases from eight pathologic categories. Truth is determined by committee using confirmatory studies performed during routine clinical practice whenever possible. Software has been developed to aid in case collection and to allow reading of the cases for the study using stand-alone Siemens Litebox workstations. Data analysis uses two methods, ROC analysis and free-response ROC (FROC) methods. This study will be one of the largest ROC/FROC studies of its kind and could benefit clinical radiology practice using PACS technology. The study design and results from a pilot FROC study are presented.

ROC-ing along: Evaluation and interpretation of receiver operating characteristic curves.

PubMed

Carter, Jane V; Pan, Jianmin; Rai, Shesh N; Galandiuk, Susan

2016-06-01

It is vital for clinicians to understand and interpret correctly medical statistics as used in clinical studies. In this review, we address current issues and focus on delivering a simple, yet comprehensive, explanation of common research methodology involving receiver operating characteristic (ROC) curves. ROC curves are used most commonly in medicine as a means of evaluating diagnostic tests. Sample data from a plasma test for the diagnosis of colorectal cancer were used to generate a prediction model. These are actual, unpublished data that have been used to describe the calculation of sensitivity, specificity, positive predictive and negative predictive values, and accuracy. The ROC curves were generated to determine the accuracy of this plasma test. These curves are generated by plotting the sensitivity (true-positive rate) on the y axis and 1 - specificity (false-positive rate) on the x axis. Curves that approach closest to the coordinate (x = 0, y = 1) are more highly predictive, whereas ROC curves that lie close to the line of equality indicate that the result is no better than that obtained by chance. The optimum sensitivity and specificity can be determined from the graph as the point where the minimum distance line crosses the ROC curve. This point corresponds to the Youden index (J), a function of sensitivity and specificity used commonly to rate diagnostic tests. The area under the curve is used to quantify the overall ability of a test to discriminate between 2 outcomes. By following these simple guidelines, interpretation of ROC curves will be less difficult and they can then be interpreted more reliably when writing, reviewing, or analyzing scientific papers. Copyright © 2016 Elsevier Inc. All rights reserved.

Can technical characteristics predict clinical performance in PET/CT imaging? A correlation study for thyroid cancer diagnosis

NASA Astrophysics Data System (ADS)

Kallergi, Maria; Menychtas, Dimitrios; Georgakopoulos, Alexandros; Pianou, Nikoletta; Metaxas, Marinos; Chatziioannou, Sofia

2013-03-01

The purpose of this study was to determine whether image characteristics could be used to predict the outcome of ROC studies in PET/CT imaging. Patients suspected for recurrent thyroid cancer underwent a standard whole body (WB) examination and an additional high-resolution head-and-neck (HN) F18-FDG PET/CT scan. The value of the latter was determined with an ROC study, the results of which showed that the WB+HN combination was better than WB alone for thyroid cancer detection and diagnosis. Following the ROC experiment, the WB and HN images of confirmed benign or malignant thyroid disease were analyzed and first and second order textural features were determined. Features included minimum, mean, and maximum intensity, as well as contrast in regions of interest encircling the thyroid lesions. Lesion size and standard uptake values (SUV) were also determined. Bivariate analysis was applied to determine relationships between WB and HN features and between observer ROC responses and the various feature values. The two sets showed significant associations in the values of SUV, contrast, and lesion size. They were completely different when the intensities were considered; no relationship was found between the WB minimum, maximum, and mean ROI values and their HN counterparts. SUV and contrast were the strongest predictors of ROC performance on PET/CT examinations of thyroid cancer. The high resolution HN images seem to enhance these relationships but without a single dramatic effect as was projected from the ROC results. A combination of features from both WB and HN datasets may possibly be a more robust predictor of ROC performance.

Towards operationalising internal distractibility (Mind Wandering) in adults with ADHD.

PubMed

Biederman, Joseph; Fitzgerald, Maura; Uchida, Mai; Spencer, Thomas J; Fried, Ronna; Wicks, Jennifer; Saunders, Alexandra; Faraone, Stephen V

2017-12-01

To investigate whether specific symptoms of attention deficit hyperactivity disorder (ADHD) can help identify ADHD patients with mind wandering. Subjects were adults ages 18-55 of both sexes (n=41) who completed the Mind-Wandering Questionnaire (MWQ) and the ADHD module of the Schedule for Affective Disorders and Schizophrenia for School-Age Children Epidemiologic Version. We used Spearman's rank correlation and Pearson's χ2 analyses to examine associations between the ADHD module and the MWQ and receiver operator characteristic (ROC) analyses to evaluate the diagnostic efficiency of the ADHD module. Out of the three ADHD domains, the inattentive ADHD scores had the strongest association with the MWQ (total: r s=0.34, df=39, p=0.03; inattentive: r s=0.38, df=39, p=0.02; Hyperactive: r s=0.17, df=39, p=0.28). Correlation analyses between individual items on the ADHD module and the MWQ showed that two inattention items ('failure to pay attention to detail' and 'trouble following instructions') were positively associated with total scores on the MWQ (p=0.02). These two inattention items had the strongest association with the MWQ (r s=0.45, df=38, p=0.004). ROC analyses showed that the combined score of the two significant inattention items had the highest efficiency (AUC=0.71) in classifying high-level mind wanderers as defined by scores greater than the median split on the MWQ. The combined score of the two inattention items best identified high-level mind wanderers. Results suggest a way to operationalise mind wandering using the symptoms of ADHD.

Using a constrained formulation based on probability summation to fit receiver operating characteristic (ROC) curves

NASA Astrophysics Data System (ADS)

Swensson, Richard G.; King, Jill L.; Good, Walter F.; Gur, David

2000-04-01

A constrained ROC formulation from probability summation is proposed for measuring observer performance in detecting abnormal findings on medical images. This assumes the observer's detection or rating decision on each image is determined by a latent variable that characterizes the specific finding (type and location) considered most likely to be a target abnormality. For positive cases, this 'maximum- suspicion' variable is assumed to be either the value for the actual target or for the most suspicious non-target finding, whichever is the greater (more suspicious). Unlike the usual ROC formulation, this constrained formulation guarantees a 'well-behaved' ROC curve that always equals or exceeds chance- level decisions and cannot exhibit an upward 'hook.' Its estimated parameters specify the accuracy for separating positive from negative cases, and they also predict accuracy in locating or identifying the actual abnormal findings. The present maximum-likelihood procedure (runs on PC with Windows 95 or NT) fits this constrained formulation to rating-ROC data using normal distributions with two free parameters. Fits of the conventional and constrained ROC formulations are compared for continuous and discrete-scale ratings of chest films in a variety of detection problems, both for localized lesions (nodules, rib fractures) and for diffuse abnormalities (interstitial disease, infiltrates or pnumothorax). The two fitted ROC curves are nearly identical unless the conventional ROC has an ill behaved 'hook,' below the constrained ROC.

On the convexity of ROC curves estimated from radiological test results.

PubMed

Pesce, Lorenzo L; Metz, Charles E; Berbaum, Kevin S

2010-08-01

Although an ideal observer's receiver operating characteristic (ROC) curve must be convex-ie, its slope must decrease monotonically-published fits to empirical data often display "hooks." Such fits sometimes are accepted on the basis of an argument that experiments are done with real, rather than ideal, observers. However, the fact that ideal observers must produce convex curves does not imply that convex curves describe only ideal observers. This article aims to identify the practical implications of nonconvex ROC curves and the conditions that can lead to empirical or fitted ROC curves that are not convex. This article views nonconvex ROC curves from historical, theoretical, and statistical perspectives, which we describe briefly. We then consider population ROC curves with various shapes and analyze the types of medical decisions that they imply. Finally, we describe how sampling variability and curve-fitting algorithms can produce ROC curve estimates that include hooks. We show that hooks in population ROC curves imply the use of an irrational decision strategy, even when the curve does not cross the chance line, and therefore usually are untenable in medical settings. Moreover, we sketch a simple approach to improve any nonconvex ROC curve by adding statistical variation to the decision process. Finally, we sketch how to test whether hooks present in ROC data are likely to have been caused by chance alone and how some hooked ROCs found in the literature can be easily explained as fitting artifacts or modeling issues. In general, ROC curve fits that show hooks should be looked on with suspicion unless other arguments justify their presence. 2010 AUR. Published by Elsevier Inc. All rights reserved.

On the convexity of ROC curves estimated from radiological test results

PubMed Central

Pesce, Lorenzo L.; Metz, Charles E.; Berbaum, Kevin S.

2010-01-01

Rationale and Objectives Although an ideal observer’s receiver operating characteristic (ROC) curve must be convex — i.e., its slope must decrease monotonically — published fits to empirical data often display “hooks.” Such fits sometimes are accepted on the basis of an argument that experiments are done with real, rather than ideal, observers. However, the fact that ideal observers must produce convex curves does not imply that convex curves describe only ideal observers. This paper aims to identify the practical implications of non-convex ROC curves and the conditions that can lead to empirical and/or fitted ROC curves that are not convex. Materials and Methods This paper views non-convex ROC curves from historical, theoretical and statistical perspectives, which we describe briefly. We then consider population ROC curves with various shapes and analyze the types of medical decisions that they imply. Finally, we describe how sampling variability and curve-fitting algorithms can produce ROC curve estimates that include hooks. Results We show that hooks in population ROC curves imply the use of an irrational decision strategy, even when the curve doesn’t cross the chance line, and therefore usually are untenable in medical settings. Moreover, we sketch a simple approach to improve any non-convex ROC curve by adding statistical variation to the decision process. Finally, we sketch how to test whether hooks present in ROC data are likely to have been caused by chance alone and how some hooked ROCs found in the literature can be easily explained as fitting artifacts or modeling issues. Conclusion In general, ROC curve fits that show hooks should be looked upon with suspicion unless other arguments justify their presence. PMID:20599155

Influence of optic disc size on the diagnostic performance of macular ganglion cell complex and peripapillary retinal nerve fiber layer analyses in glaucoma.

PubMed

Cordeiro, Daniela Valença; Lima, Verônica Castro; Castro, Dinorah P; Castro, Leonardo C; Pacheco, Maria Angélica; Lee, Jae Min; Dimantas, Marcelo I; Prata, Tiago Santos

2011-01-01

To evaluate the influence of optic disc size on the diagnostic accuracy of macular ganglion cell complex (GCC) and conventional peripapillary retinal nerve fiber layer (pRNFL) analyses provided by spectral domain optical coherence tomography (SD-OCT) in glaucoma. Eighty-two glaucoma patients and 30 healthy subjects were included. All patients underwent GCC (7 × 7 mm macular grid, consisting of RNFL, ganglion cell and inner plexiform layers) and pRNFL thickness measurement (3.45 mm circular scan) by SD-OCT. One eye was randomly selected for analysis. Initially, receiver operating characteristic (ROC) curves were generated for different GCC and pRNFL parameters. The effect of disc area on the diagnostic accuracy of these parameters was evaluated using a logistic ROC regression model. Subsequently, 1.5, 2.0, and 2.5 mm(2) disc sizes were arbitrarily chosen (based on data distribution) and the predicted areas under the ROC curves (AUCs) and sensitivities were compared at fixed specificities for each. Average mean deviation index for glaucomatous eyes was -5.3 ± 5.2 dB. Similar AUCs were found for the best pRNFL (average thickness = 0.872) and GCC parameters (average thickness = 0.824; P = 0.19). The coefficient representing disc area in the ROC regression model was not statistically significant for average pRNFL thickness (-0.176) or average GCC thickness (0.088; P ≥ 0.56). AUCs for fixed disc areas (1.5, 2.0, and 2.5 mm(2)) were 0.904, 0.891, and 0.875 for average pRNFL thickness and 0.834, 0.842, and 0.851 for average GCC thickness, respectively. The highest sensitivities - at 80% specificity for average pRNFL (84.5%) and GCC thicknesses (74.5%) - were found with disc sizes fixed at 1.5 mm(2) and 2.5 mm(2). Diagnostic accuracy was similar between pRNFL and GCC thickness parameters. Although not statistically significant, there was a trend for a better diagnostic accuracy of pRNFL thickness measurement in cases of smaller discs. For GCC analysis, an inverse effect was observed.

Beyond ROC Curvature: Strength Effects and Response Time Data Support Continuous-Evidence Models of Recognition Memory

ERIC Educational Resources Information Center

Dube, Chad; Starns, Jeffrey J.; Rotello, Caren M.; Ratcliff, Roger

2012-01-01

A classic question in the recognition memory literature is whether retrieval is best described as a continuous-evidence process consistent with signal detection theory (SDT), or a threshold process consistent with many multinomial processing tree (MPT) models. Because receiver operating characteristics (ROCs) based on confidence ratings are…

Triceps and Subscapular Skinfold Thickness Percentiles and Cut-Offs for Overweight and Obesity in a Population-Based Sample of Schoolchildren and Adolescents in Bogota, Colombia.

PubMed

Ramírez-Vélez, Robinson; López-Cifuentes, Mario Ferney; Correa-Bautista, Jorge Enrique; González-Ruíz, Katherine; González-Jiménez, Emilio; Córdoba-Rodríguez, Diana Paola; Vivas, Andrés; Triana-Reina, Hector Reynaldo; Schmidt-RioValle, Jacqueline

2016-09-24

The assessment of skinfold thickness is an objective measure of adiposity. The aims of this study were to establish Colombian smoothed centile charts and LMS L (Box-Cox transformation), M (median), and S (coefficient of variation) tables for triceps, subscapular, and triceps + subscapular skinfolds; appropriate cut-offs were selected using receiver operating characteristic (ROC) analysis based on a population-based sample of children and adolescents in Bogotá, Colombia. A cross-sectional study was conducted in 9618 children and adolescents (55.7% girls; age range of 9-17.9 years). Triceps and subscapular skinfold measurements were obtained using standardized methods. We calculated the triceps + subscapular skinfold (T + SS) sum. Smoothed percentile curves for triceps and subscapular skinfold thickness were derived using the LMS method. ROC curve analyses were used to evaluate the optimal cut-off point of skinfold thickness for overweight and obesity, based on the International Obesity Task Force definitions. Subscapular and triceps skinfolds and T + SS were significantly higher in girls than in boys (p < 0.001). The ROC analysis showed that subscapular and triceps skinfolds and T + SS have a high discriminatory power in the identification of overweight and obesity in the sample population in this study. Our results provide sex- and age-specific normative reference standards for skinfold thickness values from a population from Bogotá, Colombia.

Equivalence of binormal likelihood-ratio and bi-chi-squared ROC curve models

PubMed Central

Hillis, Stephen L.

2015-01-01

A basic assumption for a meaningful diagnostic decision variable is that there is a monotone relationship between it and its likelihood ratio. This relationship, however, generally does not hold for a decision variable that results in a binormal ROC curve. As a result, receiver operating characteristic (ROC) curve estimation based on the assumption of a binormal ROC-curve model produces improper ROC curves that have “hooks,” are not concave over the entire domain, and cross the chance line. Although in practice this “improperness” is usually not noticeable, sometimes it is evident and problematic. To avoid this problem, Metz and Pan proposed basing ROC-curve estimation on the assumption of a binormal likelihood-ratio (binormal-LR) model, which states that the decision variable is an increasing transformation of the likelihood-ratio function of a random variable having normal conditional diseased and nondiseased distributions. However, their development is not easy to follow. I show that the binormal-LR model is equivalent to a bi-chi-squared model in the sense that the families of corresponding ROC curves are the same. The bi-chi-squared formulation provides an easier-to-follow development of the binormal-LR ROC curve and its properties in terms of well-known distributions. PMID:26608405

Advanced non-contrasted computed tomography post-processing by CT-Calculometry (CT-CM) outperforms established predictors for the outcome of shock wave lithotripsy.

PubMed

Langenauer, J; Betschart, P; Hechelhammer, L; Güsewell, S; Schmid, H P; Engeler, D S; Abt, D; Zumstein, V

2018-05-29

To evaluate the predictive value of advanced non-contrasted computed tomography (NCCT) post-processing using novel CT-calculometry (CT-CM) parameters compared to established predictors of success of shock wave lithotripsy (SWL) for urinary calculi. NCCT post-processing was retrospectively performed in 312 patients suffering from upper tract urinary calculi who were treated by SWL. Established predictors such as skin to stone distance, body mass index, stone diameter or mean stone attenuation values were assessed. Precise stone size and shape metrics, 3-D greyscale measurements and homogeneity parameters such as skewness and kurtosis, were analysed using CT-CM. Predictive values for SWL outcome were analysed using logistic regression and receiver operating characteristics (ROC) statistics. Overall success rate (stone disintegration and no re-intervention needed) of SWL was 59% (184 patients). CT-CM metrics mainly outperformed established predictors. According to ROC analyses, stone volume and surface area performed better than established stone diameter, mean 3D attenuation value was a stronger predictor than established mean attenuation value, and parameters skewness and kurtosis performed better than recently emerged variation coefficient of stone density. Moreover, prediction of SWL outcome with 80% probability to be correct would be possible in a clearly higher number of patients (up to fivefold) using CT-CM-derived parameters. Advanced NCCT post-processing by CT-CM provides novel parameters that seem to outperform established predictors of SWL response. Implementation of these parameters into clinical routine might reduce SWL failure rates.

ROC-king onwards: intraepithelial lymphocyte counts, distribution & role in coeliac disease mucosal interpretation

PubMed Central

Rostami, Kamran; Marsh, Michael N; Johnson, Matt W; Mohaghegh, Hamid; Heal, Calvin; Holmes, Geoffrey; Ensari, Arzu; Aldulaimi, David; Bancel, Brigitte; Bassotti, Gabrio; Bateman, Adrian; Becheanu, Gabriel; Bozzola, Anna; Carroccio, Antonio; Catassi, Carlo; Ciacci, Carolina; Ciobanu, Alexandra; Danciu, Mihai; Derakhshan, Mohammad H; Elli, Luca; Ferrero, Stefano; Fiorentino, Michelangelo; Fiorino, Marilena; Ganji, Azita; Ghaffarzadehgan, Kamran; Going, James J; Ishaq, Sauid; Mandolesi, Alessandra; Mathews, Sherly; Maxim, Roxana; Mulder, Chris J; Neefjes-Borst, Andra; Robert, Marie; Russo, Ilaria; Rostami-Nejad, Mohammad; Sidoni, Angelo; Sotoudeh, Masoud; Villanacci, Vincenzo; Volta, Umberto; Zali, Mohammad R; Srivastava, Amitabh

2017-01-01

Objectives Counting intraepithelial lymphocytes (IEL) is central to the histological diagnosis of coeliac disease (CD), but no definitive ‘normal’ IEL range has ever been published. In this multicentre study, receiver operating characteristic (ROC) curve analysis was used to determine the optimal cut-off between normal and CD (Marsh III lesion) duodenal mucosa, based on IEL counts on >400 mucosal biopsy specimens. Design The study was designed at the International Meeting on Digestive Pathology, Bucharest 2015. Investigators from 19 centres, eight countries of three continents, recruited 198 patients with Marsh III histology and 203 controls and used one agreed protocol to count IEL/100 enterocytes in well-oriented duodenal biopsies. Demographic and serological data were also collected. Results The mean ages of CD and control groups were 45.5 (neonate to 82) and 38.3 (2–88) years. Mean IEL count was 54±18/100 enterocytes in CD and 13±8 in normal controls (p=0.0001). ROC analysis indicated an optimal cut-off point of 25 IEL/100 enterocytes, with 99% sensitivity, 92% specificity and 99.5% area under the curve. Other cut-offs between 20 and 40 IEL were less discriminatory. Additionally, there was a sufficiently high number of biopsies to explore IEL counts across the subclassification of the Marsh III lesion. Conclusion Our ROC curve analyses demonstrate that for Marsh III lesions, a cut-off of 25 IEL/100 enterocytes optimises discrimination between normal control and CD biopsies. No differences in IEL counts were found between Marsh III a, b and c lesions. There was an indication of a continuously graded dose–response by IEL to environmental (gluten) antigenic influence. PMID:28893865

Acute respiratory distress syndrome in blunt trauma: identification of independent risk factors.

PubMed

Miller, Preston R; Croce, Martin A; Kilgo, Patrick D; Scott, John; Fabian, Timothy C

2002-10-01

Acute respiratory distress syndrome (ARDS) is a major contributor to morbidity and mortality in trauma patients. Although many injuries and conditions are believed to be associated with ARDS independent risk factors in trauma patients and their relative importance in development of the syndrome are undefined. The aim of this project is to identify independent risk factors for the development of ARDS in blunt trauma patients and to examine the contributions of each factor to ARDS development. Patients with ARDS were identified from the registry of a Level I trauma center over a 4.5-year period. Records were reviewed for demographics, injury characteristics, transfusion requirements, and hospital course. Variables examined included age >65 years, Injury Severity Score (ISS) >25, hypotension on admission (systolic blood pressure <90), significant metabolic acidosis (base deficit <-5.0), severe brain injury as shown by a Glasgow Coma Scale score (GCS) <8 on admission, 24-hour transfusion requirement >10 units packed red blood cells, pulmonary contusion (PC), femur fracture, and major infection (pneumonia, empyema, or intra-abdominal abscess). Both univariate and stepwise logistic regression were used to identify independent risk factors, and receiver operating characteristic curve (ROC) analysis was used to determine the relative contribution of each risk factor. A total of 4397 patients having sustained blunt trauma were admitted to the intensive care unit and survived >24 hours between October 1995 and May 2000. Of these patients 200 (4.5%) developed ARDS. All studied variables were significantly associated with ARDS in univariate analyses. Stepwise logistic regression, however, demonstrated age >65 years, ISS >25, hypotension on admission, 24-hour transfusion requirement >10 units, and pulmonary contusion as independent risk factors, whereas admission metabolic acidosis, femur fracture, infection, and severe brain injury were not. Using a model based on the logistic regression equation derived yields better than 80 per cent discrimination in ARDS patients. The risk factors providing the greatest contribution to ARDS development were ISS >25 (ROC area 0.72) and PC (ROC area 0.68) followed by large transfusion requirement (ROC area 0.56), admission hypotension (ROC area 0.57), and age >65 (ROC area 0.54). Independent risk factors for ARDS in blunt trauma include ISS >25, PC, age >65 years, hypotension on admission, and 24-hour transfusion requirement >10 units but not admission metabolic acidosis, femur fracture, infection, or severe brain injury. Assessment of these variables allows accurate estimate of risk in the majority of cases, and the most potent contributors to the predictive value of the model are ISS >25 and PC. Improvement in understanding of which patients are actually at risk may allow for advances in treatment as well as prevention in the future.

Promotion by humus-reducing bacteria for the degradation of UV254 absorbance in reverse-osmosis concentrates pretreated with O3-assisted UV-Fenton method.

PubMed

Xia, Jiaohui; Zhang, Hui; Ding, Shaoxuan; Li, Changyu; Ding, Jincheng; Lu, Jie

2017-07-12

The primary pollutants in reverse-osmosis concentrates (ROC) are the substances with the UV absorbance at 254 nm (UV 254 ), which is closely related to humic substances that can be degraded by humus-reducing bacteria. This work studied the degradation characteristics of humus-reducing bacteria in ROC treatment. The physiological and biochemical characteristics of humus-reducing bacteria were investigated, and the effects of pH values and electron donors on the reduction of humic analog, antraquinone-2, 6-disulfonate were explored to optimize the degradation. Furthermore, the O 3 -assisted UV-Fenton method was applied for the pretreatment of ROC, and the degradation of UV 254 absorbance was apparently promoted with their removal rate, reaching 84.2% after 10 days of degradation by humus-reducing bacteria.

Clinical Decision Making Following Disasters: Efficient Identification of PTSD Risk in Adolescents

PubMed Central

Danielson, Carla Kmett; Cohen, Joseph; Adams, Zachary; Youngstrom, Eric A.; Soltis, Kathryn; Amstadter, Ananda B.; Ruggiero, Kenneth J.

2016-01-01

The present study aimed to utilize a Receiver Operating Characteristic (ROC) approach in order to improve clinical decision-making for adolescents at risk for the development of psychopathology in the aftermath of a natural disaster. Specifically we assessed theoretically-driven individual, interpersonal, and event-related vulnerability factors to determine which indices were most accurate in forecasting PTSD. Furthermore, we aimed to translate these etiological findings by identifying clinical cut-off recommendations for relevant vulnerability factors. Our study consisted of structured phone-based clinical interviews with 2,000 adolescent-parent dyads living within a 5-mile radius of tornados that devastated Joplin, MO, and northern Alabama in Spring 2011. Demographics, tornado incident characteristics, prior trauma, mental health, and family support and conflict were assessed. A subset of youth completed two behavioral assessment tasks online to assess distress tolerance and risk taking behavior. ROC analyses indicated four variables that significantly improved PTSD diagnostic efficiency: Lifetime depression (AUC=.90), trauma history (AUC=.76), social support (AUC=.70), and family conflict (AUC=.72). Youth were 2–3 times more likely to have PTSD if they had elevated scores on any of these variables. Of note, event-related characteristics (e.g., property damage) were not related to PTSD diagnostic status. The present study adds to the literature by making specific recommendations for empirically-based, efficient disaster-related PTSD assessment for adolescents following a natural disaster. Implications for practice and future trauma-related developmental psychopathology research are discussed. PMID:27103002

Clinical Decision-Making Following Disasters: Efficient Identification of PTSD Risk in Adolescents.

PubMed

Danielson, Carla Kmett; Cohen, Joseph R; Adams, Zachary W; Youngstrom, Eric A; Soltis, Kathryn; Amstadter, Ananda B; Ruggiero, Kenneth J

2017-01-01

The present study aimed to utilize a Receiver Operating Characteristic (ROC) approach in order to improve clinical decision-making for adolescents at risk for the development of psychopathology in the aftermath of a natural disaster. Specifically we assessed theoretically-driven individual, interpersonal, and event-related vulnerability factors to determine which indices were most accurate in forecasting PTSD. Furthermore, we aimed to translate these etiological findings by identifying clinical cut-off recommendations for relevant vulnerability factors. Our study consisted of structured phone-based clinical interviews with 2000 adolescent-parent dyads living within a 5-mile radius of tornados that devastated Joplin, MO, and northern Alabama in Spring 2011. Demographics, tornado incident characteristics, prior trauma, mental health, and family support and conflict were assessed. A subset of youth completed two behavioral assessment tasks online to assess distress tolerance and risk-taking behavior. ROC analyses indicated four variables that significantly improved PTSD diagnostic efficiency: Lifetime depression (AUC = .90), trauma history (AUC = .76), social support (AUC = .70), and family conflict (AUC = .72). Youth were 2-3 times more likely to have PTSD if they had elevated scores on any of these variables. Of note, event-related characteristics (e.g., property damage) were not related to PTSD diagnostic status. The present study adds to the literature by making specific recommendations for empirically-based, efficient disaster-related PTSD assessment for adolescents following a natural disaster. Implications for practice and future trauma-related developmental psychopathology research are discussed.

Separating Mnemonic Process from Participant and Item Effects in the Assessment of ROC Asymmetries

ERIC Educational Resources Information Center

Pratte, Michael S.; Rouder, Jeffrey N.; Morey, Richard D.

2010-01-01

One of the most influential findings in the study of recognition memory is that receiver operating characteristic (ROC) curves are asymmetric about the negative diagonal. This result has led to the rejection of the equal-variance signal detection model of recognition memory and has provided motivation for more complex models, such as the…

How Does One Assess the Accuracy of Academic Success Predictors? ROC Analysis Applied to University Entrance Factors

ERIC Educational Resources Information Center

Vivo, Juana-Maria; Franco, Manuel

2008-01-01

This article attempts to present a novel application of a method of measuring accuracy for academic success predictors that could be used as a standard. This procedure is known as the receiver operating characteristic (ROC) curve, which comes from statistical decision techniques. The statistical prediction techniques provide predictor models and…

Age-related cutoffs for cervical movement behaviour to distinguish chronic idiopathic neck pain patients from unimpaired subjects.

PubMed

Niederer, Daniel; Vogt, Lutz; Wilke, Jan; Rickert, Marcus; Banzer, Winfried

2015-03-01

The present study aims to develop age-dependent cutoff values in a quasi-experimental, cross-sectional diagnostic test study. One hundred and twenty (120) asymptomatic subjects (n = 100, 36♀, 18 75 years, for normative values; n = 20, 23-75 years, 15♀, for selectivity analyses) and 20 patients suffering from idiopathic neck pain (selectivity analyses, 22-71 years, 15♀) were included. Subjects performed five repetitive maximal cervical flexion/extension movements in an upright sitting position. Cervical kinematic characteristics (maximal range of motion (ROM), coefficient of variation (CV) and mean conjunct movements in rotation and flexion (CM)) were calculated from raw 3D ultrasonic data. Regression analyses were conducted to reveal associations between kinematic characteristics and age and gender and thus to determine normative values for healthy subjects. Age explains 53 % of the variance in ROM (decrease 10.2° per decade), 13 % in CV (increase 0.003 per decade) and 9 % in CM (increase 0.57° per decade). Receivers operating characteristic (ROC) analyses were conducted for differences between individual values of the kinematic characteristics and normative values to optimise cutoff values for distinguishing patients from unimpaired subjects (20 patients and 20 healthy). Cutoff values distinguished asymptomatic subjects' and chronic nonspecific neck patient's movement characteristics with sufficient quality (sensitivity 70-80 %, specificity 65-70 %). By including such classifications, the present findings expand actual research stating an age-related decrease in kinematic behaviour only using categorising span widths across decades. Future study is warranted to reveal our results' potential applicability for intervention onset decision making for idiopathic neck pain patients.

Compare diagnostic tests using transformation-invariant smoothed ROC curves⋆

PubMed Central

Tang, Liansheng; Du, Pang; Wu, Chengqing

2012-01-01

Receiver operating characteristic (ROC) curve, plotting true positive rates against false positive rates as threshold varies, is an important tool for evaluating biomarkers in diagnostic medicine studies. By definition, ROC curve is monotone increasing from 0 to 1 and is invariant to any monotone transformation of test results. And it is often a curve with certain level of smoothness when test results from the diseased and non-diseased subjects follow continuous distributions. Most existing ROC curve estimation methods do not guarantee all of these properties. One of the exceptions is Du and Tang (2009) which applies certain monotone spline regression procedure to empirical ROC estimates. However, their method does not consider the inherent correlations between empirical ROC estimates. This makes the derivation of the asymptotic properties very difficult. In this paper we propose a penalized weighted least square estimation method, which incorporates the covariance between empirical ROC estimates as a weight matrix. The resulting estimator satisfies all the aforementioned properties, and we show that it is also consistent. Then a resampling approach is used to extend our method for comparisons of two or more diagnostic tests. Our simulations show a significantly improved performance over the existing method, especially for steep ROC curves. We then apply the proposed method to a cancer diagnostic study that compares several newly developed diagnostic biomarkers to a traditional one. PMID:22639484

Predictors of Long-Term School-Based Behavioral Outcomes in the Multimodal Treatment Study of Children with Attention-Deficit/Hyperactivity Disorder

PubMed Central

Reed, Margot O.; Jakubovski, Ewgeni; Johnson, Jessica A.

2017-01-01

Abstract Objective: To explore predictors of 8-year school-based behavioral outcomes in attention-deficit/hyperactivity disorder (ADHD). Methods: We examined potential baseline predictors of school-based behavioral outcomes in children who completed the 8-year follow-up in the multimodal treatment study of children with ADHD. Stepwise logistic regression and receiver operating characteristic (ROC) analysis identified baseline predictors that were associated with a higher risk of truancy, school discipline, and in-school fights. Results: Stepwise regression analysis explained between 8.1% (in-school fights) and 12.0% (school discipline) of the total variance in school-based behavioral outcomes. Logistic regression identified several baseline characteristics that were associated with school-based behavioral difficulties 8 years later, including being male (associated with truancy and school discipline), African American (school discipline, in-school fights), increased conduct disorder (CD) symptoms (truancy), decreased affection from parents (school discipline), ADHD severity (in-school fights), and study site (truancy and school discipline). ROC analyses identified the most discriminative predictors of truancy, school discipline, and in-school fights, which were Aggression and Conduct Problem Scale Total score, family income, and race, respectively. Conclusions: A modest, but nontrivial portion of school-based behavioral outcomes, was predicted by baseline childhood characteristics. Exploratory analyses identified modifiable (lack of paternal involvement, lower parental knowledge of behavioral principles, and parental use of physical punishment), somewhat modifiable (income and having comorbid CD), and nonmodifiable (African American and male) factors that were associated with school-based behavioral difficulties. Future research should confirm that the associations between earlier specific parenting behaviors and poor subsequent school-based behavioral outcomes are, indeed, causally related and independent cooccurring childhood psychopathology. Future research might target increasing paternal involvement and parental knowledge of behavioral principles and reducing use of physical punishment to improve school-based behavioral outcomes in children with ADHD. PMID:28253029

Predictors of Long-Term School-Based Behavioral Outcomes in the Multimodal Treatment Study of Children with Attention-Deficit/Hyperactivity Disorder.

PubMed

Reed, Margot O; Jakubovski, Ewgeni; Johnson, Jessica A; Bloch, Michael H

2017-05-01

To explore predictors of 8-year school-based behavioral outcomes in attention-deficit/hyperactivity disorder (ADHD). We examined potential baseline predictors of school-based behavioral outcomes in children who completed the 8-year follow-up in the multimodal treatment study of children with ADHD. Stepwise logistic regression and receiver operating characteristic (ROC) analysis identified baseline predictors that were associated with a higher risk of truancy, school discipline, and in-school fights. Stepwise regression analysis explained between 8.1% (in-school fights) and 12.0% (school discipline) of the total variance in school-based behavioral outcomes. Logistic regression identified several baseline characteristics that were associated with school-based behavioral difficulties 8 years later, including being male (associated with truancy and school discipline), African American (school discipline, in-school fights), increased conduct disorder (CD) symptoms (truancy), decreased affection from parents (school discipline), ADHD severity (in-school fights), and study site (truancy and school discipline). ROC analyses identified the most discriminative predictors of truancy, school discipline, and in-school fights, which were Aggression and Conduct Problem Scale Total score, family income, and race, respectively. A modest, but nontrivial portion of school-based behavioral outcomes, was predicted by baseline childhood characteristics. Exploratory analyses identified modifiable (lack of paternal involvement, lower parental knowledge of behavioral principles, and parental use of physical punishment), somewhat modifiable (income and having comorbid CD), and nonmodifiable (African American and male) factors that were associated with school-based behavioral difficulties. Future research should confirm that the associations between earlier specific parenting behaviors and poor subsequent school-based behavioral outcomes are, indeed, causally related and independent cooccurring childhood psychopathology. Future research might target increasing paternal involvement and parental knowledge of behavioral principles and reducing use of physical punishment to improve school-based behavioral outcomes in children with ADHD.

Sensitivity to imputation models and assumptions in receiver operating characteristic analysis with incomplete data

PubMed Central

Karakaya, Jale; Karabulut, Erdem; Yucel, Recai M.

2015-01-01

Modern statistical methods using incomplete data have been increasingly applied in a wide variety of substantive problems. Similarly, receiver operating characteristic (ROC) analysis, a method used in evaluating diagnostic tests or biomarkers in medical research, has also been increasingly popular problem in both its development and application. While missing-data methods have been applied in ROC analysis, the impact of model mis-specification and/or assumptions (e.g. missing at random) underlying the missing data has not been thoroughly studied. In this work, we study the performance of multiple imputation (MI) inference in ROC analysis. Particularly, we investigate parametric and non-parametric techniques for MI inference under common missingness mechanisms. Depending on the coherency of the imputation model with the underlying data generation mechanism, our results show that MI generally leads to well-calibrated inferences under ignorable missingness mechanisms. PMID:26379316

Combining classifiers using their receiver operating characteristics and maximum likelihood estimation.

PubMed

Haker, Steven; Wells, William M; Warfield, Simon K; Talos, Ion-Florin; Bhagwat, Jui G; Goldberg-Zimring, Daniel; Mian, Asim; Ohno-Machado, Lucila; Zou, Kelly H

2005-01-01

In any medical domain, it is common to have more than one test (classifier) to diagnose a disease. In image analysis, for example, there is often more than one reader or more than one algorithm applied to a certain data set. Combining of classifiers is often helpful, but determining the way in which classifiers should be combined is not trivial. Standard strategies are based on learning classifier combination functions from data. We describe a simple strategy to combine results from classifiers that have not been applied to a common data set, and therefore can not undergo this type of joint training. The strategy, which assumes conditional independence of classifiers, is based on the calculation of a combined Receiver Operating Characteristic (ROC) curve, using maximum likelihood analysis to determine a combination rule for each ROC operating point. We offer some insights into the use of ROC analysis in the field of medical imaging.

Combining Classifiers Using Their Receiver Operating Characteristics and Maximum Likelihood Estimation*

PubMed Central

Haker, Steven; Wells, William M.; Warfield, Simon K.; Talos, Ion-Florin; Bhagwat, Jui G.; Goldberg-Zimring, Daniel; Mian, Asim; Ohno-Machado, Lucila; Zou, Kelly H.

2010-01-01

In any medical domain, it is common to have more than one test (classifier) to diagnose a disease. In image analysis, for example, there is often more than one reader or more than one algorithm applied to a certain data set. Combining of classifiers is often helpful, but determining the way in which classifiers should be combined is not trivial. Standard strategies are based on learning classifier combination functions from data. We describe a simple strategy to combine results from classifiers that have not been applied to a common data set, and therefore can not undergo this type of joint training. The strategy, which assumes conditional independence of classifiers, is based on the calculation of a combined Receiver Operating Characteristic (ROC) curve, using maximum likelihood analysis to determine a combination rule for each ROC operating point. We offer some insights into the use of ROC analysis in the field of medical imaging. PMID:16685884

Electrodiagnosis of ulnar neuropathy at the elbow (Une): a Bayesian approach.

PubMed

Logigian, Eric L; Villanueva, Raissa; Twydell, Paul T; Myers, Bennett; Downs, Marlene; Preston, David C; Kothari, Milind J; Herrmann, David N

2014-03-01

In ulnar neuropathy at the elbow (UNE), we determined how electrodiagnostic cutoffs [across-elbow ulnar motor conduction velocity slowing (AECV-slowing), drop in across-elbow vs. forearm CV (AECV-drop)] depend on pretest probability (PreTP). Fifty clinically defined UNE patients and 50 controls underwent ulnar conduction testing recording abductor digiti minimi (ADM) and first dorsal interosseous (FDI), stimulating wrist, below-elbow, and 6-, 8-, and 10-cm more proximally. For various PreTPs of UNE, the cutoffs required to confirm UNE (defined as posttest probability = 95%) were determined with receiver operator characteristic (ROC) curves and Bayes Theorem. On ROC and Bayesian analyses, the ADM 10-cm montage was optimal. For PreTP = 0.25, the confirmatory cutoffs were >23 m/s (AECV-drop), and <38 m/s (AECV-slowing); for PreTP = 0.75, they were much less conservative: >14 m/s, and <47 m/s, respectively. (1) In UNE, electrodiagnostic cutoffs are critically dependent on PreTP; rigid cutoffs are problematic. (2) AE distances should be standardized and at least 10 cm. Copyright © 2013 Wiley Periodicals, Inc.

Specific and social fears in children and adolescents: separating normative fears from problem indicators and phobias.

PubMed

Laporte, Paola P; Pan, Pedro M; Hoffmann, Mauricio S; Wakschlag, Lauren S; Rohde, Luis A; Miguel, Euripedes C; Pine, Daniel S; Manfro, Gisele G; Salum, Giovanni A

2017-01-01

To distinguish normative fears from problematic fears and phobias. We investigated 2,512 children and adolescents from a large community school-based study, the High Risk Study for Psychiatric Disorders. Parent reports of 18 fears and psychiatric diagnosis were investigated. We used two analytical approaches: confirmatory factor analysis (CFA)/item response theory (IRT) and nonparametric receiver operating characteristic (ROC) curve. According to IRT and ROC analyses, social fears are more likely to indicate problems and phobias than specific fears. Most specific fears were normative when mild; all specific fears indicate problems when pervasive. In addition, the situational fear of toilets and people who look unusual were highly indicative of specific phobia. Among social fears, those not restricted to performance and fear of writing in front of others indicate problems when mild. All social fears indicate problems and are highly indicative of social phobia when pervasive. These preliminary findings provide guidance for clinicians and researchers to determine the boundaries that separate normative fears from problem indicators in children and adolescents, and indicate a differential severity threshold for specific and social fears.

Evaluating risk assessments using receiver operating characteristic analysis: rationale, advantages, insights, and limitations.

PubMed

Mossman, Douglas

2013-01-01

The last two decades have witnessed major changes in the way that mental health professionals assess, describe, and think about persons' risk for future violence. Psychiatrists and psychologists have gone from believing that they could not predict violence to feeling certain they can assess violence risk with well-above-chance accuracy. Receiver operating characteristic (ROC) analysis has played a central role in changing this view. This article reviews the key concepts underlying ROC methods, the meaning of the area under the ROC curve (AUC), the relationship between AUC and effect size d, and what these two indices tell us about evaluations of violence risk. The area under the ROC curve and d provide succinct but incomplete descriptions of discrimination capacity. These indices do not provide details about sensitivity-specificity trade-offs; they do not tell us how to balance false-positive and false-negative errors; and they do not determine whether a diagnostic system is accurate enough to make practically useful distinctions between violent and non-violent subject groups. Justifying choices or clinical practices requires a contextual investigation of outcomes, a process that takes us beyond simply knowing global indices of accuracy. Copyright © 2013 John Wiley & Sons, Ltd.

An extension of the receiver operating characteristic curve and AUC-optimal classification.

PubMed

Takenouchi, Takashi; Komori, Osamu; Eguchi, Shinto

2012-10-01

While most proposed methods for solving classification problems focus on minimization of the classification error rate, we are interested in the receiver operating characteristic (ROC) curve, which provides more information about classification performance than the error rate does. The area under the ROC curve (AUC) is a natural measure for overall assessment of a classifier based on the ROC curve. We discuss a class of concave functions for AUC maximization in which a boosting-type algorithm including RankBoost is considered, and the Bayesian risk consistency and the lower bound of the optimum function are discussed. A procedure derived by maximizing a specific optimum function has high robustness, based on gross error sensitivity. Additionally, we focus on the partial AUC, which is the partial area under the ROC curve. For example, in medical screening, a high true-positive rate to the fixed lower false-positive rate is preferable and thus the partial AUC corresponding to lower false-positive rates is much more important than the remaining AUC. We extend the class of concave optimum functions for partial AUC optimality with the boosting algorithm. We investigated the validity of the proposed method through several experiments with data sets in the UCI repository.

Fair lineups are better than biased lineups and showups, but not because they increase underlying discriminability.

PubMed

Smith, Andrew M; Wells, Gary L; Lindsay, R C L; Penrod, Steven D

2017-04-01

Receiver Operating Characteristic (ROC) analysis has recently come in vogue for assessing the underlying discriminability and the applied utility of lineup procedures. Two primary assumptions underlie recommendations that ROC analysis be used to assess the applied utility of lineup procedures: (a) ROC analysis of lineups measures underlying discriminability, and (b) the procedure that produces superior underlying discriminability produces superior applied utility. These same assumptions underlie a recently derived diagnostic-feature detection theory, a theory of discriminability, intended to explain recent patterns observed in ROC comparisons of lineups. We demonstrate, however, that these assumptions are incorrect when ROC analysis is applied to lineups. We also demonstrate that a structural phenomenon of lineups, differential filler siphoning, and not the psychological phenomenon of diagnostic-feature detection, explains why lineups are superior to showups and why fair lineups are superior to biased lineups. In the process of our proofs, we show that computational simulations have assumed, unrealistically, that all witnesses share exactly the same decision criteria. When criterial variance is included in computational models, differential filler siphoning emerges. The result proves dissociation between ROC curves and underlying discriminability: Higher ROC curves for lineups than for showups and for fair than for biased lineups despite no increase in underlying discriminability. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Screening for social phobia in medical in- and outpatients with the German version of the Social Phobia Inventory (SPIN).

PubMed

Sosic, Z; Gieler, U; Stangier, U

2008-06-01

To evaluate the German version of the Social Phobia Inventory (SPIN) as a screening device and to report corresponding cut-off scores for different populations. In Study 1, 2043 subjects from a representative sample completed the SPIN. Cut-off values were established on the basis of means and standard deviations. In Study 2, different aspects of validity were examined in a clinical sample comprising 164 subjects, including social phobic individuals, individuals with other anxiety disorders and depression, and non-clinical control subjects. Internal consistency was evaluated. Convergent and divergent validity were explored using several established measures. Finally, the sensitivity and specificity of the German SPIN with regard to social anxiety classification were investigated by means of receiver operating characteristics (ROC) analyses. In Study 1, mean scores and standard deviations were used to determine cut-off scores for the German SPIN. In Study 2, excellent internal consistency and good convergent and divergent validity were obtained. ROC analyses revealed that the German SPIN performed well in discriminating between social phobic individuals on the one hand and psychiatric and non-psychiatric controls on the other. A cut-off score of 25 represented the best balance between sensitivity and specificity. Comparable to the original version, the German SPIN demonstrates solid psychometric properties and shows promise as an economic, reliable, and valid screening device.

A statistical investigation of z test and ROC curve on seismo-ionospheric anomalies in TEC associated earthquakes in Taiwan during 1999-2014

NASA Astrophysics Data System (ADS)

Shih, A. L.; Liu, J. Y. G.

2015-12-01

A median-based method and a z test are employed to find characteristics of seismo-ionospheric precursor (SIP) of the total electron content (TEC) in global ionosphere map (GIM) associated with 129 M≥5.5 earthquakes in Taiwan during 1999-2014. Results show that both negative and positive anomalies in the GIM TEC with the statistical significance of the z test appear few days before the earthquakes. The receiver operating characteristic (ROC) curve is further applied to see whether the SIPs exist in Taiwan.

Variations in recollection: the effects of complexity on source recognition.

PubMed

Parks, Colleen M; Murray, Linda J; Elfman, Kane; Yonelinas, Andrew P

2011-07-01

Whether recollection is a threshold or signal detection process is highly controversial, and the controversy has centered in part on the shape of receiver operating characteristics (ROCs) and z-transformed ROCs (zROCs). U-shaped zROCs observed in tests thought to rely heavily on recollection, such as source memory tests, have provided evidence in favor of the threshold assumption, but zROCs are not always as U-shaped as threshold theory predicts. Source zROCs have been shown to become more linear when the contribution of familiarity to source discriminations is increased, and this may account for the existing results. However, another way in which source zROCs may become more linear is if the recollection threshold begins to break down and recollection becomes more graded and Gaussian. We tested the "graded recollection" account in the current study. We found that increasing stimulus complexity (i.e., changing from single words to sentences) or increasing source complexity (i.e., changing the sources from audio to videos of speakers) resulted in flatter source zROCs. In addition, conditions expected to reduce recollection (i.e., divided attention and amnesia) had comparable effects on source memory in simple and complex conditions, suggesting that differences between simple and complex conditions were due to differences in the nature of recollection, rather than differences in the utility of familiarity. The results suggest that under conditions of high complexity, recollection can appear more graded, and it can produce curved ROCs. The results have implications for measurement models and for current theories of recognition memory.

Triceps and Subscapular Skinfold Thickness Percentiles and Cut-Offs for Overweight and Obesity in a Population-Based Sample of Schoolchildren and Adolescents in Bogota, Colombia

PubMed Central

Ramírez-Vélez, Robinson; López-Cifuentes, Mario Ferney; Correa-Bautista, Jorge Enrique; González-Ruíz, Katherine; González-Jiménez, Emilio; Córdoba-Rodríguez, Diana Paola; Vivas, Andrés; Triana-Reina, Hector Reynaldo; Schmidt-RioValle, Jacqueline

2016-01-01

The assessment of skinfold thickness is an objective measure of adiposity. The aims of this study were to establish Colombian smoothed centile charts and LMS L (Box–Cox transformation), M (median), and S (coefficient of variation) tables for triceps, subscapular, and triceps + subscapular skinfolds; appropriate cut-offs were selected using receiver operating characteristic (ROC) analysis based on a population-based sample of children and adolescents in Bogotá, Colombia. A cross-sectional study was conducted in 9618 children and adolescents (55.7% girls; age range of 9–17.9 years). Triceps and subscapular skinfold measurements were obtained using standardized methods. We calculated the triceps + subscapular skinfold (T + SS) sum. Smoothed percentile curves for triceps and subscapular skinfold thickness were derived using the LMS method. ROC curve analyses were used to evaluate the optimal cut-off point of skinfold thickness for overweight and obesity, based on the International Obesity Task Force definitions. Subscapular and triceps skinfolds and T + SS were significantly higher in girls than in boys (p < 0.001). The ROC analysis showed that subscapular and triceps skinfolds and T + SS have a high discriminatory power in the identification of overweight and obesity in the sample population in this study. Our results provide sex- and age-specific normative reference standards for skinfold thickness values from a population from Bogotá, Colombia. PMID:27669294

Wavelet coherence analysis: A new approach to distinguish organic and functional tremor types.

PubMed

Kramer, G; Van der Stouwe, A M M; Maurits, N M; Tijssen, M A J; Elting, J W J

2018-01-01

To distinguish tremor subtypes using wavelet coherence analysis (WCA). WCA enables to detect variations in coherence and phase difference between two signals over time and might be especially useful in distinguishing functional from organic tremor. In this pilot study, polymyography recordings were studied retrospectively of 26 Parkinsonian (PT), 26 functional (FT), 26 essential (ET), and 20 enhanced physiological (EPT) tremor patients. Per patient one segment of 20 s in duration, in which tremor was present continuously in the same posture, was selected. We studied several coherence and phase related parameters, and analysed all possible muscle combinations of the flexor and extensor muscles of the upper and fore arm. The area under the receiver operating characteristic curve (AUC-ROC) was applied to compare WCA and standard coherence analysis to distinguish tremor subtypes. The percentage of time with significant coherence (PTSC) and the number of periods without significant coherence (NOV) proved the most discriminative parameters. FT could be discriminated from organic (PT, ET, EPT) tremor by high NOV (31.88 vs 21.58, 23.12 and 10.20 respectively) with an AUC-ROC of 0.809, while standard coherence analysis resulted in an AUC-ROC of 0.552. EMG-EMG WCA analysis might provide additional variables to distinguish functional from organic tremor. WCA might prove to be of additional value to discriminate between tremor types. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Syntheses, structural determinations of [Ru(ROCS2)2(PPh3)2](+/0) pairs, and kinetic analyses of thermal reactions involving transient trans-[Ru(iPrOCS2)2(PPh3)2] species (ROCS2(-) = ethyl- or isopropyldithiocarbonate and PPh3 = triphenylphosphine).

PubMed

Noda, Kyoko; Ohuchi, Yuko; Hashimoto, Akira; Fujiki, Masayuki; Itoh, Sumitaka; Iwatsuki, Satoshi; Noda, Toshiaki; Suzuki, Takayoshi; Kashiwabara, Kazuo; Takagi, Hideo D

2006-02-06

Controlled-potential electrochemical oxidation of cis-[Ru(ROCS2)2(PPh3)2] (R = Et, iPr) yielded corresponding Ru(III) complexes, and the crystal structures of cis-[Ru(ROCS2)2(PPh3)2] and trans-[Ru(ROCS2)2(PPh3)2](PF6) were determined. Both pairs of complexes exhibited almost identical coordination structures. The Ru-P distances in trans-[Ru(III)(ROCS2)2(PPh3)2](PF6) [2.436(3)-2.443(3) A] were significantly longer than those in cis-[Ru(II)(ROCS2)2(PPh3)2] [2.306(1)-2.315(2) A]: the smaller ionic radius of Ru(III) than that of Ru(II) stabilizes the trans conformation for the Ru(III) complex due to the steric requirement of bulky phosphine ligands while mutual trans influence by the phosphine ligands induces significant elongation of the Ru(III)-P bonds. Cyclic voltammograms of the cis-[Ru(ROCS2)2(PPh3)2] and trans-[Ru(ROCS2)2(PPh3)2]+ complexes in dichloromethane solution exhibited typical dual redox signals corresponding to the cis-[Ru(ROCS2)2(PPh3)2](+/0) (ca. +0.15 and +0.10 V vs ferrocenium/ferrocene couple for R = Et and iPr, respectively) and to trans-[Ru(ROCS2)2(PPh3)2](+/0) (-0.05 and -0.15 V vs ferrocenium/ferrocene for R = Et and iPr, respectively) couples. Analyses on the basis of the Nicholson and Shain's method revealed that the thermal disappearance rate of transient trans-[Ru(ROCS2)2(PPh3)2] was dependent on the concentration of PPh3 in the bulk: the rate constant for the intramolecular isomerization reaction of trans-[Ru(iPrOCS2)2(PPh3)2] was determined as 0.338 +/- 0.004 s(-1) at 298.3 K (deltaH* = 41.8 +/- 1.5 kJ mol(-1) and deltaS* = -114 +/- 7 J mol(-1) K(-1)), while the dissociation rate constant of coordinated PPh3 from the trans-[Ru(iPrOCS2)2(PPh3)2] species was estimated as 0.113 +/- 0.008 s(-1) at 298.3 K (deltaH* = 97.6 +/- 0.8 kJ mol(-1) and deltaS* = 64 +/- 3 J mol(-1) K(-1)), by monitoring the EC reaction (electrode reaction followed by chemical processes) at different concentrations of PPh3 in the bulk. It was found that the trans to cis isomerization reaction takes place via the partial dissociation of iPrOCS2(-) from Ru(II), contrary to the previous claim that it takes place by the twist mechanism.

Comparison of two correlated ROC curves at a given specificity or sensitivity level.

PubMed

Bantis, Leonidas E; Feng, Ziding

2016-10-30

The receiver operating characteristic (ROC) curve is the most popular statistical tool for evaluating the discriminatory capability of a given continuous biomarker. The need to compare two correlated ROC curves arises when individuals are measured with two biomarkers, which induces paired and thus correlated measurements. Many researchers have focused on comparing two correlated ROC curves in terms of the area under the curve (AUC), which summarizes the overall performance of the marker. However, particular values of specificity may be of interest. We focus on comparing two correlated ROC curves at a given specificity level. We propose parametric approaches, transformations to normality, and nonparametric kernel-based approaches. Our methods can be straightforwardly extended for inference in terms of ROC -1 (t). This is of particular interest for comparing the accuracy of two correlated biomarkers at a given sensitivity level. Extensions also involve inference for the AUC and accommodating covariates. We evaluate the robustness of our techniques through simulations, compare them with other known approaches, and present a real-data application involving prostate cancer screening. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

D-dimer, factor VIII and von Willebrand factor predict a non-dipping pattern of blood pressure in hypertensive patients.

PubMed

Agorasti, Athanasia; Trivellas, Theodoros; Mourvati, Efthimia; Papadopoulos, Vasilios; Tsatalas, Konstantinos; Vargemezis, Vasilios; Passadakis, Ploumis

2013-06-01

The aim of this study is to assess whether the haemostatic markers D-dimer, factor VIII (FVIII) and von Willebrand factor (VWF) are predictive of non-dipping status in treated hypertensive patients; so, as easy available laboratory data can predict non-dipping pattern and help with the selection of the patients whom circadian blood pressure should be re-examined. Forty treated hypertensive patients with essential hypertension were included in the study. Twenty-four-hour ambulatory blood pressure monitoring was performed in all patients. Daytime and nocturnal average systolic, diastolic and mean blood pressures were calculated. Patients were characterised as "non-dippers" on the basis of a less than 10 % decline in nocturnal blood pressure (BP); either systolic or diastolic or mean (MAP). D-dimer as marker of fibrinolytic function, FVIII activity and VWF antigen as marker of endothelial dysfunction were measured on plasma. The predictive efficiency was analysed by receiver operating characteristic (ROC) curves. Youden index was used for the estimation of the cut-off points and the associated values for sensitivity and 1-specificity. Plasma levels of D-dimer, FVIII and VWF were significantly higher in non-dippers as compared with dippers, irrespective of the classification used (BP index); all P < 0.05. The ROC curves indicated a good diagnostic efficiency for D-dimer (AUC(ROC) = 0.697, 0.715 and 0.774), FVIII (AUC(ROC) = 0.714, 0.692 and 0.755) and VWF (AUC(ROC) = 0.706, 0.740 and 0.708) in distinguishing non-dipping pattern (systolic, diastolic or mean) in the study population; all P < 0.05. Among the three haemostatic markers, D-dimer presents the most satisfactory sensitivity/1-specificity for the differentiation of non-dippers, with a cut-off point >168 ng/ml (sensitivity/1-specificity for systolic BP non-dippers of 0.789/0.381, for diastolic BP non-dippers 0.923/0.444 and for MAP non-dippers 0.875/0.375). In conclusion, D-dimer has a good predictive value for non-dipping pattern and the decision for the 24-h ambulatory blood pressure re-monitoring among dippers could rely on its values.

Machine-Learning Algorithms Predict Graft Failure After Liver Transplantation.

PubMed

Lau, Lawrence; Kankanige, Yamuna; Rubinstein, Benjamin; Jones, Robert; Christophi, Christopher; Muralidharan, Vijayaragavan; Bailey, James

2017-04-01

The ability to predict graft failure or primary nonfunction at liver transplant decision time assists utilization of scarce resource of donor livers, while ensuring that patients who are urgently requiring a liver transplant are prioritized. An index that is derived to predict graft failure using donor and recipient factors, based on local data sets, will be more beneficial in the Australian context. Liver transplant data from the Austin Hospital, Melbourne, Australia, from 2010 to 2013 has been included in the study. The top 15 donor, recipient, and transplant factors influencing the outcome of graft failure within 30 days were selected using a machine learning methodology. An algorithm predicting the outcome of interest was developed using those factors. Donor Risk Index predicts the outcome with an area under the receiver operating characteristic curve (AUC-ROC) value of 0.680 (95% confidence interval [CI], 0.669-0.690). The combination of the factors used in Donor Risk Index with the model for end-stage liver disease score yields an AUC-ROC of 0.764 (95% CI, 0.756-0.771), whereas survival outcomes after liver transplantation score obtains an AUC-ROC of 0.638 (95% CI, 0.632-0.645). The top 15 donor and recipient characteristics within random forests results in an AUC-ROC of 0.818 (95% CI, 0.812-0.824). Using donor, transplant, and recipient characteristics known at the decision time of a transplant, high accuracy in matching donors and recipients can be achieved, potentially providing assistance with clinical decision making.

Evaluating the Unequal-Variance and Dual-Process Explanations of zROC Slopes with Response Time Data and the Diffusion Model

ERIC Educational Resources Information Center

Starns, Jeffrey J.; Ratcliff, Roger; McKoon, Gail

2012-01-01

We tested two explanations for why the slope of the z-transformed receiver operating characteristic (zROC) is less than 1 in recognition memory: the unequal-variance account (target evidence is more variable than lure evidence) and the dual-process account (responding reflects both a continuous familiarity process and a threshold recollection…

Predicting BRCA1 and BRCA2 gene mutation carriers: comparison of LAMBDA, BRCAPRO, Myriad II, and modified Couch models.

PubMed

Lindor, Noralane M; Lindor, Rachel A; Apicella, Carmel; Dowty, James G; Ashley, Amanda; Hunt, Katherine; Mincey, Betty A; Wilson, Marcia; Smith, M Cathie; Hopper, John L

2007-01-01

Models have been developed to predict the probability that a person carries a detectable germline mutation in the BRCA1 or BRCA2 genes. Their relative performance in a clinical setting is unclear. To compare the performance characteristics of four BRCA1/BRCA2 gene mutation prediction models: LAMBDA, based on a checklist and scores developed from data on Ashkenazi Jewish (AJ) women; BRCAPRO, a Bayesian computer program; modified Couch tables based on regression analyses; and Myriad II tables collated by Myriad Genetics Laboratories. Family cancer history data were analyzed from 200 probands from the Mayo Clinic Familial Cancer Program, in a multispecialty tertiary care group practice. All probands had clinical testing for BRCA1 and BRCA2 mutations conducted in a single laboratory. For each model, performance was assessed by the area under the receiver operator characteristic curve (ROC) and by tests of accuracy and dispersion. Cases "missed" by one or more models (model predicted less than 10% probability of mutation when a mutation was actually found) were compared across models. All models gave similar areas under the ROC curve of 0.71 to 0.76. All models except LAMBDA substantially under-predicted the numbers of carriers. All models were too dispersed. In terms of ranking, all prediction models performed reasonably well with similar performance characteristics. Model predictions were widely discrepant for some families. Review of cancer family histories by an experienced clinician continues to be vital to ensure that critical elements are not missed and that the most appropriate risk prediction figures are provided.

Measurements of diagnostic examination performance and correlation analysis using microvascular leakage, cerebral blood volume, and blood flow derived from 3T dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging in glial tumor grading.

PubMed

Server, Andrés; Graff, Bjørn A; Orheim, Tone E Døli; Schellhorn, Till; Josefsen, Roger; Gadmar, Øystein B; Nakstad, Per H

2011-06-01

To assess the diagnostic accuracy of microvascular leakage (MVL), cerebral blood volume (CBV) and blood flow (CBF) values derived from dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging (DSC-MR imaging) for grading of cerebral glial tumors, and to estimate the correlation between vascular permeability/perfusion parameters and tumor grades. A prospective study of 79 patients with cerebral glial tumors underwent DSC-MR imaging. Normalized relative CBV (rCBV) and relative CBF (rCBF) from tumoral (rCBVt and rCBFt), peri-enhancing region (rCBVe and rCBFe), and the value in the tumor divided by the value in the peri-enhancing region (rCBVt/e and rCBFt/e), as well as MVL, expressed as the leakage coefficient K(2) were calculated. Hemodynamic variables and tumor grades were analyzed statistically and with Pearson correlations. Receiver operating characteristic (ROC) curve analyses were also performed for each of the variables. The differences in rCBVt and the maximum MVL (MVL(max)) values were statistically significant among all tumor grades. Correlation analysis using Pearson was as follows: rCBVt and tumor grade, r = 0.774; rCBFt and tumor grade, r = 0.417; MVL(max) and tumor grade, r = 0.559; MVL(max) and rCBVt, r = 0.440; MVL(max) and rCBFt, r = 0.192; and rCBVt and rCBFt, r = 0.605. According to ROC analyses for distinguishing tumor grade, rCBVt showed the largest areas under ROC curve (AUC), except for grade III from IV. Both rCBVt and MVL(max) showed good discriminative power in distinguishing all tumor grades. rCBVt correlated strongly with tumor grade; the correlation between MVL(max) and tumor grade was moderate.

Diagnostic Performance of (18)F-Fluorodeoxyglucose in 162 Small Pulmonary Nodules Incidentally Detected in Subjects Without a History of Malignancy.

PubMed

Calcagni, Maria Lucia; Taralli, Silvia; Cardillo, Giuseppe; Graziano, Paolo; Ialongo, Pasquale; Mattoli, Maria Vittoria; Di Franco, Davide; Caldarella, Carmelo; Carleo, Francesco; Indovina, Luca; Giordano, Alessandro

2016-04-01

Solitary pulmonary nodule (SPN) still represents a diagnostic challenge. The aim of our study was to evaluate the diagnostic performance of (18)F-fluorodeoxyglucose positron emission tomography-computed tomography in one of the largest samples of small SPNs, incidentally detected in subjects without a history of malignancy (nonscreening population) and undetermined at computed tomography. One-hundred and sixty-two small (>0.8 to 1.5 cm) and, for comparison, 206 large nodules (>1.5 to 3 cm) were retrospectively evaluated. Diagnostic performance of (18)F-fluorodeoxyglucose visual analysis, receiver-operating characteristic (ROC) analysis for maximum standardized uptake value (SUVmax), and Bayesian analysis were assessed using histology or radiological follow-up as a golden standard. In 162 small nodules, (18)F-fluorodeoxyglucose visual and ROC analyses (SUVmax = 1.3) provided 72.6% and 77.4% sensitivity and 88.0% and 82.0% specificity, respectively. The prevalence of malignancy was 38%; Bayesian analysis provided 78.8% positive and 16.0% negative posttest probabilities of malignancy. In 206 large nodules (18)F-fluorodeoxyglucose visual and ROC analyses (SUVmax = 1.9) provided 89.5% and 85.1% sensitivity and 70.8% and 79.2% specificity, respectively. The prevalence of malignancy was 65%; Bayesian analysis provided 85.0% positive and 21.6% negative posttest probabilities of malignancy. In both groups, malignant nodules had a significant higher SUVmax (p < 0.0001) than benign nodules. Only in the small group, malignant nodules were significantly larger (p = 0.0054) than benign ones. (18)F-fluorodeoxyglucose can be clinically relevant to rule in and rule out malignancy in undetermined small SPNs, incidentally detected in nonscreening population with intermediate pretest probability of malignancy, as well as in larger ones. Visual analysis can be considered an optimal diagnostic criterion, adequately detecting a wide range of malignant nodules with different metabolic activity. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

The Weiss Functional Impairment Rating Scale-Parent Form for assessing ADHD: evaluating diagnostic accuracy and determining optimal thresholds using ROC analysis.

PubMed

Thompson, Trevor; Lloyd, Andrew; Joseph, Alain; Weiss, Margaret

2017-07-01

The Weiss Functional Impairment Rating Scale-Parent Form (WFIRS-P) is a 50-item scale that assesses functional impairment on six clinically relevant domains typically affected in attention-deficit/hyperactivity disorder (ADHD). As functional impairment is central to ADHD, the WFIRS-P offers potential as a tool for assessing functional impairment in ADHD. These analyses were designed to examine the overall performance of WFIRS-P in differentiating ADHD and non-ADHD cases using receiver operating characteristics (ROC) analysis. This is the first attempt to empirically determine the level of functional impairment that differentiates ADHD children from normal controls. This observational study comprised 5-19-year-olds with physician-diagnosed ADHD (n = 476) and non-ADHD controls (n = 202). ROC analysis evaluated the ability of WFIRS-P to discriminate between ADHD and non-ADHD, and identified a WFIRS-P cut-off score that optimises correct classification. Data were analysed for the complete sample, for males versus females and for participants in two age groups (5-12 versus 13-19 years). Area under the curve (AUC) was 0.91 (95% confidence interval 0.88-0.93) for the overall WFIRS-P score, suggesting highly accurate classification of ADHD distinct from non-ADHD. Sensitivity (0.83) and specificity (0.85) were maximal for a mean overall WFIRS-P score of 0.65, suggesting that this is an appropriate threshold for differentiation. DeLong's test found no significant differences in AUCs for males versus females or 5-12 versus 13-19 years, suggesting that WFIRS-P is an accurate classifier of ADHD across gender and age. When assessing function, WFIRS-P appears to provide a simple and effective basis for differentiating between individuals with/without ADHD in terms of functional impairment. Disease-specific applications of QOL research.

Least squares regression methods for clustered ROC data with discrete covariates.

PubMed

Tang, Liansheng Larry; Zhang, Wei; Li, Qizhai; Ye, Xuan; Chan, Leighton

2016-07-01

The receiver operating characteristic (ROC) curve is a popular tool to evaluate and compare the accuracy of diagnostic tests to distinguish the diseased group from the nondiseased group when test results from tests are continuous or ordinal. A complicated data setting occurs when multiple tests are measured on abnormal and normal locations from the same subject and the measurements are clustered within the subject. Although least squares regression methods can be used for the estimation of ROC curve from correlated data, how to develop the least squares methods to estimate the ROC curve from the clustered data has not been studied. Also, the statistical properties of the least squares methods under the clustering setting are unknown. In this article, we develop the least squares ROC methods to allow the baseline and link functions to differ, and more importantly, to accommodate clustered data with discrete covariates. The methods can generate smooth ROC curves that satisfy the inherent continuous property of the true underlying curve. The least squares methods are shown to be more efficient than the existing nonparametric ROC methods under appropriate model assumptions in simulation studies. We apply the methods to a real example in the detection of glaucomatous deterioration. We also derive the asymptotic properties of the proposed methods. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Do We Know Who Will Drop out?: A Review of the Predictors of Dropping out of High School--Precision, Sensitivity, and Specificity

ERIC Educational Resources Information Center

Bowers, Alex J.; Sprott, Ryan; Taff, Sherry A.

2013-01-01

The purpose of this study is to review the literature on the most accurate indicators of students at risk of dropping out of high school. We used Relative Operating Characteristic (ROC) analysis to compare the sensitivity and specificity of 110 dropout flags across 36 studies. Our results indicate that 1) ROC analysis provides a means to compare…

Inverse probability weighting estimation of the volume under the ROC surface in the presence of verification bias.

PubMed

Zhang, Ying; Alonzo, Todd A

2016-11-01

In diagnostic medicine, the volume under the receiver operating characteristic (ROC) surface (VUS) is a commonly used index to quantify the ability of a continuous diagnostic test to discriminate between three disease states. In practice, verification of the true disease status may be performed only for a subset of subjects under study since the verification procedure is invasive, risky, or expensive. The selection for disease examination might depend on the results of the diagnostic test and other clinical characteristics of the patients, which in turn can cause bias in estimates of the VUS. This bias is referred to as verification bias. Existing verification bias correction in three-way ROC analysis focuses on ordinal tests. We propose verification bias-correction methods to construct ROC surface and estimate the VUS for a continuous diagnostic test, based on inverse probability weighting. By applying U-statistics theory, we develop asymptotic properties for the estimator. A Jackknife estimator of variance is also derived. Extensive simulation studies are performed to evaluate the performance of the new estimators in terms of bias correction and variance. The proposed methods are used to assess the ability of a biomarker to accurately identify stages of Alzheimer's disease. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

On the form of ROCs constructed from confidence ratings.

PubMed

Malmberg, Kenneth J

2002-03-01

A classical question for memory researchers is whether memories vary in an all-or-nothing, discrete manner (e.g., stored vs. not stored, recalled vs. not recalled), or whether they vary along a continuous dimension (e.g., strength, similarity, or familiarity). For yes-no classification tasks, continuous- and discrete-state models predict nonlinear and linear receiver operating characteristics (ROCs), respectively (D. M. Green & J. A. Swets, 1966; N. A. Macmillan & C. D. Creelman, 1991). Recently, several authors have assumed that these predictions are generalizable to confidence ratings tasks (J. Qin, C. L. Raye, M. K. Johnson, & K. J. Mitchell, 2001; S. D. Slotnick, S. A. Klein, C. S. Dodson, & A. P. Shimamura, 2000, and A. P. Yonelinas, 1999). This assumption is shown to be unwarranted by showing that discrete-state ratings models predict both linear and nonlinear ROCs. The critical factor determining the form of the discrete-state ROC is the response strategy adopted by the classifier.

Comparison of two correlated ROC curves at a given specificity or sensitivity level

PubMed Central

Bantis, Leonidas E.; Feng, Ziding

2017-01-01

The receiver operating characteristic (ROC) curve is the most popular statistical tool for evaluating the discriminatory capability of a given continuous biomarker. The need to compare two correlated ROC curves arises when individuals are measured with two biomarkers, which induces paired and thus correlated measurements. Many researchers have focused on comparing two correlated ROC curves in terms of the area under the curve (AUC), which summarizes the overall performance of the marker. However, particular values of specificity may be of interest. We focus on comparing two correlated ROC curves at a given specificity level. We propose parametric approaches, transformations to normality, and nonparametric kernel-based approaches. Our methods can be straightforwardly extended for inference in terms of ROC−1(t). This is of particular interest for comparing the accuracy of two correlated biomarkers at a given sensitivity level. Extensions also involve inference for the AUC and accommodating covariates. We evaluate the robustness of our techniques through simulations, compare to other known approaches and present a real data application involving prostate cancer screening. PMID:27324068

Exploration of Analysis Methods for Diagnostic Imaging Tests: Problems with ROC AUC and Confidence Scores in CT Colonography

PubMed Central

Mallett, Susan; Halligan, Steve; Collins, Gary S.; Altman, Doug G.

2014-01-01

Background Different methods of evaluating diagnostic performance when comparing diagnostic tests may lead to different results. We compared two such approaches, sensitivity and specificity with area under the Receiver Operating Characteristic Curve (ROC AUC) for the evaluation of CT colonography for the detection of polyps, either with or without computer assisted detection. Methods In a multireader multicase study of 10 readers and 107 cases we compared sensitivity and specificity, using radiological reporting of the presence or absence of polyps, to ROC AUC calculated from confidence scores concerning the presence of polyps. Both methods were assessed against a reference standard. Here we focus on five readers, selected to illustrate issues in design and analysis. We compared diagnostic measures within readers, showing that differences in results are due to statistical methods. Results Reader performance varied widely depending on whether sensitivity and specificity or ROC AUC was used. There were problems using confidence scores; in assigning scores to all cases; in use of zero scores when no polyps were identified; the bimodal non-normal distribution of scores; fitting ROC curves due to extrapolation beyond the study data; and the undue influence of a few false positive results. Variation due to use of different ROC methods exceeded differences between test results for ROC AUC. Conclusions The confidence scores recorded in our study violated many assumptions of ROC AUC methods, rendering these methods inappropriate. The problems we identified will apply to other detection studies using confidence scores. We found sensitivity and specificity were a more reliable and clinically appropriate method to compare diagnostic tests. PMID:25353643

Exploration of analysis methods for diagnostic imaging tests: problems with ROC AUC and confidence scores in CT colonography.

PubMed

Mallett, Susan; Halligan, Steve; Collins, Gary S; Altman, Doug G

2014-01-01

Different methods of evaluating diagnostic performance when comparing diagnostic tests may lead to different results. We compared two such approaches, sensitivity and specificity with area under the Receiver Operating Characteristic Curve (ROC AUC) for the evaluation of CT colonography for the detection of polyps, either with or without computer assisted detection. In a multireader multicase study of 10 readers and 107 cases we compared sensitivity and specificity, using radiological reporting of the presence or absence of polyps, to ROC AUC calculated from confidence scores concerning the presence of polyps. Both methods were assessed against a reference standard. Here we focus on five readers, selected to illustrate issues in design and analysis. We compared diagnostic measures within readers, showing that differences in results are due to statistical methods. Reader performance varied widely depending on whether sensitivity and specificity or ROC AUC was used. There were problems using confidence scores; in assigning scores to all cases; in use of zero scores when no polyps were identified; the bimodal non-normal distribution of scores; fitting ROC curves due to extrapolation beyond the study data; and the undue influence of a few false positive results. Variation due to use of different ROC methods exceeded differences between test results for ROC AUC. The confidence scores recorded in our study violated many assumptions of ROC AUC methods, rendering these methods inappropriate. The problems we identified will apply to other detection studies using confidence scores. We found sensitivity and specificity were a more reliable and clinically appropriate method to compare diagnostic tests.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry.

PubMed

Silva, Fabrício R; Vidotti, Vanessa G; Cremasco, Fernanda; Dias, Marcelo; Gomi, Edson S; Costa, Vital P

2013-01-01

To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

ROC-king onwards: intraepithelial lymphocyte counts, distribution & role in coeliac disease mucosal interpretation.

PubMed

Rostami, Kamran; Marsh, Michael N; Johnson, Matt W; Mohaghegh, Hamid; Heal, Calvin; Holmes, Geoffrey; Ensari, Arzu; Aldulaimi, David; Bancel, Brigitte; Bassotti, Gabrio; Bateman, Adrian; Becheanu, Gabriel; Bozzola, Anna; Carroccio, Antonio; Catassi, Carlo; Ciacci, Carolina; Ciobanu, Alexandra; Danciu, Mihai; Derakhshan, Mohammad H; Elli, Luca; Ferrero, Stefano; Fiorentino, Michelangelo; Fiorino, Marilena; Ganji, Azita; Ghaffarzadehgan, Kamran; Going, James J; Ishaq, Sauid; Mandolesi, Alessandra; Mathews, Sherly; Maxim, Roxana; Mulder, Chris J; Neefjes-Borst, Andra; Robert, Marie; Russo, Ilaria; Rostami-Nejad, Mohammad; Sidoni, Angelo; Sotoudeh, Masoud; Villanacci, Vincenzo; Volta, Umberto; Zali, Mohammad R; Srivastava, Amitabh

2017-12-01

Counting intraepithelial lymphocytes (IEL) is central to the histological diagnosis of coeliac disease (CD), but no definitive 'normal' IEL range has ever been published. In this multicentre study, receiver operating characteristic (ROC) curve analysis was used to determine the optimal cut-off between normal and CD (Marsh III lesion) duodenal mucosa, based on IEL counts on >400 mucosal biopsy specimens. The study was designed at the International Meeting on Digestive Pathology, Bucharest 2015. Investigators from 19 centres, eight countries of three continents, recruited 198 patients with Marsh III histology and 203 controls and used one agreed protocol to count IEL/100 enterocytes in well-oriented duodenal biopsies. Demographic and serological data were also collected. The mean ages of CD and control groups were 45.5 (neonate to 82) and 38.3 (2-88) years. Mean IEL count was 54±18/100 enterocytes in CD and 13±8 in normal controls (p=0.0001). ROC analysis indicated an optimal cut-off point of 25 IEL/100 enterocytes, with 99% sensitivity, 92% specificity and 99.5% area under the curve. Other cut-offs between 20 and 40 IEL were less discriminatory. Additionally, there was a sufficiently high number of biopsies to explore IEL counts across the subclassification of the Marsh III lesion. Our ROC curve analyses demonstrate that for Marsh III lesions, a cut-off of 25 IEL/100 enterocytes optimises discrimination between normal control and CD biopsies. No differences in IEL counts were found between Marsh III a, b and c lesions. There was an indication of a continuously graded dose-response by IEL to environmental (gluten) antigenic influence. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

"Textural analysis of multiparametric MRI detects transition zone prostate cancer".

PubMed

Sidhu, Harbir S; Benigno, Salvatore; Ganeshan, Balaji; Dikaios, Nikos; Johnston, Edward W; Allen, Clare; Kirkham, Alex; Groves, Ashley M; Ahmed, Hashim U; Emberton, Mark; Taylor, Stuart A; Halligan, Steve; Punwani, Shonit

2017-06-01

To evaluate multiparametric-MRI (mpMRI) derived histogram textural-analysis parameters for detection of transition zone (TZ) prostatic tumour. Sixty-seven consecutive men with suspected prostate cancer underwent 1.5T mpMRI prior to template-mapping-biopsy (TPM). Twenty-six men had 'significant' TZ tumour. Two radiologists in consensus matched TPM to the single axial slice best depicting tumour, or largest TZ diameter for those with benign histology, to define single-slice whole TZ-regions-of-interest (ROIs). Textural-parameter differences between single-slice whole TZ-ROI containing significant tumour versus benign/insignificant tumour were analysed using Mann Whitney U test. Diagnostic accuracy was assessed by receiver operating characteristic area under curve (ROC-AUC) analysis cross-validated with leave-one-out (LOO) analysis. ADC kurtosis was significantly lower (p < 0.001) in TZ containing significant tumour with ROC-AUC 0.80 (LOO-AUC 0.78); the difference became non-significant following exclusion of significant tumour from single-slice whole TZ-ROI (p = 0.23). T1-entropy was significantly lower (p = 0.004) in TZ containing significant tumour with ROC-AUC 0.70 (LOO-AUC 0.66) and was unaffected by excluding significant tumour from TZ-ROI (p = 0.004). Combining these parameters yielded ROC-AUC 0.86 (LOO-AUC 0.83). Textural features of the whole prostate TZ can discriminate significant prostatic cancer through reduced kurtosis of the ADC-histogram where significant tumour is included in TZ-ROI and reduced T1 entropy independent of tumour inclusion. • MR textural features of prostate transition zone may discriminate significant prostatic cancer. • Transition zone (TZ) containing significant tumour demonstrates a less peaked ADC histogram. • TZ containing significant tumour reveals higher post-contrast T1-weighted homogeneity. • The utility of MR texture analysis in prostate cancer merits further investigation.

An enhancement of ROC curves made them clinically relevant for diagnostic-test comparison and optimal-threshold determination.

PubMed

Subtil, Fabien; Rabilloud, Muriel

2015-07-01

The receiver operating characteristic curves (ROC curves) are often used to compare continuous diagnostic tests or determine the optimal threshold of a test; however, they do not consider the costs of misclassifications or the disease prevalence. The ROC graph was extended to allow for these aspects. Two new lines are added to the ROC graph: a sensitivity line and a specificity line. Their slopes depend on the disease prevalence and on the ratio of the net benefit of treating a diseased subject to the net cost of treating a nondiseased one. First, these lines help researchers determine the range of specificities within which test comparisons of partial areas under the curves is clinically relevant. Second, the ROC curve point the farthest from the specificity line is shown to be the optimal threshold in terms of expected utility. This method was applied: (1) to determine the optimal threshold of ratio specific immunoglobulin G (IgG)/total IgG for the diagnosis of congenital toxoplasmosis and (2) to select, among two markers, the most accurate for the diagnosis of left ventricular hypertrophy in hypertensive subjects. The two additional lines transform the statistically valid ROC graph into a clinically relevant tool for test selection and threshold determination. Copyright © 2015 Elsevier Inc. All rights reserved.

The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets.

PubMed

Saito, Takaya; Rehmsmeier, Marc

2015-01-01

Binary classifiers are routinely evaluated with performance measures such as sensitivity and specificity, and performance is frequently illustrated with Receiver Operating Characteristics (ROC) plots. Alternative measures such as positive predictive value (PPV) and the associated Precision/Recall (PRC) plots are used less frequently. Many bioinformatics studies develop and evaluate classifiers that are to be applied to strongly imbalanced datasets in which the number of negatives outweighs the number of positives significantly. While ROC plots are visually appealing and provide an overview of a classifier's performance across a wide range of specificities, one can ask whether ROC plots could be misleading when applied in imbalanced classification scenarios. We show here that the visual interpretability of ROC plots in the context of imbalanced datasets can be deceptive with respect to conclusions about the reliability of classification performance, owing to an intuitive but wrong interpretation of specificity. PRC plots, on the other hand, can provide the viewer with an accurate prediction of future classification performance due to the fact that they evaluate the fraction of true positives among positive predictions. Our findings have potential implications for the interpretation of a large number of studies that use ROC plots on imbalanced datasets.

Effect of coagulation on treatment of municipal wastewater reverse osmosis concentrate by UVC/H2O2.

PubMed

Umar, Muhammad; Roddick, Felicity; Fan, Linhua

2014-02-15

Disposal of reverse osmosis concentrate (ROC) is a growing concern due to potential health and ecological risks. Alum coagulation was investigated as pre-treatment for the UVC/H2O2 treatment of two high salinity ROC samples (ROC A and B) of comparable organic and inorganic content. Coagulation removed a greater fraction of the organic content for ROC B (29%) than ROC A (16%) which correlated well with the reductions of colour and A254. Although the total reductions after 60 min UVC/H2O2 treatment with and without coagulation were comparable, large differences in the trends of reduction were observed which were attributed to the different nature of the organic content (humic-like) of the samples as indicated by the LC-OCD analyses and different initial (5% and 16%) biodegradability. Coagulation and UVC/H2O2 treatment preferentially removed humic-like compounds which resulted in low reaction rates after UVC/H2O2 treatment of the coagulated samples. The improvement in biodegradability was greater (2-3-fold) during UVC/H2O2 treatment of the pre-treated samples than without pre-treatment. The target DOC residual (≤ 15 mg/L) was obtained after 30 and 20 min irradiation of pre-treated ROC A and ROC B with downstream biological treatment, corresponding to reductions of 55% and 62%, respectively. Copyright © 2013 Elsevier B.V. All rights reserved.

Associations Among Indicators of Depression in Medicaid-Eligible Community-Dwelling Older Adults

PubMed Central

Byma, Elizabeth A.

2013-01-01

Purpose: The purpose of this research was to examine associations among 2 separate Minimum Data Set-Home Care (MDS-HC) depression measures (the Depression Rating Scale [DRS] and medical diagnosis of depression) with billed antidepressant medications in Medicaid paid claim files. Design and Methods: The sample for this cross-sectional research included 3,041 Medicaid-eligible older adult participants in a Home and Community Based Waiver Program and used data from the MDS-HC, Version 1 and Medicaid Paid Claim Files. Sensitivity and specificity analyses, receiver operating characteristic (ROC) curve analysis, and t tests were utilized. Results: DRS scoring indicated that 15.4% of participants had behaviors indicative of depression, whereas 42% had a medical diagnosis of depression noted in the MDS-HC. Of those with a medical diagnosis of depression, 51% had a prescribed antidepressant medication. ROC analysis suggested that the DRS was a poor distinguisher of participants with and without a medical diagnosis of depression or prescribed antidepressant medications. Implications: Approximately half of Medicaid-eligible older adults medically diagnosed with depression were treated pharmacologically. Longitudinal research is recommended to assess responsiveness of the DRS over time to pharmacological and psychotherapeutic interventions for depression. PMID:23103523

Identification of Serum Periostin as a Potential Diagnostic and Prognostic Marker for Colorectal Cancer.

PubMed

Dong, Dong; Zhang, Lufang; Jia, Li; Ji, Wei; Wang, Zhiyong; Ren, Li; Niu, Ruifang; Zhou, Yunli

2018-06-01

Periostin (POSTN) plays an important role in numerous cancers, especially in gastrointestinal malignancy. The objective of this study was to investigate the diagnostic and prognostic role of serum POSTN in colorectal cancer (CRC). Serum periostin, together with CEA, CA19.9, CA72.4, and CA242 levels were measured in samples from 108 patients with CRC and 56 healthy controls, and their correlation with clinical characteristics was further analyzed. Receiver operating curves (ROC), Kaplan-Meier curves, and log-rank analyses were used to evaluate diagnostic and prognostic significance. Serum POSTN levels were significantly higher in patients with CRC compared with healthy controls (p < 0.0001) and associated with clinical stages (p < 0.001). ROC analysis revealed that POSTN was a biomarker comparable to CEA, CA19.9, and CA72.4 to distinguish all CRC from healthy controls (AUC = 0.75). Moreover, POSTN retained its diagnostic ability for CEA-negative (AUC = 0.69) and CA19.9-negative CRC patients (AUC = 0.71). Survival analysis revealed that patients with lower serum POSTN had longer overall survival than those with high serum POSTN (p = 0.0146). Serum POSTN might be a novel diagnostic and prognostic biomarker for patients with CRC.

Association between promoter methylation of MLH1 and MSH2 and reactive oxygen species in oligozoospermic men-A pilot study.

PubMed

Gunes, S; Agarwal, A; Henkel, R; Mahmutoglu, A M; Sharma, R; Esteves, S C; Aljowair, A; Emirzeoglu, D; Alkhani, A; Pelegrini, L; Joumah, A; Sabanegh, E

2018-04-01

MLH1 and MSH2 are important genes for DNA mismatch repair and crossing over during meiosis and are implicated in male infertility. Therefore, the methylation patterns of the DNA mismatch repair genes MLH1 and MSH2 in oligozoospermic males were investigated. Ten oligozoospermic patients and 29 normozoospermic donors were analysed. Methylation profiles of the MLH1 and MSH2 promotors were analysed. In addition, sperm motility and seminal reactive oxygen species (ROS) were recorded. Receiver operating characteristic (ROC) analysis was conducted to determine the accuracy of the DNA methylation status of MLH1 and MSH2 to distinguish between oligozoospermic and normozoospermic men. In oligozoospermic men, MLH1 was significantly (p = .0013) more methylated compared to normozoospermic men. Additionally, there was a significant positive association (r = .384; p = .0159) between seminal ROS levels and MLH1 methylation. Contrary, no association between MSH2 methylation and oligozoospermia was found. ROC curve analysis for methylation status of MLH1 was significant (p = .0275) with an area under the curve of 61.1%, a sensitivity of 22.2% and a specificity of 100.0%. This pilot study indicates oligozoospermic patients have more methylation of MLH1 than normozoospermic patients. Whether hypermethylation of the MLH1 promoter plays a role in repairing relevant mismatches of sperm DNA strands in idiopathic oligozoospermia warrants further investigation. © 2017 Blackwell Verlag GmbH.

The significance of eosinophils in predicting the severity of acute ischemic stroke

PubMed Central

Wang, Jun; Ma, Li; Lin, Tao; Li, Shi-Jing; Chen, Lei-Lei; Wang, De-Zhao

2017-01-01

Background Previous studies have shown that tumor-associated tissue eosinophilia have a role in various types of solid tumors. However, the relationship between eosinophil and acute ischemic stroke (AIS) is unclear. We aimed to investigate the diagnostic significance of eosinophil in AIS patients. Methods This study included 300 AIS patients without hypereosinophilic syndrome (HES). The hematologic indices were collected from each patient, including white blood count, eosinophil count, eosinophil percentage, neutrophil count, red blood count, and platelet. The severity of AIS was estimated by national institute of health stroke scale (NIHSS). Logistic regression analyses were performed to confirm the biomarkers for NIHSS and in-hospital non-death among the cases. Moreover, receiver-operating characteristics (ROC) analyses were used to investigate the clinical performances of eosinophils and NIHSS in prediction of non-death. Results The admission NIHSS (P<0.001) and BMI (P<0.001) were predictors to the non-death of the patients. There was a significant correlation between eosinophil counts or eosinophil percentage and NIHSS score (r= -0.451, P < 0.001; r= -0.617, P<0.001, Spearson Correlation). ROC analysis showed that eosinophil counts and eosinophil percentage could predict non-death of the patients in-hospital, with the areas under the curves (AUC) of 0.791 and 0.867, respectively. Conclusions Our study revealed a relationship between eosinophil and NIHSS score in the patients with AIS. Eosinophils might have certain value for predicting the severity of AIS. PMID:29262636

VIEWDEX: an efficient and easy-to-use software for observer performance studies.

PubMed

Håkansson, Markus; Svensson, Sune; Zachrisson, Sara; Svalkvist, Angelica; Båth, Magnus; Månsson, Lars Gunnar

2010-01-01

The development of investigation techniques, image processing, workstation monitors, analysing tools etc. within the field of radiology is vast, and the need for efficient tools in the evaluation and optimisation process of image and investigation quality is important. ViewDEX (Viewer for Digital Evaluation of X-ray images) is an image viewer and task manager suitable for research and optimisation tasks in medical imaging. ViewDEX is DICOM compatible and the features of the interface (tasks, image handling and functionality) are general and flexible. The configuration of a study and output (for example, answers given) can be edited in any text editor. ViewDEX is developed in Java and can run from any disc area connected to a computer. It is free to use for non-commercial purposes and can be downloaded from http://www.vgregion.se/sas/viewdex. In the present work, an evaluation of the efficiency of ViewDEX for receiver operating characteristic (ROC) studies, free-response ROC (FROC) studies and visual grading (VG) studies was conducted. For VG studies, the total scoring rate was dependent on the number of criteria per case. A scoring rate of approximately 150 cases h(-1) can be expected for a typical VG study using single images and five anatomical criteria. For ROC and FROC studies using clinical images, the scoring rate was approximately 100 cases h(-1) using single images and approximately 25 cases h(-1) using image stacks ( approximately 50 images case(-1)). In conclusion, ViewDEX is an efficient and easy-to-use software for observer performance studies.

First trimester prediction of maternal glycemic status.

PubMed

Gabbay-Benziv, Rinat; Doyle, Lauren E; Blitzer, Miriam; Baschat, Ahmet A

2015-05-01

To predict gestational diabetes mellitus (GDM) or normoglycemic status using first trimester maternal characteristics. We used data from a prospective cohort study. First trimester maternal characteristics were compared between women with and without GDM. Association of these variables with sugar values at glucose challenge test (GCT) and subsequent GDM was tested to identify key parameters. A predictive algorithm for GDM was developed and receiver operating characteristics (ROC) statistics was used to derive the optimal risk score. We defined normoglycemic state, when GCT and all four sugar values at oral glucose tolerance test, whenever obtained, were normal. Using same statistical approach, we developed an algorithm to predict the normoglycemic state. Maternal age, race, prior GDM, first trimester BMI, and systolic blood pressure (SBP) were all significantly associated with GDM. Age, BMI, and SBP were also associated with GCT values. The logistic regression analysis constructed equation and the calculated risk score yielded sensitivity, specificity, positive predictive value, and negative predictive value of 85%, 62%, 13.8%, and 98.3% for a cut-off value of 0.042, respectively (ROC-AUC - area under the curve 0.819, CI - confidence interval 0.769-0.868). The model constructed for normoglycemia prediction demonstrated lower performance (ROC-AUC 0.707, CI 0.668-0.746). GDM prediction can be achieved during the first trimester encounter by integration of maternal characteristics and basic measurements while normoglycemic status prediction is less effective.

Cross-cultural difference and validation of the Chinese version of Montreal Cognitive Assessment in older adults residing in Eastern China: preliminary findings.

PubMed

Hu, Jian-bo; Zhou, Wei-hua; Hu, Shao-hua; Huang, Man-li; Wei, Ning; Qi, Hong-li; Huang, Jin-wen; Xu, Yi

2013-01-01

To evaluate the psychometric properties of the Chinese Montreal Cognitive Assessment (MoCA-C) and assess cross-cultural differences in a community-based cohort residing in the Eastern China. The study included 72 patients with Alzheimer's disease (AD), 84 patients with mild cognitive impairment (MCI) and 146 cognitively normal controls. Sensitivities and specificities were calculated using the recommended cut-off scores. Receiver operator characteristic (ROC) curve analyses were performed to determine optimal sensitivity and specificity. Criterion validity, inter-rater, test-retest reliability and internal consistencies of the MoCA-C were examined, and clinical observations made. The influence of age, education level and gender on MoCA score was examined. Using the recommended cut-off score of 26, the area under the ROC (AUC) for predicting MCI groups using the MoCA-C was 0.930 (95%CI: 0.894; 0.965). The MoCA-C demonstrated 92% sensitivity and 85% specificity in screening for MCI. Cultural differences from the original MoCA affected the test response rate. The MoCA-C appears to have utility as a cognitive screen for early detection of AD and for MCI and warrants further investigation regarding its applicability in primary care settings in elderly Chinese people. It will be necessary to revise the contents of the questionnaire to account for by local characteristics. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Discovery of potent NEK2 inhibitors as potential anticancer agents using structure-based exploration of NEK2 pharmacophoric space coupled with QSAR analyses.

PubMed

Khanfar, Mohammad A; Banat, Fahmy; Alabed, Shada; Alqtaishat, Saja

2017-02-01

High expression of Nek2 has been detected in several types of cancer and it represents a novel target for human cancer. In the current study, structure-based pharmacophore modeling combined with multiple linear regression (MLR)-based QSAR analyses was applied to disclose the structural requirements for NEK2 inhibition. Generated pharmacophoric models were initially validated with receiver operating characteristic (ROC) curve, and optimum models were subsequently implemented in QSAR modeling with other physiochemical descriptors. QSAR-selected models were implied as 3D search filters to mine the National Cancer Institute (NCI) database for novel NEK2 inhibitors, whereas the associated QSAR model prioritized the bioactivities of captured hits for in vitro evaluation. Experimental validation identified several potent NEK2 inhibitors of novel structural scaffolds. The most potent captured hit exhibited an [Formula: see text] value of 237 nM.

The performance characteristics of prostate-specific antigen and prostate-specific antigen density in Chinese men.

PubMed

Teoh, Jeremy Yc; Yuen, Steffi Kk; Tsu, James Hl; Wong, Charles Kw; Ho, Brian Sh; Ng, Ada Tl; Ma, Wai-Kit; Ho, Kwan-Lun; Yiu, Ming-Kwong

2017-01-01

We investigated the performance characteristics of prostate-specific antigen (PSA) and PSA density (PSAD) in Chinese men. All Chinese men who underwent transrectal ultrasound-guided prostate biopsy (TRUS-PB) from year 2000 to 2013 were included. The receiver operating characteristic (ROC) curves for both PSA and PSAD were analyzed. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) at different cut-off levels were calculated. A total of 2606 Chinese men were included. For the ROC, the area under curve was 0.770 for PSA (P < 0.001) and 0.823 for PSAD (P < 0.001). PSA of 4.5 ng ml-1 had sensitivity of 94.4%, specificity of 14.1%, PPV of 29.5%, and NPV of 86.9%; PSAD of 0.12 ng ml-1 cc-1 had sensitivity of 94.5%, specificity of 26.6%, PPV of 32.8%, and NPV of 92.7%. On multivariate logistic regression analyses, PSA cut-off at 4.5 ng ml-1 (OR 1.61, 95% CI 1.05-2.45, P= 0.029) and PSAD cut-off at 0.12 ng ml-1 cc-1 (OR 6.22, 95% CI 4.20-9.22, P< 0.001) were significant predictors for prostate cancer detection on TRUS-PB. In conclusion, the performances of PSA and PSAD at different cut-off levels in Chinese men were very different from those in Caucasians. PSA of 4.5 ng ml-1 and PSAD of 0.12 ng ml-1 cc-1 had near 95% sensitivity and were significant predictors of prostate cancer detection in Chinese men.

Comparison of FIB-4 index and aspartate aminotransferase to platelet ratio index on carcinogenesis in chronic hepatitis B treated with entecavir

PubMed Central

Nishikawa, Hiroki; Nishijima, Norihiro; Enomoto, Hirayuki; Sakamoto, Azusa; Nasu, Akihiro; Komekado, Hideyuki; Nishimura, Takashi; Kita, Ryuichi; Kimura, Toru; Iijima, Hiroko; Nishiguchi, Shuhei; Osaki, Yukio

2017-01-01

Aims: We sought to compare the effects of FIB-4 index and aspartate aminotransferase to platelet ratio index (APRI) on hepatocellular carcinoma (HCC) incidence in chronic hepatitis B (CHB) patients undergoing entecavir (ETV) therapy. Patient and methods: A total of 338 nucleosides analogue therapy naïve CHB patients initially treated with ETV were analyzed. The optimal cutoff points in each continuous variable were determined by receiver operating curve (ROC) analysis. The effects of FIB-4 index and APRI on HCC incidence were compared using time-dependent ROC analysis and factors linked to HCC incidence were also examined using univariate and multivariate analyses. Results: There were 215 males and 123 females with the median age of 52 years and the median baseline HBV-DNA level of 6.6 log copies/ml. The median follow-up interval after the initiation of ETV therapy was 4.99 years. During the follow-up period, 33 patients (9.8%) developed HCC. The 3-, 5- 7-year cumulative HCC incidence rates in all cases were 4.4%, 9.2% and 13.5%, respectively. In the multivariate analysis, FIB-4 index revealed to be an independent predictor associated with HCC incidence, while APRI was not. In the time-dependent ROC analyses for all cases and for all subgroups analyses stratified by viral status or cirrhosis status, all area under the ROCs in each time point (2-, 3-, 4-, 5-, 6-, and 7-year) of FIB-4 index were higher than those of APRI. Conclusion: FIB-4 index rather than APRI can be a useful predictor associated with HCC development for CHB patients undergoing ETV therapy. PMID:28243319

Comparison of FIB-4 index and aspartate aminotransferase to platelet ratio index on carcinogenesis in chronic hepatitis B treated with entecavir.

PubMed

Nishikawa, Hiroki; Nishijima, Norihiro; Enomoto, Hirayuki; Sakamoto, Azusa; Nasu, Akihiro; Komekado, Hideyuki; Nishimura, Takashi; Kita, Ryuichi; Kimura, Toru; Iijima, Hiroko; Nishiguchi, Shuhei; Osaki, Yukio

2017-01-01

We sought to compare the effects of FIB-4 index and aspartate aminotransferase to platelet ratio index (APRI) on hepatocellular carcinoma (HCC) incidence in chronic hepatitis B (CHB) patients undergoing entecavir (ETV) therapy. A total of 338 nucleosides analogue therapy naïve CHB patients initially treated with ETV were analyzed. The optimal cutoff points in each continuous variable were determined by receiver operating curve (ROC) analysis. The effects of FIB-4 index and APRI on HCC incidence were compared using time-dependent ROC analysis and factors linked to HCC incidence were also examined using univariate and multivariate analyses. There were 215 males and 123 females with the median age of 52 years and the median baseline HBV-DNA level of 6.6 log copies/ml. The median follow-up interval after the initiation of ETV therapy was 4.99 years. During the follow-up period, 33 patients (9.8%) developed HCC. The 3-, 5- 7-year cumulative HCC incidence rates in all cases were 4.4%, 9.2% and 13.5%, respectively. In the multivariate analysis, FIB-4 index revealed to be an independent predictor associated with HCC incidence, while APRI was not. In the time-dependent ROC analyses for all cases and for all subgroups analyses stratified by viral status or cirrhosis status, all area under the ROCs in each time point (2-, 3-, 4-, 5-, 6-, and 7-year) of FIB-4 index were higher than those of APRI. FIB-4 index rather than APRI can be a useful predictor associated with HCC development for CHB patients undergoing ETV therapy.

[Comparative Study of Patient Identifications for Conventional and Portable Chest Radiographs Utilizing ROC Analysis].

PubMed

Kawashima, Hiroki; Hayashi, Norio; Ohno, Naoki; Matsuura, Yukihiro; Sanada, Shigeru

2015-08-01

To evaluate the patient identification ability of radiographers, previous and current chest radiographs were assessed with observer study utilizing a receiver operating characteristics (ROCs) analysis. This study included portable and conventional chest radiographs from 43 same and 43 different patients. The dataset used in this study was divided into the three following groups: (1) a pair of portable radiographs, (2) a pair of conventional radiographs, and (3) a combination of each type of radiograph. Seven observers participated in this ROC study, which aimed to identify same or different patients, using these datasets. ROC analysis was conducted to calculate the average area under ROC curve obtained by each observer (AUCave), and a statistical test was performed using the multi-reader multi-case method. Comparable results were obtained with pairs of portable (AUCave: 0.949) and conventional radiographs (AUCave: 0.951). In a comparison between the same modality, there were no significant differences. In contrast, the ability to identify patients by comparing a portable and conventional radiograph (AUCave: 0.873) was lower than with the matching datasets (p=0.002 and p=0.004, respectively). In conclusion, the use of different imaging modalities reduces radiographers' ability to identify their patients.

Predictive value of pulse pressure variation for fluid responsiveness in septic patients using lung-protective ventilation strategies.

PubMed

Freitas, F G R; Bafi, A T; Nascente, A P M; Assunção, M; Mazza, B; Azevedo, L C P; Machado, F R

2013-03-01

The applicability of pulse pressure variation (ΔPP) to predict fluid responsiveness using lung-protective ventilation strategies is uncertain in clinical practice. We designed this study to evaluate the accuracy of this parameter in predicting the fluid responsiveness of septic patients ventilated with low tidal volumes (TV) (6 ml kg(-1)). Forty patients after the resuscitation phase of severe sepsis and septic shock who were mechanically ventilated with 6 ml kg(-1) were included. The ΔPP was obtained automatically at baseline and after a standardized fluid challenge (7 ml kg(-1)). Patients whose cardiac output increased by more than 15% were considered fluid responders. The predictive values of ΔPP and static variables [right atrial pressure (RAP) and pulmonary artery occlusion pressure (PAOP)] were evaluated through a receiver operating characteristic (ROC) curve analysis. Thirty-four patients had characteristics consistent with acute lung injury or acute respiratory distress syndrome and were ventilated with high levels of PEEP [median (inter-quartile range) 10.0 (10.0-13.5)]. Nineteen patients were considered fluid responders. The RAP and PAOP significantly increased, and ΔPP significantly decreased after volume expansion. The ΔPP performance [ROC curve area: 0.91 (0.82-1.0)] was better than that of the RAP [ROC curve area: 0.73 (0.59-0.90)] and pulmonary artery occlusion pressure [ROC curve area: 0.58 (0.40-0.76)]. The ROC curve analysis revealed that the best cut-off for ΔPP was 6.5%, with a sensitivity of 0.89, specificity of 0.90, positive predictive value of 0.89, and negative predictive value of 0.90. Automatized ΔPP accurately predicted fluid responsiveness in septic patients ventilated with low TV.

Fluorescence spectroscopy for diagnosis of squamous intraepithelial lesions of the cervix.

PubMed

Mitchell, M F; Cantor, S B; Ramanujam, N; Tortolero-Luna, G; Richards-Kortum, R

1999-03-01

To calculate receiver operating characteristic (ROC) curves for fluorescence spectroscopy in order to measure its performance in the diagnosis of squamous intraepithelial lesions (SILs) and to compare these curves with those for other diagnostic methods: colposcopy, cervicography, speculoscopy, Papanicolaou smear screening, and human papillomavirus (HPV) testing. Data from our previous clinical study were used to calculate ROC curves for fluorescence spectroscopy. Curves for other techniques were calculated from other investigators' reports. To identify these, a MEDLINE search for articles published from 1966 to 1996 was carried out, using the search terms "colposcopy," "cervicoscopy," "cervicography," "speculoscopy," "Papanicolaou smear," "HPV testing," "fluorescence spectroscopy," and "polar probe" in conjunction with the terms "diagnosis," "positive predictive value," "negative predictive value," and "receiver operating characteristic curve." We found 270 articles, from which articles were selected if they reported results of studies involving high-disease-prevalence populations, reported findings of studies in which colposcopically directed biopsy was the criterion standard, and included sufficient data for recalculation of the reported sensitivities and specificities. We calculated ROC curves for fluorescence spectroscopy using Bayesian and neural net algorithms. A meta-analytic approach was used to calculate ROC curves for the other techniques. Areas under the curves were calculated. Fluorescence spectroscopy using the neural net algorithm had the highest area under the ROC curve, followed by fluorescence spectroscopy using the Bayesian algorithm, followed by colposcopy, the standard diagnostic technique. Cervicography, Papanicolaou smear screening, and HPV testing performed comparably with each other but not as well as fluorescence spectroscopy and colposcopy. Fluorescence spectroscopy performs better than colposcopy and other techniques in the diagnosis of SILs. Because it also permits real-time diagnosis and has the potential of being used by inexperienced health care personnel, this technology holds bright promise.

Description of the ambulance services participating in the Aus-ROC Australian and New Zealand out-of-hospital cardiac arrest Epistry.

PubMed

Beck, Ben; Bray, Janet E; Smith, Karen; Walker, Tony; Grantham, Hugh; Hein, Cindy; Thorrowgood, Melanie; Smith, Anthony; Inoue, Madoka; Smith, Tony; Dicker, Bridget; Swain, Andy; Bosley, Emma; Pemberton, Katherine; McKay, Michael; Johnston-Leek, Malcolm; Cameron, Peter; Perkins, Gavin D; Finn, Judith

2016-12-01

The present study aimed to describe and examine similarities and differences in the current service provision and resuscitation protocols of the ambulance services participating in the Aus-ROC Australian and New Zealand out-of-hospital cardiac arrest (OHCA) Epistry. Understanding these similarities and differences is important in identifying ambulance service factors that might explain regional variation in survival of OHCA in the Aus-ROC Epistry. A structured questionnaire was completed by each of the ambulance services participating in the Aus-ROC Epistry. These ambulance services were SA Ambulance Service, Ambulance Victoria, St John Ambulance Western Australia, Queensland Ambulance Service, St John Ambulance NT, St John New Zealand and Wellington Free Ambulance. The survey aimed to describe ambulance service and dispatch characteristics, resuscitation protocols and details of cardiac arrest registries. We observed similarities between services with respect to the treatment of OHCA and dispatch systems. Differences between services were observed in the serviced population; the proportion of paramedics with basic life support, advanced life support or intensive care training skills; the number of OHCA cases attended; guidelines related to withholding or terminating resuscitation attempts; and the variables that might be used to define 'attempted resuscitation'. All seven participating ambulance services were noted to have existing OHCA registries. There is marked variation between ambulance services currently participating in the Aus-ROC Australian and New Zealand OHCA Epistry with respect to workforce characteristics and key variable definitions. This variation between ambulance services might account for a proportion of the regional variation in survival of OHCA. © 2016 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

Meta-analysis of Diagnostic Accuracy and ROC Curves with Covariate Adjusted Semiparametric Mixtures.

PubMed

Doebler, Philipp; Holling, Heinz

2015-12-01

Many screening tests dichotomize a measurement to classify subjects. Typically a cut-off value is chosen in a way that allows identification of an acceptable number of cases relative to a reference procedure, but does not produce too many false positives at the same time. Thus for the same sample many pairs of sensitivities and false positive rates result as the cut-off is varied. The curve of these points is called the receiver operating characteristic (ROC) curve. One goal of diagnostic meta-analysis is to integrate ROC curves and arrive at a summary ROC (SROC) curve. Holling, Böhning, and Böhning (Psychometrika 77:106-126, 2012a) demonstrated that finite semiparametric mixtures can describe the heterogeneity in a sample of Lehmann ROC curves well; this approach leads to clusters of SROC curves of a particular shape. We extend this work with the help of the [Formula: see text] transformation, a flexible family of transformations for proportions. A collection of SROC curves is constructed that approximately contains the Lehmann family but in addition allows the modeling of shapes beyond the Lehmann ROC curves. We introduce two rationales for determining the shape from the data. Using the fact that each curve corresponds to a natural univariate measure of diagnostic accuracy, we show how covariate adjusted mixtures lead to a meta-regression on SROC curves. Three worked examples illustrate the method.

Statistical evidences of seismo-ionospheric precursors applying receiver operating characteristic (ROC) curve on the GPS total electron content in China

NASA Astrophysics Data System (ADS)

Chen, Yuh-Ing; Huang, Chi-Shen; Liu, Jann-Yenq

2015-12-01

Evidence of the seismo-ionospheric precursor (SIP) is reported by statistically investigating the relationship between the total electron content (TEC) in global ionosphere map (GIM) and 56 M ⩾ 6.0 earthquakes during 1998-2013 in China. A median-based method together with the z test is employed to examine the TEC variations 30 days before and after the earthquake. It is found that the TEC significantly decreases 0600-1000 LT 1-6 days before the earthquake, and anomalously increases in 3 time periods of 1300-1700 LT 12-15 days; 0000-0500 LT 15-17 days; and 0500-0900 LT 22-28 days before the earthquake. The receiver operating characteristic (ROC) curve is then used to evaluate the efficiency of TEC for predicting M ⩾ 6.0 earthquakes in China during a specified time period. Statistical results suggest that the SIP is the significant TEC reduction in the morning period of 0600-1000 LT. The SIP is further confirmed since the area under the ROC curve is positively associated with the earthquake magnitude.

The role of stenosis ratio as a predictor of surgical satisfaction in patients with lumbar spinal canal stenosis: a receiver-operator characteristic (ROC) curve analysis.

PubMed

Mohammadi, Hassanreza R; Azimi, Parisa; Benzel, Edward C; Shahzadi, Sohrab; Azhari, Shirzad

2016-09-01

The aim of this study was to elucidate independent factors that predict surgical satisfaction in lumbar spinal canal stenosis (LSCS) patients. Patients who underwent surgery were grouped based on the age, gender, duration of symptoms, walking distance, Neurogenic Claudication Outcome Score (NCOS) and the stenosis ratio (SR) described by Lurencin. We recorded on 2-year patient satisfaction using standardized measure. The optimal cut-off points in SR, NCOS and walking distance for predicting surgical satisfaction were estimated from sensitivity and specificity calculations and receiver operator characteristic (ROC) curves. One hundred fifty consecutive patients (51 male, 99 female, mean age 62.4±10.9 years) were followed up for 34±13 months (range 24-49). One, two, three and four level stenosis was observed in 10.7%, 39.3%, 36.0 % and 14.0% of patients, respectively. Post-surgical satisfaction was 78.5% at the 2 years follow up. In ROC curve analysis, the asymptotic significance is less than 0.05 in SR and the optimal cut-off value of SR to predict worsening surgical satisfaction was measured as more than 0.52, with 85.4% sensitivity and 77.4% specificity (AUC 0.798, 95% CI 0.73-0.90; P<0.01). The present study suggests that the SR, with a cut-off set a 0.52 cross-sectional area, may be superior to walking distance and NCOS in patients with degenerative lumbar stenosis considered for surgical treatment. Using a ROC curve analysis, a radiological feature, the SR, demonstrated superiority in predicting patient satisfaction, compared to functional and clinical characteristics such as walking distance and NCOS.

Identification of arginine and its "Downstream" molecules as potential markers of breast cancer.

PubMed

Hu, Lu; Gao, Yu; Cao, Yunfeng; Zhang, Yinxu; Xu, Minghao; Wang, Yuanyuan; Jing, Yu; Guo, Shengnan; Jing, Fangyu; Hu, Xiaodan; Zhu, Zhitu

2016-10-01

Breast cancer (BC) is the most commonly diagnosed cancer in women worldwide. Arginine is a semiessential amino acid in humans and is essential for several biological pathways in malignant and normal cells, such as ornithine and N1, N12-diacetylspermine (DiAcSpm). This study aimed to determine the role of arginine and these downstream molecules in BC. Plasma arginine, ornithine, and arginine-to-ornithine ratio (AOR) were analysed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Urine samples were measured by the colloid gold aggregation to test determination of urinary diAcSpm. A principal component analysis was performed to evaluate the results observed between breast tumor and control characteristics. Differences in individual metabolite concentrations between BC patients and controls were tested by receiver operating characteristics (ROC) analyses. Student's t tests were used to detect the differences between two groups of normally distributed variables, and Wilcoxon sign rank tests were performed for asymmetrically distributed variables. As we analyzed, BC patients had lower plasma arginine and arginine/ornithine level, and higher plasma ornithine and urinary DiAcSpm concentrations as compared with control patients (P = 0.028, 0.020, 0.002, and 0.011, respectively). And the ROC curve was drawn and the area under the curve of the metabolites was calculated to be 0.659 (P = 0.028), 0.645 (P = 0.045), 0.7233 (P = 0.002), 0.683 (P = 0.011), respectively. In addition, our analysis showed that arginine concentrations and AOR had a positive correlation with ER status, while ornithine had a negative correlation with T stage (P = 0.042, 0.023, respectively).In conclusion, arginine and these downstream molecules were biomarkers for BC. More studies are needed to highlight the theoretical strengths. © 2016 IUBMB Life, 68(10):817-822, 2016. © 2016 International Union of Biochemistry and Molecular Biology.

A Prospective Cohort Study of Absconsion Incidents in Forensic Psychiatric Settings: Can We Identify Those at High-Risk?

PubMed Central

Cullen, Alexis E.; Jewell, Amelia; Tully, John; Coghlan, Suzanne; Dean, Kimberlie; Fahy, Tom

2015-01-01

Background Incidents of absconsion in forensic psychiatric units can have potentially serious consequences, yet surprisingly little is known about the characteristics of patients who abscond from these settings. The few previous studies conducted to date have employed retrospective designs, and no attempt has been made to develop an empirically-derived risk assessment scale. In this prospective study, we aimed to identify predictors of absconsion over a two-year period and investigate the feasibility of developing a brief risk assessment scale. Methods The study examined a representative sample of 135 patients treated in forensic medium- and low-secure wards. At baseline, demographic, clinical, treatment-related, and offending/behavioural factors were ascertained from electronic medical records and the treating teams. Incidents of absconsion (i.e., failure to return from leave, incidents of escape, and absconding whilst on escorted leave) were assessed at a two-year follow-up. Logistic regression analyses were used to determine the strongest predictors of absconsion which were then weighted according to their ability to discriminate absconders and non-absconders. The predictive utility of a brief risk assessment scale based on these weighted items was evaluated using receiver operator characteristics (ROC). Results During the two-year follow-up period, 27 patients (20%) absconded, accounting for 56 separate incidents. In multivariate analyses, four factors relating to offending and behaviour emerged as the strongest predictors of absconsion: history of sexual offending, previous absconsion, recent inpatient verbal aggression, and recent inpatient substance use. The weighted risk scale derived from these factors had moderate-to-good predictive accuracy (ROC area under the curve: 0.80; sensitivity: 067; specificity: 0.71), a high negative predictive value (0.91), but a low positive predictive value (0.34). Conclusion Potentially-targetable recent behaviours, such as inpatient verbal aggression and substance use, are strong predictors of absconsion in forensic settings; the absence of these factors may enable clinical teams to identify unnecessarily restricted low-risk individuals. PMID:26401653

Wavelet and receiver operating characteristic analysis of heart rate variability

NASA Astrophysics Data System (ADS)

McCaffery, G.; Griffith, T. M.; Naka, K.; Frennaux, M. P.; Matthai, C. C.

2002-02-01

Multiresolution wavelet analysis has been used to study the heart rate variability in two classes of patients with different pathological conditions. The scale dependent measure of Thurner et al. was found to be statistically significant in discriminating patients suffering from hypercardiomyopathy from a control set of normal subjects. We have performed Receiver Operating Characteristc (ROC) analysis and found the ROC area to be a useful measure by which to label the significance of the discrimination, as well as to describe the severity of heart dysfunction.

Prognostic subgroups for remission and response in the Coordinated Anxiety Learning and Management (CALM) trial.

PubMed

Kelly, J MacLaren; Jakubovski, Ewgeni; Bloch, Michael H

2015-03-01

Most patients with anxiety disorders receive treatment in primary care settings. Limited moderator data are available to inform clinicians of likely prognostic outcomes for individual patients. We identify baseline characteristics associated with outcome in adults seeking treatment for anxiety disorders. We conducted an exploratory moderator analysis from the Coordinated Anxiety Learning and Management (CALM) trial. In the CALM trial, 1,004 adults who met DSM-IV criteria for generalized anxiety disorder (GAD), panic disorder, social anxiety disorder, and/or posttraumatic stress disorder (PTSD) were randomized to usual care (UC) or a collaborative care intervention (ITV) of cognitive-behavioral therapy and/or pharmacotherapy between June 2006 and April 2008. Logistic regression was used to examine baseline characteristics associated with remission and response overall and by treatment condition. Receiver operating curve (ROC) analyses identified subgroups associated with similar likelihood of response and remission of global anxiety symptoms. Remission was defined as score < 6 on the 12-item Brief Symptom Inventory (BSI-12) anxiety and somatization subscales. Response was defined as at least 50% reduction on BSI-12, or meeting remission criteria. Randomization to ITV over UC was often the strongest predictor of outcome. Several baseline patient characteristics were associated with poor treatment outcome including comorbid depression, increased severity of underlying anxiety disorder(s) (P < .001), low socioeconomic status (perceived [P < .001] and actual [P < .05]), and limited social support (P < .001). Patient characteristics associated with particular benefit from ITV were being female (P < .05), increased depression (P < .01)/GAD severity (P < .05), and low socioeconomic status (P < .05). ROC analysis demonstrated prognostic subgroups with large differences in response likelihood. Further research should focus on the effectiveness of implementing the ITV intervention of CALM in community treatment centers where patients typically are of low socioeconomic status and may particularly benefit from ITV. ClinicalTrials.gov identifier: NCT00347269. © Copyright 2015 Physicians Postgraduate Press, Inc.

Bayesian semiparametric estimation of covariate-dependent ROC curves

PubMed Central

Rodríguez, Abel; Martínez, Julissa C.

2014-01-01

Receiver operating characteristic (ROC) curves are widely used to measure the discriminating power of medical tests and other classification procedures. In many practical applications, the performance of these procedures can depend on covariates such as age, naturally leading to a collection of curves associated with different covariate levels. This paper develops a Bayesian heteroscedastic semiparametric regression model and applies it to the estimation of covariate-dependent ROC curves. More specifically, our approach uses Gaussian process priors to model the conditional mean and conditional variance of the biomarker of interest for each of the populations under study. The model is illustrated through an application to the evaluation of prostate-specific antigen for the diagnosis of prostate cancer, which contrasts the performance of our model against alternative models. PMID:24174579

Recent developments in imaging system assessment methodology, FROC analysis and the search model.

PubMed

Chakraborty, Dev P

2011-08-21

A frequent problem in imaging is assessing whether a new imaging system is an improvement over an existing standard. Observer performance methods, in particular the receiver operating characteristic (ROC) paradigm, are widely used in this context. In ROC analysis lesion location information is not used and consequently scoring ambiguities can arise in tasks, such as nodule detection, involving finding localized lesions. This paper reviews progress in the free-response ROC (FROC) paradigm in which the observer marks and rates suspicious regions and the location information is used to determine whether lesions were correctly localized. Reviewed are FROC data analysis, a search-model for simulating FROC data, predictions of the model and a method for estimating the parameters. The search model parameters are physically meaningful quantities that can guide system optimization.

Diagnostic performance of traditional hepatobiliary biomarkers of drug-induced liver injury in the rat.

PubMed

Ennulat, Daniela; Magid-Slav, Michal; Rehm, Sabine; Tatsuoka, Kay S

2010-08-01

Nonclinical studies provide the opportunity to anchor biochemical with morphologic findings; however, liver injury is often complex and heterogeneous, confounding the ability to relate biochemical changes with specific patterns of injury. The aim of the current study was to compare diagnostic performance of hepatobiliary markers for specific manifestations of drug-induced liver injury in rat using data collected in a recent hepatic toxicogenomics initiative in which rats (n = 3205) were given 182 different treatments for 4 or 14 days. Diagnostic accuracy of alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (Tbili), serum bile acids (SBA), alkaline phosphatase (ALP), gamma glutamyl transferase (GGT), total cholesterol (Chol), and triglycerides (Trig) was evaluated for specific types of liver histopathology by Receiver Operating Characteristic (ROC) analysis. To assess the relationship between biochemical and morphologic changes in the absence of hepatocellular necrosis, a second ROC analysis was performed on a subset of rats (n = 2504) given treatments (n = 152) that did not cause hepatocellular necrosis. In the initial analysis, ALT, AST, Tbili, and SBA had the greatest diagnostic utility for manifestations of hepatocellular necrosis and biliary injury, with comparable magnitude of area under the ROC curve and serum hepatobiliary marker changes for both. In the absence of hepatocellular necrosis, ALT increases were observed with biochemical or morphologic evidence of cholestasis. In both analyses, diagnostic utility of ALP and GGT for biliary injury was limited; however, ALP had modest diagnostic value for peroxisome proliferation, and ALT, AST, and total Chol had moderate diagnostic utility for phospholipidosis. None of the eight markers evaluated had diagnostic value for manifestations of hypertrophy, cytoplasmic rarefaction, inflammation, or lipidosis.

Strain ratio ultrasound elastography increases the accuracy of colour-Doppler ultrasound in the evaluation of Thy-3 nodules. A bi-centre university experience.

PubMed

Cantisani, Vito; Maceroni, Piero; D'Andrea, Vito; Patrizi, Gregorio; Di Segni, Mattia; De Vito, Corrado; Grazhdani, Hektor; Isidori, Andrea M; Giannetta, Elisa; Redler, Adriano; Frattaroli, Fabrizio; Giacomelli, Laura; Di Rocco, Giorgio; Catalano, Carlo; D'Ambrosio, Ferdinando

2016-05-01

To assess whether ultrasound elastography (USE) with strain ratio increases diagnostic accuracy of Doppler ultrasound in further characterisation of cytologically Thy3 thyroid nodules. In two different university diagnostic centres, 315 patients with indeterminate cytology (Thy3) in thyroid nodules aspirates were prospectively evaluated with Doppler ultrasound and strain ratio USE before surgery. Ultrasonographic features were analysed separately and together as ultrasound score, to assess sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Receiver operating characteristic (ROC) curves to identify optimal cut-off value of the strain ratio were also provided. Diagnosis on a surgical specimen was considered the standard of reference. Higher strain ratio values were found in malignant nodules, with an optimum strain ratio cut-off of 2.09 at ROC analysis. USE with strain ratio showed 90.6% sensitivity, 93% specificity, 82.8% PPV, 96.4% NPV, while US score yielded a sensitivity of 52.9%, specificity of 84.3%, PPV 55.6% and NPV 82.9%. The diagnostic gain with strain ratio was statistically significant as proved by ROC areas, which was 0.9182 for strain ratio and 0.6864 for US score. USE with strain ratio should be considered a useful additional tool to colour-Doppler US, since it improves characterisation of thyroid nodules with indeterminate cytology. • Strain ratio measurements improve differentiation of thyroid nodules with indeterminate cytology • Elastography with strain ratio is more reliable than ultrasound features and ultrasound score • Strain ratio may help to better select patients with Thy 3 nodules candidate for surgery.

[Correlation between percentage of body fat and simple anthropometric parameters in children aged 6-9 years in Guangzhou].

PubMed

Yan, H C; Hao, Y T; Guo, Y F; Wei, Y H; Zhang, J H; Huang, G P; Mao, L M; Zhang, Z Q

2017-11-10

Objective: To evaluate the accuracy of simple anthropometric parameters in diagnosing obesity in children in Guangzhou. Methods: A cross-sectional study, including 465 children aged 6-9 years, was carried out in Guangzhou. Their body height and weight, waist circumference (WC) and hip circumference were measured according to standard procedure. Body mass index (BMI), waist to hip ratio (WHR) and waist-to-height ratio (WHtR) were calculated. Body fat percentage (BF%) was determined by dual-energy X-ray absorptiometry. Multiple regression analysis was applied to evaluate the correlations between age-adjusted physical indicators and BF%, after the adjustment for age. Obesity was defined by BF%. Receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic accuracy of the indicators for childhood obesity. Area under-ROC curves (AUCs) were calculated and the best cut-off point that maximizing 'sensitivity + specificity-1' was determined. Results: BMI showed the strongest association with BF% through multiple regression analysis. For 'per-standard deviation increase' of BMI, BF% increased by 5.3% ( t =23.1, P <0.01) in boys and 4.6% ( t =17.5, P <0.01) in girls, respectively. The ROC curve analysis indicated that BMI exhibited the largest AUC in both boys (AUC=0.908) and girls (AUC=0.895). The sensitivity was 80.8% in boys and 81.8% in girls, and the specificity was 88.2% in boys and 87.1% in girls. Both the AUCs for WHtR and WC were less than 0.8 in boys and girls. WHR had the smallest AUCs (<0.8) in both boys and girls. Conclusion: BMI appeared to be a good predicator for BF% in children aged 6-9 years in Guangzhou.

Controlling Nutritional Status (CONUT) score is a prognostic marker for gastric cancer patients after curative resection.

PubMed

Kuroda, Daisuke; Sawayama, Hiroshi; Kurashige, Junji; Iwatsuki, Masaaki; Eto, Tsugio; Tokunaga, Ryuma; Kitano, Yuki; Yamamura, Kensuke; Ouchi, Mayuko; Nakamura, Kenichi; Baba, Yoshifumi; Sakamoto, Yasuo; Yamashita, Yoichi; Yoshida, Naoya; Chikamoto, Akira; Baba, Hideo

2018-03-01

Controlling Nutritional Status (CONUT), as calculated from serum albumin, total cholesterol concentration, and total lymphocyte count, was previously shown to be useful for nutritional assessment. The current study investigated the potential use of CONUT as a prognostic marker in gastric cancer patients after curative resection. Preoperative CONUT was retrospectively calculated in 416 gastric cancer patients who underwent curative resection at Kumamoto University Hospital from 2005 to 2014. The patients were divided into two groups: CONUT-high (≥4) and CONUT-low (≤3), according to time-dependent receiver operating characteristic (ROC) analysis. The associations of CONUT with clinicopathological factors and survival were evaluated. CONUT-high patients were significantly older (p < 0.001) and had a lower body mass index (p = 0.019), deeper invasion (p < 0.001), higher serum carcinoembryonic antigen (p = 0.037), and higher serum carbohydrate antigen 19-9 (p = 0.007) compared with CONUT-low patients. CONUT-high patients had significantly poorer overall survival (OS) compared with CONUT-low patients according to univariate and multivariate analyses (hazard ratio: 5.09, 95% confidence interval 3.12-8.30, p < 0.001). In time-dependent ROC analysis, CONUT had a higher area under the ROC curve (AUC) for the prediction of 5-year OS than the neutrophil lymphocyte ratio, the Modified Glasgow Prognostic Score, or pStage. When the time-dependent AUC curve was used to predict OS, CONUT tended to maintain its predictive accuracy for long-term survival at a significantly higher level for an extended period after surgery when compared with the other markers tested. CONUT is useful for not only estimating nutritional status but also for predicting long-term OS in gastric cancer patients after curative resection.

Utility of Shear Wave Elastography for Differentiating Biliary Atresia From Infantile Hepatitis Syndrome.

PubMed

Wang, Xiaoman; Qian, Linxue; Jia, Liqun; Bellah, Richard; Wang, Ning; Xin, Yue; Liu, Qinglin

2016-07-01

The purpose of this study was to investigate the potential utility of shear wave elastography (SWE) for diagnosis of biliary atresia and for differentiating biliary atresia from infantile hepatitis syndrome by measuring liver stiffness. Thirty-eight patients with biliary atresia and 17 patients with infantile hepatitis syndrome were included, along with 31 healthy control infants. The 3 groups underwent SWE. The hepatic tissue of each patient with biliary atresia had been surgically biopsied. Statistical analyses for mean values of the 3 groups were performed. Optimum cutoff values using SWE for differentiation between the biliary atresia and control groups were calculated by a receiver operating characteristic (ROC) analysis. The mean SWE values ± SD for the 3 groups were as follows: biliary atresia group, 20.46 ± 10.19 kPa; infantile hepatitis syndrome group, 6.29 ± 0.99 kPa; and control group, 6.41 ± 1.08 kPa. The mean SWE value for the biliary atresia group was higher than the values for the control and infantile hepatitis syndrome groups (P < .01). The mean SWE values between the control and infantile hepatitis syndrome groups were not statistically different. The ROC analysis showed a cutoff value of 8.68 kPa for differentiation between the biliary atresia and control groups. The area under the ROC curve was 0.997, with sensitivity of 97.4%, specificity of 100%, a positive predictive value of 100%, and a negative predictive value of 96.9%. Correlation analysis suggested a positive correlation between SWE values and age for patients with biliary atresia, with a Pearson correlation coefficient of 0.463 (P < .05). The significant increase in liver SWE values in neonates and infants with biliary atresia supports their application for differentiating biliary atresia from infantile hepatitis syndrome.

Differentiating benign from malignant mediastinal lymph nodes visible at EBUS using grey-scale textural analysis.

PubMed

Edey, Anthony J; Pollentine, Adrian; Doody, Claire; Medford, Andrew R L

2015-04-01

Recent data suggest that grey-scale textural analysis on endobronchial ultrasound (EBUS) imaging can differentiate benign from malignant lymphadenopathy. The objective of studies was to evaluate grey-scale textural analysis and examine its clinical utility. Images from 135 consecutive clinically indicated EBUS procedures were evaluated retrospectively using MATLAB software (MathWorks, Natick, MA, USA). Manual node mapping was performed to obtain a region of interest and grey-scale textural features (range of pixel values and entropy) were analysed. The initial analysis involved 94 subjects and receiver operating characteristic (ROC) curves were generated. The ROC thresholds were then applied on a second cohort (41 subjects) to validate the earlier findings. A total of 371 images were evaluated. There was no difference in proportions of malignant disease (56% vs 53%, P = 0.66) in the prediction (group 1) and validation (group 2) sets. There was no difference in range of pixel values in group 1 but entropy was significantly higher in the malignant group (5.95 vs 5.77, P = 0.03). Higher entropy was seen in adenocarcinoma versus lymphoma (6.00 vs 5.50, P < 0.05). An ROC curve for entropy gave an area under the curve of 0.58 with 51% sensitivity and 71% specificity for entropy greater than 5.94 for malignancy. In group 2, the entropy threshold phenotyped only 47% of benign cases and 20% of malignant cases correctly. These findings suggest that use of EBUS grey-scale textural analysis for differentiation of malignant from benign lymphadenopathy may not be accurate. Further studies are required. © 2015 Asian Pacific Society of Respirology.

Risk Factors Predicting Infectious Lactational Mastitis: Decision Tree Approach versus Logistic Regression Analysis.

PubMed

Fernández, Leónides; Mediano, Pilar; García, Ricardo; Rodríguez, Juan M; Marín, María

2016-09-01

Objectives Lactational mastitis frequently leads to a premature abandonment of breastfeeding; its development has been associated with several risk factors. This study aims to use a decision tree (DT) approach to establish the main risk factors involved in mastitis and to compare its performance for predicting this condition with a stepwise logistic regression (LR) model. Methods Data from 368 cases (breastfeeding women with mastitis) and 148 controls were collected by a questionnaire about risk factors related to medical history of mother and infant, pregnancy, delivery, postpartum, and breastfeeding practices. The performance of the DT and LR analyses was compared using the area under the receiver operating characteristic (ROC) curve. Sensitivity, specificity and accuracy of both models were calculated. Results Cracked nipples, antibiotics and antifungal drugs during breastfeeding, infant age, breast pumps, familial history of mastitis and throat infection were significant risk factors associated with mastitis in both analyses. Bottle-feeding and milk supply were related to mastitis for certain subgroups in the DT model. The areas under the ROC curves were similar for LR and DT models (0.870 and 0.835, respectively). The LR model had better classification accuracy and sensitivity than the DT model, but the last one presented better specificity at the optimal threshold of each curve. Conclusions The DT and LR models constitute useful and complementary analytical tools to assess the risk of lactational infectious mastitis. The DT approach identifies high-risk subpopulations that need specific mastitis prevention programs and, therefore, it could be used to make the most of public health resources.

Analysis of Exhaled Breath Volatile Organic Compounds in Inflammatory Bowel Disease: A Pilot Study.

PubMed

Hicks, Lucy C; Huang, Juzheng; Kumar, Sacheen; Powles, Sam T; Orchard, Timothy R; Hanna, George B; Williams, Horace R T

2015-09-01

Distinguishing between the inflammatory bowel diseases [IBD], Crohn's disease [CD] and ulcerative colitis [UC], is important for determining management and prognosis. Selected ion flow tube mass spectrometry [SIFT-MS] may be used to analyse volatile organic compounds [VOCs] in exhaled breath: these may be altered in disease states, and distinguishing breath VOC profiles can be identified. The aim of this pilot study was to identify, quantify, and analyse VOCs present in the breath of IBD patients and controls, potentially providing insights into disease pathogenesis and complementing current diagnostic algorithms. SIFT-MS breath profiling of 56 individuals [20 UC, 18 CD, and 18 healthy controls] was undertaken. Multivariate analysis included principal components analysis and partial least squares discriminant analysis with orthogonal signal correction [OSC-PLS-DA]. Receiver operating characteristic [ROC] analysis was performed for each comparative analysis using statistically significant VOCs. OSC-PLS-DA modelling was able to distinguish both CD and UC from healthy controls and from one other with good sensitivity and specificity. ROC analysis using combinations of statistically significant VOCs [dimethyl sulphide, hydrogen sulphide, hydrogen cyanide, ammonia, butanal, and nonanal] gave integrated areas under the curve of 0.86 [CD vs healthy controls], 0.74 [UC vs healthy controls], and 0.83 [CD vs UC]. Exhaled breath VOC profiling was able to distinguish IBD patients from controls, as well as to separate UC from CD, using both multivariate and univariate statistical techniques. Copyright © 2015 European Crohn’s and Colitis Organisation (ECCO). Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

The prognostic value of preoperative inflammation-based prognostic scores and nutritional status for overall survival in resected patients with nonmetastatic Siewert type II/III adenocarcinoma of esophagogastric junction.

PubMed

Zhang, Lixiang; Su, Yezhou; Chen, Zhangming; Wei, Zhijian; Han, Wenxiu; Xu, Aman

2017-07-01

Immune and nutritional status of patients have been reported to predict postoperative complications, recurrence, and prognosis of patients with cancer. Therefore, this retrospective study aimed to explore the prognostic value of preoperative inflammation-based prognostic scores [neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR)] and nutritional status [prognostic nutritional index (PNI), body mass index (BMI), hemoglobin, albumin, and prealbumin] for overall survival (OS) in adenocarcinoma of esophagogastric junction (AEG) patients. A total of 355 patients diagnosed with Siewert type II/III AEG and underwent surgery between October 2010 and December 2011 were followed up until October 2016. Receiver operating characteristic (ROC) curve analysis was used to determine the cutoff values of NLR, PLR, and PNI. Kaplan-Meier curves and Cox regression analyses were used to calculate the OS characteristics. The ideal cutoff values for predicting OS were 3.5 for NLR, 171 for PLR, and 51.3 for PNI according to the ROC curve. The patients with hemoglobin <120 g/L (P = .001), prealbumin <180 mg/L (P = .000), PNI <51.3 (P = .010), NLR >3.5 (P = .000), PLR >171 (P = .006), and low BMI group (P = .000) had shorter OS. And multivariate survival analysis using the Cox proportional hazards model showed that the tumor-node-metastasis stage, BMI, NLR, and prealbumin levels were independent risk factors for the OS. Our study demonstrated that preoperative prealbumin, BMI, and NLR were independent prognostic factors of AEG patients.

Bayesian modeling and inference for diagnostic accuracy and probability of disease based on multiple diagnostic biomarkers with and without a perfect reference standard.

PubMed

Jafarzadeh, S Reza; Johnson, Wesley O; Gardner, Ian A

2016-03-15

The area under the receiver operating characteristic (ROC) curve (AUC) is used as a performance metric for quantitative tests. Although multiple biomarkers may be available for diagnostic or screening purposes, diagnostic accuracy is often assessed individually rather than in combination. In this paper, we consider the interesting problem of combining multiple biomarkers for use in a single diagnostic criterion with the goal of improving the diagnostic accuracy above that of an individual biomarker. The diagnostic criterion created from multiple biomarkers is based on the predictive probability of disease, conditional on given multiple biomarker outcomes. If the computed predictive probability exceeds a specified cutoff, the corresponding subject is allocated as 'diseased'. This defines a standard diagnostic criterion that has its own ROC curve, namely, the combined ROC (cROC). The AUC metric for cROC, namely, the combined AUC (cAUC), is used to compare the predictive criterion based on multiple biomarkers to one based on fewer biomarkers. A multivariate random-effects model is proposed for modeling multiple normally distributed dependent scores. Bayesian methods for estimating ROC curves and corresponding (marginal) AUCs are developed when a perfect reference standard is not available. In addition, cAUCs are computed to compare the accuracy of different combinations of biomarkers for diagnosis. The methods are evaluated using simulations and are applied to data for Johne's disease (paratuberculosis) in cattle. Copyright © 2015 John Wiley & Sons, Ltd.

Significance of MPEG-7 textural features for improved mass detection in mammography.

PubMed

Eltonsy, Nevine H; Tourassi, Georgia D; Fadeev, Aleksey; Elmaghraby, Adel S

2006-01-01

The purpose of the study is to investigate the significance of MPEG-7 textural features for improving the detection of masses in screening mammograms. The detection scheme was originally based on morphological directional neighborhood features extracted from mammographic regions of interest (ROIs). Receiver Operating Characteristics (ROC) was performed to evaluate the performance of each set of features independently and merged into a back-propagation artificial neural network (BPANN) using the leave-one-out sampling scheme (LOOSS). The study was based on a database of 668 mammographic ROIs (340 depicting cancer regions and 328 depicting normal parenchyma). Overall, the ROC area index of the BPANN using the directional morphological features was Az=0.85+/-0.01. The MPEG-7 edge histogram descriptor-based BPNN showed an ROC area index of Az=0.71+/-0.01 while homogeneous textural descriptors using 30 and 120 channels helped the BPNN achieve similar ROC area indexes of Az=0.882+/-0.02 and Az=0.877+/-0.01 respectively. After merging the MPEG-7 homogeneous textural features with the directional neighborhood features the performance of the BPANN increased providing an ROC area index of Az=0.91+/-0.01. MPEG-7 homogeneous textural descriptor significantly improved the morphology-based detection scheme.

Sensitivity and specificity of machine learning classifiers and spectral domain OCT for the diagnosis of glaucoma.

PubMed

Vidotti, Vanessa G; Costa, Vital P; Silva, Fabrício R; Resende, Graziela M; Cremasco, Fernanda; Dias, Marcelo; Gomi, Edson S

2012-06-15

Purpose. To investigate the sensitivity and specificity of machine learning classifiers (MLC) and spectral domain optical coherence tomography (SD-OCT) for the diagnosis of glaucoma. Methods. Sixty-two patients with early to moderate glaucomatous visual field damage and 48 healthy individuals were included. All subjects underwent a complete ophthalmologic examination, achromatic standard automated perimetry, and RNFL imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec, Inc., Dublin, California, USA). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters. Subsequently, the following MLCs were tested: Classification Tree (CTREE), Random Forest (RAN), Bagging (BAG), AdaBoost M1 (ADA), Ensemble Selection (ENS), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Naive-Bayes (NB), and Support Vector Machine (SVM). Areas under the ROC curves (aROCs) obtained for each parameter and each MLC were compared. Results. The mean age was 57.0±9.2 years for healthy individuals and 59.9±9.0 years for glaucoma patients (p=0.103). Mean deviation values were -4.1±2.4 dB for glaucoma patients and -1.5±1.6 dB for healthy individuals (p<0.001). The SD-OCT parameters with the greater aROCs were inferior quadrant (0.813), average thickness (0.807), 7 o'clock position (0.765), and 6 o'clock position (0.754). The aROCs from classifiers varied from 0.785 (ADA) to 0.818 (BAG). The aROC obtained with BAG was not significantly different from the aROC obtained with the best single SD-OCT parameter (p=0.93). Conclusions. The SD-OCT showed good diagnostic accuracy in a group of patients with early glaucoma. In this series, MLCs did not improve the sensitivity and specificity of SD-OCT for the diagnosis of glaucoma.

A tutorial on the use of ROC analysis for computer-aided diagnostic systems.

PubMed

Scheipers, Ulrich; Perrey, Christian; Siebers, Stefan; Hansen, Christian; Ermert, Helmut

2005-07-01

The application of the receiver operating characteristic (ROC) curve for computer-aided diagnostic systems is reviewed. A statistical framework is presented and different methods of evaluating the classification performance of computer-aided diagnostic systems, and, in particular, systems for ultrasonic tissue characterization, are derived. Most classifiers that are used today are dependent on a separation threshold, which can be chosen freely in many cases. The separation threshold separates the range of output values of the classification system into different target groups, thus conducting the actual classification process. In the first part of this paper, threshold specific performance measures, e.g., sensitivity and specificity, are presented. In the second part, a threshold-independent performance measure, the area under the ROC curve, is reviewed. Only the use of separation threshold-independent performance measures provides classification results that are overall representative for computer-aided diagnostic systems. The following text was motivated by the lack of a complete and definite discussion of the underlying subject in available textbooks, references and publications. Most manuscripts published so far address the theme of performance evaluation using ROC analysis in a manner too general to be practical for everyday use in the development of computer-aided diagnostic systems. Nowadays, the user of computer-aided diagnostic systems typically handles huge amounts of numerical data, not always distributed normally. Many assumptions made in more or less theoretical works on ROC analysis are no longer valid for real-life data. The paper aims at closing the gap between theoretical works and real-life data. The review provides the interested scientist with information needed to conduct ROC analysis and to integrate algorithms performing ROC analysis into classification systems while understanding the basic principles of classification.

A novel assay for detecting canine parvovirus using a quartz crystal microbalance biosensor.

PubMed

Kim, Yong Kwan; Lim, Seong-In; Choi, Sarah; Cho, In-Soo; Park, Eun-Hye; An, Dong-Jun

2015-07-01

Rapid and accurate diagnosis is crucial to reduce both the shedding and clinical signs of canine parvovirus (CPV). The quartz crystal microbalance (QCM) is a new tool for measuring frequency changes associated with antigen-antibody interactions. In this study, the QCM biosensor and ProLinker™ B were used to rapidly diagnosis CPV infection. ProLinker™ B enables antibodies to be attached to a gold-coated quartz surface in a regular pattern and in the correct orientation for antigen binding. Receiver operating characteristics (ROC) curves were used to set a cut-off value using reference CPVs (two groups: one CPV-positive and one CPV-negative). The ROC curves overlapped and the point of intersection was used as the cut-off value. A QCM biosensor with a cut-off value of -205 Hz showed 95.4% (104/109) sensitivity and 98.0% (149/152) specificity when used to test 261 field fecal samples compared to PCR. In conclusion, the QCM biosensor described herein is eminently suitable for the rapid diagnosis of CPV infection with high sensitivity and specificity. Therefore, it is a promising analytical tool that will be useful for clinical diagnosis, which requires rapid and reliable analyses. Copyright © 2015 Elsevier B.V. All rights reserved.

Screening of depression in cardiology: A study on 617 cardiovascular patients.

PubMed

Tesio, Valentina; Marra, Sebastiano; Molinaro, Stefania; Torta, Riccardo; Gaita, Fiorenzo; Castelli, Lorys

2017-10-15

Depression screening in the cardiovascular disease (CVD) care setting is under-performed, also because the issue of the optimal screening tools cut-off is still open. We analysed which HADS (Hospital Anxiety and Depression Scale) total score cut-off value shows the best properties in two groups of 357 Acute Coronary Syndrome (ACS) and 260 Chronic Coronary Artery Disease (CAD) hospitalized patients. A Receiver Operating Characteristics (ROC) curve was plotted for both groups using the Montgomery-Asberg Depression Rating Scale (MADRS) as the criterion. Accuracy, positive (PPV) and negative (NPV) predictive values were computed for different cut-off scores. The ROC curves confirmed the excellent/very good accuracy of the HADS in both groups, with an area under the curve of 0.911 for the ACS and 0.893 for the CAD patients. The cut-off of 14 showed the best compromise between high sensitivity and good specificity in both groups, with high negative predicted values (95.5% and 92.4%, respectively). Using a cut-off value of 14, the HADS could be considered a good screening tool to identify hospitalized CAD and ACS patients requiring a more accurate depression assessment, in order to promptly plan the most appropriate treatment strategies and prevent the negative effects of depression in CVD patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Screening for Sleep Apnoea in Mild Cognitive Impairment: The Utility of the Multivariable Apnoea Prediction Index

PubMed Central

Wilson, Georgina; Terpening, Zoe; Wong, Keith; Grunstein, Ron; Norrie, Louisa; Lewis, Simon J. G.; Naismith, Sharon L.

2014-01-01

Purpose. Mild cognitive impairment (MCI) is considered an “at risk” state for dementia and efforts are needed to target modifiable risk factors, of which Obstructive sleep apnoea (OSA) is one. This study aims to evaluate the predictive utility of the multivariate apnoea prediction index (MAPI), a patient self-report survey, to assess OSA in MCI. Methods. Thirty-seven participants with MCI and 37 age-matched controls completed the MAPI and underwent polysomnography (PSG). Correlations were used to compare the MAPI and PSG measures including oxygen desaturation index and apnoea-hypopnoea index (AHI). Receiver-operating characteristics (ROC) curve analyses were performed using various cut-off scores for apnoea severity. Results. In controls, there was a significant moderate correlation between higher MAPI scores and more severe apnoea (AHI: r = 0.47, P = 0.017). However, this relationship was not significant in the MCI sample. ROC curve analysis indicated much lower area under the curve (AUC) in the MCI sample compared to the controls across all AHI severity cut-off scores. Conclusions. In older people, the MAPI moderately correlates with AHI severity but only in those who are cognitively intact. Development of further screening tools is required in order to accurately screen for OSA in MCI. PMID:24551457

Operating characteristics of depression and anxiety disorder phenotype dimensions and trait neuroticism: a theoretical examination of the fear and distress disorders from the Netherlands study of depression and anxiety.

PubMed

Tully, Phillip J; Wardenaar, Klaas J; Penninx, Brenda W J H

2015-03-15

The receiver operating characteristics (ROC) of anhedonic depression and anxious arousal to detect the distress- (major depression, dysthymia, generalized anxiety disorder) and fear-disorder clusters (i.e. panic disorder, agoraphobia, social phobia) have not been reported in a large sample. A sample of 2981 persons underwent structured psychiatric interview; n=652 were without lifetime depression and anxiety disorder history. Participants also completed a neuroticism scale (Revised NEO Five Factor Inventory [NEO-FFI]), and the 30-item short adaptation of the Mood and Anxiety Symptoms Questionnaire (MASQ-D30) measuring anhedonic depression, anxious arousal and general distress. Maximal sensitivity and specificity was determined by the Youden Index and the area-under-the-curve (AUC) in ROC analysis. A total of 2624 completed all measures (age M=42.4 years±13.1, 1760 females [67.1%]), including 1060 (40.4%) persons who met criteria for a distress-disorder, and 973 (37.1%) who met criteria for a fear-disorder. The general distress dimension provided the highest ROC values in the detection of the distress-disorders (AUC=.814, sensitivity=71.95%, specificity=76.34%, positive predictive value=67.33, negative predictive value=80.07). None of the measures provided suitable operating characteristics in the detection of the fear-disorders with specificity values <75%. Over sampling of depression and anxiety disorders may lead to inflated positive- and negative predictive values. The MASQ-D30 general distress dimension showed clinically suitable operating characteristics in the detection of distress-disorders. Neither neuroticism nor the MASQ-D30 dimensions provided suitable operating characteristics in the detection of the fear-disorders. Copyright © 2014 Elsevier B.V. All rights reserved.

bcROCsurface: an R package for correcting verification bias in estimation of the ROC surface and its volume for continuous diagnostic tests.

PubMed

To Duc, Khanh

2017-11-18

Receiver operating characteristic (ROC) surface analysis is usually employed to assess the accuracy of a medical diagnostic test when there are three ordered disease status (e.g. non-diseased, intermediate, diseased). In practice, verification bias can occur due to missingness of the true disease status and can lead to a distorted conclusion on diagnostic accuracy. In such situations, bias-corrected inference tools are required. This paper introduce an R package, named bcROCsurface, which provides utility functions for verification bias-corrected ROC surface analysis. The shiny web application of the correction for verification bias in estimation of the ROC surface analysis is also developed. bcROCsurface may become an important tool for the statistical evaluation of three-class diagnostic markers in presence of verification bias. The R package, readme and example data are available on CRAN. The web interface enables users less familiar with R to evaluate the accuracy of diagnostic tests, and can be found at http://khanhtoduc.shinyapps.io/bcROCsurface_shiny/ .

Diagnostic accuracy of the Kampala Trauma Score using estimated Abbreviated Injury Scale scores and physician opinion.

PubMed

Gardner, Andrew; Forson, Paa Kobina; Oduro, George; Stewart, Barclay; Dike, Nkechi; Glover, Paul; Maio, Ronald F

2017-01-01

The Kampala Trauma Score (KTS) has been proposed as a triage tool for use in low- and middle-income countries (LMICs). This study aimed to examine the diagnostic accuracy of KTS in predicting emergency department outcomes using timely injury estimation with Abbreviated Injury Scale (AIS) score and physician opinion to calculate KTS scores. This was a diagnostic accuracy study of KTS among injured patients presenting to Komfo Anokye Teaching Hospital A&E, Ghana. South African Triage Scale (SATS); KTS component variables, including AIS scores and physician opinion for serious injury quantification; and ED disposition were collected. Agreement between estimated AIS score and physician opinion were analyzed with normal, linear weighted, and maximum kappa. Receiver operating characteristic (ROC) analysis of KTS-AIS and KTS-physician opinion was performed to evaluate each measure's ability to predict A&E mortality and need for hospital admission to the ward or theatre. A total of 1053 patients were sampled. There was moderate agreement between AIS criteria and physician opinion by normal (κ=0.41), weighted (κ lin =0.47), and maximum (κ max =0.53) kappa. A&E mortality ROC area for KTS-AIS was 0.93, KTS-physician opinion 0.89, and SATS 0.88 with overlapping 95% confidence intervals (95%CI). Hospital admission ROC area for KTS-AIS was 0.73, KTS-physician opinion 0.79, and SATS 0.71 with statistical similarity. When evaluating only patients with serious injuries, KTS-AIS (ROC 0.88) and KTS-physician opinion (ROC 0.88) performed similarly to SATS (ROC 0.78) in predicting A&E mortality. The ROC area for KTS-AIS (ROC 0.71; 95%CI 0.66-0.75) and KTS-physician opinion (ROC 0.74; 95%CI 0.69-0.79) was significantly greater than SATS (ROC 0.57; 0.53-0.60) with regard to need for admission. KTS predicted mortality and need for admission from the ED well when early estimation of the number of serious injuries was used, regardless of method (i.e. AIS criteria or physician opinion). This study provides evidence for KTS to be used as a practical and valid triage tool to predict patient prognosis, ED outcomes and inform referral decision-making from first- or second-level hospitals in LMICs. Copyright © 2016 Elsevier Ltd. All rights reserved.

Diagnostic accuracy of the Kampala Trauma Score using estimated Abbreviated Injury Scale scores and physician opinion

PubMed Central

Gardner, Andrew; Forson, Paa Kobina; Oduro, George; Stewart, Barclay; Dike, Nkechi; Glover, Paul; Maio, Ronald F.

2016-01-01

Background The Kampala Trauma Score (KTS) has been proposed as a triage tool for use in low- and middle-income countries (LMICs). This study aimed to examine the diagnostic accuracy of KTS in predicting emergency department outcomes using timely injury estimation with Abbreviated Injury Scale (AIS) score and physician opinion to calculate KTS scores. Methods This was a diagnostic accuracy study of KTS among injured patients presenting to Komfo Anokye Teaching Hospital A&E, Ghana. South African Triage Scale (SATS); KTS component variables, including AIS scores and physician opinion for serious injury quantification; and ED disposition were collected. Agreement between estimated AIS score and physician opinion were analyzed with normal, linear weighted, and maximum kappa. Receiver operating characteristic (ROC) analysis of KTS-AIS and KTS-physician opinion was performed to evaluate each measure’s ability to predict A&E mortality and need for hospital admission to the ward or theatre. Results A total of 1,053 patients were sampled. There was moderate agreement between AIS criteria and physician opinion by normal (κ=0.41), weighted (κlin=0.47), and maximum (κmax=0.53) kappa. A&E mortality ROC area for KTS-AIS was 0.93, KTS-physician opinion 0.89, and SATS 0.88 with overlapping 95% confidence intervals (95%CI). Hospital admission ROC area for KTS-AIS was 0.73, KTS-physician opinion 0.79, and SATS 0.71 with statistical similarity. When evaluating only patients with serious injuries, KTS-AIS (ROC 0.88) and KTS-physician opinion (ROC 0.88) performed similarly to SATS (ROC 0.78) in predicting A&E mortality. The ROC area for KTS-AIS (ROC 0.71; 95%CI 0.66–0.75) and KTS-physician opinion (ROC 0.74; 95%CI 0.69–0.79) was significantly greater than SATS (ROC 0.57; 0.53–0.60) with regard to need for admission. Conclusions KTS predicted mortality and need for admission from the ED well when early estimation of the number of serious injuries was used, regardless of method (i.e. AIS criteria or physician opinion). This study provides evidence for KTS to be used as a practical and valid triage tool to predict patient prognosis, ED outcomes and inform referral decision-making from first- or second-level hospitals in LMICs. PMID:27908493

Currency crisis indication by using ensembles of support vector machine classifiers

NASA Astrophysics Data System (ADS)

Ramli, Nor Azuana; Ismail, Mohd Tahir; Wooi, Hooy Chee

2014-07-01

There are many methods that had been experimented in the analysis of currency crisis. However, not all methods could provide accurate indications. This paper introduces an ensemble of classifiers by using Support Vector Machine that's never been applied in analyses involving currency crisis before with the aim of increasing the indication accuracy. The proposed ensemble classifiers' performances are measured using percentage of accuracy, root mean squared error (RMSE), area under the Receiver Operating Characteristics (ROC) curve and Type II error. The performances of an ensemble of Support Vector Machine classifiers are compared with the single Support Vector Machine classifier and both of classifiers are tested on the data set from 27 countries with 12 macroeconomic indicators for each country. From our analyses, the results show that the ensemble of Support Vector Machine classifiers outperforms single Support Vector Machine classifier on the problem involving indicating a currency crisis in terms of a range of standard measures for comparing the performance of classifiers.

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays

PubMed Central

Goodman, Corey W.; Major, Heather J.; Walls, William D.; Sheffield, Val C.; Casavant, Thomas L.; Darbro, Benjamin W.

2016-01-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. PMID:25595567

Neyman-Pearson classification algorithms and NP receiver operating characteristics

PubMed Central

Tong, Xin; Feng, Yang; Li, Jingyi Jessica

2018-01-01

In many binary classification applications, such as disease diagnosis and spam detection, practitioners commonly face the need to limit type I error (that is, the conditional probability of misclassifying a class 0 observation as class 1) so that it remains below a desired threshold. To address this need, the Neyman-Pearson (NP) classification paradigm is a natural choice; it minimizes type II error (that is, the conditional probability of misclassifying a class 1 observation as class 0) while enforcing an upper bound, α, on the type I error. Despite its century-long history in hypothesis testing, the NP paradigm has not been well recognized and implemented in classification schemes. Common practices that directly limit the empirical type I error to no more than α do not satisfy the type I error control objective because the resulting classifiers are likely to have type I errors much larger than α, and the NP paradigm has not been properly implemented in practice. We develop the first umbrella algorithm that implements the NP paradigm for all scoring-type classification methods, such as logistic regression, support vector machines, and random forests. Powered by this algorithm, we propose a novel graphical tool for NP classification methods: NP receiver operating characteristic (NP-ROC) bands motivated by the popular ROC curves. NP-ROC bands will help choose α in a data-adaptive way and compare different NP classifiers. We demonstrate the use and properties of the NP umbrella algorithm and NP-ROC bands, available in the R package nproc, through simulation and real data studies. PMID:29423442

Neyman-Pearson classification algorithms and NP receiver operating characteristics.

PubMed

Tong, Xin; Feng, Yang; Li, Jingyi Jessica

2018-02-01

In many binary classification applications, such as disease diagnosis and spam detection, practitioners commonly face the need to limit type I error (that is, the conditional probability of misclassifying a class 0 observation as class 1) so that it remains below a desired threshold. To address this need, the Neyman-Pearson (NP) classification paradigm is a natural choice; it minimizes type II error (that is, the conditional probability of misclassifying a class 1 observation as class 0) while enforcing an upper bound, α, on the type I error. Despite its century-long history in hypothesis testing, the NP paradigm has not been well recognized and implemented in classification schemes. Common practices that directly limit the empirical type I error to no more than α do not satisfy the type I error control objective because the resulting classifiers are likely to have type I errors much larger than α, and the NP paradigm has not been properly implemented in practice. We develop the first umbrella algorithm that implements the NP paradigm for all scoring-type classification methods, such as logistic regression, support vector machines, and random forests. Powered by this algorithm, we propose a novel graphical tool for NP classification methods: NP receiver operating characteristic (NP-ROC) bands motivated by the popular ROC curves. NP-ROC bands will help choose α in a data-adaptive way and compare different NP classifiers. We demonstrate the use and properties of the NP umbrella algorithm and NP-ROC bands, available in the R package nproc, through simulation and real data studies.

Face recognition in schizophrenia: do individual and average ROCs tell the same story?

PubMed

Tiberghien, Guy; Martin, Clara; Baudouin, Jean-Yves; Franck, Nicolas; Guillaume, Fabrice; Huron, Caroline

2015-01-01

Many studies have shown that recollection process is impaired in patients with schizophrenia, whereas familiarity is generally spared. However, in these studies, the Receiver Operating Characteristic (ROC) presented is average ROC likely to mask individual differences. In the present study using a face-recognition task, we computed the individual ROC of patients with schizophrenia and control participants. Each group was divided into two subgroups on the basis of the type of recognition processes implemented: recognition based on familiarity only and recognition based on familiarity and recollection. The recognition performance of the schizophrenia patients was below that of the control participants only when recognition was based solely on familiarity. For the familiarity-alone patients, the score obtained on the Scale for the Assessment of Positive Symptoms (SAPS) was correlated with the variance of the old-face familiarity. For the familiarity-recollection patients, the score obtained on the Scale for the Assessment of Negative Symptoms (SANS) was correlated with the decision criterion and with the old-face recollection probability. These results show that one cannot ascribe the impaired recognition observed in patients with schizophrenia to a recollection deficit alone. These results show that individual ROC can be used to distinguish between subtypes of schizophrenia and could serve as a basis for setting up specific cognitive remediation therapy for individuals with schizophrenia.

A general framework for the use of logistic regression models in meta-analysis.

PubMed

Simmonds, Mark C; Higgins, Julian Pt

2016-12-01

Where individual participant data are available for every randomised trial in a meta-analysis of dichotomous event outcomes, "one-stage" random-effects logistic regression models have been proposed as a way to analyse these data. Such models can also be used even when individual participant data are not available and we have only summary contingency table data. One benefit of this one-stage regression model over conventional meta-analysis methods is that it maximises the correct binomial likelihood for the data and so does not require the common assumption that effect estimates are normally distributed. A second benefit of using this model is that it may be applied, with only minor modification, in a range of meta-analytic scenarios, including meta-regression, network meta-analyses and meta-analyses of diagnostic test accuracy. This single model can potentially replace the variety of often complex methods used in these areas. This paper considers, with a range of meta-analysis examples, how random-effects logistic regression models may be used in a number of different types of meta-analyses. This one-stage approach is compared with widely used meta-analysis methods including Bayesian network meta-analysis and the bivariate and hierarchical summary receiver operating characteristic (ROC) models for meta-analyses of diagnostic test accuracy. © The Author(s) 2014.

Validation of Three Previously Developed Short Forms of the Beck Depression Inventory for Youth: A Replication.

PubMed

Blackmon, Jaime E; Liptak, Cori; Recklitis, Christopher J

2017-03-01

Three previously developed short forms of the Beck Depression Inventory-Youth (BDI-Y) were validated against the standard 20-item BDI-Y; 168 adolescent survivors completed the standard and short-form versions of the BDI-Y. The short forms were evaluated for internal consistency and compared with the standard BDI-Y using correlation coefficients and receiver operating characteristic curve analyses. The three short forms had good internal consistency (α > 0.85), high correlations with the total BDI-Y scale (r > 0.85), and good discrimination compared with the standard BDI-Y cutoff score (area under the ROC curve >0.95). Consistent with prior findings, strong psychometric properties of an eight-item short form support its use as a screening measure for adolescent cancer survivors.

Optimal threshold estimation for binary classifiers using game theory.

PubMed

Sanchez, Ignacio Enrique

2016-01-01

Many bioinformatics algorithms can be understood as binary classifiers. They are usually compared using the area under the receiver operating characteristic ( ROC ) curve. On the other hand, choosing the best threshold for practical use is a complex task, due to uncertain and context-dependent skews in the abundance of positives in nature and in the yields/costs for correct/incorrect classification. We argue that considering a classifier as a player in a zero-sum game allows us to use the minimax principle from game theory to determine the optimal operating point. The proposed classifier threshold corresponds to the intersection between the ROC curve and the descending diagonal in ROC space and yields a minimax accuracy of 1-FPR. Our proposal can be readily implemented in practice, and reveals that the empirical condition for threshold estimation of "specificity equals sensitivity" maximizes robustness against uncertainties in the abundance of positives in nature and classification costs.

The Worksite Health Promotion Capacity Instrument (WHPCI): development, validation and approaches for determining companies' levels of health promotion capacity.

PubMed

Jung, Julia; Nitzsche, Anika; Neumann, Melanie; Wirtz, Markus; Kowalski, Christoph; Wasem, Jürgen; Stieler-Lorenz, Brigitte; Pfaff, Holger

2010-09-13

The Worksite Health Promotion Capacity Instrument (WHPCI) was developed to assess two key factors for effective worksite health promotion: collective willingness and the systematic implementation of health promotion activities in companies. This study evaluates the diagnostic qualities of the WHPCI based on its subscales Health Promotion Willingness and Health Promotion Management, which can be used to place companies into four different categories based on their level of health promotion capacity. Psychometric evaluation was conducted using exploratory factor and reliability analyses with data taken from a random sample of managers from n = 522 German information and communication technology (ICT) companies. Receiver operating characteristic (ROC) analyses were conducted to determine further diagnostic qualities of the instrument and to establish the cut-off scores used to determine each company's level of health promotion capacity. The instrument's subscales, Health Promotion Willingness and Health Promotion Management, are based on one-dimensional constructs, each with very good reliability (Cronbach's alpha = 0.83/0.91). ROC analyses demonstrated satisfactory diagnostic accuracy with an area under the curve (AUC) of 0.76 (SE = 0.021; 95% CI 0.72-0.80) for the Health Promotion Willingness scale and 0.81 (SE = 0.021; 95% CI 0.77-0.86) for the Health Promotion Management scale. A cut-off score with good sensitivity (71%/76%) and specificity (69%/75%) was determined for each scale. Both scales were found to have good predictive power and exhibited good efficiency. Our findings indicate preliminary evidence for the validity and reliability of both subscales of the WHPCI. The goodness of each cut-off score suggests that the scales are appropriate for determining companies' levels of health promotion capacity. Support in implementing (systematic) worksite health promotion can then be tailored to each company's needs based on their current capacity level.

Contribution of occupational factors to the incidence and persistence of chronic low back pain among workers: results from the longitudinal VISAT study.

PubMed

Esquirol, Yolande; Niezborala, Michel; Visentin, Monique; Leguevel, Anne; Gonzalez, Ignacio; Marquié, Jean-Claude

2017-03-01

Among the aetiological factors of chronic low back pain (CLBP), occupational factors are often suspected, but their contribution remains to be ascertained. This study aimed to determine the impact of a wide range of occupational factors on the incidence and persistence of CLBP. From the VISAT (VIeillissement SAnté Travail) study, 1560 workers were examined at baseline and 5 years later. CLBP was defined as having low back pain or specific treatment for at least 6 months. Participants newly affected with CLBP and those with persistent CLBP at follow-up were distinguished. In addition to individual factors, a broad panel of occupational factors were analysed, covering employment, physical, organisational and psychosocial factors. Multivariate analyses were used to determine predictive factors of incidence and persistence of CLBP. Receiver operating characteristic (ROC) curves were performed to analyse the contribution of occupational factors. 22.6% of participants without any CLBP initially presented with CLBP 5 years later, while 53.7% of participants with CLBP at baseline had CLBP at the second collection. Carrying heavy loads, the lack of recognition of completed work and productivity-related income predicted a higher risk of incidence of CLBP. However, no significant association between occupational factors and the risk for persistence of CLBP was observed, while the risk was multiplied by two for history of depression and rheumatological events. ROC curves confirmed the significant contribution of occupational factors to incidence of CLBP. Occupational factors played a pivotal role in the incidence of CLBP, while individual factors were the main determinants of persistence of CLBP. 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/.

Hippocampal subfield volumetry in mild cognitive impairment, Alzheimer's disease and semantic dementia.

PubMed

La Joie, Renaud; Perrotin, Audrey; de La Sayette, Vincent; Egret, Stéphanie; Doeuvre, Loïc; Belliard, Serge; Eustache, Francis; Desgranges, Béatrice; Chételat, Gaël

2013-01-01

Hippocampal atrophy is a well-known feature of Alzheimer's disease (AD), but sensitivity and specificity of hippocampal volumetry are limited. Neuropathological studies have shown that hippocampal subfields are differentially vulnerable to AD; hippocampal subfield volumetry may thus prove to be more accurate than global hippocampal volumetry to detect AD. CA1, subiculum and other subfields were manually delineated from 40 healthy controls, 18 AD, 17 amnestic Mild Cognitive Impairment (aMCI), and 8 semantic dementia (SD) patients using a previously developed high resolution MRI procedure. Non-parametric group comparisons and receiver operating characteristic (ROC) analyses were conducted. Complementary analyses were conducted to evaluate differences of hemispheric asymmetry and anterior-predominance between AD and SD patients and to distinguish aMCI patients with or without β-amyloid deposition as assessed by Florbetapir-TEP. Global hippocampi were atrophied in all three patient groups and volume decreases were maximal in the CA1 subfield (22% loss in aMCI, 27% in both AD and SD; all p < 0.001). In aMCI, CA1 volumetry was more accurate than global hippocampal measurement to distinguish patients from controls (areas under the ROC curve = 0.88 and 0.76, respectively; p = 0.05) and preliminary analyses suggest that it was independent from the presence of β-amyloid deposition. In patients with SD, whereas the degree of CA1 and subiculum atrophy was similar to that found in AD patients, hemispheric and anterior-posterior asymmetry were significantly more marked than in AD with greater involvement of the left and anterior hippocampal subfields. The findings suggest that CA1 measurement is more sensitive than global hippocampal volumetry to detect structural changes at the pre-dementia stage, although the predominance of CA1 atrophy does not appear to be specific to AD pathophysiological processes.

FDG-PET Response Prediction in Pediatric Hodgkin's Lymphoma: Impact of Metabolically Defined Tumor Volumes and Individualized SUV Measurements on the Positive Predictive Value.

PubMed

Hussien, Amr Elsayed M; Furth, Christian; Schönberger, Stefan; Hundsdoerfer, Patrick; Steffen, Ingo G; Amthauer, Holger; Müller, Hans-Wilhelm; Hautzel, Hubertus

2015-01-28

In pediatric Hodgkin's lymphoma (pHL) early response-to-therapy prediction is metabolically assessed by (18)F-FDG PET carrying an excellent negative predictive value (NPV) but an impaired positive predictive value (PPV). Aim of this study was to improve the PPV while keeping the optimal NPV. A comparison of different PET data analyses was performed applying individualized standardized uptake values (SUV), PET-derived metabolic tumor volume (MTV) and the product of both parameters, termed total lesion glycolysis (TLG); One-hundred-eight PET datasets (PET1, n = 54; PET2, n = 54) of 54 children were analysed by visual and semi-quantitative means. SUVmax, SUVmean, MTV and TLG were obtained the results of both PETs and the relative change from PET1 to PET2 (Δ in %) were compared for their capability of identifying responders and non-responders using receiver operating characteristics (ROC)-curves. In consideration of individual variations in noise and contrasts levels all parameters were additionally obtained after threshold correction to lean body mass and background; All semi-quantitative SUV estimates obtained at PET2 were significantly superior to the visual PET2 analysis. However, ΔSUVmax revealed the best results (area under the curve, 0.92; p < 0.001; sensitivity 100%; specificity 85.4%; PPV 46.2%; NPV 100%; accuracy, 87.0%) but was not significantly superior to SUVmax-estimation at PET2 and ΔTLGmax. Likewise, the lean body mass and background individualization of the datasets did not impove the results of the ROC analyses; Sophisticated semi-quantitative PET measures in early response assessment of pHL patients do not perform significantly better than the previously proposed ΔSUVmax. All analytical strategies failed to improve the impaired PPV to a clinically acceptable level while preserving the excellent NPV.

Effectiveness of computer-aided diagnosis (CADx) of breast pathology using immunohistochemistry results of core needle biopsy samples for synaptophysin, oestrogen receptor and CK14/p63 for classification of epithelial proliferative lesions of the breast.

PubMed

Maeda, Ichiro; Kubota, Manabu; Ohta, Jiro; Shinno, Kimika; Tajima, Shinya; Ariizumi, Yasushi; Doi, Masatomo; Oana, Yoshiyasu; Kanemaki, Yoshihide; Tsugawa, Koichiro; Ueno, Takahiko; Takagi, Masayuki

2017-12-01

The aim of this study was to develop a computer-aided diagnosis (CADx) system for identifying breast pathology. Two sets of 100 consecutive core needle biopsy (CNB) specimens were collected for test and validation studies. All 200 CNB specimens were stained with antibodies targeting oestrogen receptor (ER), synaptophysin and CK14/p63. All stained slides were scanned in a whole-slide imaging system and photographed. The photographs were analysed using software to identify the proportions of tumour cells that were positive and negative for each marker. In the test study, the cut-off values for synaptophysin (negative and positive) and CK14/p63 (negative and positive) were decided using receiver operating characteristic (ROC) analysis. For ER analysis, samples were divided into groups with <10% positive or >10% positive cells and decided using receiver operating characteristic (ROC) analysis. Finally, these two groups categorised as ER-low, ER-intermediate (non-low and non-high) and ER-high groups. In the validation study, the second set of immunohistochemical slides were analysed using these cut-off values. The cut-off values for synaptophysin, <10% ER positive, >10% ER positive and CK14/p63 were 0.14%, 2.17%, 77.93% and 18.66%, respectively. The positive predictive value for malignancy (PPV) was 100% for synaptophysin-positive/ER-high/(CK14/p63)-any or synaptophysin-positive/ER-low/(CK14/p63)-any. The PPV was 25% for synaptophysin-positive/ER-intermediate/(CK14/p63)-positive. For synaptophysin-negative/(CK14/p63)-negative, the PPVs for ER-low, ER-intermediate and ER-high were 100%, 80.0% and 95.8%, respectively. The PPV was 4.5% for synaptophysin-negative/ER-intermediate/(CK14/p63)-positive. The CADx system was able to analyse sufficient data for all types of epithelial proliferative lesions of the breast including invasive breast cancer. This system may be useful for pathological diagnosis of breast CNB in routine investigations. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Plant stress biomarkers from biosimulations: the Transcriptome-To-Metabolome (TTM) technology - effects of drought stress on rice.

PubMed

Phelix, C F; Feltus, F A

2015-01-01

Measuring biomarkers from plant tissue samples is challenging and expensive when the desire is to integrate transcriptomics, fluxomics, metabolomics, lipidomics, proteomics, physiomics and phenomics. We present a computational biology method where only the transcriptome needs to be measured and is used to derive a set of parameters for deterministic kinetic models of metabolic pathways. The technology is called Transcriptome-To-Metabolome (TTM) biosimulations, currently under commercial development, but available for non-commercial use by researchers. The simulated results on metabolites of 30 primary and secondary metabolic pathways in rice (Oryza sativa) were used as the biomarkers to predict whether the transcriptome was from a plant that had been under drought conditions. The rice transcriptomes were accessed from public archives and each individual plant was simulated. This unique quality of the TTM technology allows standard analyses on biomarker assessments, i.e. sensitivity, specificity, positive and negative predictive values, accuracy, receiver operator characteristics (ROC) curve and area under the ROC curve (AUC). Two validation methods were also used, the holdout and 10-fold cross validations. Initially 17 metabolites were identified as candidate biomarkers based on either statistical significance on binary phenotype when compared with control samples or recognition from the literature. The top three biomarkers based on AUC were gibberellic acid 12 (0.89), trehalose (0.80) and sn1-palmitate-sn2-oleic-phosphatidylglycerol (0.70). Neither heat map analyses of transcriptomes nor all 300 metabolites clustered the stressed and control groups effectively. The TTM technology allows the emergent properties of the integrated system to generate unique and useful 'Omics' information. © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands.

Biomarkers in Trypanosoma cruzi-infected and uninfected individuals with varying severity of cardiomyopathy in Santa Cruz, Bolivia.

PubMed

Okamoto, Emi E; Sherbuk, Jacqueline E; Clark, Eva H; Marks, Morgan A; Gandarilla, Omar; Galdos-Cardenas, Gerson; Vasquez-Villar, Angel; Choi, Jeong; Crawford, Thomas C; Do, Rose Q; Q, Rose; Fernandez, Antonio B; Colanzi, Rony; Flores-Franco, Jorge Luis; Gilman, Robert H; Bern, Caryn

2014-10-01

Twenty to thirty percent of persons with Trypanosoma cruzi infection eventually develop cardiomyopathy. If an early indicator were to be identified and validated in longitudinal studies, this could enable treatment to be prioritized for those at highest risk. We evaluated cardiac and extracellular matrix remodeling markers across cardiac stages in T. cruzi infected (Tc+) and uninfected (Tc-) individuals. Participants were recruited in a public hospital in Santa Cruz, Bolivia and assigned cardiac severity stages by electrocardiogram and echocardiogram. BNP, NTproBNP, CKMB, troponin I, MMP-2, MMP-9, TIMP-1, TIMP-2, TGFb1, and TGFb2 were measured in specimens from 265 individuals using multiplex bead systems. Biomarker levels were compared between Tc+ and Tc- groups, and across cardiac stages. Receivers operating characteristic (ROC) curves were created; for markers with area under curve>0.60, logistic regression was performed. Analyses stratified by cardiac stage showed no significant differences in biomarker levels by Tc infection status. Among Tc+ individuals, those with cardiac insufficiency had higher levels of BNP, NTproBNP, troponin I, MMP-2, TIMP-1, and TIMP-2 than those with normal ejection fraction and left ventricular diameter. No individual marker distinguished between the two earliest Tc+ stages, but in ROC-based analyses, MMP-2/MMP-9 ratio was significantly higher in those with than those without ECG abnormalities. BNP, NTproBNP, troponin I, MMP-2, TIMP-1, and TIMP-2 levels rose with increasing severity stage but did not distinguish between Chagas cardiomyopathy and other cardiomyopathies. Among Tc+ individuals without cardiac insufficiency, only the MMP-2/MMP-9 ratio differed between those with and without ECG changes.

Non-small cell lung cancer: Whole-lesion histogram analysis of the apparent diffusion coefficient for assessment of tumor grade, lymphovascular invasion and pleural invasion.

PubMed

Tsuchiya, Naoko; Doai, Mariko; Usuda, Katsuo; Uramoto, Hidetaka; Tonami, Hisao

2017-01-01

Investigating the diagnostic accuracy of histogram analyses of apparent diffusion coefficient (ADC) values for determining non-small cell lung cancer (NSCLC) tumor grades, lymphovascular invasion, and pleural invasion. We studied 60 surgically diagnosed NSCLC patients. Diffusion-weighted imaging (DWI) was performed in the axial plane using a navigator-triggered single-shot, echo-planar imaging sequence with prospective acquisition correction. The ADC maps were generated, and we placed a volume-of-interest on the tumor to construct the whole-lesion histogram. Using the histogram, we calculated the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC, skewness, and kurtosis. Histogram parameters were correlated with tumor grade, lymphovascular invasion, and pleural invasion. We performed a receiver operating characteristics (ROC) analysis to assess the diagnostic performance of histogram parameters for distinguishing different pathologic features. The ADC mean, 10th, 25th, 50th, 75th, 90th, and 95th percentiles showed significant differences among the tumor grades. The ADC mean, 25th, 50th, 75th, 90th, and 95th percentiles were significant histogram parameters between high- and low-grade tumors. The ROC analysis between high- and low-grade tumors showed that the 95th percentile ADC achieved the highest area under curve (AUC) at 0.74. Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis. Kurtosis achieved the highest AUC at 0.809. Pleural invasion was only associated with skewness, with the AUC of 0.648. ADC histogram analyses on the basis of the entire tumor volume are able to stratify NSCLCs' tumor grade, lymphovascular invasion and pleural invasion.

The predictive value of noninvasive serum markers of liver fibrosis in patients with chronic hepatitis C.

PubMed

Gökcan, Hale; Kuzu, Ufuk Barış; Öztaş, Erkin; Saygılı, Fatih; Öztuna, Derya; Suna, Nuretdin; Tenlik, İlyas; Akdoğan, Meral; Kaçar, Sabite; Kılıç, Zeki Mesut Yalın; Kayaçetin, Ertuğrul

2016-03-01

This study aims to show the predictive value of noninvasive serum markers on the hepatic fibrosis level. This cross sectional study involves 120 patients with chronic hepatitis C. The noninvasive markers used were as follows: age-platelet index (AP index), cirrhosis discriminant score (CDS), aspartate aminotransferase (AST)-alanine aminotransferase (ALT) ratio (AAR), fibrosis-4 (FIB-4) index, AST-platelet ratio index (APRI), Goteborg University Cirrhosis Index (GUCI), FibroQ, King's score, platelet count. Concurrent liver biopsies were evaluated using the modified Ishak and Knodell scoring systems. In accordance with the Knodell scores, F3-F4 scores were defined as "severe fibrosis," and the modified Ishak scores stage of ≥3 (F3-F6) were defined as "clinically significant fibrosis." Receiver Operating Characteristic (ROC) curve analyses were carried out to compare the noninvasive markers with hepatic fibrosis level. Mean age of the patients was 51.7±11.6. A total of 10 patients (8.3%) with Knodell scores and 24 patients (20%) with modified Ishak scores were evaluated to have ≥F3 hepatic fibrosis. ROC analyses with the Knodell and modified Ishak scores were as follows: AP index=0.61-0.57, CDS=0.66-0.55, AAR=0.60-0.49, FIB-4=0.70-0.68, APRI=0.67-0.72, GUCI=0.66-0.72, FibroQ=0.64-0.54, King's score=0.68-0.54, platelet count=0.61-0.55. We found that APRI, FIB-4, King's score, and GUCI can be used to determination patients with mild fibrosis with a high negative predictive value and in the differentiation of severe/significant fibrosis from mild to moderate fibrosis.

Biomarkers in Trypanosoma cruzi-Infected and Uninfected Individuals with Varying Severity of Cardiomyopathy in Santa Cruz, Bolivia

PubMed Central

Clark, Eva H.; Marks, Morgan A.; Gandarilla, Omar; Galdos-Cardenas, Gerson; Vasquez-Villar, Angel; Choi, Jeong; Crawford, Thomas C.; Q., Rose; Fernandez, Antonio B.; Colanzi, Rony; Flores-Franco, Jorge Luis; Gilman, Robert H.; Bern, Caryn

2014-01-01

Background Twenty to thirty percent of persons with Trypanosoma cruzi infection eventually develop cardiomyopathy. If an early indicator were to be identified and validated in longitudinal studies, this could enable treatment to be prioritized for those at highest risk. We evaluated cardiac and extracellular matrix remodeling markers across cardiac stages in T. cruzi infected (Tc+) and uninfected (Tc−) individuals. Methods Participants were recruited in a public hospital in Santa Cruz, Bolivia and assigned cardiac severity stages by electrocardiogram and echocardiogram. BNP, NTproBNP, CKMB, troponin I, MMP-2, MMP-9, TIMP-1, TIMP-2, TGFb1, and TGFb2 were measured in specimens from 265 individuals using multiplex bead systems. Biomarker levels were compared between Tc+ and Tc− groups, and across cardiac stages. Receivers operating characteristic (ROC) curves were created; for markers with area under curve>0.60, logistic regression was performed. Results Analyses stratified by cardiac stage showed no significant differences in biomarker levels by Tc infection status. Among Tc+ individuals, those with cardiac insufficiency had higher levels of BNP, NTproBNP, troponin I, MMP-2, TIMP-1, and TIMP-2 than those with normal ejection fraction and left ventricular diameter. No individual marker distinguished between the two earliest Tc+ stages, but in ROC-based analyses, MMP-2/MMP-9 ratio was significantly higher in those with than those without ECG abnormalities. Conclusions BNP, NTproBNP, troponin I, MMP-2, TIMP-1, and TIMP-2 levels rose with increasing severity stage but did not distinguish between Chagas cardiomyopathy and other cardiomyopathies. Among Tc+ individuals without cardiac insufficiency, only the MMP-2/MMP-9 ratio differed between those with and without ECG changes. PMID:25275382

Prediction of infarction development after endovascular stroke therapy with dual-energy computed tomography.

PubMed

Djurdjevic, Tanja; Rehwald, Rafael; Knoflach, Michael; Matosevic, Benjamin; Kiechl, Stefan; Gizewski, Elke Ruth; Glodny, Bernhard; Grams, Astrid Ellen

2017-03-01

After intraarterial recanalisation (IAR), the haemorrhage and the blood-brain barrier (BBB) disruption can be distinguished using dual-energy computed tomography (DECT). The aim of the present study was to investigate whether future infarction development can be predicted from DECT. DECT scans of 20 patients showing 45 BBB disrupted areas after IAR were assessed and compared with follow-up examinations. Receiver operator characteristic (ROC) analyses using densities from the iodine map (IM) and virtual non-contrast (VNC) were performed. Future infarction areas are denser than future non-infarction areas on IM series (23.44 ± 24.86 vs. 5.77 ± 2.77; p < 0.0001) and more hypodense on VNC series (29.71 ± 3.33 vs. 35.33 ± 3.50; p < 0.0001). ROC analyses for the IM series showed an area under the curve (AUC) of 0.99 (cut-off: <9.97 HU; p < 0.05; sensitivity 91.18 %; specificity 100.00 %; accuracy 0.93) for the prediction of future infarctions. The AUC for the prediction of haemorrhagic infarctions was 0.78 (cut-off >17.13 HU; p < 0.05; sensitivity 90.00 %; specificity 62.86 %; accuracy 0.69). The VNC series allowed prediction of infarction volume. Future infarction development after IAR can be reliably predicted with the IM series. The prediction of haemorrhages and of infarction size is less reliable. • The IM series (DECT) can predict future infarction development after IAR. • Later haemorrhages can be predicted using the IM and the BW series. • The volume of definable hypodense areas in VNC correlates with infarction volume.

Enteral tube feeding of patients with acute stroke: when does the risk of diarrhoea increase?

PubMed

Arevalo-Manso, J J; Martinez-Sanchez, P; Juarez-Martin, B; Fuentes, B; Ruiz-Ares, G; Sanz-Cuesta, B E; Parrilla-Novo, P; Diez-Tejedor, E

2014-12-01

We aimed to evaluate the relationship between the length of time acute stroke patients underwent enteral tube feeding (ETF) and episodes of diarrhoea, and to investigate the temporal cut-off point at which diarrhoea risk increases. An observational, retrospective study was conducted on patients with acute stroke admitted to a Stroke Centre. Patients undergoing ETF (ETF group) and those not undergoing ETF (control group) were analysed and matched by age and stroke severity. Data regarding demographic and clinical variables were recorded. The analysis was conducted using a receiver operating characteristic (ROC) curve and multivariate analyses. A total of 130 inpatients was included (age 75.08 ± 11.53 years, 56.2% men). The ETF group had higher diarrhoea frequency (27.7% vs 6.2%, P = 0.001). The length of time on ETF was associated with diarrhoea development (odds ratio (OR), 1.12 increment per day; 95% confidence interval (CI) 1.05-1.18; P < 0.001), after adjusting for confounders. The ROC curve showed 7 days on ETF as a cut-off point for diarrhoea risk. Seven days or more on ETF was independently associated with diarrhoea (OR, 6.26; 95% CI 1.66-23.62; P = 0.007), whereas less than 7 days was not when compared with the control group (OR, 0.38; 95% CI 0.04-3.91; P = 0.413). The length of time on ETF is associated with diarrhoea development in patients with acute stroke, demonstrating a temporal cut-off point. Seven days or longer on ETF is related to the occurrence of diarrhoea, whereas less than 7 days on ETF does not show this effect. © 2014 The Authors; Internal Medicine Journal © 2014 Royal Australasian College of Physicians.

Validation of the REMA score for predicting mast cell clonality and systemic mastocytosis in patients with systemic mast cell activation symptoms.

PubMed

Alvarez-Twose, I; González-de-Olano, D; Sánchez-Muñoz, L; Matito, A; Jara-Acevedo, M; Teodosio, C; García-Montero, A; Morgado, J M; Orfao, A; Escribano, L

2012-01-01

A variable percentage of patients with systemic mast cell (MC) activation symptoms meet criteria for systemic mastocytosis (SM). We prospectively evaluated the clinical utility of the REMA score versus serum baseline tryptase (sBt) levels for predicting MC clonality and SM in 158 patients with systemic MC activation symptoms in the absence of mastocytosis in the skin (MIS). World Health Organization criteria for SM were applied in all cases. MC clonality was defined as the presence of KIT-mutated MC or by a clonal HUMARA test. The REMA score consisted of the assignment of positive or negative points as follows: male (+1), female (-1), sBt <15 μg/l (-1) or >25 μg/l (+2), presence (-2) or absence (+1) of pruritus, hives or angioedema and presence (+3) of presyncope or syncope. Efficiency of the REMA score for predicting MC clonality and SM was assessed by receiver operating characteristic (ROC) curve analyses and compared to those obtained by means of sBt levels alone. Molecular studies revealed the presence of clonal MC in 68/80 SM cases and in 11/78 patients who did not meet the criteria for SM. ROC curve analyses confirmed the greater sensitivity and a similar specificity of the REMA score versus sBt levels (84 vs. 59% and 74 vs. 70% for MC clonality and 87 vs. 62% and 73 vs. 71% for SM, respectively). Our results confirm the clinical utility of the REMA score to predict MC clonality and SM in patients suffering from systemic MC activation symptoms without MIS. Copyright © 2011 S. Karger AG, Basel.

Validation of the Brazilian Portuguese Version of Geriatric Anxiety Inventory--GAI-BR.

PubMed

Massena, Patrícia Nitschke; de Araújo, Narahyana Bom; Pachana, Nancy; Laks, Jerson; de Pádua, Analuiza Camozzato

2015-07-01

The Geriatric Anxiety Inventory (GAI) is a recently developed scale aiming to evaluate symptoms of anxiety in later life. This 20-item scale uses dichotomous answers highlighting non-somatic anxiety complaints of elderly people. The present study aimed to evaluate the psychometric properties of the Brazilian Portuguese version GAI (GAI-BR) in a sample from community and outpatient psychogeriatric clinic. A mixed convenience sample of 72 subjects was recruited for answering the research protocol. The interview procedures were structured with questionnaires about sociodemographic data, clinical health status, anxiety, and depression previously validated instruments, Mini-Mental State Examination, Mini International Neuropsychiatric Interview, and GAI-BR. Twenty-two percent of the sample were interviewed twice for test-retest reliability. For internal consistency analyses, the Cronbach's α test was applied. The Spearman correlation test was applied to evaluate the test-retest GAI-BR reliability. A ROC (receiver operating characteristic) curve study was made to estimate the GAI-BR area under curve, cut-off points, sensitivity, and specificity for the Generalized Anxiety Disorder diagnosis. The GAI-BR version showed high internal consistency (Cronbach's α = 0.91) and strong and significant test-retest reliability (ρ = 0.85, p < 0.001). It also showed moderate and significant correlation with the Beck Anxiety Inventory (ρ = 0.68, p < 0.001) and the State-Trait Anxiety Inventory (ρ = 0.61, p < 0.001) showing evidence of concurrent validation. The cut-off point of 13 estimated by ROC curve analyses showed sensitivity of 83.3% and specificity of 84.6% to detect Generalized Anxiety Disorder (DSM-IV). GAI-BR has demonstrated very good psychometric properties and can be a reliable instrument to measure anxiety in Brazilian elderly people.

Sensitivity and specificity of a screening test to document traumatic experiences and to diagnose post-traumatic stress disorder in ARDS patients after intensive care treatment.

PubMed

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.

The value of "liver windows" settings in the detection of small renal cell carcinomas on unenhanced computed tomography.

PubMed

Sahi, Kamal; Jackson, Stuart; Wiebe, Edward; Armstrong, Gavin; Winters, Sean; Moore, Ronald; Low, Gavin

2014-02-01

To assess if "liver window" settings improve the conspicuity of small renal cell carcinomas (RCC). Patients were analysed from our institution's pathology-confirmed RCC database that included the following: (1) stage T1a RCCs, (2) an unenhanced computed tomography (CT) abdomen performed ≤ 6 months before histologic diagnosis, and (3) age ≥ 17 years. Patients with multiple tumours, prior nephrectomy, von Hippel-Lindau disease, and polycystic kidney disease were excluded. The unenhanced CT was analysed, and the tumour locations were confirmed by using corresponding contrast-enhanced CT or magnetic resonance imaging studies. Representative single-slice axial, coronal, and sagittal unenhanced CT images were acquired in "soft tissue windows" (width, 400 Hounsfield unit (HU); level, 40 HU) and liver windows (width, 150 HU; level, 88 HU). In addition, single-slice axial, coronal, and sagittal unenhanced CT images of nontumourous renal tissue (obtained from the same cases) were acquired in soft tissue windows and liver windows. These data sets were randomized, unpaired, and were presented independently to 3 blinded radiologists for analysis. The presence or absence of suspicious findings for tumour was scored on a 5-point confidence scale. Eighty-three of 415 patients met the study criteria. Receiver operating characteristics (ROC) analysis, t test analysis, and kappa analysis were used. ROC analysis showed statistically superior diagnostic performance for liver windows compared with soft tissue windows (area under the curve of 0.923 vs 0.879; P = .0002). Kappa statistics showed "good" vs "moderate" agreement between readers for liver windows compared with soft tissue windows. Use of liver windows settings improves the detection of small RCCs on the unenhanced CT. Copyright © 2014 Canadian Association of Radiologists. Published by Elsevier Inc. All rights reserved.

The response time threshold for predicting favourable neurological outcomes in patients with bystander-witnessed out-of-hospital cardiac arrest.

PubMed

Ono, Yuichi; Hayakawa, Mineji; Iijima, Hiroaki; Maekawa, Kunihiko; Kodate, Akira; Sadamoto, Yoshihiro; Mizugaki, Asumi; Murakami, Hiromoto; Katabami, Kenichi; Sawamura, Atsushi; Gando, Satoshi

2016-10-01

It is well established that the period of time between a call being made to emergency medical services (EMS) and the time at which the EMS arrive at the scene (i.e. the response time) affects survival outcomes in patients who experience out-of-hospital cardiac arrest (OHCA). However, the relationship between the response time and favourable neurological outcomes remains unclear. We therefore aimed to determine a response time threshold in patients with bystander-witnessed OHCA that is associated with positive neurological outcomes and to assess the relationship between the response time and neurological outcomes in patients with OHCA. This study was a retrospective, observational analysis of data from 204,277 episodes of bystander-witnessed OHCA between 2006 and 2012 in Japan. We used classification and regression trees (CARTs) and receiver operating characteristic (ROC) curve analyses to determine the threshold of response time associated with favourable neurological outcomes (Cerebral Performance Category 1 or 2) 1 month after cardiac arrest. Both CARTs and ROC analyses indicated that a threshold of 6.5min was associated with improved neurological outcomes in all bystander-witnessed OHCA events of cardiac origin. Furthermore, bystander cardiopulmonary resuscitation (CPR) prolonged the threshold of response time by 1min (up to 7.5min). The adjusted odds ratio for favourable neurological outcomes in patients with OHCA who received care within ≤6.5min was 1.935 (95% confidential interval: 1.834-2.041, P<0.001). A response time of ≤6.5min was closely associated with favourable neurological outcomes in all bystander-witnessed patients with OHCA. Bystander CPR prolonged the response time threshold by 1min. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Nailfold Videocapillaroscopic Features and Other Clinical Risk Factors for Digital Ulcers in Systemic Sclerosis: A Multicenter, Prospective Cohort Study.

PubMed

Cutolo, Maurizio; Herrick, Ariane L; Distler, Oliver; Becker, Mike O; Beltran, Emma; Carpentier, Patrick; Ferri, Clodoveo; Inanç, Murat; Vlachoyiannopoulos, Panayiotis; Chadha-Boreham, Harbajan; Cottreel, Emmanuelle; Pfister, Thomas; Rosenberg, Daniel; Torres, Juan V; Smith, Vanessa

2016-10-01

To identify nailfold videocapillaroscopic features and other clinical risk factors for new digital ulcers (DUs) during a 6-month period in patients with systemic sclerosis (SSc). In this multicenter, prospective, observational cohort study, the videoCAPillaroscopy (CAP) study, we evaluated 623 patients with SSc from 59 centers (14 countries). Patients were stratified into 2 groups: a DU history group and a no DU history group. At enrollment, patients underwent detailed nailfold videocapillaroscopic evaluation and assessment of demographic characteristics, DU status, and clinical and SSc characteristics. Risk factors for developing new DUs were assessed using univariable and multivariable logistic regression (MLR) analyses. Of the 468 patients in the DU history group (mean ± SD age 54.0 ± 13.7 years), 79.5% were female, 59.8% had limited cutaneous SSc, and 22% developed a new DU during follow-up. The strongest risk factors for new DUs identified by MLR in the DU history group included the mean number of capillaries per millimeter in the middle finger of the dominant hand, the number of DUs (categorized as 0, 1, 2, or ≥3), and the presence of critical digital ischemia. The receiver operating characteristic (ROC) of the area under the curve (AUC) of the final MLR model was 0.738 (95% confidence interval [95% CI] 0.681-0.795). Internal validation through bootstrap generated a ROC AUC of 0.633 (95% CI 0.510-0.756). This international prospective study, which included detailed nailfold videocapillaroscopic evaluation and extensive clinical characterization of patients with SSc, identified the mean number of capillaries per millimeter in the middle finger of the dominant hand, the number of DUs at enrollment, and the presence of critical digital ischemia at enrollment as risk factors for the development of new DUs. © 2016, American College of Rheumatology.

Nailfold Videocapillaroscopic Features and Other Clinical Risk Factors for Digital Ulcers in Systemic Sclerosis: A Multicenter, Prospective Cohort Study

PubMed Central

Herrick, Ariane L.; Distler, Oliver; Becker, Mike O.; Beltran, Emma; Carpentier, Patrick; Ferri, Clodoveo; Inanç, Murat; Vlachoyiannopoulos, Panayiotis; Chadha‐Boreham, Harbajan; Cottreel, Emmanuelle; Pfister, Thomas; Rosenberg, Daniel; Torres, Juan V.; Cutolo, Maurizio; Herrick, Ariane L.; Distler, Oliver; Becker, Mike; Beltran, Emma; Carpentier, Patrick; Ferri, Clodoveo; Inanç, Murat; Vlachoyiannopoulos, Panayiotis; Smith, Vanessa; Erlacher, L; Hirschl, M; Kiener, HP; Pilger, E; Smith, V; Blockmans, D; Wautrecht, J‐C; Becvár, R; Carpentier, P; Frances, C; Lok, C; Sparsa, A; Hachulla, E; Quere, I; Allanore, Y; Agard, C; Riemekasten, G; Hunzelmann, N; Stücker, M; Ahmadi‐Simab, K; Sunderkötter, C; Wohlrab, J; Müller‐Ladner, U; Schneider, M; Vlachoyianopoulos, P; Vassilopoulos, D; Drosos, A; Antonopoulos, A; Balbir‐Gurman, A; Langevitz, P; Rosner, I; Levy, Y; Cutolo, M; Bombardieri, S; Ferraccioli, G; Mazzuca, S; Grassi, W; Lunardi, C; Airó, P; Riccieri, V; Voskuyl, AE; Schuerwegh, A; Santos, L; Rodrigues, AC; Grilo, A; Amaral, MC; Román Ivorra, JA; Castellvi, I; Distler, O; Spertini, F; Müller, R; Inanç, M; Oksel, F; Turkcapar, N; Herrick, A; Denton, C; McHugh, N; Chattopadhyay, C; Hall, F; Buch, M

2016-01-01

Objective To identify nailfold videocapillaroscopic features and other clinical risk factors for new digital ulcers (DUs) during a 6‐month period in patients with systemic sclerosis (SSc). Methods In this multicenter, prospective, observational cohort study, the videoCAPillaroscopy (CAP) study, we evaluated 623 patients with SSc from 59 centers (14 countries). Patients were stratified into 2 groups: a DU history group and a no DU history group. At enrollment, patients underwent detailed nailfold videocapillaroscopic evaluation and assessment of demographic characteristics, DU status, and clinical and SSc characteristics. Risk factors for developing new DUs were assessed using univariable and multivariable logistic regression (MLR) analyses. Results Of the 468 patients in the DU history group (mean ± SD age 54.0 ± 13.7 years), 79.5% were female, 59.8% had limited cutaneous SSc, and 22% developed a new DU during follow‐up. The strongest risk factors for new DUs identified by MLR in the DU history group included the mean number of capillaries per millimeter in the middle finger of the dominant hand, the number of DUs (categorized as 0, 1, 2, or ≥3), and the presence of critical digital ischemia. The receiver operating characteristic (ROC) of the area under the curve (AUC) of the final MLR model was 0.738 (95% confidence interval [95% CI] 0.681–0.795). Internal validation through bootstrap generated a ROC AUC of 0.633 (95% CI 0.510–0.756). Conclusion This international prospective study, which included detailed nailfold videocapillaroscopic evaluation and extensive clinical characterization of patients with SSc, identified the mean number of capillaries per millimeter in the middle finger of the dominant hand, the number of DUs at enrollment, and the presence of critical digital ischemia at enrollment as risk factors for the development of new DUs. PMID:27111549

Homology search with binary and trinary scoring matrices.

PubMed

Smith, Scott F

2006-01-01

Protein homology search can be accelerated with the use of bit-parallel algorithms in conjunction with constraints on the values contained in the scoring matrices. Trinary scoring matrices (containing only the values -1, 0, and 1) allow for significant acceleration without significant reduction in the receiver operating characteristic (ROC) score of a Smith-Waterman search. Binary scoring matrices (containing the values 0 and 1) result in some reduction in ROC score, but result in even more acceleration. Binary scoring matrices and five-bit saturating scores can be used for fast prefilters to the Smith-Waterman algorithm.

Proximal caries detection: Sirona Sidexis versus Kodak Ektaspeed Plus.

PubMed

Khan, Emad A; Tyndall, Donald A; Ludlow, John B; Caplan, Daniel

2005-01-01

This study compared the accuracy of intraoral film and a charge-coupled device (CCD) receptor for proximal caries detection. Four observers evaluated images of the proximal surfaces of 40 extracted posterior teeth. The presence or absence of caries was scored using a five-point confidence scale. The actual status of each surface was determined from ground section histology. Responses were evaluated by means of receiver operating characteristic (ROC) analysis. Areas under ROC curves (Az) were assessed through a paired t-test. The performance of the CCD-based intraoral sensor was not different statistically from Ektaspeed Plus film in detecting proximal caries.

Evaluation of basal sex hormone levels for activation of the hypothalamic-pituitary-gonadal axis.

PubMed

Ding, Yu; Li, Juan; Yu, Yongguo; Yang, Peirong; Li, Huaiyuan; Shen, Yongnian; Huang, Xiaodong; Liu, Shijian

2018-03-28

This study aimed to identify the predictive value of basal sex hormone levels for activation of the hypothalamic-pituitary-gonadal (HPG) axis in girls. Gonadotropin-releasing hormone (GnRH) stimulation tests were performed and evaluated in a total of 1750 girls with development of secondary sex characteristics. Correlation analyses were conducted between basal sex hormones and peak luteinizing hormone (LH) levels ≥5 IU/L during the GnRH stimulation test. Receiver operating characteristic (ROC) curves for basal levels of LH, follicle-stimulating hormone (FSH), LH/FSH, and estradiol (E2) before the GnRH stimulation test were plotted. The area under the curve (AUC) and 95% confidence intervals (CIs) were measured for each curve. The maximum AUC value was observed for basal LH levels (0.77, 95% CI: 0.74-0.79), followed by basal FSH levels (0.73, 95% CI: 0.70-0.75), the basal LH/FSH ratio (0.68, 95% CI: 0.65-0.71), and basal E2 levels (0.61, 95% CI: 0.59-0.64). The appropriate cutoff value of basal LH levels associated with a positive response of the GnRH stimulation test was 0.35 IU/L, with a sensitivity of 63.96% and specificity of 76.3% from the ROC curves when Youden's index showed the maximum value. When 100% of patients had peak LH levels ≥5 IU/L, basal LH values were >2.72 IU/L, but the specificity was only 5.45%. Increased basal LH levels are a significant predictor of a positive response during the GnRH stimulation test for assessing activation of the HPG axis in most girls with early pubertal signs.

Oxidative status in different settings and with different methodological approaches compared by Receiver Operating Characteristic curve analysis.

PubMed

Cighetti, Giuliana; Bamonti, Fabrizia; Aman, Caroline S; Gregori, Dario; De Giuseppe, Rachele; Novembrino, Cristina; de Liso, Federica; Maiavacca, Rita; Paroni, Rita

2015-01-01

To test the performance of different analytical approaches in highlighting the occurrence of deregulated redox status in various physio-pathological situations. 35 light and 61 heavy smokers, 19 chronic renal failure, 59 kidney transplanted patients, and 87 healthy controls were retrospectively considered for the study. Serum oxidative stress and antioxidant status, assessed by spectrophotometric Reactive Oxygen Metabolites (d-ROMs) and Total Antioxidant Capacity (TAC) tests, respectively, were compared with plasma free (F-MDA) and total (T-MDA) malondialdehyde, both quantified by isotope-dilution-gas chromatography-mass spectrometry (ID-GC-MS). Sensitivity, specificity and cut-off points of T-MDA, F-MDA, d-ROMs and TAC were evaluated by both Receiver Operating Characteristic (ROC) analyses and area under the ROC curve (AUC). Only T-MDA assay showed a clear absence of oxidative stress in controls and significant increase in all patients (AUC 1.00, sensitivity and specificity 100%). Accuracy was good for d-ROMs (AUC 0.87, sensitivity 72.8%, specificity 100%) and F-MDA (AUC 0.82, sensitivity 74.7%, specificity 83.9%), but not high enough for TAC to show in patients impaired antioxidant defense (AUC 0.66, sensitivity 52.0%, specificity 92.9%). This study reveals T-MDA as the best marker to detect oxidative stress, shows the ability of d-ROMs to identify modified oxidative status particularly in the presence of high damages, and evidences the poor TAC performance. d-ROMs and TAC assays could be useful for routine purposes; however, for an accurate clinical data evaluation, their comparison versus a "gold standard method" is required. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Automatic Mexico Gulf Oil Spill Detection from Radarsat-2 SAR Satellite Data Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Marghany, Maged

2016-10-01

In this work, a genetic algorithm is exploited for automatic detection of oil spills of small and large size. The route is achieved using arrays of RADARSAT-2 SAR ScanSAR Narrow single beam data obtained in the Gulf of Mexico. The study shows that genetic algorithm has automatically segmented the dark spot patches related to small and large oil spill pixels. This conclusion is confirmed by the receiveroperating characteristic (ROC) curve and ground data which have been documented. The ROC curve indicates that the existence of oil slick footprints can be identified with the area under the curve between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. The small oil spill sizes represented 30% of the discriminated oil spill pixels in ROC curve. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills of either small or large size and the ScanSAR Narrow single beam mode serves as an excellent sensor for oil spill patterns detection and surveying in the Gulf of Mexico.

Inflammatory Asthma Phenotype Discrimination Using an Electronic Nose Breath Analyzer.

PubMed

Plaza, V; Crespo, A; Giner, J; Merino, J L; Ramos-Barbón, D; Mateus, E F; Torrego, A; Cosio, B G; Agustí, A; Sibila, O

2015-01-01

Patients with persistent asthma have different inflammatory phenotypes. The electronic nose is a new technology capable of distinguishing volatile organic compound (VOC) breath-prints in exhaled breath. The aim of the study was to investigate the capacity of electronic nose breath-print analysis to discriminate between different inflammatory asthma phenotypes (eosinophilic, neutrophilic, paucigranulocytic) determined by induced sputum in patients with persistent asthma. Fifty-two patients with persistent asthma were consecutively included in a cross-sectional proof-of-concept study. Inflammatory asthma phenotypes (eosinophilic, neutrophilic and paucigranulocytic) were recognized by inflammatory cell counts in induced sputum. VOC breath-prints were analyzed using the electronic nose Cyranose 320 and assessed by discriminant analysis on principal component reduction, resulting in cross-validated accuracy values. Receiver operating characteristic (ROC) curves were calculated. VOC breath-prints were different in eosinophilic asthmatics compared with both neutrophilic asthmatics (accuracy 73%; P=.008; area under ROC, 0.92) and paucigranulocytic asthmatics (accuracy 74%; P=.004; area under ROC, 0.79). Likewise, neutrophilic and paucigranulocytic breath-prints were also different (accuracy 89%; P=.001; area under ROC, 0.88). An electronic nose can discriminate inflammatory phenotypes in patients with persistent asthma in a regular clinical setting. ClinicalTrials.gov identifier: NCT02026336.

Estimating the Area Under ROC Curve When the Fitted Binormal Curves Demonstrate Improper Shape.

PubMed

Bandos, Andriy I; Guo, Ben; Gur, David

2017-02-01

The "binormal" model is the most frequently used tool for parametric receiver operating characteristic (ROC) analysis. The binormal ROC curves can have "improper" (non-concave) shapes that are unrealistic in many practical applications, and several tools (eg, PROPROC) have been developed to address this problem. However, due to the general robustness of binormal ROCs, the improperness of the fitted curves might carry little consequence for inferences about global summary indices, such as the area under the ROC curve (AUC). In this work, we investigate the effect of severe improperness of fitted binormal ROC curves on the reliability of AUC estimates when the data arise from an actually proper curve. We designed theoretically proper ROC scenarios that induce severely improper shape of fitted binormal curves in the presence of well-distributed empirical ROC points. The binormal curves were fitted using maximum likelihood approach. Using simulations, we estimated the frequency of severely improper fitted curves, bias of the estimated AUC, and coverage of 95% confidence intervals (CIs). In Appendix S1, we provide additional information on percentiles of the distribution of AUC estimates and bias when estimating partial AUCs. We also compared the results to a reference standard provided by empirical estimates obtained from continuous data. We observed up to 96% of severely improper curves depending on the scenario in question. The bias in the binormal AUC estimates was very small and the coverage of the CIs was close to nominal, whereas the estimates of partial AUC were biased upward in the high specificity range and downward in the low specificity range. Compared to a non-parametric approach, the binormal model led to slightly more variable AUC estimates, but at the same time to CIs with more appropriate coverage. The improper shape of the fitted binormal curve, by itself, ie, in the presence of a sufficient number of well-distributed points, does not imply unreliable AUC-based inferences. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Measuring diagnostic and predictive accuracy in disease management: an introduction to receiver operating characteristic (ROC) analysis.

PubMed

Linden, Ariel

2006-04-01

Diagnostic or predictive accuracy concerns are common in all phases of a disease management (DM) programme, and ultimately play an influential role in the assessment of programme effectiveness. Areas, such as the identification of diseased patients, predictive modelling of future health status and costs and risk stratification, are just a few of the domains in which assessment of accuracy is beneficial, if not critical. The most commonly used analytical model for this purpose is the standard 2 x 2 table method in which sensitivity and specificity are calculated. However, there are several limitations to this approach, including the reliance on a single defined criterion or cut-off for determining a true-positive result, use of non-standardized measurement instruments and sensitivity to outcome prevalence. This paper introduces the receiver operator characteristic (ROC) analysis as a more appropriate and useful technique for assessing diagnostic and predictive accuracy in DM. Its advantages include; testing accuracy across the entire range of scores and thereby not requiring a predetermined cut-off point, easily examined visual and statistical comparisons across tests or scores, and independence from outcome prevalence. Therefore the implementation of ROC as an evaluation tool should be strongly considered in the various phases of a DM programme.

Receiver Operating Characteristic Curve Analysis of Beach Water Quality Indicator Variables

PubMed Central

Morrison, Ann Michelle; Coughlin, Kelly; Shine, James P.; Coull, Brent A.; Rex, Andrea C.

2003-01-01

Receiver operating characteristic (ROC) curve analysis is a simple and effective means to compare the accuracies of indicator variables of bacterial beach water quality. The indicator variables examined in this study were previous day's Enterococcus density and antecedent rainfall at 24, 48, and 96 h. Daily Enterococcus densities and 15-min rainfall values were collected during a 5-year (1996 to 2000) study of four Boston Harbor beaches. The indicator variables were assessed for their ability to correctly classify water as suitable or unsuitable for swimming at a maximum threshold Enterococcus density of 104 CFU/100 ml. Sensitivity and specificity values were determined for each unique previous day's Enterococcus density and antecedent rainfall volume and used to construct ROC curves. The area under the ROC curve was used to compare the accuracies of the indicator variables. Twenty-four-hour antecedent rainfall classified elevated Enterococcus densities more accurately than previous day's Enterococcus density (P = 0.079). An empirically derived threshold for 48-h antecedent rainfall, corresponding to a sensitivity of 0.75, was determined from the 1996 to 2000 data and evaluated to ascertain if the threshold would produce a 0.75 sensitivity with independent water quality data collected in 2001 from the same beaches. PMID:14602593

Receiver operating characteristic analysis of age-related changes in lineup performance.

PubMed

Humphries, Joyce E; Flowe, Heather D

2015-04-01

In the basic face memory literature, support has been found for the late maturation hypothesis, which holds that face recognition ability is not fully developed until at least adolescence. Support for the late maturation hypothesis in the criminal lineup identification literature, however, has been equivocal because of the analytic approach that has been used to examine age-related changes in identification performance. Recently, receiver operator characteristic (ROC) analysis was applied for the first time in the adult eyewitness memory literature to examine whether memory sensitivity differs across different types of lineup tests. ROC analysis allows for the separation of memory sensitivity from response bias in the analysis of recognition data. Here, we have made the first ROC-based comparison of adults' and children's (5- and 6-year-olds and 9- and 10-year-olds) memory performance on lineups by reanalyzing data from Humphries, Holliday, and Flowe (2012). In line with the late maturation hypothesis, memory sensitivity was significantly greater for adults compared with young children. Memory sensitivity for older children was similar to that for adults. The results indicate that the late maturation hypothesis can be generalized to account for age-related performance differences on an eyewitness memory task. The implications for developmental eyewitness memory research are discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

Determining decision thresholds and evaluating indicators when conservation status is measured as a continuum.

PubMed

Connors, B M; Cooper, A B

2014-12-01

Categorization of the status of populations, species, and ecosystems underpins most conservation activities. Status is often based on how a system's current indicator value (e.g., change in abundance) relates to some threshold of conservation concern. Receiver operating characteristic (ROC) curves can be used to quantify the statistical reliability of indicators of conservation status and evaluate trade-offs between correct (true positive) and incorrect (false positive) classifications across a range of decision thresholds. However, ROC curves assume a discrete, binary relationship between an indicator and the conservation status it is meant to track, which is a simplification of the more realistic continuum of conservation status, and may limit the applicability of ROC curves in conservation science. We describe a modified ROC curve that treats conservation status as a continuum rather than a discrete state. We explored the influence of this continuum and typical sources of variation in abundance that can lead to classification errors (i.e., random variation and measurement error) on the true and false positive rates corresponding to varying decision thresholds and the reliability of change in abundance as an indicator of conservation status, respectively. We applied our modified ROC approach to an indicator of endangerment in Pacific salmon (Oncorhynchus nerka) (i.e., percent decline in geometric mean abundance) and an indicator of marine ecosystem structure and function (i.e., detritivore biomass). Failure to treat conservation status as a continuum when choosing thresholds for indicators resulted in the misidentification of trade-offs between true and false positive rates and the overestimation of an indicator's reliability. We argue for treating conservation status as a continuum when ROC curves are used to evaluate decision thresholds in indicators for the assessment of conservation status. © 2014 Society for Conservation Biology.

Three-class ROC analysis--the equal error utility assumption and the optimality of three-class ROC surface using the ideal observer.

PubMed

He, Xin; Frey, Eric C

2006-08-01

Previously, we have developed a decision model for three-class receiver operating characteristic (ROC) analysis based on decision theory. The proposed decision model maximizes the expected decision utility under the assumption that incorrect decisions have equal utilities under the same hypothesis (equal error utility assumption). This assumption reduced the dimensionality of the "general" three-class ROC analysis and provided a practical figure-of-merit to evaluate the three-class task performance. However, it also limits the generality of the resulting model because the equal error utility assumption will not apply for all clinical three-class decision tasks. The goal of this study was to investigate the optimality of the proposed three-class decision model with respect to several other decision criteria. In particular, besides the maximum expected utility (MEU) criterion used in the previous study, we investigated the maximum-correctness (MC) (or minimum-error), maximum likelihood (ML), and Nyman-Pearson (N-P) criteria. We found that by making assumptions for both MEU and N-P criteria, all decision criteria lead to the previously-proposed three-class decision model. As a result, this model maximizes the expected utility under the equal error utility assumption, maximizes the probability of making correct decisions, satisfies the N-P criterion in the sense that it maximizes the sensitivity of one class given the sensitivities of the other two classes, and the resulting ROC surface contains the maximum likelihood decision operating point. While the proposed three-class ROC analysis model is not optimal in the general sense due to the use of the equal error utility assumption, the range of criteria for which it is optimal increases its applicability for evaluating and comparing a range of diagnostic systems.

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays.

PubMed

Goodman, Corey W; Major, Heather J; Walls, William D; Sheffield, Val C; Casavant, Thomas L; Darbro, Benjamin W

2015-04-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. Copyright © 2015 Elsevier Inc. All rights reserved.

Determination of glucose-6-phosphate dehydrogenase cut-off values in a Tunisian population.

PubMed

Laouini, Naouel; Sahli, Chaima Abdelhafidh; Jouini, Latifa; Haloui, Sabrine; Fredj, Sondes Hadj; Daboubi, Rym; Siala, Hajer; Ouali, Faida; Becher, Meriam; Toumi, Nourelhouda; Bibi, Amina; Messsaoud, Taieb

2017-07-26

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is the commonest enzymopathy worldwide. The incidence depends essentially on the methods used for the assessment. In this respect, we attempted in this study to set cut-off values of G6PD activity to discriminate among normal, heterozygous, and deficient individuals using the World Health Organization (WHO) classification and the receiver operating characteristics (ROC) curve analysis. Blood samples from 250 female and 302 male subjects were enrolled in this study. The G6PD activity was determined using a quantitative assay. The common G6PD mutations in Tunisia were determined using the amplification refractory mutation system (ARMS-PCR) method. The ROC curve was used to choice the best cut-off. Normal G6PD values were 7.69±2.37, 7.86±2.39, and 7.51±2.35 U/g Hb for the entire, male, and female groups, respectively. Cut-off values for the total, male, and female were determined using the WHO classification and ROC curves analysis. In the male population, both cut-offs established using ROC curve analysis (4.00 U/g Hb) and the 60% level (3.82 U/g Hb), respectively are sensitive and specific resulting in a good efficiency of discrimination between deficient and normal males. For the female group the ROC cut-off (5.84 U/g Hb) seems better than the 60% level cut-off (3.88 U/g Hb) to discriminate between normal and heterozygote or homozygote women with higher Youden Index. The establishment of the normal values for a population is important for a better evaluation of the assay result. The ROC curve analysis is an alternative method to determine the status of patients since it correlates DNA analysis and G6PD activity.

The Landscape of Circular RNA Expression Profiles in Papillary Thyroid Carcinoma Based on RNA Sequencing.

PubMed

Lan, Xiabin; Xu, Jiajie; Chen, Chao; Zheng, Chuanming; Wang, Jiafeng; Cao, Jun; Zhu, Xuhang; Ge, Minghua

2018-05-25

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. However, the molecular mechanisms responsible for its tumorigenesis and progression remain largely unknown. Circular RNA (circRNA) is a novel type of noncoding RNA that can serve as an ideal biomarker due to its stability. Recent evidence suggests that circRNAs play important roles in tumorigenesis. This study aims to investigate circRNA expression profiles and their potential biological functions in PTC. High-throughput RNA sequencing was used to assess circRNA expression profiles in PTC, and quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate dysregulated circRNAs. Receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic value of circRNAs for PTC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were employed to determine the biological functions of differentially expressed circRNAs. Bioinformatic analyses were applied to predict interactions between circRNAs and microRNAs (miRNAs), and a circRNA-miRNA-mRNA network was constructed using Cytoscape software. We identified a number of differentially expressed circRNAs in PTC tissues compared with paired normal thyroid tissues, with chr5: 160757890-160763776-, chr12: 40696591-40697936+, chr7: 22330794-22357656-, and chr21: 16386665-16415895- being upregulated, and chr7: 91924203-91957214+, chr2: 179514891-179516047-, chr9: 16435553-16437522-, and chr22: 36006931-36007153- being downregulated. These findings were confirmed by qRT-PCR, and ROC curves indicated that they can serve as potential biomarkers for PTC. GO and KEGG pathway analyses showed that some of these circRNAs are related to cancers. Additionally, bioinformatic analyses revealed a potential competing-endogenous-RNA-regulating network among circRNAs, miRNAs, and mRNAs. Our study results depict the landscape of circRNA expression profiles in PTC and also provide potential biomarkers for PTC. Further functional and mechanistic studies of these circRNAs may improve our understanding of PTC tumorigenesis. © 2018 The Author(s). Published by S. Karger AG, Basel.

The correlational research among serum CXCL13 levels, circulating plasmablasts and memory B cells in patients with systemic lupus erythematosus: A STROBE-compliant article.

PubMed

Fang, Chenglong; Luo, Tingting; Lin, Ling

2017-12-01

We investigated whether serum CXC ligand 13 protein (CXCL13) levels correlate with the circulating plasmablasts and memory B-cells alteration in systemic lupus erythematosus (SLE) patients. The diagnostic use of CXCL13 concentrations in active lupus was also analyzed.A total of 36 SLE patients and 18 healthy controls were included. Serum CXCL13 levels were examined by enzyme-linked immunosorbent assay. The frequency and absolute count of circulating plasmablasts and memory B cells were analyzed by flow cytometry. Receiver operating characteristic curves (ROC curves) were generated to analyze the utility of serum CXCL13 level and plasmablasts frequency as tools for the recognition of active SLE.Elevation of serum CXCL13 levels, higher plasmablasts frequency, and reduction of memory B-cells count were observed in SLE patients, compared with healthy controls. Interestingly, correlational analyses showed not only significantly positive association between CXCL13 levels and SLE Disease Activity Index (SLEDAI) or plasmablasts frequency, but an inverse correlation between CXCL13 concentration and memory B-cell count. ROC curves showed that serum CXCL13 level and plasmablasts frequency were practical in identifying active disease from overall SLE patients, with considerable accuracy.Serum CXCL13 levels correlate with the alteration of plasmablasts and memory B cells in SLE. CXCL13 may be used as a practical tool in judgment of active SLE.

A signal-detection-based diagnostic-feature-detection model of eyewitness identification.

PubMed

Wixted, John T; Mickes, Laura

2014-04-01

The theoretical understanding of eyewitness identifications made from a police lineup has long been guided by the distinction between absolute and relative decision strategies. In addition, the accuracy of identifications associated with different eyewitness memory procedures has long been evaluated using measures like the diagnosticity ratio (the correct identification rate divided by the false identification rate). Framed in terms of signal-detection theory, both the absolute/relative distinction and the diagnosticity ratio are mainly relevant to response bias while remaining silent about the key issue of diagnostic accuracy, or discriminability (i.e., the ability to tell the difference between innocent and guilty suspects in a lineup). Here, we propose a signal-detection-based model of eyewitness identification, one that encourages the use of (and helps to conceptualize) receiver operating characteristic (ROC) analysis to measure discriminability. Recent ROC analyses indicate that the simultaneous presentation of faces in a lineup yields higher discriminability than the presentation of faces in isolation, and we propose a diagnostic feature-detection hypothesis to account for that result. According to this hypothesis, the simultaneous presentation of faces allows the eyewitness to appreciate that certain facial features (viz., those that are shared by everyone in the lineup) are non-diagnostic of guilt. To the extent that those non-diagnostic features are discounted in favor of potentially more diagnostic features, the ability to discriminate innocent from guilty suspects will be enhanced.

Quantitative Criteria to Screen for Cannabis Use Disorder.

PubMed

Casajuana, Cristina; López-Pelayo, Hugo; Miquel, Laia; Balcells-Oliveró, María Mercedes; Colom, Joan; Gual, Antoni

2018-06-27

The Standard Joint Unit (1 SJU = 7 mg of 9-Tetrahydrocannabinol) simplifies the exploration of risky patterns of cannabis use. This study proposes a preliminary quantitative cutoff criterion to screen for cannabis use disorder (CUD). Socio-demographical data and information on cannabis quantities, frequency of use, and risk for CUD (measured with the Cannabis Abuse Screening Test (CAST) of cannabis users recruited in Barcelona (from February 2015 to June 2016) were collected. CAST scores were categorized into low, moderate, and high risk for CUD, based on the SJU consumed and frequency. Receiver operating characteristic (ROC) analysis related daily SJU with CUD. Participants (n = 473) were on average 29 years old (SD = 10), men (77.1%), and single (74.6%). With an average of 4 joints per smoking day, 82.5% consumed cannabis almost every day. Risk for CUD (9.40% low, 23.72% moderate, 66.88% high) increased significantly with more frequency and quantities consumed. The ROC analyses suggest 1.2 SJU per day as a cutoff criterion to screen for at least moderate risk for CUD (sensitivity 69.4%, specificity 63.6%). Frequency and quantity should be considered when exploring cannabis risks. A 1 SJU per day is proposed as a preliminary quantitative-based criterion to screen users with at least a moderate risk for CUD. © 2018 S. Karger AG, Basel.

Potential role of liver enzymes levels as predictor markers of glucose metabolism disorders in Tunisian population.

PubMed

Bouhajja, Houda; Abdelhedi, Rania; Amouri, Ali; Hadj Kacem, Faten; Marrakchi, Rim; Safi, Wajdi; Mrabet, Houcem; Chtourou, Lassaad; Charfi, Nadia; Fourati, Mouna; Bensassi, Salwa; Jamoussi, Kamel; Abid, Mohamed; Ayadi, Hammadi; Feki, Mouna Mnif; Elleuch, Noura Bougacha

2018-03-10

The relationship between liver enzymes and type 2 diabetes (T2D) risk is inconclusive. We aimed to evaluate the association between liver markers and risk of carbohydrate metabolism disorders and their discriminatory power for T2D prediction. This cross-sectional study enrolled 216 participants classified as normoglycemic, prediabetes, newly-diagnosed diabetes and diagnosed diabetes. All participants underwent anthropometric and biochemical measurements. The relationship between hepatic enzymes and glucose metabolism markers was evaluated by ANCOVA analyses. The associations between liver enzymes and incident carbohydrate metabolism disorders were analyzed through logistic regression and their discriminatory capacity for T2D by receiver operating characteristic (ROC) analysis. High alkaline phosphatase (AP), alanine aminotransferase (ALT), γ-glutamyltransferase (γGT) and aspartate aminotrasferase (AST) levels were independently related to decreased insulin sensitivity. Interestingly, higher AP level was significantly associated with increased risk of prediabetes (p=0.017), newly-diagnosed diabetes (p=0.004) and T2D (p=0.007). Elevated γGT level was an independent risk factor for T2D (p=0.032) and undiagnosed-T2D (p=0.010) in prediabetic and normoglycemic subjects, respectively. In ROC analysis, AP was a powerful predictor of incident diabetes and significantly improved T2D prediction. Liver enzymes within normal range, specifically AP levels, are associated with increased risk of carbohydrate metabolism disorders and significantly improved T2D prediction.

A preliminary evaluation of the validity of binge-eating disorder defining features in a community-based sample.

PubMed

Klein, Kelly M; Forney, K Jean; Keel, Pamela K

2016-05-01

Little empirical attention has been paid to the DSM-5 definition of binge-eating disorder (BED), particularly to the associated features of binge episodes. The present study sought to determine how the associated features and undue influence of weight/shape on self-evaluation contribute to evidence of a clinically significant eating disorder. Secondary analyses were conducted on data (N = 80; 76.3% women, 76.3% Caucasian, ages 18-43) collected through an epidemiological study of eating patterns. Descriptive statistics were used to report the sample prevalence of the features, independently and in combination. Correlations and alpha reliability were employed to examine relationships among associated features, distress regarding bingeing, and clinical diagnosis. Regression models and receiver-operating characteristic (ROC) curves were used to determine the utility of the features for explaining variance in distress. Internal consistency reliability for indicators was low, and several features demonstrated low or nonsignificant associations with distress and diagnosis. Feeling disgusted/depressed/guilty was the only unique predictor of distress (p = 0.001). For the ROC curves, three features was the best threshold for predicting distress. Results support the need to refine the features to ensure better detection of clinically significant eating pathology for research inclusion and treatment of the illness. © 2015 Wiley Periodicals, Inc. (Int J Eat Disord 2016; 49:524-528). © 2015 Wiley Periodicals, Inc.

Three regularities of recognition memory: the role of bias.

PubMed

Hilford, Andrew; Maloney, Laurence T; Glanzer, Murray; Kim, Kisok

2015-12-01

A basic assumption of Signal Detection Theory is that decisions are made on the basis of likelihood ratios. In a preceding paper, Glanzer, Hilford, and Maloney (Psychonomic Bulletin & Review, 16, 431-455, 2009) showed that the likelihood ratio assumption implies that three regularities will occur in recognition memory: (1) the Mirror Effect, (2) the Variance Effect, (3) the normalized Receiver Operating Characteristic (z-ROC) Length Effect. The paper offered formal proofs and computational demonstrations that decisions based on likelihood ratios produce the three regularities. A survey of data based on group ROCs from 36 studies validated the likelihood ratio assumption by showing that its three implied regularities are ubiquitous. The study noted, however, that bias, another basic factor in Signal Detection Theory, can obscure the Mirror Effect. In this paper we examine how bias affects the regularities at the theoretical level. The theoretical analysis shows: (1) how bias obscures the Mirror Effect, not the other two regularities, and (2) four ways to counter that obscuring. We then report the results of five experiments that support the theoretical analysis. The analyses and the experimental results also demonstrate: (1) that the three regularities govern individual, as well as group, performance, (2) alternative explanations of the regularities are ruled out, and (3) that Signal Detection Theory, correctly applied, gives a simple and unified explanation of recognition memory data.

Prognostic value of preoperative serum CA 242 in Esophageal squamous cell carcinoma cases.

PubMed

Feng, Ji-Feng; Huang, Ying; Chen, Qi-Xun

2013-01-01

Carbohydrate antigen (CA) 242 is inversely related to prognosis in many cancers. However, few data regarding CA 242 in esophageal cancer (EC) are available. The aim of this study was to determine the prognostic value of CA 242 and propose an optimum cut-off point in predicting survival difference in patients with esophageal squamous cell carcinoma (ESCC). A retrospective analysis was conducted of 192 cases. A receiver operating characteristic (ROC) curve for survival prediction was plotted to verify the optimum cuf- off point. Univariate and multivariate analyses were performed to evaluate prognostic parameters for survival. The positive rate for CA 242 was 7.3% (14/192). The ROC curve for survival prediction gave an optimum cut-off of 2.15 (U/ml). Patients with CA 242 ≤ 2.15 U/ml had significantly better 5-year survival than patients with CA 242 >2.15 U/ml (45.4% versus 22.6%; P=0.003). Multivariate analysis showed that differentiation (P=0.033), CA 242 (P=0.017), T grade (P=0.004) and N staging (P<0.001) were independent prognostic factors. Preoperative CA 242 is a predictive factor for long-term survival in ESCC, especially in nodal-negative patients. We conclude that 2.15 U/ml may be the optimum cuf-off point for CA 242 in predicting survival in ESCC.

A better way to evaluate remote monitoring programs in chronic disease care: receiver operating characteristic analysis.

PubMed

Brown Connolly, Nancy E

2014-12-01

This foundational study applies the process of receiver operating characteristic (ROC) analysis to evaluate utility and predictive value of a disease management (DM) model that uses RM devices for chronic obstructive pulmonary disease (COPD). The literature identifies a need for a more rigorous method to validate and quantify evidence-based value for remote monitoring (RM) systems being used to monitor persons with a chronic disease. ROC analysis is an engineering approach widely applied in medical testing, but that has not been evaluated for its utility in RM. Classifiers (saturated peripheral oxygen [SPO2], blood pressure [BP], and pulse), optimum threshold, and predictive accuracy are evaluated based on patient outcomes. Parametric and nonparametric methods were used. Event-based patient outcomes included inpatient hospitalization, accident and emergency, and home health visits. Statistical analysis tools included Microsoft (Redmond, WA) Excel(®) and MedCalc(®) (MedCalc Software, Ostend, Belgium) version 12 © 1993-2013 to generate ROC curves and statistics. Persons with COPD were monitored a minimum of 183 days, with at least one inpatient hospitalization within 12 months prior to monitoring. Retrospective, de-identified patient data from a United Kingdom National Health System COPD program were used. Datasets included biometric readings, alerts, and resource utilization. SPO2 was identified as a predictive classifier, with an optimal average threshold setting of 85-86%. BP and pulse were failed classifiers, and areas of design were identified that may improve utility and predictive capacity. Cost avoidance methodology was developed. RESULTS can be applied to health services planning decisions. Methods can be applied to system design and evaluation based on patient outcomes. This study validated the use of ROC in RM program evaluation.

Theoretical vs. empirical discriminability: the application of ROC methods to eyewitness identification.

PubMed

Wixted, John T; Mickes, Laura

2018-01-01

Receiver operating characteristic (ROC) analysis was introduced to the field of eyewitness identification 5 years ago. Since that time, it has been both influential and controversial, and the debate has raised an issue about measuring discriminability that is rarely considered. The issue concerns the distinction between empirical discriminability (measured by area under the ROC curve) vs. underlying/theoretical discriminability (measured by d' or variants of it). Under most circumstances, the two measures will agree about a difference between two conditions in terms of discriminability. However, it is possible for them to disagree, and that fact can lead to confusion about which condition actually yields higher discriminability. For example, if the two conditions have implications for real-world practice (e.g., a comparison of competing lineup formats), should a policymaker rely on the area-under-the-curve measure or the theory-based measure? Here, we illustrate the fact that a given empirical ROC yields as many underlying discriminability measures as there are theories that one is willing to take seriously. No matter which theory is correct, for practical purposes, the singular area-under-the-curve measure best identifies the diagnostically superior procedure. For that reason, area under the ROC curve informs policy in a way that underlying theoretical discriminability never can. At the same time, theoretical measures of discriminability are equally important, but for a different reason. Without an adequate theoretical understanding of the relevant task, the field will be in no position to enhance empirical discriminability.

AVC: Selecting discriminative features on basis of AUC by maximizing variable complementarity.

PubMed

Sun, Lei; Wang, Jun; Wei, Jinmao

2017-03-14

The Receiver Operator Characteristic (ROC) curve is well-known in evaluating classification performance in biomedical field. Owing to its superiority in dealing with imbalanced and cost-sensitive data, the ROC curve has been exploited as a popular metric to evaluate and find out disease-related genes (features). The existing ROC-based feature selection approaches are simple and effective in evaluating individual features. However, these approaches may fail to find real target feature subset due to their lack of effective means to reduce the redundancy between features, which is essential in machine learning. In this paper, we propose to assess feature complementarity by a trick of measuring the distances between the misclassified instances and their nearest misses on the dimensions of pairwise features. If a misclassified instance and its nearest miss on one feature dimension are far apart on another feature dimension, the two features are regarded as complementary to each other. Subsequently, we propose a novel filter feature selection approach on the basis of the ROC analysis. The new approach employs an efficient heuristic search strategy to select optimal features with highest complementarities. The experimental results on a broad range of microarray data sets validate that the classifiers built on the feature subset selected by our approach can get the minimal balanced error rate with a small amount of significant features. Compared with other ROC-based feature selection approaches, our new approach can select fewer features and effectively improve the classification performance.

Optimal algorithm for automatic detection of microaneurysms based on receiver operating characteristic curve

NASA Astrophysics Data System (ADS)

Xu, Lili; Luo, Shuqian

2010-11-01

Microaneurysms (MAs) are the first manifestations of the diabetic retinopathy (DR) as well as an indicator for its progression. Their automatic detection plays a key role for both mass screening and monitoring and is therefore in the core of any system for computer-assisted diagnosis of DR. The algorithm basically comprises the following stages: candidate detection aiming at extracting the patterns possibly corresponding to MAs based on mathematical morphological black top hat, feature extraction to characterize these candidates, and classification based on support vector machine (SVM), to validate MAs. Feature vector and kernel function of SVM selection is very important to the algorithm. We use the receiver operating characteristic (ROC) curve to evaluate the distinguishing performance of different feature vectors and different kernel functions of SVM. The ROC analysis indicates the quadratic polynomial SVM with a combination of features as the input shows the best discriminating performance.

Optimal algorithm for automatic detection of microaneurysms based on receiver operating characteristic curve.

PubMed

Xu, Lili; Luo, Shuqian

2010-01-01

Microaneurysms (MAs) are the first manifestations of the diabetic retinopathy (DR) as well as an indicator for its progression. Their automatic detection plays a key role for both mass screening and monitoring and is therefore in the core of any system for computer-assisted diagnosis of DR. The algorithm basically comprises the following stages: candidate detection aiming at extracting the patterns possibly corresponding to MAs based on mathematical morphological black top hat, feature extraction to characterize these candidates, and classification based on support vector machine (SVM), to validate MAs. Feature vector and kernel function of SVM selection is very important to the algorithm. We use the receiver operating characteristic (ROC) curve to evaluate the distinguishing performance of different feature vectors and different kernel functions of SVM. The ROC analysis indicates the quadratic polynomial SVM with a combination of features as the input shows the best discriminating performance.

Effect of age on the diagnostic efficiency of HbA1c for diabetes in a Chinese middle-aged and elderly population: The Shanghai Changfeng Study.

PubMed

Wu, Li; Lin, Huandong; Gao, Jian; Li, Xiaoming; Xia, Mingfeng; Wang, Dan; Aleteng, Qiqige; Ma, Hui; Pan, Baishen; Gao, Xin

2017-01-01

Glycated hemoglobin A1c (HbA1c) ≥6.5% (or 48mmol/mol) has been recommended as a new diagnostic criterion for diabetes; however, limited literature is available regarding the effect of age on the HbA1c for diagnosing diabetes and the causes for this age effect remain unknown. In this study, we investigated whether and why age affects the diagnostic efficiency of HbA1c for diabetes in a community-based Chinese population. In total, 4325 participants without previously known diabetes were enrolled in this study. Participants were stratified by age. Receiver operating characteristic curve (ROC) was plotted for each age group and the area under the curve (AUC) represented the diagnostic efficiency of HbA1c for diabetes defined by the plasma glucose criteria. The area under the ROC curve in each one-year age group was defined as AUCage. Multiple regression analyses were performed to identify factors inducing the association between age and AUCage based on the changes in the β and P values of age. The current threshold of HbA1c (≥6.5% or 48mmol/mol) showed low sensitivity (35.6%) and high specificity (98.9%) in diagnosing diabetes. ROC curve analyses showed that the diagnostic efficiency of HbA1c in the ≥75 years age group was significantly lower than that in the 45-54 years age group (AUC: 0.755 vs. 0.878; P<0.001). Pearson correlation analysis showed that the AUCage of HbA1c was negatively correlated with age (r = -0.557, P = 0.001). When adjusting the red blood cell (RBC) count in the multiple regression model, the negative association between age and AUCage disappeared, with the regression coefficient of age reversed to 0.001 and the P value increased to 0.856. The diagnostic efficiency of HbA1c for diabetes decreased with aging, and this age effect was induced by the decreasing RBC count with age. HbA1c is unsuitable for diagnosing diabetes in elderly individuals because of their physiologically decreased RBC count.

Effect of age on the diagnostic efficiency of HbA1c for diabetes in a Chinese middle-aged and elderly population: The Shanghai Changfeng Study

PubMed Central

Gao, Jian; Li, Xiaoming; Xia, Mingfeng; Wang, Dan; Aleteng, Qiqige; Ma, Hui; Pan, Baishen

2017-01-01

Background and aims Glycated hemoglobin A1c (HbA1c) ≥6.5% (or 48mmol/mol) has been recommended as a new diagnostic criterion for diabetes; however, limited literature is available regarding the effect of age on the HbA1c for diagnosing diabetes and the causes for this age effect remain unknown. In this study, we investigated whether and why age affects the diagnostic efficiency of HbA1c for diabetes in a community-based Chinese population. Methods In total, 4325 participants without previously known diabetes were enrolled in this study. Participants were stratified by age. Receiver operating characteristic curve (ROC) was plotted for each age group and the area under the curve (AUC) represented the diagnostic efficiency of HbA1c for diabetes defined by the plasma glucose criteria. The area under the ROC curve in each one-year age group was defined as AUCage. Multiple regression analyses were performed to identify factors inducing the association between age and AUCage based on the changes in the β and P values of age. Results The current threshold of HbA1c (≥6.5% or 48mmol/mol) showed low sensitivity (35.6%) and high specificity (98.9%) in diagnosing diabetes. ROC curve analyses showed that the diagnostic efficiency of HbA1c in the ≥75 years age group was significantly lower than that in the 45–54 years age group (AUC: 0.755 vs. 0.878; P<0.001). Pearson correlation analysis showed that the AUCage of HbA1c was negatively correlated with age (r = -0.557, P = 0.001). When adjusting the red blood cell (RBC) count in the multiple regression model, the negative association between age and AUCage disappeared, with the regression coefficient of age reversed to 0.001 and the P value increased to 0.856. Conclusions The diagnostic efficiency of HbA1c for diabetes decreased with aging, and this age effect was induced by the decreasing RBC count with age. HbA1c is unsuitable for diagnosing diabetes in elderly individuals because of their physiologically decreased RBC count. PMID:28886160

Role of subdural electrocorticography in prediction of long-term seizure outcome in epilepsy surgery

PubMed Central

Juhász, Csaba; Shah, Aashit; Sood, Sandeep; Chugani, Harry T.

2009-01-01

Since prediction of long-term seizure outcome using preoperative diagnostic modalities remains suboptimal in epilepsy surgery, we evaluated whether interictal spike frequency measures obtained from extraoperative subdural electrocorticography (ECoG) recording could predict long-term seizure outcome. This study included 61 young patients (age 0.4–23.0 years), who underwent extraoperative ECoG recording prior to cortical resection for alleviation of uncontrolled focal seizures. Patient age, frequency of preoperative seizures, neuroimaging findings, ictal and interictal ECoG measures were preoperatively obtained. The seizure outcome was prospectively measured [follow-up period: 2.5–6.4 years (mean 4.6 years)]. Univariate and multivariate logistic regression analyses determined how well preoperative demographic and diagnostic measures predicted long-term seizure outcome. Following the initial cortical resection, Engel Class I, II, III and IV outcomes were noted in 35, 6, 12 and 7 patients, respectively. One child died due to disseminated intravascular coagulation associated with pseudomonas sepsis 2 days after surgery. Univariate regression analyses revealed that incomplete removal of seizure onset zone, higher interictal spike-frequency in the preserved cortex and incomplete removal of cortical abnormalities on neuroimaging were associated with a greater risk of failing to obtain Class I outcome. Multivariate logistic regression analysis revealed that incomplete removal of seizure onset zone was the only independent predictor of failure to obtain Class I outcome. The goodness of regression model fit and the predictive ability of regression model were greatest in the full regression model incorporating both ictal and interictal measures [R2 0.44; Area under the receiver operating characteristic (ROC) curve: 0.81], slightly smaller in the reduced model incorporating ictal but not interictal measures (R2 0.40; Area under the ROC curve: 0.79) and slightly smaller again in the reduced model incorporating interictal but not ictal measures (R2 0.27; Area under the ROC curve: 0.77). Seizure onset zone and interictal spike frequency measures on subdural ECoG recording may both be useful in predicting the long-term seizure outcome of epilepsy surgery. Yet, the additive clinical impact of interictal spike frequency measures to predict long-term surgical outcome may be modest in the presence of ictal ECoG and neuroimaging data. PMID:19286694

Validation of the Cepstral Spectral Index of Dysphonia (CSID) as a Screening Tool for Voice Disorders: Development of Clinical Cutoff Scores.

PubMed

Awan, Shaheen N; Roy, Nelson; Zhang, Dong; Cohen, Seth M

2016-03-01

The purposes of this study were to (1) evaluate the performance of the Cepstral Spectral Index of Dysphonia (CSID--a multivariate estimate of dysphonia severity) as a potential screening tool for voice disorder identification and (2) identify potential clinical cutoff scores to classify voice-disordered cases versus controls. Subjects were 332 men and women (116 men, 216 women) comprised of subjects who presented to a physician with a voice-related complaint and a group of non-voice-related control subjects. Voice-disordered cases versus controls were initially defined via three reference standards: (1) auditory-perceptual judgment (dysphonia +/-); (2) Voice Handicap Index (VHI) score (VHI +/-); and (3) laryngoscopic description (laryngoscopic +/-). Speech samples were analyzed using the Analysis of Dysphonia in Speech and Voice program. Cepstral and spectral measures were combined into a CSID multivariate formula which estimated dysphonia severity for Rainbow Passage samples (i.e., the CSIDR). The ability of the CSIDR to accurately classify cases versus controls in relation to each reference standard was evaluated via a combination of logistic regression and receiver operating characteristic (ROC) analyses. The ability of the CSIDR to discriminate between cases and controls was represented by the "area under the ROC curve" (AUC). ROC classification of dysphonia-positive cases versus controls resulted in a strong AUC = 0.85. A CSIDR cutoff of ≈24 achieved the best balance between sensitivity and specificity, whereas a more liberal cutoff score of ≈19 resulted in higher sensitivity while maintaining respectable specificity which may be preferred for screening purposes. Weaker but adequate AUCs = 0.75 and 0.73 were observed for the classification of VHI-positive and laryngoscopic-positive cases versus controls, respectively. Logistic regression analyses indicated that subject age may be a significant covariate in the discrimination of dysphonia-positive and VHI-positive cases versus controls. The CSIDR can provide a strong level of accuracy for the classification of voice-disordered cases versus controls, particularly when auditory-perceptual judgment is used as the reference standard. Although users often focus on a cutoff score that achieves a balance between sensitivity and specificity, more liberal cutoffs for screening purposes versus conservative cutoffs when cost or risk of further evaluation is deemed to be high should also be considered. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Regional homogeneity of resting-state brain abnormalities in bipolar and unipolar depression.

PubMed

Liu, Chun-Hong; Ma, Xin; Wu, Xia; Zhang, Yu; Zhou, Fu-Chun; Li, Feng; Tie, Chang-Le; Dong, Jie; Wang, Yong-Jun; Yang, Zhi; Wang, Chuan-Yue

2013-03-05

Bipolar disorder patients experiencing a depressive episode (BD-dep) without an observed history of mania are often misdiagnosed and are consequently treated as having unipolar depression (UD), leading to inadequate treatment and poor outcomes. An essential solution to this problem is to identify objective biological markers that distinguish BD-dep and UD patients at an early stage. However, studies directly comparing the brain dysfunctions associated with BD-dep and UD are rare. More importantly, the specificity of the differences in brain activity between these mental disorders has not been examined. With whole-brain regional homogeneity analysis and region-of-interest (ROI) based receiver operating characteristic (ROC) analysis, we aimed to compare the resting-state brain activity of BD-dep and UD patients. Furthermore, we examined the specific differences and whether these differences were attributed to the brain abnormality caused by BD-dep, UD, or both. Twenty-one bipolar and 21 unipolar depressed patients, as well as 26 healthy subjects matched for gender, age, and educational levels, participated in the study. We compared the differences in the regional homogeneity (ReHo) of the BD-dep and UD groups and further identified their pathophysiological abnormality. In the brain regions showing a difference between the BD-dep and UD groups, we further conducted receptive operation characteristic (ROC) analyses to confirm the effectiveness of the identified difference in classifying the patients. We observed ReHo differences between the BD-dep and UD groups in the right ventrolateral middle frontal gyrus, right dorsal anterior insular, right ventral anterior insular, right cerebellum posterior gyrus, right posterior cingulate cortex, right parahippocampal gyrus, and left cerebellum anterior gyrus. Further ROI comparisons and ROC analysis on these ROIs showed that the right parahippocampal gyrus reflected abnormality specific to the BD-dep group, while the right middle frontal gyrus, the right dorsal anterior insular, the right cerebellum posterior gyrus, and the right posterior cingulate cortex showed abnormality specific to the UD group. We found brain regions showing resting state ReHo differences and examined their sensitivity and specificity, suggesting a potential neuroimaging biomarker to distinguish between BD-dep and UD patients. We further clarified the pathophysiological abnormality of these regions for each of the two patient populations. Copyright © 2012 Elsevier Inc. All rights reserved.

Assessing the Classification Accuracy of Early Numeracy Curriculum-Based Measures Using Receiver Operating Characteristic Curve Analysis

ERIC Educational Resources Information Center

Laracy, Seth D.; Hojnoski, Robin L.; Dever, Bridget V.

2016-01-01

Receiver operating characteristic curve (ROC) analysis was used to investigate the ability of early numeracy curriculum-based measures (EN-CBM) administered in preschool to predict performance below the 25th and 40th percentiles on a quantity discrimination measure in kindergarten. Areas under the curve derived from a sample of 279 students ranged…

The Obsessive Compulsive Scale of the Child Behavior Checklist Predicts Obsessive-Compulsive Disorder: A Receiver Operating Characteristic Curve Analysis

ERIC Educational Resources Information Center

Hudziak, James J.; Althoff, Robert R.; Stanger, Catherine; van Beijsterveldt, C. E. M.; Nelson, Elliot C.; Hanna, Gregory L.; Boomsma, Dorret I.; Todd, Richard D.

2006-01-01

Background: The purpose of this study was to determine a score on the Obsessive Compulsive Scale (OCS) from the Child Behavior Checklist (CBCL) to screen for obsessive compulsive disorder (OCD) in children and to rigorously test the specificity and sensitivity of a single cutpoint. Methods: A receiver operating characteristic (ROC) curve analysis…

Experimental design and statistical methods for improved hit detection in high-throughput screening.

PubMed

Malo, Nathalie; Hanley, James A; Carlile, Graeme; Liu, Jing; Pelletier, Jerry; Thomas, David; Nadon, Robert

2010-09-01

Identification of active compounds in high-throughput screening (HTS) contexts can be substantially improved by applying classical experimental design and statistical inference principles to all phases of HTS studies. The authors present both experimental and simulated data to illustrate how true-positive rates can be maximized without increasing false-positive rates by the following analytical process. First, the use of robust data preprocessing methods reduces unwanted variation by removing row, column, and plate biases. Second, replicate measurements allow estimation of the magnitude of the remaining random error and the use of formal statistical models to benchmark putative hits relative to what is expected by chance. Receiver Operating Characteristic (ROC) analyses revealed superior power for data preprocessed by a trimmed-mean polish method combined with the RVM t-test, particularly for small- to moderate-sized biological hits.

Adaptive histogram equalization in digital radiography of destructive skeletal lesions.

PubMed

Braunstein, E M; Capek, P; Buckwalter, K; Bland, P; Meyer, C R

1988-03-01

Adaptive histogram equalization, an image-processing technique that distributes pixel values of an image uniformly throughout the gray scale, was applied to 28 plain radiographs of bone lesions, after they had been digitized. The non-equalized and equalized digital images were compared by two skeletal radiologists with respect to lesion margins, internal matrix, soft-tissue mass, cortical breakthrough, and periosteal reaction. Receiver operating characteristic (ROC) curves were constructed on the basis of the responses. Equalized images were superior to nonequalized images in determination of cortical breakthrough and presence or absence of periosteal reaction. ROC analysis showed no significant difference in determination of margins, matrix, or soft-tissue masses.

Responsiveness and minimal clinically important changes for the Tampa Scale of Kinesiophobia after lumbar fusion during cognitive behavioral rehabilitation.

PubMed

Monticone, Marco; Ambrosini, Emilia; Rocca, Barbara; Foti, Calogero; Ferrante, Simona

2017-06-01

The Tampa Scale of Kinesiophobia (TSK) is a commonly-used measure for the assessment of fear of movement beliefs in chronic complaints, but its responsiveness in subjects after lumbar fusion has been never reported. Evaluating the responsiveness and minimal clinically important differences (MCIDs) for the TSK and its subscales after lumbar fusion. Population-based cohort study. Secondary care rehabilitation hospital. In-patients undergoing rehabilitation after lumbar fusion. At the beginning and end of a four-week motor and cognitive-behavioral rehabilitation program, 180 patients completed the TSK. After the intervention, the global perceived effect (GPE) was analyzed to produce a dichotomous outcome (improved vs. stable). Responsiveness for the TSK and its subscales were calculated by distribution (effect size [ES], standardized response mean [SRM]) and anchor-based methods (receiver operating characteristics (ROC) curves; correlations between change scores of the TSK and its subscales and GPE). ROC curves were also used to compute MCID values. The ES ranged from 1.63 to 1.77 and the SRM from 1.25 to 1.39 for TSK and its subscales. The ROC analyses revealed a value of area under the curve (0.999 [95% CI: 0.978; 1.000], 0.998 [95% CI: 0.975; 1.000], 0.990 [95% CI: 0.962; 0.999] for the TSK, Harm and Activity Avoidance subscales, respectively). MCID values greater than 6 (95% CI: >5; >6), 4 (95% CI: >3; >5), and 2 (95% CI: >2; >2) were achieved for the TSK, Harm and Activity Avoidance subscales, respectively. Correlations between change scores of the TSK and its subscales and GPE were high (0.786-0.830). The TSK and its subscales were sensitive in detecting clinical changes in subjects undergoing rehabilitation after lumbar fusion. The obtained MCID values will help in the design of future randomized controlled trials and in the interpretation of the clinical impact of a rehabilitation program after lumbar fusion.

Validation of the Predictive Value of Modeled Human Chorionic Gonadotrophin Residual Production in Low-Risk Gestational Trophoblastic Neoplasia Patients Treated in NRG Oncology/Gynecologic Oncology Group-174 Phase III Trial.

PubMed

You, Benoit; Deng, Wei; Hénin, Emilie; Oza, Amit; Osborne, Raymond

2016-01-01

In low-risk gestational trophoblastic neoplasia, chemotherapy effect is monitored and adjusted with serum human chorionic gonadotrophin (hCG) levels. Mathematical modeling of hCG kinetics may allow prediction of methotrexate (MTX) resistance, with production parameter "hCGres." This approach was evaluated using the GOG-174 (NRG Oncology/Gynecologic Oncology Group-174) trial database, in which weekly MTX (arm 1) was compared with dactinomycin (arm 2). Database (210 patients, including 78 with resistance) was split into 2 sets. A 126-patient training set was initially used to estimate model parameters. Patient hCG kinetics from days 7 to 45 were fit to: [hCG(time)] = hCG7 * exp(-k * time) + hCGres, where hCGres is residual hCG tumor production, hCG7 is the initial hCG level, and k is the elimination rate constant. Receiver operating characteristic (ROC) analyses defined putative hCGRes predictor of resistance. An 84-patient test set was used to assess prediction validity. The hCGres was predictive of outcome in both arms, with no impact of treatment arm on unexplained variability of kinetic parameter estimates. The best hCGres cutoffs to discriminate resistant versus sensitive patients were 7.7 and 74.0 IU/L in arms 1 and 2, respectively. By combining them, 2 predictive groups were defined (ROC area under the curve, 0.82; sensitivity, 93.8%; specificity, 70.5%). The predictive value of hCGres-based groups regarding resistance was reproducible in test set (ROC area under the curve, 0.81; sensitivity, 88.9%; specificity, 73.1%). Both hCGres and treatment arm were associated with resistance by logistic regression analysis. The early predictive value of the modeled kinetic parameter hCGres regarding resistance seems promising in the GOG-174 study. This is the second positive evaluation of this approach. Prospective validation is warranted.

Multiparametric voxel-based analyses of standardized uptake values and apparent diffusion coefficients of soft-tissue tumours with a positron emission tomography/magnetic resonance system: Preliminary results.

PubMed

Sagiyama, Koji; Watanabe, Yuji; Kamei, Ryotaro; Hong, Sungtak; Kawanami, Satoshi; Matsumoto, Yoshihiro; Honda, Hiroshi

2017-12-01

To investigate the usefulness of voxel-based analysis of standardized uptake values (SUVs) and apparent diffusion coefficients (ADCs) for evaluating soft-tissue tumour malignancy with a PET/MR system. Thirty-five subjects with either ten low/intermediate-grade tumours or 25 high-grade tumours were prospectively enrolled. Zoomed diffusion-weighted and fluorodeoxyglucose ( 18 FDG)-PET images were acquired along with fat-suppressed T2-weighted images (FST2WIs). Regions of interest (ROIs) were drawn on FST2WIs including the tumour in all slices. ROIs were pasted onto PET and ADC-maps to measure SUVs and ADCs within tumour ROIs. Tumour volume, SUVmax, ADCminimum, the heterogeneity and the correlation coefficients of SUV and ADC were recorded. The parameters of high- and low/intermediate-grade groups were compared, and receiver operating characteristic (ROC) analysis was also performed. The mean correlation coefficient for SUV and ADC in high-grade sarcomas was lower than that of low/intermediate-grade tumours (-0.41 ± 0.25 vs. -0.08 ± 0.34, P < 0.01). Other parameters did not differ significantly. ROC analysis demonstrated that correlation coefficient showed the best diagnostic performance for differentiating the two groups (AUC 0.79, sensitivity 96.0%, specificity 60%, accuracy 85.7%). SUV and ADC determined via PET/MR may be useful for differentiating between high-grade and low/intermediate-grade soft tissue tumours. • PET/MR allows voxel-based comparison of SUVs and ADCs in soft-tissue tumours. • A comprehensive assessment of internal heterogeneity was performed with scatter plots. • SUVmax or ADCminimum could not differentiate high-grade sarcoma from low/intermediate-grade tumours. • Only the correlation coefficient between SUV and ADC differentiated the two groups. • The correlation coefficient showed the best diagnostic performance by ROC analysis.

Anthropometric markers and their association with incident type 2 diabetes mellitus: which marker is best for prediction? Pooled analysis of four German population-based cohort studies and comparison with a nationwide cohort study

PubMed Central

Hartwig, Saskia; Kluttig, Alexander; Tiller, Daniel; Fricke, Julia; Müller, Grit; Schipf, Sabine; Völzke, Henry; Schunk, Michaela; Meisinger, Christa; Schienkiewitz, Anja; Heidemann, Christin; Moebus, Susanne; Pechlivanis, Sonali; Werdan, Karl; Kuss, Oliver; Tamayo, Teresa; Haerting, Johannes; Greiser, Karin Halina

2016-01-01

Objective To compare the association between different anthropometric measurements and incident type 2 diabetes mellitus (T2DM) and to assess their predictive ability in different regions of Germany. Methods Data of 10 258 participants from 4 prospective population-based cohorts were pooled to assess the association of body weight, body mass index (BMI), waist circumference (WC), waist-to-hip-ratio (WHR) and waist-to-height-ratio (WHtR) with incident T2DM by calculating HRs of the crude, adjusted and standardised markers, as well as providing receiver operator characteristic (ROC) curves. Differences between HRs and ROCs for the different anthropometric markers were calculated to compare their predictive ability. In addition, data of 3105 participants from the nationwide survey were analysed separately using the same methods to provide a nationally representative comparison. Results Strong associations were found for each anthropometric marker and incidence of T2DM. Among the standardised anthropometric measures, we found the strongest effect on incident T2DM for WC and WHtR in the pooled sample (HR for 1 SD difference in WC 1.97, 95% CI 1.75 to 2.22, HR for WHtR 1.93, 95% CI 1.71 to 2.17 in women) and in female DEGS participants (HR for WC 2.24, 95% CI 1.91 to 2.63, HR for WHtR 2.10, 95% CI 1.81 to 2.44), whereas the strongest association in men was found for WHR among DEGS participants (HR 2.29, 95% CI 1.89 to 2.78). ROC analysis showed WHtR to be the strongest predictor for incident T2DM. Differences in HR and ROCs between the different markers confirmed WC and WHtR to be the best predictors of incident T2DM. Findings were consistent across study regions and age groups (<65 vs ≥65 years). Conclusions We found stronger associations between anthropometric markers that reflect abdominal obesity (ie, WC and WHtR) and incident T2DM than for BMI and weight. The use of these measurements in risk prediction should be encouraged. PMID:26792214

Anthropometric markers and their association with incident type 2 diabetes mellitus: which marker is best for prediction? Pooled analysis of four German population-based cohort studies and comparison with a nationwide cohort study.

PubMed

Hartwig, Saskia; Kluttig, Alexander; Tiller, Daniel; Fricke, Julia; Müller, Grit; Schipf, Sabine; Völzke, Henry; Schunk, Michaela; Meisinger, Christa; Schienkiewitz, Anja; Heidemann, Christin; Moebus, Susanne; Pechlivanis, Sonali; Werdan, Karl; Kuss, Oliver; Tamayo, Teresa; Haerting, Johannes; Greiser, Karin Halina

2016-01-20

To compare the association between different anthropometric measurements and incident type 2 diabetes mellitus (T2DM) and to assess their predictive ability in different regions of Germany. Data of 10,258 participants from 4 prospective population-based cohorts were pooled to assess the association of body weight, body mass index (BMI), waist circumference (WC), waist-to-hip-ratio (WHR) and waist-to-height-ratio (WHtR) with incident T2DM by calculating HRs of the crude, adjusted and standardised markers, as well as providing receiver operator characteristic (ROC) curves. Differences between HRs and ROCs for the different anthropometric markers were calculated to compare their predictive ability. In addition, data of 3105 participants from the nationwide survey were analysed separately using the same methods to provide a nationally representative comparison. Strong associations were found for each anthropometric marker and incidence of T2DM. Among the standardised anthropometric measures, we found the strongest effect on incident T2DM for WC and WHtR in the pooled sample (HR for 1 SD difference in WC 1.97, 95% CI 1.75 to 2.22, HR for WHtR 1.93, 95% CI 1.71 to 2.17 in women) and in female DEGS participants (HR for WC 2.24, 95% CI 1.91 to 2.63, HR for WHtR 2.10, 95% CI 1.81 to 2.44), whereas the strongest association in men was found for WHR among DEGS participants (HR 2.29, 95% CI 1.89 to 2.78). ROC analysis showed WHtR to be the strongest predictor for incident T2DM. Differences in HR and ROCs between the different markers confirmed WC and WHtR to be the best predictors of incident T2DM. Findings were consistent across study regions and age groups (<65 vs ≥ 65 years). We found stronger associations between anthropometric markers that reflect abdominal obesity (ie, WC and WHtR) and incident T2DM than for BMI and weight. The use of these measurements in risk prediction should be encouraged. 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/

Suppression of LH during ovarian stimulation: analysing threshold values and effects on ovarian response and the outcome of assisted reproduction in down-regulated women stimulated with recombinant FSH.

PubMed

Balasch, J; Vidal, E; Peñarrubia, J; Casamitjana, R; Carmona, F; Creus, M; Fábregues, F; Vanrell, J A

2001-08-01

It has been recently suggested that gonadotrophin-releasing hormone agonist down-regulation in some normogonadotrophic women may result in profound suppression of LH concentrations, impairing adequate oestradiol synthesis and IVF and pregnancy outcome. The aims of this study, where receiver-operating characteristic (ROC) analysis was used, were: (i) to assess the usefulness of serum LH measurement on stimulation day 7 (S7) as a predictor of ovarian response, IVF outcome, implantation, and the outcome of pregnancy in patients treated with recombinant FSH under pituitary suppression; and (ii) to define the best threshold value, if any, to discriminate between women with 'low' or 'normal' LH concentrations. A total of 144 infertile women undergoing IVF/intracytoplasmic sperm injection (ICSI) treatment were included. Seventy-two consecutive patients having a positive pregnancy test (including 58 ongoing pregnancies and 14 early pregnancy losses) were initially selected. As a control non-pregnant group, the next non-conception IVF/ICSI cycle after each conceptual cycle in our assisted reproduction programme was used. The median and range of LH values in non-conception cycles, conception cycles, ongoing pregnancies, and early pregnancy losses, clearly overlapped. ROC analysis showed that serum LH concentration on S7 was unable to discriminate between conception and non-conception cycles (AUC(ROC) = 0.52; 95% CI: 0.44 to 0.61) or ongoing pregnancy versus early pregnancy loss groups (AUC(ROC) = 0.59; 95% CI: 0.46 to 0.70). To assess further the potential impact of suppressed concentrations of circulating LH during ovarian stimulation on the outcome of IVF/ICSI treatment, the three threshold values of mid-follicular serum LH proposed in the literature (<1, < or =0.7, <0.5 IU/l) to discriminate between women with 'low' or 'normal' LH were applied to our study population. No significant differences were found with respect to ovarian response, IVF/ICSI outcome, implantation, and the outcome of pregnancy between 'low' and 'normal' S7 LH women as defined by those threshold values. Our results do not support the need for additional exogenous LH supplementation in down-regulated women receiving a recombinant FSH-only preparation.

A knowledge-driven probabilistic framework for the prediction of protein-protein interaction networks.

PubMed

Browne, Fiona; Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

2010-03-01

This study applied a knowledge-driven data integration framework for the inference of protein-protein interactions (PPI). Evidence from diverse genomic features is integrated using a knowledge-driven Bayesian network (KD-BN). Receiver operating characteristic (ROC) curves may not be the optimal assessment method to evaluate a classifier's performance in PPI prediction as the majority of the area under the curve (AUC) may not represent biologically meaningful results. It may be of benefit to interpret the AUC of a partial ROC curve whereby biologically interesting results are represented. Therefore, the novel application of the assessment method referred to as the partial ROC has been employed in this study to assess predictive performance of PPI predictions along with calculating the True positive/false positive rate and true positive/positive rate. By incorporating domain knowledge into the construction of the KD-BN, we demonstrate improvement in predictive performance compared with previous studies based upon the Naive Bayesian approach. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Evaluation of computer-aided detection of lesions in mammograms obtained with a digital phase-contrast mammography system.

PubMed

Tanaka, Toyohiko; Nitta, Norihisa; Ohta, Shinichi; Kobayashi, Tsuyoshi; Kano, Akiko; Tsuchiya, Keiko; Murakami, Yoko; Kitahara, Sawako; Wakamiya, Makoto; Furukawa, Akira; Takahashi, Masashi; Murata, Kiyoshi

2009-12-01

A computer-aided detection (CAD) system was evaluated for its ability to detect microcalcifications and masses on images obtained with a digital phase-contrast mammography (PCM) system, a system characterised by the sharp images provided by phase contrast and by the high resolution of 25-μm-pixel mammograms. Fifty abnormal and 50 normal mammograms were collected from about 3,500 mammograms and printed on film for reading on a light box. Seven qualified radiologists participated in an observer study based on receiver operating characteristic (ROC) analysis. The average of the areas under ROC curve (AUC) values for the ROC analysis with and without CAD were 0.927 and 0.897 respectively (P = 0.015). The AUC values improved from 0.840 to 0.888 for microcalcifications (P = 0.034) and from 0.947 to 0.962 for masses (P = 0.025) respectively. The application of CAD to the PCM system is a promising approach for the detection of breast cancer in its early stages.

Assessment of insulin sensitivity by the hyperinsulinemic euglycemic clamp: Comparison with the spectral analysis of photoplethysmography.

PubMed

De Souza, Aglecio Luiz; Batista, Gisele Almeida; Alegre, Sarah Monte

2017-01-01

We compare spectral analysis of photoplethysmography (PTG) with insulin resistance measured by the hyperinsulinemic euglycemic clamp (HEC) technique. A total of 100 nondiabetic subjects, 43 men and 57 women aged 20-63years, 30 lean, 42 overweight and 28 obese were enrolled in the study. These patients underwent an examination with HEC, and an examination with the PTG spectral analysis and calculation of the PTG Total Power (PTG-TP). Receiver-operating characteristic (ROC) curves were constructed to determine the specificity and sensitivity of PTG-TP in the assessment of insulin resistance. There is a moderate correlation between insulin sensitivity (M-value) and PTG-TP (r=- 0.64, p<0.0001). The ROC curves showed that the most relevant cutoff to the whole study group was a PTG-TP>406.2. This cut-off had a sensitivity=95.7%, specificity =84,4% and the area under the ROC curve (AUC)=0.929 for identifying insulin resistance. All AUC ROC curve analysis were significant (p<0.0001). The use of the PTG-TP marker measured from the PTG spectral analysis is a useful tool in screening and follow up of IR, especially in large-scale studies. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A principled approach to setting optimal diagnostic thresholds: where ROC and indifference curves meet.

PubMed

Irwin, R John; Irwin, Timothy C

2011-06-01

Making clinical decisions on the basis of diagnostic tests is an essential feature of medical practice and the choice of the decision threshold is therefore crucial. A test's optimal diagnostic threshold is the threshold that maximizes expected utility. It is given by the product of the prior odds of a disease and a measure of the importance of the diagnostic test's sensitivity relative to its specificity. Choosing this threshold is the same as choosing the point on the Receiver Operating Characteristic (ROC) curve whose slope equals this product. We contend that a test's likelihood ratio is the canonical decision variable and contrast diagnostic thresholds based on likelihood ratio with two popular rules of thumb for choosing a threshold. The two rules are appealing because they have clear graphical interpretations, but they yield optimal thresholds only in special cases. The optimal rule can be given similar appeal by presenting indifference curves, each of which shows a set of equally good combinations of sensitivity and specificity. The indifference curve is tangent to the ROC curve at the optimal threshold. Whereas ROC curves show what is feasible, indifference curves show what is desirable. Together they show what should be chosen. Copyright © 2010 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Cardiopulmonary exercise testing for the prediction of morbidity risk after rectal cancer surgery.

PubMed

West, M A; Parry, M G; Lythgoe, D; Barben, C P; Kemp, G J; Grocott, M P W; Jack, S

2014-08-01

This study investigated the relationship between objectively measured physical fitness variables derived by cardiopulmonary exercise testing (CPET) and in-hospital morbidity after rectal cancer surgery. Patients scheduled for rectal cancer surgery underwent preoperative CPET (reported blind to patient characteristics) with recording of morbidity (recorded blind to CPET variables). Non-parametric receiver operating characteristic (ROC) curves and logistic regression were used to assess the relationship between CPET variables and postoperative morbidity. Of 105 patients assessed, 95 (72 men) were included; ten patients had no surgery and were excluded (3 by choice, 7 owing to unresectable metastasis). Sixty-eight patients had received neoadjuvant treatment. ROC curve analysis of oxygen uptake (V˙o2 ) at estimated lactate threshold (θ^L ) and peak V˙o2 gave an area under the ROC curve of 0·87 (95 per cent confidence interval 0·78 to 0·95; P < 0·001) and 0·85 (0·77 to 0·93; P < 0·001) respectively, indicating that they can help discriminate patients at risk of postoperative morbidity. The optimal cut-off points identified were 10·6 and 18·6 ml per kg per min for V˙o2 at θ^L and peak respectively. CPET can help predict morbidity after rectal cancer surgery. © 2014 BJS Society Ltd. Published by John Wiley & Sons Ltd.

Visualization of the significance of Receiver Operating Characteristics based on confidence ellipses

NASA Astrophysics Data System (ADS)

Sarlis, Nicholas V.; Christopoulos, Stavros-Richard G.

2014-03-01

The Receiver Operating Characteristics (ROC) is used for the evaluation of prediction methods in various disciplines like meteorology, geophysics, complex system physics, medicine etc. The estimation of the significance of a binary prediction method, however, remains a cumbersome task and is usually done by repeating the calculations by Monte Carlo. The FORTRAN code provided here simplifies this problem by evaluating the significance of binary predictions for a family of ellipses which are based on confidence ellipses and cover the whole ROC space. Catalogue identifier: AERY_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERY_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 11511 No. of bytes in distributed program, including test data, etc.: 72906 Distribution format: tar.gz Programming language: FORTRAN. Computer: Any computer supporting a GNU FORTRAN compiler. Operating system: Linux, MacOS, Windows. RAM: 1Mbyte Classification: 4.13, 9, 14. Nature of problem: The Receiver Operating Characteristics (ROC) is used for the evaluation of prediction methods in various disciplines like meteorology, geophysics, complex system physics, medicine etc. The estimation of the significance of a binary prediction method, however, remains a cumbersome task and is usually done by repeating the calculations by Monte Carlo. The FORTRAN code provided here simplifies this problem by evaluating the significance of binary predictions for a family of ellipses which are based on confidence ellipses and cover the whole ROC space. Solution method: Using the statistics of random binary predictions for a given value of the predictor threshold ɛt, one can construct the corresponding confidence ellipses. The envelope of these corresponding confidence ellipses is estimated when ɛt varies from 0 to 1. This way a new family of ellipses is obtained, named k-ellipses, which covers the whole ROC plane and leads to a well defined Area Under the Curve (AUC). For the latter quantity, Mason and Graham [1] have shown that it follows the Mann-Whitney U-statistics [2] which can be applied [3] for the estimation of the statistical significance of each k-ellipse. As the transformation is invertible, any point on the ROC plane corresponds to a unique value of k, thus to a unique p-value to obtain this point by chance. The present FORTRAN code provides this p-value field on the ROC plane as well as the k-ellipses corresponding to the (p=)10%, 5% and 1% significance levels using as input the number of the positive (P) and negative (Q) cases to be predicted. Unusual features: In some machines, the compiler directive -O2 or -O3 should be used to avoid NaN’s in some points of the p-field along the diagonal. Running time: Depending on the application, e.g., 4s for an Intel(R) Core(TM)2 CPU E7600 at 3.06 GHz with 2 GB RAM for the examples presented here References: [1] S.J. Mason, N.E. Graham, Quart. J. Roy. Meteor. Soc. 128 (2002) 2145. [2] H.B. Mann, D.R. Whitney, Ann. Math. Statist. 18 (1947) 50. [3] L.C. Dinneen, B.C. Blakesley, J. Roy. Stat. Soc. Ser. C Appl. Stat. 22 (1973) 269.

Computed tomographic (CT) neuroradiological evaluation of intra-axial and extra-axial lesions: a receiver operating characteristic (ROC) study of film and 1K workstation

NASA Astrophysics Data System (ADS)

El-Saden, Suzie; Hademenos, George J.; Zhu, Wei; Sayre, James W.; Glenn, Brad; Steidler, Jim; Kode, L.; King, Brian; Quinones, Diana; Valentino, Daniel J.; Bentsen, John R.

1995-04-01

Digital display workstations are now commonly used for cross-sectional image viewing; however, few receiver operating characteristic (ROC) studies have been performed to evaluate the diagnostic efficiency of hard copy versus a workstation display for neuroradiology applications. We have performed an ROC study of film and 1K workstation based on the diagnostic performance of neuroradiology fellows to detect subtle intra- axial (high density (HD) and low density (LD)) and extra-axial (fluid, blood) lesions presented on computed tomographic (CT) images. An ROC analysis of the interpretation of approximately 200 CT images (1/2 normals and 1/2 abnormals) was performed by five experienced observers. The total number of abnormal images were equally divided among the three represented types of lesions (HD, LD, and extra-axial lesions). The images comprising the extra-axial lesion group were further subdivided into the following three distinct types: subdural hemorrhage, subarachnoid hemorrhage, and epidural hemorrhage. A fraction of the abnormal images were represented by more than one type of lesion, e.g., one abnormal image could contain both a HD and LD lesion. The digitized CT images were separated into four groups and read on the standard light box and a 1K workstation monitor equipped with simple image processing functions. Confidence ratings were scaled on a range from 0 (least confident) to 4 (most confident). Reader order sequences were randomized for each reader and for each modality. Each observer read from a total of eight different groups with a four-week intermission following the fourth group. The randomly assigned image number, lesion type and approximate location, incidental findings and comments, and confidence ratings were reported in individual worksheets for each image. ROC curves that were generated and analyzed for the various subgroups are presented in addition to the overall generalized jackknifed estimates of the grouped data. Also, 95% confidence intervals are presented for the differences in the area under the ROC curves. Although there were no statistically significant differences in the diagnostic accuracy between the original CT slice with HD and LD lesions viewed on the light box and on the 1K display workstation, the observers tended to record extra- axial lesions more frequently and with more confidence on the 1K display in comparison to the light box primarily due to the added advantage of adjusting the display window levels.

Easy and accurate variance estimation of the nonparametric estimator of the partial area under the ROC curve and its application.

PubMed

Yu, Jihnhee; Yang, Luge; Vexler, Albert; Hutson, Alan D

2016-06-15

The receiver operating characteristic (ROC) curve is a popular technique with applications, for example, investigating an accuracy of a biomarker to delineate between disease and non-disease groups. A common measure of accuracy of a given diagnostic marker is the area under the ROC curve (AUC). In contrast with the AUC, the partial area under the ROC curve (pAUC) looks into the area with certain specificities (i.e., true negative rate) only, and it can be often clinically more relevant than examining the entire ROC curve. The pAUC is commonly estimated based on a U-statistic with the plug-in sample quantile, making the estimator a non-traditional U-statistic. In this article, we propose an accurate and easy method to obtain the variance of the nonparametric pAUC estimator. The proposed method is easy to implement for both one biomarker test and the comparison of two correlated biomarkers because it simply adapts the existing variance estimator of U-statistics. In this article, we show accuracy and other advantages of the proposed variance estimation method by broadly comparing it with previously existing methods. Further, we develop an empirical likelihood inference method based on the proposed variance estimator through a simple implementation. In an application, we demonstrate that, depending on the inferences by either the AUC or pAUC, we can make a different decision on a prognostic ability of a same set of biomarkers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The use of intraoperative triggered electromyography to detect misplaced pedicle screws: a systematic review and meta-analysis.

PubMed

Mikula, Anthony L; Williams, Seth K; Anderson, Paul A

2016-04-01

Insertion of instruments or implants into the spine carries a risk for injury to neural tissue. Triggered electromyography (tEMG) is an intraoperative neuromonitoring technique that involves electrical stimulation of a tool or screw and subsequent measurement of muscle action potentials from myotomes innervated by nerve roots near the stimulated instrument. The authors of this study sought to determine the ability of tEMG to detect misplaced pedicle screws (PSs). The authors searched the U.S. National Library of Medicine, the Web of Science Core Collection database, and the Cochrane Central Register of Controlled Trials for PS studies. A meta-analysis of these studies was performed on a per-screw basis to determine the ability of tEMG to detect misplaced PSs. Sensitivity, specificity, and receiver operating characteristic (ROC) area under the curve (AUC) were calculated overall and in subgroups. Twenty-six studies were included in the systematic review. The authors analyzed 18 studies in which tEMG was used during PS placement in the meta-analysis, representing data from 2932 patients and 15,065 screws. The overall sensitivity of tEMG for detecting misplaced PSs was 0.78, and the specificity was 0.94. The overall ROC AUC was 0.96. A tEMG current threshold of 10-12 mA (ROC AUC 0.99) and a pulse duration of 300 µsec (ROC AUC 0.97) provided the most accurate testing parameters for detecting misplaced screws. Screws most accurately conducted EMG signals (ROC AUC 0.98). Triggered electromyography has very high specificity but only fair sensitivity for detecting malpositioned PSs.

Statistical properties of a utility measure of observer performance compared to area under the ROC curve

NASA Astrophysics Data System (ADS)

Abbey, Craig K.; Samuelson, Frank W.; Gallas, Brandon D.; Boone, John M.; Niklason, Loren T.

2013-03-01

The receiver operating characteristic (ROC) curve has become a common tool for evaluating diagnostic imaging technologies, and the primary endpoint of such evaluations is the area under the curve (AUC), which integrates sensitivity over the entire false positive range. An alternative figure of merit for ROC studies is expected utility (EU), which focuses on the relevant region of the ROC curve as defined by disease prevalence and the relative utility of the task. However if this measure is to be used, it must also have desirable statistical properties keep the burden of observer performance studies as low as possible. Here, we evaluate effect size and variability for EU and AUC. We use two observer performance studies recently submitted to the FDA to compare the EU and AUC endpoints. The studies were conducted using the multi-reader multi-case methodology in which all readers score all cases in all modalities. ROC curves from the study were used to generate both the AUC and EU values for each reader and modality. The EU measure was computed assuming an iso-utility slope of 1.03. We find mean effect sizes, the reader averaged difference between modalities, to be roughly 2.0 times as big for EU as AUC. The standard deviation across readers is roughly 1.4 times as large, suggesting better statistical properties for the EU endpoint. In a simple power analysis of paired comparison across readers, the utility measure required 36% fewer readers on average to achieve 80% statistical power compared to AUC.

Scene perception and memory revealed by eye movements and receiver-operating characteristic analyses: does a cultural difference truly exist?

PubMed

Evans, Kris; Rotello, Caren M; Li, Xingshan; Rayner, Keith

2009-02-01

Cultural differences have been observed in scene perception and memory: Chinese participants purportedly attend to the background information more than did American participants. We investigated the influence of culture by recording eye movements during scene perception and while participants made recognition memory judgements. Real-world pictures with a focal object on a background were shown to both American and Chinese participants while their eye movements were recorded. Later, memory for the focal object in each scene was tested, and the relationship between the focal object (studied, new) and the background context (studied, new) was manipulated. Receiver-operating characteristic (ROC) curves show that both sensitivity and response bias were changed when objects were tested in new contexts. However, neither the decrease in accuracy nor the response bias shift differed with culture. The eye movement patterns were also similar across cultural groups. Both groups made longer and more fixations on the focal objects than on the contexts. The similarity of eye movement patterns and recognition memory behaviour suggests that both Americans and Chinese use the same strategies in scene perception and memory.

Filling in the blanks. An estimation of illicit cannabis growers' profits in Belgium.

PubMed

Vanhove, Wouter; Surmont, Tim; Van Damme, Patrick; De Ruyver, Brice

2014-05-01

As a result of increased pressure on cannabis cultivation in The Netherlands, the number of confiscated indoor cannabis plantations in Belgium is rising. Although increases are reported for all plantations sizes, half of the seized plantations contain less than 50 plants. In this study, factors and variables that influence costs and benefits of indoor cannabis cultivation are investigated as well as how these costs and benefits vary between different cannabis grower types. Real-situation data of four growers were used to perform financial analyses. Costs included fixed and variable material costs, as well as opportunity costs. Gross revenue per grow cycle was calculated based on most recent forensic findings for illicit Belgian cannabis plantations and was adjusted for the risk of getting caught. Finally, gross revenues and return on costs (ROC) were calculated over 1 year (4 cycles). Financial analysis shows that in all cases gross revenues as well as ROC are considerable, even after a single growth cycle. Highest profitability was found for large-scale (600 plants, ROC=6.8) and mid-scale plantations (150 plants, ROC=6.0). However, industrial plantations (23,000 plants, ROC=1.4) and micro-scale plantations (5 plants, ROC=2.8) are also highly remunerative. Shift of police focus away from micro-scale growers, least likely to be involved in criminal gangs, to large-scale and industrial scale plantations would influence costs as a result of changing risks of getting caught. However, sensitivity analysis shows that this does not significantly influence the conclusions on profitability of different types of indoor cannabis growers. Seizure and confiscation of profits are important elements in the integral and integrated policy approach required for tackling illicit indoor cannabis plantations. The large return of costs evidenced in the present study, underpin the policy relevance of confiscating those illicit profits as part of enforcement. Copyright © 2014 Elsevier B.V. All rights reserved.

Improving fMRI reliability in presurgical mapping for brain tumours.

PubMed

Stevens, M Tynan R; Clarke, David B; Stroink, Gerhard; Beyea, Steven D; D'Arcy, Ryan Cn

2016-03-01

Functional MRI (fMRI) is becoming increasingly integrated into clinical practice for presurgical mapping. Current efforts are focused on validating data quality, with reliability being a major factor. In this paper, we demonstrate the utility of a recently developed approach that uses receiver operating characteristic-reliability (ROC-r) to: (1) identify reliable versus unreliable data sets; (2) automatically select processing options to enhance data quality; and (3) automatically select individualised thresholds for activation maps. Presurgical fMRI was conducted in 16 patients undergoing surgical treatment for brain tumours. Within-session test-retest fMRI was conducted, and ROC-reliability of the patient group was compared to a previous healthy control cohort. Individually optimised preprocessing pipelines were determined to improve reliability. Spatial correspondence was assessed by comparing the fMRI results to intraoperative cortical stimulation mapping, in terms of the distance to the nearest active fMRI voxel. The average ROC-r reliability for the patients was 0.58±0.03, as compared to 0.72±0.02 in healthy controls. For the patient group, this increased significantly to 0.65±0.02 by adopting optimised preprocessing pipelines. Co-localisation of the fMRI maps with cortical stimulation was significantly better for more reliable versus less reliable data sets (8.3±0.9 vs 29±3 mm, respectively). We demonstrated ROC-r analysis for identifying reliable fMRI data sets, choosing optimal postprocessing pipelines, and selecting patient-specific thresholds. Data sets with higher reliability also showed closer spatial correspondence to cortical stimulation. ROC-r can thus identify poor fMRI data at time of scanning, allowing for repeat scans when necessary. ROC-r analysis provides optimised and automated fMRI processing for improved presurgical mapping. 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/

Circulating basal anti-Müllerian hormone levels as predictor of ovarian response in women undergoing ovarian stimulation for in vitro fertilization.

PubMed

Nardo, Luciano G; Gelbaya, Tarek A; Wilkinson, Hannah; Roberts, Stephen A; Yates, Allen; Pemberton, Phil; Laing, Ian

2009-11-01

To evaluate the clinical value of basal anti-Müllerian hormone (AMH) measurements compared with other available determinants, apart from chronologic age, in the prediction of ovarian response to gonadotrophin stimulation. Prospective cohort study. Tertiary referral center for reproductive medicine and an IVF unit. Women undergoing their first cycle of controlled ovarian hyperstimulation (COH) for in vitro fertilization (IVF). Basal levels of FSH and AMH as well as antral follicle count (AFC) were measured in 165 subjects. All patients were followed prospectively and their cycle outcomes recorded. Predictive value of FSH, AMH, and AFC for extremes of ovarian response to stimulation. Out of the 165 women, 134 were defined as normal responders, 15 as poor responders, and 16 as high responders. Subjects in the poor response group were significantly older then those in the other two groups. Anti-Müllerian hormone levels and AFC were markedly raised in the high responders and decreased in the poor responders. Compared with FSH and AFC, AMH performed better in the prediction of excessive response to ovarian stimulation-AMH area under receiver operating characteristic curve (ROC(AUC)) 0.81, FSH ROC(AUC) 0.66, AFC ROC(AUC) 0.69. For poor response, AMH (ROC(AUC) 0.88) was a significantly better predictor than FSH (ROC(AUC) 0.63) but not AFC (ROC(AUC) 0.81). AMH prediction of ovarian response was independent of age and PCOS. Anti-Müllerian hormone cutoffs of >3.75 ng/mL and <1.0 ng/mL would have modest sensitivity and specificity in predicting the extremes of response. Circulating AMH has the ability to predict excessive and poor response to stimulation with exogenous gonadotrophins. Overall, this biomarker is superior to basal FSH and AFC, and has the potential to be incorporated in to work-up protocols to predict patient's ovarian response to treatment and to individualize strategies aiming at reducing the cancellation rate and the iatrogenic complications of COH.

A new comparison of hyperspectral anomaly detection algorithms for real-time applications

NASA Astrophysics Data System (ADS)

Díaz, María.; López, Sebastián.; Sarmiento, Roberto

2016-10-01

Due to the high spectral resolution that remotely sensed hyperspectral images provide, there has been an increasing interest in anomaly detection. The aim of anomaly detection is to stand over pixels whose spectral signature differs significantly from the background spectra. Basically, anomaly detectors mark pixels with a certain score, considering as anomalies those whose scores are higher than a threshold. Receiver Operating Characteristic (ROC) curves have been widely used as an assessment measure in order to compare the performance of different algorithms. ROC curves are graphical plots which illustrate the trade- off between false positive and true positive rates. However, they are limited in order to make deep comparisons due to the fact that they discard relevant factors required in real-time applications such as run times, costs of misclassification and the competence to mark anomalies with high scores. This last fact is fundamental in anomaly detection in order to distinguish them easily from the background without any posterior processing. An extensive set of simulations have been made using different anomaly detection algorithms, comparing their performances and efficiencies using several extra metrics in order to complement ROC curves analysis. Results support our proposal and demonstrate that ROC curves do not provide a good visualization of detection performances for themselves. Moreover, a figure of merit has been proposed in this paper which encompasses in a single global metric all the measures yielded for the proposed additional metrics. Therefore, this figure, named Detection Efficiency (DE), takes into account several crucial types of performance assessment that ROC curves do not consider. Results demonstrate that algorithms with the best detection performances according to ROC curves do not have the highest DE values. Consequently, the recommendation of using extra measures to properly evaluate performances have been supported and justified by the conclusions drawn from the simulations.

ROC curves predicted by a model of visual search.

PubMed

Chakraborty, D P

2006-07-21

In imaging tasks where the observer is uncertain whether lesions are present, and where they could be present, the image is searched for lesions. In the free-response paradigm, which closely reflects this task, the observer provides data in the form of a variable number of mark-rating pairs per image. In a companion paper a statistical model of visual search has been proposed that has parameters characterizing the perceived lesion signal-to-noise ratio, the ability of the observer to avoid marking non-lesion locations, and the ability of the observer to find lesions. The aim of this work is to relate the search model parameters to receiver operating characteristic (ROC) curves that would result if the observer reported the rating of the most suspicious finding on an image as the overall rating. Also presented are the probability density functions (pdfs) of the underlying latent decision variables corresponding to the highest rating for normal and abnormal images. The search-model-predicted ROC curves are 'proper' in the sense of never crossing the chance diagonal and the slope is monotonically changing. They also have the interesting property of not allowing the observer to move the operating point continuously from the origin to (1, 1). For certain choices of parameters the operating points are predicted to be clustered near the initial steep region of the curve, as has been observed by other investigators. The pdfs are non-Gaussians, markedly so for the abnormal images and for certain choices of parameter values, and provide an explanation for the well-known observation that experimental ROC data generally imply a wider pdf for abnormal images than for normal images. Some features of search-model-predicted ROC curves and pdfs resemble those predicted by the contaminated binormal model, but there are significant differences. The search model appears to provide physical explanations for several aspects of experimental ROC curves.

Predicting malignant and tuberculous pleural effusions through demographics and pleural fluid analysis of patients.

PubMed

Valdés, Luis; San-José, Esther; Ferreiro, Lucía; Golpe, Antonio; González-Barcala, Francisco-Javier; Toubes, María E; Rodríguez-Álvarez, María X; Álvarez-Dobaño, José M; Rodríguez-Núñez, Nuria; Rábade, Carlos; Gude, Francisco

2015-04-01

The differential diagnosis of malignant and tuberculous pleural effusion is frequently difficult. The aim of our study is to determine the discrimination value of demographic parameters and different biological markers in pleural fluid. In pleural fluid obtained from 106 patients with tuberculous, 250 with malignant and 218 with miscellaneous pleural effusion, clinical and analytical parameters were analysed, applying polytomous regression analysis and the receiver operating characteristic (ROC) curves. The three groups could be differentiated using the measured markers. Age, tumour necrosing factor-alpha, lactate dehydrogenase (LDH), adenosine deaminase (ADA), C-reactive protein (CRP) and carcinoembryonic antigen (CEA) were significant predictors for discriminating tuberculous from malignant pleural effusions; nucleated cells, lymphocytes, cholesterol, LDH, ADA, CRP, CEA and CA15.3 distinguish between malignant and miscellaneous pleural effusions. The ROC areas (95% confidence interval) were, 0.973 (0.953, 0.992) for tuberculous, 0.922 (0.900, 0.943) for miscellaneous, and 0.927 (0.907, 0.948) for malignant pleural effusion. The polytomous model correctly classified a significantly high proportion of patients with tuberculosis (85.8%) and cancer (81.6%). The incorrect classification rate was 17.8%, which increased to 19.5% in the correction using bootstrap. The results obtained to estimate the probability of tuberculous and malignant pleural effusion confirm that this model achieves a high diagnostic accuracy. This model should be applied to determine which patients with a pleural effusion of unknown origin would not benefit from further invasive procedures. © 2014 John Wiley & Sons Ltd.

Discriminability of Personality Profiles in Isolated and Co-Morbid Marijuana and Nicotine Users

PubMed Central

Ketcherside, Ariel; Jeon-Slaughter, Haekyung; Baine, Jessica L.; Filbey, Francesca M

2016-01-01

Specific personality traits have been linked with substance use disorders (SUDs), genetic mechanisms, and brain systems. Thus, determining the specificity of personality traits to types of SUD can advance the field towards defining SUD endophenotypes as well as understanding the brain systems involved for the development of novel treatments. Disentangling these factors is particularly important in highly co-morbid SUDs, such as marijuana and nicotine use, so treatment can occur effectively for both. This study evaluated personality traits that distinguish isolated and co-morbid use of marijuana and nicotine. To that end, we collected the NEO Five Factor Inventory in participants who used marijuana-only (n=59), nicotine-only (n=27), both marijuana and nicotine (n=28), and in non-using controls (n=28). We used factor analyses to identify personality profiles, which are linear combinations of the five NEO Factors. We then conducted Receiver Operating Characteristics (ROC) curve analysis to test accuracy of the personality factors in discriminating isolated and co-morbid marijuana and nicotine users from each other. ROC curve analysis distinguished the four groups based on their NEO personality patterns. Results showed that NEO Factor 2 (openness, extraversion, agreeableness) discriminated marijuana and marijuana + nicotine users from controls and nicotine-only users with high predictability. Additional ANOVA results showed that the openness dimension discriminated marijuana users from nicotine users. These findings suggest that personality dimensions distinguish marijuana users from nicotine users and should be considered in prevention strategies. PMID:27086256

Diffuse reflectance spectroscopy from 400-1600 nm to evaluate tumor resection margins during head and neck surgery (Conference Presentation)

NASA Astrophysics Data System (ADS)

Brouwer de Koning, Susan G.; Baltussen, E. J. M.; Karakullukcu, M. Baris; Smit, L.; van Veen, R. L. P.; Hendriks, Benno H. W.; Sterenborg, H. J. C. M.; Ruers, Theo J. M.

2017-02-01

This ex vivo study evaluates the feasibility of diffuse reflectance spectroscopy (DRS) for discriminating tumor from healthy oral tissue, with the aim to develop a technique that can be used to determine a complete excision of tumor through intraoperative margin assessment. DRS spectra were acquired on fresh surgical specimens from patients with an oral squamous cell carcinoma. The spectra represent a measure of diffuse light reflectance (wavelength range of 400-1600 nm), detected after illuminating tissue with a source fiber at 1.0 and 2.0 mm distances from a detection fiber. Spectra were obtained from 23 locations of tumor tissue and 16 locations of healthy muscle tissue. Biopsies were taken from all measured locations to facilitate an optimal correlation between spectra and pathological information. The area under the spectrum was used as a parameter to classify spectra of tumor and healthy tissue. Next, a receiver operating characteristics (ROC) analysis was performed to provide the area under the receiver operating curve (AUROC) as a measure for discriminative power. The area under the spectrum between 650 and 750 nm was used in the ROC analysis and provided AUROC values of 0.99 and 0.97, for distances of 1 mm and 2 mm between source and detector fiber, respectively. DRS can discriminate tumor from healthy oral tissue in an ex vivo setting. More specimens are needed to further evaluate this technique with component analyses and classification methods, prior to in vivo patient measurements.

The Italian version of the 16-item prodromal questionnaire (iPQ-16): Field-test and psychometric features.

PubMed

Lorenzo, Pelizza; Silvia, Azzali; Federica, Paterlini; Sara, Garlassi; Ilaria, Scazza; Pupo, Simona; Andrea, Raballo

2018-03-20

Among current early screeners for psychosis-risk states, the Prodromal Questionnaire-16 items (PQ-16) is often used. We aimed to assess validity and reliability of the Italian version of the PQ-16 in a young adult help-seeking population. We included 154 individuals aged 18-35years seeking help at the Reggio Emilia outpatient mental health services in a large semirural catchment area (550.000 inhabitants). Participants completed the Italian version of the PQ-16 (iPQ-16) and were subsequently evaluated with the Comprehensive Assessment of At-Risk Mental States (CAARMS). We examined diagnostic accuracy (i.e. specificity, sensitivity, negative and positive likelihood ratios, and negative and positive predictive values) and content, convergent, and concurrent validity between PQ-16 and CAARMS using Cronbach's alpha, Spearman's rho, and Cohen's kappa, respectively. We also tested the validity of the adopted PQ-16 cut-offs through Receiver Operating Characteristic (ROC) curves plotted against CAARMS diagnoses and the 1-year predictive validity of the PQ-16. The iPQ-16 showed high internal consistency and acceptable diagnostic accuracy and concurrent validity. ROC analyses pointed to a cut-off score of ≥5 as best cut-off. After 12months of follow-up, 8.7% of participants with a PQ-16 symptom total score of ≥5 who were below the CAARMS psychosis threshold at the baseline, developed a psychotic disorder. Psychometric properties of the iPQ-16 were satisfactory. Copyright © 2018. Published by Elsevier B.V.

Gingivitis and salivary osmolality in children with cerebral palsy.

PubMed

Santos, Maria Teresa Botti Rodrigues; Ferreira, Maria Cristina Duarte; Guaré, Renata Oliveira; Diniz, Michele Baffi; Rösing, Cassiano Kuchenbecker; Rodrigues, Jonas Almeida; Duarte, Danilo Antonio

2016-11-01

To investigate the influence of salivary osmolality on the occurrence of gingivitis in children with cerebral palsy (CP). A total of 82 children with spastic CP were included in this cross-sectional study. Oral motor performance and gingival conditions were evaluated. Unstimulated saliva was collected using cotton swabs, and salivary osmolality was measured using a freezing point depression osmometer. Spearman's coefficient, receiver operating characteristic (ROC), and multiple logistic regression analyses were performed. Strong correlation (r > 0.7) was determined among salivary osmolality, salivary flow rate, visible plaque, dental calculus, and the occurrence of gingivitis. The area under the ROC to predict the influence of salivary osmolality on the occurrence of gingivitis was 0.88 (95% CI 0.81-0.96; P < 0.001). The cutoff value of 84.5 for salivary osmolality presented good sensitivity and specificity, both higher than 77%. The proportion of children presenting salivary osmolality ≤84.5 mOsm/kgH 2 O and gingivitis was 22.5%, whereas for the group presenting osmolality >84.5 mOsm/kgH 2 O, the proportion of children with gingivitis was 77.5%. Salivary osmolality above 84.5 increased the likelihood of gingivitis fivefold, whereas each additional 0.1 mL of salivary flow reduced the likelihood of gingivitis by 97%. Gingivitis occurs more frequently in children with CP showing increased values of salivary osmolality. © 2016 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Total Urine Protein-to-Creatinine Ratio Can Predict the Presence of Microalbuminuria

PubMed Central

Yamamoto, Kyoko; Yamamoto, Hiroyuki; Yoshida, Katsumi; Niwa, Koichiro; Nishi, Yutaro; Mizuno, Atsushi; Kuwabara, Masanari; Asano, Taku; Sakoda, Kunihiro; Niinuma, Hiroyuki; Nakahara, Fumiko; Takeda, Kyoko; Shindoh, Chiyohiko; Komatsu, Yasuhiro

2014-01-01

Background The Kidney Disease: Improving Global Outcomes chronic kidney disease (CKD) guidelines recommend that CKD be classified based on the etiology, glomerular filtration rate (GFR) and degree of albuminuria. The present study aimed to establish a method that predicts the presence of microalbuminuria by measuring the total urine protein-to-creatinine ratio (TPCR) in patients with cardiovascular disease (CVD) risk factors. Methods and Results We obtained urine samples from 1,033 patients who visited the cardiovascular clinic at St. Luke's International Hospital from February 2012 to August 2012. We measured the TPCR and the urine albumin-to-creatinine ratio (ACR) from random spot urine samples. We performed correlation, receiver operating characteristic (ROC) curve, sensitivity, and subgroup analyses. There was a strong positive correlation between the TPCR and ACR (R2 = 0.861, p<0.001). A ROC curve analysis for the TPCR revealed a sensitivity of 94.4%, a specificity of 86.1%, and an area under the curve of 0.903 for detecting microalbuminuria for a TPCR cut-off value of 84 mg/g of creatinine. The subgroup analysis indicated that the cut-off value could be used for patients with CVD risk factors. Conclusions These results suggest that the TPCR with an appropriate cut-off value could be used to screen for the presence of microalbuminuria in patients with CVD risk factors. This simple, inexpensive measurement has broader applications, leading to earlier intervention and public benefit. PMID:24614247

Pancreatic thickness as a predictive factor for postoperative pancreatic fistula after distal pancreatectomy using an endopath stapler.

PubMed

Okano, Keiichi; Oshima, Minoru; Kakinoki, Keitaro; Yamamoto, Naoki; Akamoto, Shintaro; Yachida, Shinichi; Hagiike, Masanobu; Kamada, Hideki; Masaki, Tsutomu; Suzuki, Yasuyuki

2013-02-01

No consistent risk factor has yet been established for the development of pancreatic fistula (PF) after distal pancreatectomy (DP) with a stapler. A total of 31 consecutive patients underwent DP with an endopath stapler between June 2006 and December 2010 using a slow parenchymal flattening technique. The risk factors for PF after DP with an endopath stapler were identified based on univariate and multivariate analyses. Clinical PF developed in 7 of 31 (22 %) patients who underwent DP with a stapler. The pancreata were significantly thicker at the transection line in patients with PF (19.4 ± 1.47 mm) in comparison to patients without PF (12.6 ± 0.79 mm; p = 0.0003). A 16-mm cut-off for pancreatic thickness was established based on the receiver operating characteristic (ROC) curve; the area under the ROC curve was 0.875 (p = 0.0215). Pancreatic thickness (p = 0.0006) and blood transfusion (p = 0.028) were associated with postoperative PF in a univariate analysis. Pancreatic thickness was the only significant independent factor (odds ratio 9.99; p = 0.036) according to a multivariate analysis with a specificity of 72 %, and a sensitivity of 85 %. Pancreatic thickness is a significant independent risk factor for PF development after DP with an endopath stapler. The stapler technique is thus considered to be an appropriate modality in patients with a pancreatic thicknesses of <16 mm.

Prospective comparison among transient elastography, supersonic shear imaging, and ARFI imaging for predicting fibrosis in nonalcoholic fatty liver disease

PubMed Central

Joo, Sae Kyung; Woo, Hyunsik; Lee, Dong Hyeon; Jung, Yong Jin; Kim, Byeong Gwan; Lee, Kook Lae

2017-01-01

The diagnostic performance of supersonic shear imaging (SSI) in comparison with those of transient elastography (TE) and acoustic radiation force impulse imaging (ARFI) for staging fibrosis in nonalcoholic fatty liver disease (NAFLD) patients has not been fully assessed, especially in Asian populations with relatively lean NAFLD compared to white populations. Thus, we focused on comparing the diagnostic performances of TE, ARFI, and SSI for staging fibrosis in a head-to-head manner, and identifying the clinical, anthropometric, biochemical, and histological features which might affect liver stiffness measurement (LSM) in our prospective biopsy-proven NAFLD cohort. In this study, ninety-four patients with biopsy-proven NAFLD were included prospectively. Liver stiffness was measured using TE, SSI, and ARFI within 1 month of liver biopsy. The diagnostic performance for staging fibrosis was assessed using receiver operating characteristic (ROC) analysis. Anthropometric data were evaluated as covariates influencing LSM by regression analyses. Liver stiffness correlated with fibrosis stage (p < 0.05); the area under the ROC curve of TE (kPa), SSI (kPa), and ARFI (m/s) were as follows: 0.757, 0.759, and 0.657 for significant fibrosis and 0.870, 0.809, and 0.873 for advanced fibrosis. Anthropometric traits were significant confounders affecting SSI, while serum liver injury markers significantly confounded TE and ARFI. In conclusion, the LSM methods had similar diagnostic performance for staging fibrosis in patients with NAFLD. Pre-LSM anthropometric evaluation may help predict the reliability of SSI. PMID:29176844

Prediction of sickness absenteeism, disability pension and sickness presenteeism among employees with back pain.

PubMed

Bergström, Gunnar; Hagberg, Jan; Busch, Hillevi; Jensen, Irene; Björklund, Christina

2014-06-01

The primary aim of this study was to evaluate the predictive ability of the Örebro Musculoskeletal Pain Screening Questionnaire (ÖMPSQ) concerning long-term sick leave, sickness presenteeism and disability pension during a follow-up period of 2 years. The study group consisted of 195 employees visiting the occupational health service (OHS) due to back pain. Using receiver operating characteristic (ROC) curves, the area under the curve (AUC) varied from 0.67 to 0.93, which was from less accurate for sickness presenteeism to highly accurate for the prediction of disability pension. For registered sick leave during 6 months following the baseline the AUC from the ROC analyses was moderately accurate (0.81) and a cut off score of 90 rendered a high sensitivity of 0.89 but a low specificity of 0.46 whereas a cut off score of 105 improves the specificity substantially but at the cost of some sensitivity. The predictive ability appears to decrease with time. Several workplace factors beyond those included in the ÖMPSQ were considered but only social support at the workplace was significantly related to future long-term sick leave besides the total score of the ÖMPSQ. The results of this study extend and confirm the findings of earlier research on the ÖMPSQ. Assessment of psychosocial risk factors among employees seeking help for back pain at the OHS could be helpful in the prevention of work disabling problems.

Lymphopenia predicts poor prognosis in patients with esophageal squamous cell carcinoma.

PubMed

Feng, Ji-Feng; Liu, Jin-Shi; Huang, Ying

2014-12-01

Lymphopenia is a useful predictive factor in several cancers. The aim of this study was to determine the prognostic value of lymphopenia in patients with esophageal squamous cell carcinoma (ESCC).A retrospective analysis of 307 consecutive patients who had undergone esophagectomy for ESCC was conducted. In our study, a lymphocyte count (LC) of fewer than 1.0 Giga/L was defined as lymphopenia. Kaplan-Meier method was used to calculate the cancer-specific survival (CSS). Cox regression analyses were performed to evaluate the prognostic factors. Receiver operating characteristic (ROC) curve was also plotted to verify the accuracy of LC for CSS prediction.The mean LC was 1.55 ± 0.64 Giga/L (range 0.4-3.7 Giga/L). The incidence of lymphopenia (LC < 1.0 Giga/L) was 16.6% (51/307). Patients with lymphopenia (LC < 1.0 Giga/L) had a significantly shorter 5-year CSS (21.6% vs 43.8%, P = 0.004). On multivariate analysis, lymphopenia (LC < 1.0 Giga/L) was an independent prognostic factor in patients with ESCC (P = 0.013). Lymphopenia had a hazard ratio (HR) of 1.579 [95% confidence interval (CI): 1.100-2.265] for CSS. ROC curve demonstrated that lymphopenia (LC < 1.0 Giga/L) predicts survival with a sensitivity of 86.2% and a specificity of 27.2%. Lymphopenia (LC < 1.0 Giga/L) is still an independent predictive factor for long-term survival in patients with ESCC.

Methodologies for the assessment of earthquake-triggered landslides hazard. A comparison of Logistic Regression and Artificial Neural Network models.

NASA Astrophysics Data System (ADS)

García-Rodríguez, M. J.; Malpica, J. A.; Benito, B.

2009-04-01

In recent years, interest in landslide hazard assessment studies has increased substantially. They are appropriate for evaluation and mitigation plan development in landslide-prone areas. There are several techniques available for landslide hazard research at a regional scale. Generally, they can be classified in two groups: qualitative and quantitative methods. Most of qualitative methods tend to be subjective, since they depend on expert opinions and represent hazard levels in descriptive terms. On the other hand, quantitative methods are objective and they are commonly used due to the correlation between the instability factors and the location of the landslides. Within this group, statistical approaches and new heuristic techniques based on artificial intelligence (artificial neural network (ANN), fuzzy logic, etc.) provide rigorous analysis to assess landslide hazard over large regions. However, they depend on qualitative and quantitative data, scale, types of movements and characteristic factors used. We analysed and compared an approach for assessing earthquake-triggered landslides hazard using logistic regression (LR) and artificial neural networks (ANN) with a back-propagation learning algorithm. One application has been developed in El Salvador, a country of Central America where the earthquake-triggered landslides are usual phenomena. In a first phase, we analysed the susceptibility and hazard associated to the seismic scenario of the 2001 January 13th earthquake. We calibrated the models using data from the landslide inventory for this scenario. These analyses require input variables representing physical parameters to contribute to the initiation of slope instability, for example, slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness, while the occurrence or non-occurrence of landslides is considered as dependent variable. The results of the landslide susceptibility analysis are checked using landslide location data. These results show a high concordance between the landslide inventory and the high susceptibility estimated zone with an adjustment of 95.1 % for ANN model and 89.4% for LR model. In addition, we make a comparative analysis of both techniques using the Receiver Operating Characteristic (ROC) curve, a graphical plot of the sensitivity vs. (1 - specificity) for a binary classifier system in function of its discrimination threshold, and calculating the Area Under the ROC (AUROC) value for each model. Finally, the previous models are used for the developing a new probabilistic landslide hazard map for future events. They are obtained combining the expected triggering factor (calculated earthquake ground motion) for a return period of 475 years with the susceptibility map.

Area and volume ratios for prediction of visual outcome in idiopathic macular hole.

PubMed

Geng, Xing-Yun; Wu, Hui-Qun; Jiang, Jie-Hui; Jiang, Kui; Zhu, Jun; Xu, Yi; Dong, Jian-Cheng; Yan, Zhuang-Zhi

2017-01-01

To predict the visual outcome in patients undergoing macular hole surgery by two novel three-dimensional morphological parameters on optical coherence tomography (OCT): area ratio factor (ARF) and volume ratio factor (VRF). A clinical case series was conducted, including 54 eyes of 54 patients with an idiopathic macular hole (IMH). Each patient had an OCT examination before and after surgery. Morphological parameters of the macular hole, such as minimum diameter, base diameter, and height were measured. Then, the macular hole index (MHI), tractional hole index (THI), and hole form factor (HFF) were calculated. Meanwhile, novel postoperative macular hole (MH) factors, ARF and VRF were calculated by three-dimensional morphology. Bivariate correlations were performed to acquire asymptotic significance values between the steady best corrected visual acuity (BCVA) after surgery and 2D/3D arguments of MH by the Pearson method with two-tailed test. All significant factors were analyzed by the receiver operating characteristic (ROC) curve analysis of SPSS software which were responsible for vision recovery. ROC curves analyses were performed to further discuss the different parameters on the prediction of visual outcome. The mean and standard deviation values of patients' age, symptoms duration, and follow-up time were 64.8±8.9y (range: 28-81), 18.6±11.5d (range: 2-60), and 11.4±0.4mo (range: 6-24), respectively. Steady-post-BCVA analyzed with bivariate correlations was found to be significantly correlated with base diameter ( r =0.521, P <0.001), minimum diameter ( r =0.514, P <0.001), MHI ( r =-0.531, P <0.001), THI ( r =-0.386, P =0.004), HFF ( r =-0.508, P <0.001), and ARF ( r =-0.532, P <0.001). Other characteristic parameters such as age, duration of surgery, height, diameter hole index, and VRF were not statistically significant with steady-post-BCVA. According to area under the curve (AUC) values, values of ARF, MHI, HFF, minimum diameter, THI, and base diameter are 0.806, 0.772, 0.750, 0.705, 0.690, and 0.686, respectively. However, Steady-post-BCVA analysis with bivariate correlations for VRF was no statistical significance. Results of ROC curve analysis indicated that the MHI value, HFF, and ARF was greater than 0.427, 1.027 and 1.558 respectively which could correlate with better visual acuity. Compared with MHI and HFF, ARF could effectively express three-dimensional characteristics of macular hole and achieve better sensitivity and specificity. Thus, ARF could be the most effective parameter to predict the visual outcome in macular hole surgery.

From Humans to Rats and Back Again: Bridging the Divide between Human and Animal Studies of Recognition Memory with Receiver Operating Characteristics

ERIC Educational Resources Information Center

Koen, Joshua D.; Yonelinas, Andrew P.

2011-01-01

Receiver operating characteristics (ROCs) have been used extensively to study the processes underlying human recognition memory, and this method has recently been applied in studies of rats. However, the extent to which the results from human and animal studies converge is neither entirely clear, nor is it known how the different methods used to…

Validation of a German version of the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E).

PubMed

Metternich, Birgitta; Wagner, Kathrin; Buschmann, Franziska; Anger, Robin; Schulze-Bonhage, Andreas

2012-12-01

Goal of the present study was the validation of a German version of the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E). 197 adult epilepsy patients completed the NDDI-E (185 completed both the NDDI-E and BDI). 95 patients received psychiatric consults. 33 patients received a diagnosis of major depression according to ICD-10 criteria. Internal consistency of the NDDI-E was .83. Receiver operating characteristics (ROC) showed an area under the curve of 0.92. Applying a cutoff score of ≥14 resulted in both sensitivity and specificity of 0.85. In the subsample with psychiatric consult, at the same optimal cutoff, sensitivity was 0.92, and specificity was 0.86. Further analyses showed a high concurrent validity with the BDI. The German version of the NDDI-E constitutes a brief and reliable depression screening instrument for epilepsy patients. Copyright © 2012 Elsevier Inc. All rights reserved.

Using the Autism-spectrum quotient to discriminate Autism Spectrum Disorder from ADHD in adult patients with and without comorbid Substance Use Disorder.

PubMed

Sizoo, Bram B; van den Brink, Wim; Gorissen-van Eenige, Marielle; Koeter, Maarten W; van Wijngaarden-Cremers, Patricia J M; van der Gaag, Rutger Jan

2009-09-01

It is unknown whether the Autism-spectrum quotient (AQ) can discriminate between Autism Spectrum Disorder (ASD) and Attention Deficit and Hyperactivity Disorder (ADHD) with or without comorbid Substance Use Disorder (SUD). ANOVA's were used to analyse the mean AQ (sub)scores of 129 adults with ASD or ADHD. We applied receiver operating characteristic (ROC) computations to assess discriminant power. All but one of the mean AQ (sub)scores were significantly higher for adults with ASD compared to those with ADHD. The SUD status in general was not significantly associated with AQ (sub)scores. On the Social Skills subscale patients with ASD and comorbid SUD showed less impairment than those without SUD. The cut-off score 26 yielded 73% correct classifications. The clinical use of the AQ in differentiating between ASD and ADHD is limited.

Universal School Readiness Screening at Kindergarten Entry

ERIC Educational Resources Information Center

Quirk, Matthew; Dowdy, Erin; Dever, Bridget; Carnazzo, Katherine; Bolton, Courtney

2018-01-01

Researchers examined the concurrent and predictive validity of a brief (12-item) teacher-rated school readiness screener, the Kindergarten Student Entrance Profile (KSEP), using receiver operating characteristic (ROC) curve analysis to examine associations between (N = 78) children's social-emotional (SE) and cognitive (COG) readiness with…

Immunohistochemistry of cytokeratins 7, 8, 17, 18, and 19, and GLUT-1 aids differentiation of desmoplastic malignant mesothelioma from fibrous pleuritis.

PubMed

Horiuchi, Toshikatsu; Ogata, Sho; Tominaga, Susumu; Hiroi, Sadayuki; Kawahara, Kunimitsu; Hebisawa, Akira; Irei, Isao; Ito, Ichiro; Kameya, Toru; Tsujimura, Tohru; Nakano, Takashi; Nakanishi, Kuniaki; Kawai, Toshiaki

2013-05-01

It is difficult to distinguish desmoplastic malignant mesothelioma (DMM) from fibrous pleuritis (FP). We investigated the utility of immunohistochemistry as a way of differentiating between DMM and FP. We examined 11 DMMs and 46 FPs with the aid of antibodies against 18 cytokeratin (CK) subtypes, calponin, caldesmon, desmin, and GLUT-1. The best sensitivity and specificity cut-off values in the receiver operating characteristic curves (ROC) for CKs 7, 8, 17, 18, and 19, and GLUT-1 were each above 60%. When cases with either DMM or FP were partitioned by the staining score associated with the best sensitivity and specificity cut-off values in ROC, the incidence of a positive expression for CKs 7, 8, 17, 18, and 19, and GLUT-1 was significantly higher in DMM than in FP. In conclusion, immunohistochemistry for CKs 7, 8, 17, 18, and 19, and GLUT-1 may be useful, alongside histological characteristics, for separating DMM from FP.

A comprehensive visual rating scale of brain magnetic resonance imaging: application in elderly subjects with Alzheimer's disease, mild cognitive impairment, and normal cognition.

PubMed

Jang, Jae-Won; Park, So Young; Park, Young Ho; Baek, Min Jae; Lim, Jae-Sung; Youn, Young Chul; Kim, SangYun

2015-01-01

Brain magnetic resonance imaging (MRI) shows cerebral structural changes. However, a unified comprehensive visual rating scale (CVRS) has seldom been studied. Thus, we combined brain atrophy and small vessel disease scales and used an MRI template as a CVRS. The aims of this study were to design a simple and reliable CVRS, validate it by investigating cerebral structural changes in clinical groups, and made comparison to the volumetric measurements. Elderly subjects (n = 260) with normal cognition (NC, n = 65), mild cognitive impairment (MCI, n = 101), or Alzheimer's disease (AD, n = 94) were evaluated with brain MRI according to the CVRS of brain atrophy and small vessel disease. Validation of the CVRS with structural changes, neuropsychological tests, and volumetric analyses was performed. The CVRS revealed a high intra-rater and inter-rater agreement and it reflected the structural changes of subjects with NC, MCI, and AD better than volumetric measures (CVRS-coronal: F = 13.5, p < 0.001; CVRS-axial: F = 19.9, p < 0.001). The area under the receiver operation curve (aROC) of the CVRS showed higher accuracy than volumetric analyses. (NC versus MCI aROC: CVRS-coronal, 0.777; CVRS-axial, 0.773; MCI versus AD aROC: CVRS-coronal, 0.680; CVRS-axial, 0.681). The CVRS can be used clinically to conveniently measure structural changes of brain. It reflected cerebral structural changes of clinical groups and correlated with the age better than volumetric measures.

Initial Validation of a Comprehensive Assessment Instrument for Bereavement-Related Grief Symptoms and Risk of Complications: The Indicator of Bereavement Adaptation—Cruse Scotland (IBACS)

PubMed Central

Schut, Henk; Stroebe, Margaret S.; Wilson, Stewart; Birrell, John

2016-01-01

Objective This study assessed the validity of the Indicator of Bereavement Adaptation Cruse Scotland (IBACS). Designed for use in clinical and non-clinical settings, the IBACS measures severity of grief symptoms and risk of developing complications. Method N = 196 (44 male, 152 female) help-seeking, bereaved Scottish adults participated at two timepoints: T1 (baseline) and T2 (after 18 months). Four validated assessment instruments were administered: CORE-R, ICG-R, IES-R, SCL-90-R. Discriminative ability was assessed using ROC curve analysis. Concurrent validity was tested through correlation analysis at T1. Predictive validity was assessed using correlation analyses and ROC curve analysis. Optimal IBACS cutoff values were obtained by calculating a maximal Youden index J in ROC curve analysis. Clinical implications were compared across instruments. Results ROC curve analysis results (AUC = .84, p < .01, 95% CI between .77 and .90) indicated the IBACS is a good diagnostic instrument for assessing complicated grief. Positive correlations (p < .01, 2-tailed) with all four instruments at T1 demonstrated the IBACS' concurrent validity, strongest with complicated grief measures (r = .82). Predictive validity was shown to be fair in T2 ROC curve analysis results (n = 67, AUC = .78, 95% CI between .65 and .92; p < .01). Predictive validity was also supported by stable positive correlations between IBACS and other instruments at T2. Clinical indications were found not to differ across instruments. Conclusions The IBACS offers effective grief symptom and risk assessment for use by non-clinicians. Indications are sufficient to support intake assessment for a stepped model of bereavement intervention. PMID:27741246

Multicenter external validation of two malignancy risk prediction models in patients undergoing 18F-FDG-PET for solitary pulmonary nodule evaluation.

PubMed

Perandini, Simone; Soardi, G A; Larici, A R; Del Ciello, A; Rizzardi, G; Solazzo, A; Mancino, L; Zeraj, F; Bernhart, M; Signorini, M; Motton, M; Montemezzi, S

2017-05-01

To achieve multicentre external validation of the Herder and Bayesian Inference Malignancy Calculator (BIMC) models. Two hundred and fifty-nine solitary pulmonary nodules (SPNs) collected from four major hospitals which underwent 18-FDG-PET characterization were included in this multicentre retrospective study. The Herder model was tested on all available lesions (group A). A subgroup of 180 SPNs (group B) was used to provide unbiased comparison between the Herder and BIMC models. Receiver operating characteristic (ROC) area under the curve (AUC) analysis was performed to assess diagnostic accuracy. Decision analysis was performed by adopting the risk threshold stated in British Thoracic Society (BTS) guidelines. Unbiased comparison performed In Group B showed a ROC AUC for the Herder model of 0.807 (95 % CI 0.742-0.862) and for the BIMC model of 0.822 (95 % CI 0.758-0.875). Both the Herder and the BIMC models were proven to accurately predict the risk of malignancy when tested on a large multicentre external case series. The BIMC model seems advantageous on the basis of a more favourable decision analysis. • The Herder model showed a ROC AUC of 0.807 on 180 SPNs. • The BIMC model showed a ROC AUC of 0.822 on 180 SPNs. • Decision analysis is more favourable to the BIMC model.

Diagnostic accuracy of presepsin (sCD14-ST) as a biomarker of infection and sepsis in the emergency department.

PubMed

de Guadiana Romualdo, Luis García; Torrella, Patricia Esteban; Acebes, Sergio Rebollo; Otón, María Dolores Albaladejo; Sánchez, Roberto Jiménez; Holgado, Ana Hernando; Santos, Enrique Jiménez; Freire, Alejandro Ortín

2017-01-01

Presepsin is a promising biomarker for the diagnosis and prognosis of sepsis. However, results reported about its value to diagnose sepsis in an emergency department (ED) are controversial, probably due to differences in the design of the studies. We have evaluated the diagnostic accuracy of presepsin for infection and sepsis, compared with procalcitonin (PCT) and C-reactive protein (CRP), in patients presenting to the emergency department (ED) with suspected infection. 223 patients with suspected infection were enrolled for the study. Blood samples were collected on admission for measurement of biomarkers. Definitive diagnosis was obtained afterwards by analysis of digital medical records. Receiver operating characteristic (ROC) curve analysis was conducted to determine the diagnostic accuracy. Infection was confirmed in 200 patients, including 130 with non-complicated infection and 70 with sepsis. Median CRP, PCT and presepsin levels were significantly higher in patients with infection and sepsis. PCT was the biomarker with the highest performance for infection (ROC AUC: 0.910); for sepsis, PCT (ROC AUC: 0.815) and presepsin (ROC AUC: 0.775) shown a similar performance. Although presepsin is a valuable biomarker for diagnosis of infection and sepsis, its diagnostic accuracy in our study does not improve that of PCT. Its introduction in clinical practice is not justified. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of ROC on chest direct digital radiography (DR) after image processing in diagnosis of SARS

NASA Astrophysics Data System (ADS)

Lv, Guozheng; Lan, Rihui; Zeng, Qingsi; Zheng, Zhong

2004-05-01

The Severe Acute Respiratory Syndrome (SARS, also called Infectious Atypical Pneumonia), which initially broke out in late 2002, has threatened the public"s health seriously. How to confirm the patients contracting SARS becomes an urgent issue in diagnosis. This paper intends to evaluate the importance of Image Processing in the diagnosis on SARS at the early stage. Receiver Operating Characteristics (ROC) analysis has been employed in this study to compare the value of DR images in the diagnosis of SARS patients before and after image processing by Symphony Software supplied by E-Com Technology Ltd., and DR image study of 72 confirmed or suspected SARS patients were reviewed respectively. All the images taken from the studied patients were processed by Symphony. Both the original and processed images were taken into ROC analysis, based on which the ROC graph for each group of images has been produced as described below: For processed images: a = 1.9745, b = 1.4275, SA = 0.8714; For original images: a = 0.9066, b = 0.8310, SA = 0.7572; (a - intercept, b - slop, SA - Area below the curve). The result shows significant difference between the original images and processed images (P<0.01). In summary, the images processed by Symphony are superior to the original ones in detecting the opacity lesion, and increases the accuracy of SARS diagnosis.

Does consideration of either psychological or material disadvantage improve coronary risk prediction? Prospective observational study of Scottish men.

PubMed

Macleod, John; Metcalfe, Chris; Smith, George Davey; Hart, Carole

2007-09-01

To assess the value of psychosocial risk factors in discriminating between individuals at higher and lower risk of coronary heart disease, using risk prediction equations. Prospective observational study. Scotland. 5191 employed men aged 35 to 64 years and free of coronary heart disease at study enrollment Area under receiver operating characteristic (ROC) curves for risk prediction equations including different risk factors for coronary heart disease. During the first 10 years of follow up, 203 men died of coronary heart disease and a further 200 were admitted to hospital with this diagnosis. Area under the ROC curve for the standard Framingham coronary risk factors was 74.5%. Addition of "vital exhaustion" and psychological stress led to areas under the ROC curve of 74.5% and 74.6%, respectively. Addition of current social class and lifetime social class to the standard Framingham equation gave areas under the ROC curve of 74.6% and 74.9%, respectively. In no case was there strong evidence for improved discrimination of the model containing the novel risk factor over the standard model. Consideration of psychosocial risk factors, including those that are strong independent predictors of heart disease, does not substantially influence the ability of risk prediction tools to discriminate between individuals at higher and lower risk of coronary heart disease.

Assessing multiple-group diagnostic problems with multi-dimensional receiver operating characteristic surfaces: Application to proton MR Spectroscopy (MRS) in HIV-related neurological injury

PubMed Central

Yiannoutsos, Constantin T.; Nakas, Christos T.; Navia, Bradford A.

2013-01-01

We present the multi-dimensional Receiver Operating Characteristic (ROC) surface, a plot of the true classification rates of tests based on levels of biological markers, for multi-group discrimination, as an extension of the ROC curve, commonly used in two-group diagnostic testing. The volume under this surface (VUS) is a global accuracy measure of a test to classify subjects in multiple groups and useful to detect trends in marker measurements. We used three-dimensional ROC surfaces, and associated VUS, to discriminate between HIV-negative (NEG), HIV-positive neurologically asymptomatic (NAS) subjects and patients with AIDS demential complex (ADC), using brain metabolites measured by proton MRS. These were ratios of markers of inflammation, Choline (Cho) and myoinositol (MI), and brain injury, N-acetyl aspartate (NAA), divided by Creatine (Cr), measured in the basal ganglia and the frontal white matter. Statistically significant trends were observed in the three groups with respect to MI/Cr (VUS=0.43; 95% confidence interval (CI) 0.33-0.53), Cho/Cr (0.36; 0.27-0.45) in the basal ganglia and NAA/Cr in the frontal white matter (FWM) (0.29; 0.20-0.38), suggesting a continuum of injury during the neurologically asymptomatic stage of HIV infection, particularly with respect to brain inflammation. Adjusting for age increased the combined classification accuracy of age and NAA/Cr (p=0.053). Pairwise comparisons suggested that neuronal damage associated with NAA/Cr decreases was mainly observed in individuals with ADC, raising issues of synergism between HIV infection and age and possible acceleration of neurological deterioration in an aging HIV-positive population. The three-dimensional ROC surface and its associated VUS are useful for assessing marker accuracy, detecting data trends and offering insight in disease processes affecting multiple groups. PMID:18191586

Blood-based biomarkers used to predict disease activity in Crohn's disease and ulcerative colitis.

PubMed

Burakoff, Robert; Pabby, Vikas; Onyewadume, Louisa; Odze, Robert; Adackapara, Cheryl; Wang, Wei; Friedman, Sonia; Hamilton, Matthew; Korzenik, Joshua; Levine, Jonathan; Makrauer, Frederick; Cheng, Changming; Smith, Hai Choo; Liew, Choong-Chin; Chao, Samuel

2015-05-01

Identifying specific genes that are differentially expressed during inflammatory bowel disease flares may help stratify disease activity. The aim of this study was to identify panels of genes to be able to distinguish disease activity in Crohn's disease (CD) and ulcerative colitis (UC). Patients were grouped into categories based on disease and severity determined by histological grading. Whole blood was collected by PAXgene Blood RNA collection tubes, (PreAnalytiX) and gene expression analysis using messenger RNA was conducted. Logistic regression was performed on multiple combinations of common probe sets, and data were evaluated in terms of discrimination by computing the area under the receiving operator characteristic curve (ROC-AUC). Nine inactive CD, 8 mild CD, 10 moderate-to-severe CD, 9 inactive UC, 8 mild UC, 10 moderate-to-severe UC, and 120 controls were hybridized to Affymetrix U133 Plus 2 microarrays. Panels of 6 individual genes discriminated the stages of disease activity: CD with mild severity {ROC-AUC, 0.89 (95% confidence interval [CI], 0.84%-0.95%)}, CD with moderate-to-severe severity (ROC-AUC 0.98 [95% CI, 0.97-1.0]), UC with mild severity (ROC-AUC 0.92 [95% CI, 0.87-0.96]), and UC with moderate-to-severe severity (ROC-AUC 0.99 [95% CI, 0.97-1.0]). Validation by real-time reverse transcription-PCR confirmed the Affymetrix microarray data. The specific whole blood gene panels reliably distinguished CD and UC and determined the activity of disease, with high sensitivity and specificity in our cohorts of patients. This simple serological test has the potential to become a biomarker to determine the activity of disease.

Utility as a rationale for choosing observer performance assessment paradigms for detection tasks in medical imaging.

PubMed

Wunderlich, Adam; Abbey, Craig K

2013-11-01

Studies of lesion detectability are often carried out to evaluate medical imaging technology. For such studies, several approaches have been proposed to measure observer performance, such as the receiver operating characteristic (ROC), the localization ROC (LROC), the free-response ROC (FROC), the alternative free-response ROC (AFROC), and the exponentially transformed FROC (EFROC) paradigms. Therefore, an experimenter seeking to carry out such a study is confronted with an array of choices. Traditionally, arguments for different approaches have been made on the basis of practical considerations (statistical power, etc.) or the gross level of analysis (case-level or lesion-level). This article contends that a careful consideration of utility should form the rationale for matching the assessment paradigm to the clinical task of interest. In utility theory, task performance is commonly evaluated with total expected utility, which integrates the various event utilities against the probability of each event. To formalize the relationship between expected utility and the summary curve associated with each assessment paradigm, the concept of a "natural" utility structure is proposed. A natural utility structure is defined for a summary curve when the variables associated with the summary curve axes are sufficient for computing total expected utility, assuming that the disease prevalence is known. Natural utility structures for ROC, LROC, FROC, AFROC, and EFROC curves are introduced, clarifying how the utilities of correct and incorrect decisions are aggregated by summary curves. Further, conditions are given under which general utility structures for localization-based methodologies reduce to case-based assessment. Overall, the findings reveal how summary curves correspond to natural utility structures of diagnostic tasks, suggesting utility as a motivating principle for choosing an assessment paradigm.

Multi-probe-based resonance-frequency electrical impedance spectroscopy for detection of suspicious breast lesions: improving performance using partial ROC optimization

NASA Astrophysics Data System (ADS)

Lederman, Dror; Zheng, Bin; Wang, Xingwei; Wang, Xiao Hui; Gur, David

2011-03-01

We have developed a multi-probe resonance-frequency electrical impedance spectroscope (REIS) system to detect breast abnormalities. Based on assessing asymmetry in REIS signals acquired between left and right breasts, we developed several machine learning classifiers to classify younger women (i.e., under 50YO) into two groups of having high and low risk for developing breast cancer. In this study, we investigated a new method to optimize performance based on the area under a selected partial receiver operating characteristic (ROC) curve when optimizing an artificial neural network (ANN), and tested whether it could improve classification performance. From an ongoing prospective study, we selected a dataset of 174 cases for whom we have both REIS signals and diagnostic status verification. The dataset includes 66 "positive" cases recommended for biopsy due to detection of highly suspicious breast lesions and 108 "negative" cases determined by imaging based examinations. A set of REIS-based feature differences, extracted from the two breasts using a mirror-matched approach, was computed and constituted an initial feature pool. Using a leave-one-case-out cross-validation method, we applied a genetic algorithm (GA) to train the ANN with an optimal subset of features. Two optimization criteria were separately used in GA optimization, namely the area under the entire ROC curve (AUC) and the partial area under the ROC curve, up to a predetermined threshold (i.e., 90% specificity). The results showed that although the ANN optimized using the entire AUC yielded higher overall performance (AUC = 0.83 versus 0.76), the ANN optimized using the partial ROC area criterion achieved substantially higher operational performance (i.e., increasing sensitivity level from 28% to 48% at 95% specificity and/ or from 48% to 58% at 90% specificity).

Impact of Wisteria floribunda Agglutinin-Positive Mac-2-Binding Protein in Patients with Hepatitis C Virus-Related Compensated Liver Cirrhosis.

PubMed

Hasegawa, Kunihiro; Takata, Ryo; Nishikawa, Hiroki; Enomoto, Hirayuki; Ishii, Akio; Iwata, Yoshinori; Miyamoto, Yuho; Ishii, Noriko; Yuri, Yukihisa; Nakano, Chikage; Nishimura, Takashi; Yoh, Kazunori; Aizawa, Nobuhiro; Sakai, Yoshiyuki; Ikeda, Naoto; Takashima, Tomoyuki; Iijima, Hiroko; Nishiguchi, Shuhei

2016-09-12

We aimed to examine the effect of Wisteria floribunda agglutinin-positive Mac-2-binding protein (WFA⁺-M2BP) level on survival comparing with other laboratory liver fibrosis markers in hepatitis C virus (HCV)-related compensated liver cirrhosis (LC) (n = 165). For assessing prognostic performance of continuous fibrosis markers, we adapted time-dependent receiver operating characteristics (ROC) curves for clinical outcome. In time-dependent ROC analysis, annual area under the ROCs (AUROCs) were plotted. We also calculated the total sum of AUROCs in all time-points (TAAT score) in each fibrosis marker. WFA⁺-M2BP value ranged from 0.66 cutoff index (COI) to 19.95 COI (median value, 5.29 COI). Using ROC analysis for survival, the optimal cutoff point for WFA⁺-M2BP was 6.15 COI (AUROC = 0.79348, sensitivity = 80.0%, specificity = 74.78%). The cumulative five-year survival rate in patients with WFA⁺-M2BP ≥ 6.15 COI (n = 69) was 43.99%, while that in patients with WFA⁺-M2BP < 6.15 COI (n = 96) was 88.40% (p < 0.0001). In the multivariate analysis, absence of hepatocellular carcinoma (p = 0.0008), WFA⁺-M2BP < 6.15 COI (p = 0.0132), achievement of sustained virological response (p < 0.0001) and des-γ-carboxy prothrombin < 41 mAU/mL (p = 0.0018) were significant favorable predictors linked to survival. In time-dependent ROC analysis in all cases, WFA⁺-M2BP had the highest TAAT score among liver fibrosis markers. In conclusion, WFA⁺-M2BP can be a useful predictor in HCV-related compensated LC.

Clinical diagnostic accuracy of acute colonic diverticulitis in patients admitted with acute abdominal pain, a receiver operating characteristic curve analysis.

PubMed

Jamal Talabani, A; Endreseth, B H; Lydersen, S; Edna, T-H

2017-01-01

The study investigated the capability of clinical findings, temperature, C-reactive protein (CRP), and white blood cell (WBC) count to discern patients with acute colonic diverticulitis from all other patients admitted with acute abdominal pain. The probability of acute diverticulitis was assessed by the examining doctor, using a scale from 0 (zero probability) to 10 (100 % probability). Receiver operating characteristic (ROC) curves were used to assess the clinical diagnostic accuracy of acute colonic diverticulitis in patients admitted with acute abdominal pain. Of 833 patients admitted with acute abdominal pain, 95 had acute colonic diverticulitis. ROC curve analysis gave an area under the ROC curve (AUC) of 0.95 (CI 0.92 to 0.97) for ages <65 years, AUC = 0.86 (CI 0.78 to 0.93) in older patients. Separate analysis showed an AUC = 0.83 (CI 0.80 to 0.86) of CRP alone. White blood cell count and temperature were almost useless to discriminate acute colonic diverticulitis from other types of acute abdominal pain, AUC = 0.59 (CI 0.53 to 0.65) for white blood cell count and AUC = 0.57 (0.50 to 0.63) for temperature, respectively. This prospective study demonstrates that standard clinical evaluation by non-specialist doctors based on history, physical examination, and initial blood tests on admission provides a high degree of diagnostic precision in patients with acute colonic diverticulitis.

Incidental Context Information Increases Recollection

ERIC Educational Resources Information Center

Ameen-Ali, Kamar E.; Norman, Liam J.; Eacott, Madeline J.; Easton, Alexander

2017-01-01

The current study describes a receiver-operating characteristic (ROC) task for human participants based on the spontaneous recognition memory paradigms typically used with rodents. Recollection was significantly higher when an object was in the same location and background as at encoding, a combination used to assess episodic-like memory in…

ROC evaluation of SPECT myocardial lesion detectability with and without single iteration non-uniform Chang attenuation compensation using an anthropomorphic female phantom

NASA Astrophysics Data System (ADS)

Jang, Sunyoung; Jaszczak, R. J.; Tsui, B. M. W.; Metz, C. E.; Gilland, D. R.; Turkington, T. G.; Coleman, R. E.

1998-08-01

The purpose of this work was to evaluate lesion detectability with and without nonuniform attenuation compensation (AC) in myocardial perfusion SPECT imaging in women using an anthropomorphic phantom and receiver operating characteristics (ROC) methodology. Breast attenuation causes artifacts in reconstructed images and may increase the difficulty of diagnosis of myocardial perfusion imaging in women. The null hypothesis tested using the ROC study was that nonuniform AC does not change the lesion detectability in myocardial perfusion SPECT imaging in women. The authors used a filtered backprojection (FBP) reconstruction algorithm and Chang's (1978) single iteration method for AC. In conclusion, with the authors' proposed myocardial defect model nuclear medicine physicians demonstrated no significant difference for the detection of the anterior wall defect; however, a greater accuracy for the detection of the inferior wall defect was observed without nonuniform AC than with it (P-value=0.0034). Medical physicists did not demonstrate any statistically significant difference in defect detection accuracy with or without nonuniform AC in the female phantom.

Profound Effect of Profiling Platform and Normalization Strategy on Detection of Differentially Expressed MicroRNAs – A Comparative Study

PubMed Central

Meyer, Swanhild U.; Kaiser, Sebastian; Wagner, Carola; Thirion, Christian; Pfaffl, Michael W.

2012-01-01

Background Adequate normalization minimizes the effects of systematic technical variations and is a prerequisite for getting meaningful biological changes. However, there is inconsistency about miRNA normalization performances and recommendations. Thus, we investigated the impact of seven different normalization methods (reference gene index, global geometric mean, quantile, invariant selection, loess, loessM, and generalized procrustes analysis) on intra- and inter-platform performance of two distinct and commonly used miRNA profiling platforms. Methodology/Principal Findings We included data from miRNA profiling analyses derived from a hybridization-based platform (Agilent Technologies) and an RT-qPCR platform (Applied Biosystems). Furthermore, we validated a subset of miRNAs by individual RT-qPCR assays. Our analyses incorporated data from the effect of differentiation and tumor necrosis factor alpha treatment on primary human skeletal muscle cells and a murine skeletal muscle cell line. Distinct normalization methods differed in their impact on (i) standard deviations, (ii) the area under the receiver operating characteristic (ROC) curve, (iii) the similarity of differential expression. Loess, loessM, and quantile analysis were most effective in minimizing standard deviations on the Agilent and TLDA platform. Moreover, loess, loessM, invariant selection and generalized procrustes analysis increased the area under the ROC curve, a measure for the statistical performance of a test. The Jaccard index revealed that inter-platform concordance of differential expression tended to be increased by loess, loessM, quantile, and GPA normalization of AGL and TLDA data as well as RGI normalization of TLDA data. Conclusions/Significance We recommend the application of loess, or loessM, and GPA normalization for miRNA Agilent arrays and qPCR cards as these normalization approaches showed to (i) effectively reduce standard deviations, (ii) increase sensitivity and accuracy of differential miRNA expression detection as well as (iii) increase inter-platform concordance. Results showed the successful adoption of loessM and generalized procrustes analysis to one-color miRNA profiling experiments. PMID:22723911

Non-small cell lung cancer: Whole-lesion histogram analysis of the apparent diffusion coefficient for assessment of tumor grade, lymphovascular invasion and pleural invasion

PubMed Central

Tsuchiya, Naoko; Doai, Mariko; Usuda, Katsuo; Uramoto, Hidetaka

2017-01-01

Purpose Investigating the diagnostic accuracy of histogram analyses of apparent diffusion coefficient (ADC) values for determining non-small cell lung cancer (NSCLC) tumor grades, lymphovascular invasion, and pleural invasion. Materials and methods We studied 60 surgically diagnosed NSCLC patients. Diffusion-weighted imaging (DWI) was performed in the axial plane using a navigator-triggered single-shot, echo-planar imaging sequence with prospective acquisition correction. The ADC maps were generated, and we placed a volume-of-interest on the tumor to construct the whole-lesion histogram. Using the histogram, we calculated the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC, skewness, and kurtosis. Histogram parameters were correlated with tumor grade, lymphovascular invasion, and pleural invasion. We performed a receiver operating characteristics (ROC) analysis to assess the diagnostic performance of histogram parameters for distinguishing different pathologic features. Results The ADC mean, 10th, 25th, 50th, 75th, 90th, and 95th percentiles showed significant differences among the tumor grades. The ADC mean, 25th, 50th, 75th, 90th, and 95th percentiles were significant histogram parameters between high- and low-grade tumors. The ROC analysis between high- and low-grade tumors showed that the 95th percentile ADC achieved the highest area under curve (AUC) at 0.74. Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis. Kurtosis achieved the highest AUC at 0.809. Pleural invasion was only associated with skewness, with the AUC of 0.648. Conclusions ADC histogram analyses on the basis of the entire tumor volume are able to stratify NSCLCs' tumor grade, lymphovascular invasion and pleural invasion. PMID:28207858

Association of serum microRNAs with islet autoimmunity, disease progression and metabolic impairment in relatives at risk of type 1 diabetes.

PubMed

Snowhite, Isaac V; Allende, Gloria; Sosenko, Jay; Pastori, Ricardo L; Messinger Cayetano, Shari; Pugliese, Alberto

2017-08-01

MicroRNAs (miRNAs) are key regulators of gene expression and novel biomarkers for many diseases. We investigated the hypothesis that serum levels of some miRNAs would be associated with islet autoimmunity and/or progression to type 1 diabetes. We measured levels of 93 miRNAs most commonly detected in serum. This retrospective cohort study included 150 autoantibody-positive and 150 autoantibody-negative family-matched siblings enrolled in the TrialNet Pathway to Prevention Study. This was a young cohort (mean age = 11 years), and most autoantibody-positive relatives were at high risk because they had multiple autoantibodies, with 39/150 (26%, progressors) developing type 1 diabetes within an average 8.7 months of follow-up. We analysed miRNA levels in relation to autoantibody status, future development of diabetes and OGTT C-peptide and glucose indices of disease progression. Fifteen miRNAs were differentially expressed when comparing autoantibody-positive/negative siblings (range -2.5 to 1.3-fold). But receiver operating characteristic (ROC) analysis indicated low specificity and sensitivity. Seven additional miRNAs were differentially expressed among autoantibody-positive relatives according to disease progression; ROC returned significant AUC values and identified miRNA cut-off levels associated with an increased risk of disease in both cross-sectional and survival analyses. Levels of several miRNAs showed significant correlations (r values range 0.22-0.55) with OGTT outcomes. miR-21-3p, miR-29a-3p and miR-424-5p had the most robust associations. Serum levels of selected miRNAs are associated with disease progression and confer additional risk of the development of type 1 diabetes in young autoantibody-positive relatives. Further studies, including longitudinal assessments, are warranted to further define miRNA biomarkers for prediction of disease risk and progression.

Can adverse maternal and perinatal outcomes be predicted when blood pressure becomes elevated? Secondary analyses from the CHIPS (Control of Hypertension In Pregnancy Study) randomized controlled trial.

PubMed

Magee, Laura A; von Dadelszen, Peter; Singer, Joel; Lee, Terry; Rey, Evelyne; Ross, Susan; Asztalos, Elizabeth; Murphy, Kellie E; Menzies, Jennifer; Sanchez, Johanna; Gafni, Amiram; Gruslin, Andrée; Helewa, Michael; Hutton, Eileen; Lee, Shoo K; Logan, Alexander G; Ganzevoort, Wessel; Welch, Ross; Thornton, Jim G; Moutquin, Jean Marie

2016-07-01

For women with chronic or gestational hypertension in CHIPS (Control of Hypertension In Pregnancy Study, NCT01192412), we aimed to examine whether clinical predictors collected at randomization could predict adverse outcomes. This was a planned, secondary analysis of data from the 987 women in the CHIPS Trial. Logistic regression was used to examine the impact of 19 candidate predictors on the probability of adverse perinatal (pregnancy loss or high level neonatal care for >48 h, or birthweight <10th percentile) or maternal outcomes (severe hypertension, preeclampsia, or delivery at <34 or <37 weeks). A model containing all candidate predictors was used to start the stepwise regression process based on goodness of fit as measured by the Akaike information criterion. For face validity, these variables were forced into the model: treatment group ("less tight" or "tight" control), antihypertensive type at randomization, and blood pressure within 1 week before randomization. Continuous variables were represented continuously or dichotomized based on the smaller p-value in univariate analyses. An area-under-the-receiver-operating-curve (AUC ROC) of ≥0.70 was taken to reflect a potentially useful model. Point estimates for AUC ROC were <0.70 for all but severe hypertension (0.70, 95% CI 0.67-0.74) and delivery at <34 weeks (0.71, 95% CI 0.66-0.75). Therefore, no model warranted further assessment of performance. CHIPS data suggest that when women with chronic hypertension develop an elevated blood pressure in pregnancy, or formerly normotensive women develop new gestational hypertension, maternal and current pregnancy clinical characteristics cannot predict adverse outcomes in the index pregnancy. © 2016 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).

Validity of the Patient Health Questionnaire-9 to screen for depression in a high-HIV burden primary healthcare clinic in Johannesburg, South Africa.

PubMed

Cholera, R; Gaynes, B N; Pence, B W; Bassett, J; Qangule, N; Macphail, C; Bernhardt, S; Pettifor, A; Miller, W C

2014-01-01

Integration of depression screening into primary care may increase access to mental health services in sub-Saharan Africa, but this approach requires validated screening instruments. We sought to validate the Patient Health Questionnaire-9 (PHQ-9) as a depression screening tool at a high HIV-burden primary care clinic in Johannesburg, South Africa. We conducted a validation study of an interviewer-administered PHQ-9 among 397 patients. Sensitivity and specificity of the PHQ-9 were calculated with the Mini International Neuropsychiatric Interview (MINI) as the reference standard; receiver operating characteristic (ROC) curve analyses were performed. The prevalence of depression was 11.8%. One-third of participants tested positive for HIV. HIV-infected patients were more likely to be depressed (15%) than uninfected patients (9%; p=0.08). Using the standard cutoff score of ≥10, the PHQ-9 had a sensitivity of 78.7% (95% CI: 64.3-89.3) and specificity of 83.4% (95% CI: 79.1-87.2). The area under the ROC curve was 0.88 (95% CI: 0.83-0.92). Test performance did not vary by HIV status or language. In sensitivity analyses, reference test bias associated with the MINI appeared unlikely. We were unable to conduct qualitative work to adapt the PHQ-9 to this cultural context. This is the first validation study of the PHQ-9 in a primary care clinic in sub-Saharan Africa. It highlights the potential for using primary care as an access point for identifying depressive symptoms during routine HIV testing. The PHQ-9 showed reasonable accuracy in classifying cases of depression, was easily implemented by lay health workers, and is a useful screening tool in this setting. Copyright © 2014 Elsevier B.V. All rights reserved.

Association between the abdominal obesity anthropometric indicators and metabolic disorders in a Chinese population.

PubMed

Dong, J; Ni, Y-Q; Chu, X; Liu, Y-Q; Liu, G-X; Zhao, J; Yang, Y-B; Yan, Y-X

2016-02-01

Obesity has become a major health problem in contemporary society and it is closely related to many chronic diseases, so it is an important issue for measuring adiposity accurately and predicting its future. Prevention and treatment of overweight and obesity has become one of the key prevention and treatment of metabolic disorders. In this study, we compared the ability of the four anthropometric indicators (body mass index, waist circumstance, waist-height ratio, waist-to-hip ratio) to identify metabolic disorders (hypertension, hyperlipidaemia, hyperglycemia and hyperuricemia) by receiver operating characteristic (ROC) curve analyses and to provide evidence for clinical practice. In this large scale cross-sectional study, 13,275 Han adults (including 7595 males and 5680 females) received physical examination between January, 2009 and January, 2010 in Xuanwu Hospital of Capital Medical University were investigated by the means of questionnaire, Meanwhile, the physical examination and serological results were recorded. A package known as Statistical Package for Social Scientist (SPSS) was employed to analyse the responses while t-test, one-way analysis of variance (ANOVA), ROC analysis and chi-square statistical methods were used to test the hypotheses. WC, WHtR, WHR and BMI were all significantly (P < 0.001) correlated with all metabolic risk factors regardless of gender. And the area under the curve (AUC) of WHtR was significantly greater than that of WC, BMI or WHR in the prediction of hypertension, hyperlipidaemia, hyperglycemia and hyperuricemia. Our data show that WHtR was the best predictor of various metabolic disorders. The diagnostic value in descending order was WHtR > WHR > WC > BMI. Therefore we recommend WHtR in assessment of obese patients, in order to better assess the risks of their metabolic diseases. Copyright © 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Aortic elongation and the risk for dissection: the Tübingen Aortic Pathoanatomy (TAIPAN) project†.

PubMed

Krüger, Tobias; Oikonomou, Alexandre; Schibilsky, David; Lescan, Mario; Bregel, Katharina; Vöhringer, Luise; Schneider, Wilke; Lausberg, Henning; Blumenstock, Gunnar; Bamberg, Fabian; Schlensak, Christian

2017-06-01

We measured aortic dimensions, particularly length parameters, using 3D imaging with the aim of refining the risk-morphology for Stanford type A aortic dissection (TAD). Computer tomography angiography studies were analysed using the curved multiplanar reformats. At defined landmarks, the diameters and lengths of aortic segments were recorded. Three groups were compared retrospectively: patients actually suffering from a TAD (TAD-group; n  = 150), patients before suffering a TAD (preTAD-group n  = 15) and a healthy control group ( n  = 215). Receiver operating characteristic curves (ROCs) were analysed (control versus preTAD) to study the diagnostic value of the individual variables. Median diameters of preTAD (43 mm) and TAD (50 mm) aortas were significantly ( P  < 0.001) larger than those of the control group (35 mm). Ninety-three percent of preTAD and 68% of TAD aortas were less than 55 mm in the mid-ascending aorta. The ascending aorta and the aortic arch were significantly longer in both preTAD and TAD aortas compared to control aortas ( P  < 0.001); in the control aortas the central line distance from the aortic valve to the brachiocephalic trunk was 93 mm. In preTAD aortas, it was 111 mm, and it was 117 mm in TAD aortas ( P  < 0.001). In ROC analysis, the area under the curve was 0.912 for the ascending diameter and 0.787 for the ascending and arch lengths. TAD-prediction based on the aortic diameter is ineffective. Besides circumferential dilatation, ascending aorta elongation precedes TAD and appears to be a useful additional parameter for prognostication. We propose a diagnostic score involving ascending aorta diameter and length. © The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Development and validation of a clinical prediction rule for chest wall syndrome in primary care

PubMed Central

2012-01-01

Background Chest wall syndrome (CWS), the main cause of chest pain in primary care practice, is most often an exclusion diagnosis. We developed and evaluated a clinical prediction rule for CWS. Methods Data from a multicenter clinical cohort of consecutive primary care patients with chest pain were used (59 general practitioners, 672 patients). A final diagnosis was determined after 12 months of follow-up. We used the literature and bivariate analyses to identify candidate predictors, and multivariate logistic regression was used to develop a clinical prediction rule for CWS. We used data from a German cohort (n = 1212) for external validation. Results From bivariate analyses, we identified six variables characterizing CWS: thoracic pain (neither retrosternal nor oppressive), stabbing, well localized pain, no history of coronary heart disease, absence of general practitioner’s concern, and pain reproducible by palpation. This last variable accounted for 2 points in the clinical prediction rule, the others for 1 point each; the total score ranged from 0 to 7 points. The area under the receiver operating characteristic (ROC) curve was 0.80 (95% confidence interval 0.76-0.83) in the derivation cohort (specificity: 89%; sensitivity: 45%; cut-off set at 6 points). Among all patients presenting CWS (n = 284), 71% (n = 201) had a pain reproducible by palpation and 45% (n = 127) were correctly diagnosed. For a subset (n = 43) of these correctly classified CWS patients, 65 additional investigations (30 electrocardiograms, 16 thoracic radiographies, 10 laboratory tests, eight specialist referrals, one thoracic computed tomography) had been performed to achieve diagnosis. False positives (n = 41) included three patients with stable angina (1.8% of all positives). External validation revealed the ROC curve to be 0.76 (95% confidence interval 0.73-0.79) with a sensitivity of 22% and a specificity of 93%. Conclusions This CWS score offers a useful complement to the usual CWS exclusion diagnosing process. Indeed, for the 127 patients presenting CWS and correctly classified by our clinical prediction rule, 65 additional tests and exams could have been avoided. However, the reproduction of chest pain by palpation, the most important characteristic to diagnose CWS, is not pathognomonic. PMID:22866824

Stiff Landings Are Associated With Increased ACL Injury Risk in Young Female Basketball and Floorball Players.

PubMed

Leppänen, Mari; Pasanen, Kati; Kujala, Urho M; Vasankari, Tommi; Kannus, Pekka; Äyrämö, Sami; Krosshaug, Tron; Bahr, Roald; Avela, Janne; Perttunen, Jarmo; Parkkari, Jari

2017-02-01

Few prospective studies have investigated the biomechanical risk factors of anterior cruciate ligament (ACL) injury. To investigate the relationship between biomechanical characteristics of vertical drop jump (VDJ) performance and the risk of ACL injury in young female basketball and floorball players. Cohort study; Level of evidence, 3. At baseline, a total of 171 female basketball and floorball players (age range, 12-21 years) participated in a VDJ test using 3-dimensional motion analysis. The following biomechanical variables were analyzed: (1) knee valgus angle at initial contact (IC), (2) peak knee abduction moment, (3) knee flexion angle at IC, (4) peak knee flexion angle, (5) peak vertical ground-reaction force (vGRF), and (6) medial knee displacement. All new ACL injuries, as well as match and training exposure, were then recorded for 1 to 3 years. Cox regression models were used to calculate hazard ratios (HRs) and 95% CIs. Fifteen new ACL injuries occurred during the study period (0.2 injuries/1000 player-hours). Of the 6 factors considered, lower peak knee flexion angle (HR for each 10° increase in knee flexion angle, 0.55; 95% CI, 0.34-0.88) and higher peak vGRF (HR for each 100-N increase in vGRF, 1.26; 95% CI, 1.09-1.45) were the only factors associated with increased risk of ACL injury. A receiver operating characteristic (ROC) curve analysis showed an area under the curve of 0.6 for peak knee flexion and 0.7 for vGRF, indicating a failed-to-fair combined sensitivity and specificity of the test. Stiff landings, with less knee flexion and greater vGRF, in a VDJ test were associated with increased risk of ACL injury among young female basketball and floorball players. However, although 2 factors (decreased peak knee flexion and increased vGRF) had significant associations with ACL injury risk, the ROC curve analyses revealed that these variables cannot be used for screening of athletes.

Vitamin D supplementation as a potential cause of U-shaped associations between vitamin D levels and negative health outcomes: a decision tree analysis for risk of frailty.

PubMed

Kojima, Gotaro; Iliffe, Steve; Tanabe, Marianne

2017-10-16

A recent controversy in vitamin D research is a "U-shaped association", with elevated disease risks at both high and low 25-hydroxyvitamin D (25 (OH) D) levels. This is a cross-sectional study of 238 male nursing home veterans in Hawaii. Classification and regression tree (CART) analysis identified groups based on 25 (OH) D and vitamin D supplementation for frailty risk. Characteristics were examined and compared across the groups using logistic regression and receiver operating characteristic (ROC) curve analyses. CART analysis identified three distinct groups: vitamin D supplement users (n = 86), non-users with low vitamin D (n = 55), and non-users with high vitamin D (n = 97). Supplement users were the most frail, but had high mean 25 (OH) D of 26.6 ng/mL, which was compatible with 27.1 ng/mL in non-users with high vitamin D, while mean 25 (OH) D of non-users with low vitamin D was 11.7 ng/mL. Supplement users and non-users with low vitamin D were significantly more likely to be frail (odds ratio (OR) = 9.90, 95% CI = 2.18-44.86, p = 0.003; OR = 4.28, 95% CI = 1.44-12.68, p = 0.009, respectively), compared with non-users with low vitamin D. ROC curve analysis showed the three groups significantly predicted frailty (area under the curve = 0.73), with sensitivity of 64.4% and specificity of 76.7%, while 25 (OH) D did not predict frailty. In these nursing home veterans, vitamin D supplement users were the most frail but with high 25 (OH) D. This can potentially be a cause of U-shaped associations between vitamin D levels and negative health outcomes.

Assessment of mortality by qSOFA in patients with sepsis outside ICU: A post hoc subgroup analysis by the Japanese Association for Acute Medicine Sepsis Registry Study Group.

PubMed

Umemura, Yutaka; Ogura, Hiroshi; Gando, Satoshi; Kushimoto, Shigeki; Saitoh, Daizoh; Mayumi, Toshihiko; Fujishima, Seitaro; Abe, Toshikazu; Ikeda, Hiroto; Kotani, Joji; Miki, Yasuo; Shiraishi, Shin-Ichiro; Shiraishi, Atsushi; Suzuki, Koichiro; Suzuki, Yasushi; Takeyama, Naoshi; Takuma, Kiyotsugu; Tsuruta, Ryosuke; Yamaguchi, Yoshihiro; Yamashita, Norio; Aikawa, Naoki

2017-11-01

Quick sequential organ failure assessment (qSOFA) was proposed in the new sepsis definition (Sepsis-3). Although qSOFA was created to identify patients with suspected infection and likely to have poor outcomes, the clinical utility of qSOFA to screen sepsis has not been fully evaluated. We investigated the number of patients diagnosed as having severe sepsis who could not be identified by the qSOFA criteria and what clinical signs could complement the qSOFA score. This retrospective analysis of a multicenter prospective registry included adult patients with severe sepsis diagnosed outside the intensive care unit (ICU) by conventional criteria proposed in 2003. We conducted receiver operating characteristic (ROC) analyses to assess the predictive value for in-hospital mortality and compared clinical characteristics between survivors and non-survivors with qSOFA score ≤ 1 point (qSOFA-negative). Among 387 eligible patients, 63 (16.3%) patients were categorized as qSOFA-negative, and 10 (15.9%) of these patients died. The area under the ROC curve for the qSOFA score was 0.615, which was superior to that for the systemic inflammatory response syndrome score (0.531, P = 0.019) but inferior to that for the SOFA score (0.702, P = 0.005). Multivariate logistic regression analysis showed that hypothermia might be associated with poor outcome independently of qSOFA criteria. Our findings suggested that qSOFA had a suboptimal level of predictive value outside the ICU and could not identify 16.3% of patients who were once actually diagnosed with sepsis. Hypothermia might be associated with an increased risk of death that cannot be identified by qSOFA. Copyright © 2017 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Technical note: Validation of a handheld meter for measuring β-hydroxybutyrate concentrations in plasma and serum from dairy cows.

PubMed

Pineda, A; Cardoso, F C

2015-12-01

The use of handheld meters for cow-side tests for β-hydroxybutyrate (BHB) concentrations in whole blood has become common. The aim of this study was to compare serum BHB (sBHB) and plasma BHB (pBHB) concentrations analyzed using either a "gold standard" enzymatic laboratory method (LM; Randox Laboratories Ltd., Antrim, UK; cat. no. RB1007) or a handheld meter (PX; Precision Xtra, Abbott Diabetes Care Inc., Alameda, CA). Results from 374 (187 serum and 187 plasma) samples taken from Holstein cows from 11 d before (52 samples) to 5 d after parturition (137 samples) were used for the analysis. Statistical analysis was performed using the MIXED, REG, and LOGISTIC procedures of SAS (v9.4; SAS Institute Inc., Cary, NC). A linear mixed model with repeated measures was fitted for LM and PX. Regression and correlation analyses were completed to estimate the relationship and agreement between the 2 methods. Lin's concordance correlation coefficient (CCC) and Bland-Altman plots were used to evaluate agreement between LM and PX. Cross-validation by randomly splitting the data in model-building and validation sets was performed to estimate and validate the equation that predicted the LM results using PX. Receiver operating characteristic (ROC) curves were used to estimate the sensitivity (Se) and specificity (Sp) of PX at different threshold levels. The CCC was 0.74 for pBHB and 0.68 for sBHB. The 95% confidence interval of agreement of the Bland-Altman plot encompassed 96% of the difference between LM and PX for pBHB and 95% for sBHB. The mean difference for pBHB was -0.50±0.25mmol, and that for sBHB was -0.63±0.41mmol. The highest Se and Sp for PX were achieved when the threshold for ketosis was set to 1.8mmol/L for pBHB and 2.1mmol/L for sBHB. The area under the ROC curve was 0.97 for pBHB and 0.96 for sBHB. The negative bias shown by the Bland-Altman plots suggested that PX yielded higher pBHB and sBHB concentrations than the LM. However, the excellent test characteristics and area under the ROC curve close to 1 indicated that PX at the adjusted thresholds was able to accurately classify between samples <1.2mmol/L and those ≥1.2mmol/L based on the gold standard test. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Testing a Neurocomputational Model of Recollection, Familiarity, and Source Recognition

ERIC Educational Resources Information Center

Elfman, Kane W.; Parks, Colleen M.; Yonelinas, Andrew P.

2008-01-01

The authors assess whether the complementary learning systems model of the medial temporal lobes (Norman & O'Reilly, 2003) is able to account for source recognition receiver operating characteristics (ROCs). The model assumes that recognition reflects the contribution of a hippocampally mediated recollection process and a cortically mediated…

The Variance Reaction Time Model

ERIC Educational Resources Information Center

Sikstrom, Sverker

2004-01-01

The variance reaction time model (VRTM) is proposed to account for various recognition data on reaction time, the mirror effect, receiver-operating-characteristic (ROC) curves, etc. The model is based on simple and plausible assumptions within a neural network: VRTM is a two layer neural network where one layer represents items and one layer…

A bivariate contaminated binormal model for robust fitting of proper ROC curves to a pair of correlated, possibly degenerate, ROC datasets.

PubMed

Zhai, Xuetong; Chakraborty, Dev P

2017-06-01

The objective was to design and implement a bivariate extension to the contaminated binormal model (CBM) to fit paired receiver operating characteristic (ROC) datasets-possibly degenerate-with proper ROC curves. Paired datasets yield two correlated ratings per case. Degenerate datasets have no interior operating points and proper ROC curves do not inappropriately cross the chance diagonal. The existing method, developed more than three decades ago utilizes a bivariate extension to the binormal model, implemented in CORROC2 software, which yields improper ROC curves and cannot fit degenerate datasets. CBM can fit proper ROC curves to unpaired (i.e., yielding one rating per case) and degenerate datasets, and there is a clear scientific need to extend it to handle paired datasets. In CBM, nondiseased cases are modeled by a probability density function (pdf) consisting of a unit variance peak centered at zero. Diseased cases are modeled with a mixture distribution whose pdf consists of two unit variance peaks, one centered at positive μ with integrated probability α, the mixing fraction parameter, corresponding to the fraction of diseased cases where the disease was visible to the radiologist, and one centered at zero, with integrated probability (1-α), corresponding to disease that was not visible. It is shown that: (a) for nondiseased cases the bivariate extension is a unit variances bivariate normal distribution centered at (0,0) with a specified correlation ρ 1 ; (b) for diseased cases the bivariate extension is a mixture distribution with four peaks, corresponding to disease not visible in either condition, disease visible in only one condition, contributing two peaks, and disease visible in both conditions. An expression for the likelihood function is derived. A maximum likelihood estimation (MLE) algorithm, CORCBM, was implemented in the R programming language that yields parameter estimates and the covariance matrix of the parameters, and other statistics. A limited simulation validation of the method was performed. CORCBM and CORROC2 were applied to two datasets containing nine readers each contributing paired interpretations. CORCBM successfully fitted the data for all readers, whereas CORROC2 failed to fit a degenerate dataset. All fits were visually reasonable. All CORCBM fits were proper, whereas all CORROC2 fits were improper. CORCBM and CORROC2 were in agreement (a) in declaring only one of the nine readers as having significantly different performances in the two modalities; (b) in estimating higher correlations for diseased cases than for nondiseased ones; and (c) in finding that the intermodality correlation estimates for nondiseased cases were consistent between the two methods. All CORCBM fits yielded higher area under curve (AUC) than the CORROC2 fits, consistent with the fact that a proper ROC model like CORCBM is based on a likelihood-ratio-equivalent decision variable, and consequently yields higher performance than the binormal model-based CORROC2. The method gave satisfactory fits to four simulated datasets. CORCBM is a robust method for fitting paired ROC datasets, always yielding proper ROC curves, and able to fit degenerate datasets. © 2017 American Association of Physicists in Medicine.

Usefulness of CA125 and their kinetic parameters and positron emission tomography/computed tomography (PET/CT) with fluorodeoxyglucose ([18F] FDG) in the detection of recurrent ovarian cancer levels.

PubMed

Palomar Muñoz, Azahara; Cordero García, José Manuel; Talavera Rubio, Prado; García Vicente, Ana M; González García, Beatriz; Bellón Guardia, María Emiliana; Soriano Castrejón, Ángel; Aranda Aguilar, Enrique

2017-12-21

To assess the usefulness of cancer antigen 125 (CA125) serum levels and kinetic values, velocity (CA125vel) and doubling time (CA125dt), as well as fluorodeoxyglucose ([ 18 F]FDG) positron emission tomography/computed tomography (PET/CT), in the detection of ovarian cancer recurrence. To assess the optimal cut-off for CA125, CA125vel and CA125dt to detect relapse with [ 18 F]FDG-PET/CT. A retrospective analysis was performed of 59 [ 18 F]FDG-PET/CT (48 patients) for suspected recurrence of ovarian cancer. Receiver operating characteristic (ROC) curves were plotted and area-under-the curve (AUC) statistics were computed for CA125, CA125vel and CA125dt. The results obtained in the group with normal and high (>35U/ml) CA125 levels were compared. Forty-four cases of recurrence were diagnosed (7 had CA125 ≤35U/ml), whereas 15 showed no disease. All of them were correctly catalogued by PET/CT. In ROC analysis, the discriminatory power of CA125 was relatively high (AUC 0.835) and the optimal cut-off point to reflect active disease was 23.9U/ml. The ROC analyses for the CA125vel and CA125dt showed an AUC of 0.849 and 0.728, respectively, with an optimal cut-off point of 1.96U/ml/month and 0.76 months, respectively. In patients with normal CA125 and recurrence of ovarian cancer, the CA125vel was significantly higher than in patients without recurrence (p=0.029). [ 18 F]FDG-PET/CT is more accurate than CA125 parameters in the detection of ovarian cancer recurrence. CA125 serum levels are essential; nevertheless, CA125 kinetic values must be considered to detect relapse. Particularly in patients with CA125 within normal values, in which a higher CA125vel is indicative of recurrence. Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

Non-localization and localization ROC analyses using clinically based scoring

NASA Astrophysics Data System (ADS)

Paquerault, Sophie; Samuelson, Frank W.; Myers, Kyle J.; Smith, Robert C.

2009-02-01

We are investigating the potential for differences in study conclusions when assessing the estimated impact of a computer-aided detection (CAD) system on readers' performance. The data utilized in this investigation were derived from a multi-reader multi-case observer study involving one hundred mammographic background images to which fixed-size and fixed-intensity Gaussian signals were added, generating a low- and high-intensity signal sets. The study setting allowed CAD assessment in two situations: when CAD sensitivity was 1) superior or 2) lower than the average reader. Seven readers were asked to review each set in the unaided and CAD-aided reading modes, mark and rate their findings. Using this data, we studied the effect on study conclusion of three clinically-based receiver operating characteristic (ROC) scoring definitions. These scoring definitions included both location-specific and non-location-specific rules. The results showed agreement in the estimated impact of CAD on the overall reader performance. In the study setting where CAD sensitivity is superior to the average reader, the mean difference in AUC between the CAD-aided read and unaided read was 0.049 (95%CIs: -0.027; 0.130) for the image scoring definition that is based on non-location-specific rules, and 0.104 (95%CIs: 0.036; 0.174) and 0.090 (95%CIs: 0.031; 0.155) for image scoring definitions that are based on location-specific rules. The increases in AUC were statistically significant for the location-specific scoring definitions. It was further observed that the variance on these estimates was reduced when using the location-specific scoring definitions compared to that using a non-location-specific scoring definition. In the study setting where CAD sensitivity is equivalent or lower than the average reader, the mean differences in AUC are slightly above 0.01 for all image scoring definitions. These increases in AUC were not statistical significant for any of the image scoring definitions. The results on the variance analysis differed from those observed in the other study setting. This investigation furthers our understanding of the relationships between non-localization-specific and localization-specific ROC assessment methodologies and their relevance to clinical practice.

Reticulo-rumen temperature as a predictor of calving time in primiparous and parous Holstein females.

PubMed

Costa, J B G; Ahola, J K; Weller, Z D; Peel, R K; Whittier, J C; Barcellos, J O J

2016-06-01

The objective of this research was to define and analyze drops in reticulo-rumen temperature (Trr) as an indicator of calving time in Holstein females. Data were collected from 111 primiparous and 150 parous Holstein females between November 2012 and March 2013. Between -15 and -5 d relative to anticipated calving date, each female received an orally administered temperature sensing reticulo-rumen bolus that collected temperatures hourly. Daily mean Trr was calculated from d -5 to 0 relative to using all Trr values (A-Trr) or only Trr values ≥37.7°C (W-Trr) not altered by water intake. To identify a Trr drop, 2 methodologies for computing the baseline temperature were used. Generalized linear models (GLM) were used to estimate the probability of calving within the next 12 or 24 h for primiparous, parous, and all females, based on the size of the Trr drop. For all GLM, a large drop in Trr corresponded with a large estimated probability of calving. The predictive power of the GLM was assessed using receiver-operating characteristic (ROC) curves. The ROC curve analyses showed that all models, regardless of methodology in calculation of the baseline or tested category (primiparous or parous), were able to predict calving; however, area under the ROC curve values, an indication of prediction quality, were greater for methods predicting calving within 24 h. Further comparisons between GLM for primiparous and parous, and using baseline 1 and 2, provide insight on the differences in predictive performance. Based on the GLM, Trr drops of 0.2, 0.3, and 0.4°C were identified as useful indicators of parturition and further analyzed using sensitivity, specificity, and diagnostic odds ratios. Based on sensitivity, specificity, and diagnostic odds ratios, the best indicator of calving was an average Trr drop ≥0.2°C, regardless of methodology used to compute the baseline or category of animal evaluated. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

An in-vitro evaluation of Kodak Insight and Ektaspeed Plus film with a CMOS detector for natural proximal caries: ROC analysis.

PubMed

Nair, M K; Nair, U P

2001-01-01

This study compared the diagnostic efficacy of Kodak Ektaspeed Plus film, Kodak Insight film, a newly introduced E/F-speed film, and Schick CMOS-APS digital sensor, with respect to caries detection in 92 proximal surfaces of extracted unrestored teeth, 51 of which were carious. Ground truth was evaluated histologically and the lesions classified as enamel or dentinal. Eight observers read the radiographs using a five-point confidence rating scale to record their diagnoses. Analyses using receiver operating characteristic curves revealed the areas under each curve that indicated the diagnostic accuracy (Ektaspeed Plus - 0.760, Insight - 0.778 and CMOS-APS sensor - 0.732). ANOVA revealed significant differences with respect to caries depth (p<0.031) and observers (p<0.0001). Weighted kappa analyses indicated moderate to substantial inter- and intra-observer agreement (0.42 and 0.66, respectively). The results suggest that none of the imaging modalities evaluated in this study differed in their diagnostic capabilities with respect to proximal decay detection and that the Insight film which was used with 20% less radiation exposure than Ektaspeed Plus film was as good as the other two sensors for this purpose.

Prognostic value of inflammation-based scores in patients with osteosarcoma

PubMed Central

Liu, Bangjian; Huang, Yujing; Sun, Yuanjue; Zhang, Jianjun; Yao, Yang; Shen, Zan; Xiang, Dongxi; He, Aina

2016-01-01

Systemic inflammation responses have been associated with cancer development and progression. C-reactive protein (CRP), Glasgow prognostic score (GPS), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), and neutrophil-platelet score (NPS) have been shown to be independent risk factors in various types of malignant tumors. This retrospective analysis of 162 osteosarcoma cases was performed to estimate their predictive value of survival in osteosarcoma. All statistical analyses were performed by SPSS statistical software. Receiver operating characteristic (ROC) analysis was generated to set optimal thresholds; area under the curve (AUC) was used to show the discriminatory abilities of inflammation-based scores; Kaplan-Meier analysis was performed to plot the survival curve; cox regression models were employed to determine the independent prognostic factors. The optimal cut-off points of NLR, PLR, and LMR were 2.57, 123.5 and 4.73, respectively. GPS and NLR had a markedly larger AUC than CRP, PLR and LMR. High levels of CRP, GPS, NLR, PLR, and low level of LMR were significantly associated with adverse prognosis (P < 0.05). Multivariate Cox regression analyses revealed that GPS, NLR, and occurrence of metastasis were top risk factors associated with death of osteosarcoma patients. PMID:28008988

Expected p-values in light of an ROC curve analysis applied to optimal multiple testing procedures.

PubMed

Vexler, Albert; Yu, Jihnhee; Zhao, Yang; Hutson, Alan D; Gurevich, Gregory

2017-01-01

Many statistical studies report p-values for inferential purposes. In several scenarios, the stochastic aspect of p-values is neglected, which may contribute to drawing wrong conclusions in real data experiments. The stochastic nature of p-values makes their use to examine the performance of given testing procedures or associations between investigated factors to be difficult. We turn our focus on the modern statistical literature to address the expected p-value (EPV) as a measure of the performance of decision-making rules. During the course of our study, we prove that the EPV can be considered in the context of receiver operating characteristic (ROC) curve analysis, a well-established biostatistical methodology. The ROC-based framework provides a new and efficient methodology for investigating and constructing statistical decision-making procedures, including: (1) evaluation and visualization of properties of the testing mechanisms, considering, e.g. partial EPVs; (2) developing optimal tests via the minimization of EPVs; (3) creation of novel methods for optimally combining multiple test statistics. We demonstrate that the proposed EPV-based approach allows us to maximize the integrated power of testing algorithms with respect to various significance levels. In an application, we use the proposed method to construct the optimal test and analyze a myocardial infarction disease dataset. We outline the usefulness of the "EPV/ROC" technique for evaluating different decision-making procedures, their constructions and properties with an eye towards practical applications.

Developing a new diagnostic algorithm for human papilloma virus associated oropharyngeal carcinoma: an investigation of HPV DNA assays.

PubMed

Cohen, Natasha; Gupta, Michael; Doerwald-Munoz, Lilian; Jang, Dan; Young, James Edward Massey; Archibald, Stuart; Jackson, Bernard; Lee, Jenny; Chernesky, Max

2017-02-13

Human papilloma virus (HPV) has been implicated in the development of a large proportion of oropharyngeal squamous cell carcinoma (OPSCC). Current techniques used to diagnose HPV etiology require histopathologic analysis. We aim to investigate the diagnostic accuracy of a new application non-histopathologic diagnostic tests to help assist diagnosis of HPV-related oropharyngeal tumors. Patients with OPSCC with nodal metastasis were consecutively recruited from a multidisciplinary cancer clinic. Appropriate samples were collected and analyzed. The various tests examined included COBAS® 4800, Cervista® HR and Genotyping. These tests were compared to p16 staining, which was used as the diagnostic standard. StataIC 14.2 was used to perform analysis, including sensitivity, specificity and receiver operator characteristic [ROC] curves. The COBAS® FNA (area under ROC 0.863) and saliva (area under ROC 0.847) samples performed well in diagnosing HPV positive and negative tumors. Samples tested with Cervista® did not corroborate p16 status reliably. We were able to increase the diagnostic yield of the COBAS® FNA samples by applying the results of the saliva test to negative FNA samples which correctly identified 11 additional p16 positive tumors (area under ROC 0.915). Surrogate testing for HPV using alternate methods is feasible and closely predicts the results of standard diagnostic methods. In the future, these could minimize invasive procedures for diagnosing HPV-related oropharyngeal cancer, but also help to diagnose and treat patients with unknown primaries.

Linguistic adaptation, validation and comparison of 3 routinely used neuropathic pain questionnaires.

PubMed

Li, Jun; Feng, Yi; Han, Jisheng; Fan, Bifa; Wu, Dasheng; Zhang, Daying; Du, Dongping; Li, Hui; Lim, Jian; Wang, Jiashuang; Jin, Yi; Fu, Zhijian

2012-01-01

Neuropathic pain questionnaires are efficient diagnostic tools for neuropathic pain and play an important role in neuropathic pain epidemiologic studies in China. No comparison data was available in regards to the Leeds Assessment of Neuropathic Symptoms and Signs (LANSS), the Neuropathic Pain Questionnaire (NPQ) and ID Pain within and among the same population. To achieve a linguistic adaptation, validation, and comparison of Chinese versions of the 3 neuropathic pain questionnaires (LANSS, NPQ and ID Pain). A nonrandomized, controlled, prospective, multicenter trial. Ten pain centers in China. Two forward translations followed by comparison and reconciliation of the translations. Comparison of the 2 backward translations with the original version was made to establish consistency and accuracy of the translations. Pilot testing and pain specialists' evaluations were also required. A total of 140 patients were enrolled in 10 centers throughout China: 70 neuropathic pain patients and 70 nociceptive pain patients. Reliability (Cronbach's alpha coefficients and Guttman split-half coefficients) and validity (sensitivity, specificity, positive and negative predictive values, receiver operating characteristic [ROC] curves and the area under the ROC curves) of the 3 questionnaires were determined. ROC curves and the area under the ROC curves of the 3 questionnaires were also compared. Chinese versions of LANSS, NPQ and ID Pain had a good reliability (Cronbach's alpha coefficients and Guttman split-half coefficients were greater than 0.7). Sensitivity, specificity, positive and negative predictive values of the Chinese versions of LANSS and ID Pain were considerably high ( > 80%). The area under the ROC curves of LANSS and ID Pain was significantly higher than that of NPQ (P < 0.05). There was no statistically significant difference between the area under the ROC curves of LANSS and ID Pain (P > 0.05). The study was based on patients with a high school degree or above, which limited the application of the 3 neuropathic pain questionnaires to patients with lower educational levels. The Chinese versions of LANSS and ID Pain developed and validated by this study can be used as a diagnostic tool in differentiating neuropathic pain in patients whose native language is Chinese (Mandarin).

A novel teaching tool using dynamic cues improves visualisation of chest lesions by naive observers

NASA Astrophysics Data System (ADS)

Mohamed Ali, M. A.; Toomey, R. J.; Ryan, J. T.; Cuffe, F. C.; Brennan, P. C.

2009-02-01

Introduction Dynamic cueing is an effective way of stimulating perception of regions of interest within radiological images. This study explores the impact of a novel teaching tool using dynamic cueing for lesion detection on plain chest radiographs. Materials and methods Observer performance studies were carried out where 36 novices examined 30 chest images in random order. Half of these contained between one and three simulated pulmonary nodules. Three groups were investigated: A (control: no teaching tool), B (retested immediately after undergoing the teaching tool) and C (retested a week after undergoing the teaching tool). The teaching tool involved dynamically displaying the same images with and without lesions. Results were compared using Receiver Operating Characteristics (ROC), sensitivity and specificity analyses. Results The second reading showed significantly greater area under the ROC curve (Az value) (p<0.0001) and higher sensitivity value (p=0.004) compared to the first reading for Group B. No differences between readings were demonstrated for groups A or C. When the magnitudes of the above changes were compared between Group B and the other two groups, greater changes in Az value for Group B were noted (B vs. A:p=0.0003, B vs. C:p=0.0005). For sensitivity, when Group B was compared to Group A, the magnitude of the change was significantly greater (p=0.0029) whereas when Group B was compared to Group C, the magnitude change demonstrated a level approaching significance (p=0.0768). Conclusions The novel teaching tool improves identification of pulmonary nodular lesions on chest radiographs in the short term.

Differences in Clinical Features of Methamphetamine Users with Persistent Psychosis and Patients with Schizophrenia.

PubMed

Wang, Liang-Jen; Lin, Shih-Ku; Chen, Yi-Chih; Huang, Ming-Chyi; Chen, Tzu-Ting; Ree, Shao-Chun; Chen, Chih-Ken

Methamphetamine exerts neurotoxic effects and elicits psychotic symptoms. This study attempted to compare clinical differences between methamphetamine users with persistent psychosis (MAP) and patients with schizophrenia. In addition, we examined the discrimination validity by using symptom clusters to differentiate between MAP and schizophrenia. We enrolled 53 MAP patients and 53 patients with schizophrenia. The psychopathology of participants was assessed using the Chinese version of the Diagnostic Interview for Genetic Studies and the 18-item Brief Psychiatric Rating Scale. Logistic regression was used to examine the predicted probability scores of different symptom combinations on discriminating between MAP and schizophrenia. The receiver operating characteristic (ROC) analyses and area under the curve (AUC) were further applied to examine the discrimination validity of the predicted probability scores on differentiating between MAP and schizophrenia. We found that MAP and schizophrenia demonstrated similar patterns of delusions. Compared to patients with schizophrenia, MAP experienced significantly higher proportions of visual hallucinations and of somatic or tactile hallucinations. However, MAP exhibited significantly lower severity in conceptual disorganization, mannerism/posturing, blunted affect, emotional withdrawal, and motor retardation compared to patients with schizophrenia. The ROC analysis showed that a predicted probability score combining the aforementioned 7 items of symptoms could significantly differentiate between MAP and schizophrenia (AUC = 0.77). Findings in the current study suggest that nuanced differences might exist in the clinical presentation of secondary psychosis (MAP) and primary psychosis (schizophrenia). Combining the symptoms as a whole may help with differential diagnosis for MAP and schizophrenia. © 2016 S. Karger AG, Basel.

Brief screening for mild cognitive impairment: validation of the Brazilian version of the Montreal cognitive assessment.

PubMed

Memória, Cláudia M; Yassuda, Mônica S; Nakano, Eduardo Y; Forlenza, Orestes V

2013-01-01

The Montreal Cognitive Assessment (MoCA) is a brief cognitive schedule that has been developed for the screening of patients with Mild Cognitive Impairment (MCI). MCI is recognized as a high-risk state for Alzheimer's disease. The aim of the present study is to examine the reliability and validity of the Brazilian version of the MoCA test (MoCA-BR) in a sample of older individuals with at least 4 years of education. The MoCA-BR was administered to 112 older adults who were classified into three diagnostic groups according to their cognitive state (Alzheimer's disease, n = 28; MCI, n = 43; normal controls, n = 41). This procedure was based on clinical and neuropsychological data. The performance in the MoCA-BR was compared with the Mini-mental state examination (MMSE) and the Cambridge Cognitive Examination. Diagnostic accuracy was examined with the receiver operating characteristic (ROC) curve analyses. Cronbach's alpha for the MoCA-BR was 0.75. Temporal stability (retesting after 3 months) using intraclass correlation coefficient was 0.75 (p < 0.001). The sensitivity and specificity of the MoCA-BR for MCI were 81% and 77%, respectively, with a cut-off score of 25 points. The area under the ROC curve for predicting MCI was 0.82 ± 0.06. The present results indicate that the MoCA-BR maintains its core diagnostic properties rendering it a valid and reliable tool for the screening of MCI among older individuals with at least 4 years of education. Copyright © 2012 John Wiley & Sons, Ltd.

Discriminability of personality profiles in isolated and Co-morbid marijuana and nicotine users.

PubMed

Ketcherside, Ariel; Jeon-Slaughter, Haekyung; Baine, Jessica L; Filbey, Francesca M

2016-04-30

Specific personality traits have been linked with substance use disorders (SUDs), genetic mechanisms, and brain systems. Thus, determining the specificity of personality traits to types of SUD can advance the field towards defining SUD endophenotypes as well as understanding the brain systems involved for the development of novel treatments. Disentangling these factors is particularly important in highly co morbid SUDs, such as marijuana and nicotine use, so treatment can occur effectively for both. This study evaluated personality traits that distinguish isolated and co-morbid use of marijuana and nicotine. To that end, we collected the NEO Five Factor Inventory in participants who used marijuana-only (n=59), nicotine-only (n=27), both marijuana and nicotine (n=28), and in non-using controls (n=28). We used factor analyses to identify personality profiles, which are linear combinations of the five NEO Factors. We then conducted Receiver Operating Characteristics (ROC) curve analysis to test accuracy of the personality factors in discriminating isolated and co-morbid marijuana and nicotine users from each other. ROC curve analysis distinguished the four groups based on their NEO personality patterns. Results showed that NEO Factor 2 (openness, extraversion, agreeableness) discriminated marijuana and marijuana+nicotine users from controls and nicotine-only users with high predictability. Additional ANOVA results showed that the openness dimension discriminated marijuana users from nicotine users. These findings suggest that personality dimensions distinguish marijuana users from nicotine users and should be considered in prevention strategies. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

RNA-DNA hybrid (R-loop) immunoprecipitation mapping: an analytical workflow to evaluate inherent biases

PubMed Central

Halász, László; Karányi, Zsolt; Boros-Oláh, Beáta; Kuik-Rózsa, Tímea; Sipos, Éva; Nagy, Éva; Mosolygó-L, Ágnes; Mázló, Anett; Rajnavölgyi, Éva; Halmos, Gábor; Székvölgyi, Lóránt

2017-01-01

The impact of R-loops on the physiology and pathology of chromosomes has been demonstrated extensively by chromatin biology research. The progress in this field has been driven by technological advancement of R-loop mapping methods that largely relied on a single approach, DNA-RNA immunoprecipitation (DRIP). Most of the DRIP protocols use the experimental design that was developed by a few laboratories, without paying attention to the potential caveats that might affect the outcome of RNA-DNA hybrid mapping. To assess the accuracy and utility of this technology, we pursued an analytical approach to estimate inherent biases and errors in the DRIP protocol. By performing DRIP-sequencing, qPCR, and receiver operator characteristic (ROC) analysis, we tested the effect of formaldehyde fixation, cell lysis temperature, mode of genome fragmentation, and removal of free RNA on the efficacy of RNA-DNA hybrid detection and implemented workflows that were able to distinguish complex and weak DRIP signals in a noisy background with high confidence. We also show that some of the workflows perform poorly and generate random answers. Furthermore, we found that the most commonly used genome fragmentation method (restriction enzyme digestion) led to the overrepresentation of lengthy DRIP fragments over coding ORFs, and this bias was enhanced at the first exons. Biased genome sampling severely compromised mapping resolution and prevented the assignment of precise biological function to a significant fraction of R-loops. The revised workflow presented herein is established and optimized using objective ROC analyses and provides reproducible and highly specific RNA-DNA hybrid detection. PMID:28341774

Calibration and comparison of accelerometer cut points in preschool children.

PubMed

van Cauwenberghe, Eveline; Labarque, Valery; Trost, Stewart G; de Bourdeaudhuij, Ilse; Cardon, Greet

2011-06-01

The present study aimed to develop accelerometer cut points to classify physical activities (PA) by intensity in preschoolers and to investigate discrepancies in PA levels when applying various accelerometer cut points. To calibrate the accelerometer, 18 preschoolers (5.8 ± 0.4 years) performed eleven structured activities and one free play session while wearing a GT1M ActiGraph accelerometer using 15 s epochs. The structured activities were chosen based on the direct observation system Children's Activity Rating Scale (CARS) while the criterion measure of PA intensity during free play was provided using a second-by-second observation protocol (modified CARS). Receiver Operating Characteristic (ROC) curve analyses were used to determine the accelerometer cut points. To examine the classification differences, accelerometer data of four consecutive days from 114 preschoolers (5.5 ± 0.3 years) were classified by intensity according to previously published and the newly developed accelerometer cut points. Differences in predicted PA levels were evaluated using repeated measures ANOVA and Chi Square test. Cut points were identified at 373 counts/15 s for light (sensitivity: 86%; specificity: 91%; Area under ROC curve: 0.95), 585 counts/15 s for moderate (87%; 82%; 0.91) and 881 counts/15 s for vigorous PA (88%; 91%; 0.94). Further, applying various accelerometer cut points to the same data resulted in statistically and biologically significant differences in PA. Accelerometer cut points were developed with good discriminatory power for differentiating between PA levels in preschoolers and the choice of accelerometer cut points can result in large discrepancies.

Ultrasonographic Evaluation of Cervical Lymph Nodes in Thyroid Cancer.

PubMed

Machado, Maria Regina Marrocos; Tavares, Marcos Roberto; Buchpiguel, Carlos Alberto; Chammas, Maria Cristina

2017-02-01

Objective To determine what ultrasonographic features can identify metastatic cervical lymph nodes, both preoperatively and in recurrences after complete thyroidectomy. Study Design Prospective. Setting Outpatient clinic, Department of Head and Neck Surgery, School of Medicine, University of São Paulo, Brazil. Subjects and Methods A total of 1976 lymph nodes were evaluated in 118 patients submitted to total thyroidectomy with or without cervical lymph node dissection. All the patients were examined by cervical ultrasonography, preoperatively and/or postoperatively. The following factors were assessed: number, size, shape, margins, presence of fatty hilum, cortex, echotexture, echogenicity, presence of microcalcification, presence of necrosis, and type of vascularity. The specificity, sensitivity, positive predictive value, and negative predictive value of each variable were calculated. Univariate and multivariate logistic regression analyses were conducted. A receiver operator characteristic (ROC) curve was plotted to determine the best cutoff value for the number of variables to discriminate malignant lymph nodes. Results Significant differences were found between metastatic and benign lymph nodes with regard to all of the variables evaluated ( P < .05). Logistic regression analysis revealed that size and echogenicity were the best combination of altered variables (odds ratio, 40.080 and 7.288, respectively) in discriminating malignancy. The ROC curve analysis showed that 4 was the best cutoff value for the number of altered variables to discriminate malignant lymph nodes, with a combined specificity of 85.7%, sensitivity of 96.4%, and efficiency of 91.0%. Conclusion Greater diagnostic accuracy was achieved by associating the ultrasonographic variables assessed rather than by considering them individually.

Tumour xenograft detection through quantitative analysis of the metabolic profile of urine in mice

NASA Astrophysics Data System (ADS)

Moroz, Jennifer; Turner, Joan; Slupsky, Carolyn; Fallone, Gino; Syme, Alasdair

2011-02-01

The metabolic content of urine from NIH III nude mice (n = 22) was analysed before and after inoculation with human glioblastoma multiforme (GBM) cancer cells. An age- and gender-matched control population (n = 14) was also studied to identify non-tumour-related changes. Urine samples were collected daily for 6 weeks, beginning 1 week before cell injection. Metabolite concentrations were obtained via targeted profiling with Chenomx Suite 5.1, based on nuclear magnetic resonance (NMR) spectra acquired on an Oxford 800 MHz cold probe NMR spectrometer. The Wilcoxon rank sum test was used to evaluate the significance of the change in metabolite concentration between the two time points. Both the metabolite concentrations and the ratios of pairs of metabolites were studied. The complicated inter-relationships between metabolites were assessed through partial least-squares discriminant analysis (PLS-DA). Receiver operating characteristic (ROC) curves were generated for all variables and the area under the curve (AUC) calculated. The data indicate that the number of statistically significant changes in metabolite concentrations was more pronounced in the tumour-bearing population than in the control animals. This was also true of the ratios of pairs of metabolites. ROC analysis suggests that the ratios were better able to differentiate between the pre- and post-injection samples compared to the metabolite concentrations. PLS-DA models produced good separation between the populations and had the best AUC results (all models exceeded 0.937). These results demonstrate that metabolomics may be used as a screening tool for GBM cells grown in xenograft models in mice.

Problematic internet use (PIU): Associations with the impulsive-compulsive spectrum. An application of machine learning in psychiatry.

PubMed

Ioannidis, Konstantinos; Chamberlain, Samuel R; Treder, Matthias S; Kiraly, Franz; Leppink, Eric W; Redden, Sarah A; Stein, Dan J; Lochner, Christine; Grant, Jon E

2016-12-01

Problematic internet use is common, functionally impairing, and in need of further study. Its relationship with obsessive-compulsive and impulsive disorders is unclear. Our objective was to evaluate whether problematic internet use can be predicted from recognised forms of impulsive and compulsive traits and symptomatology. We recruited volunteers aged 18 and older using media advertisements at two sites (Chicago USA, and Stellenbosch, South Africa) to complete an extensive online survey. State-of-the-art out-of-sample evaluation of machine learning predictive models was used, which included Logistic Regression, Random Forests and Naïve Bayes. Problematic internet use was identified using the Internet Addiction Test (IAT). 2006 complete cases were analysed, of whom 181 (9.0%) had moderate/severe problematic internet use. Using Logistic Regression and Naïve Bayes we produced a classification prediction with a receiver operating characteristic area under the curve (ROC-AUC) of 0.83 (SD 0.03) whereas using a Random Forests algorithm the prediction ROC-AUC was 0.84 (SD 0.03) [all three models superior to baseline models p < 0.0001]. The models showed robust transfer between the study sites in all validation sets [p < 0.0001]. Prediction of problematic internet use was possible using specific measures of impulsivity and compulsivity in a population of volunteers. Moreover, this study offers proof-of-concept in support of using machine learning in psychiatry to demonstrate replicability of results across geographically and culturally distinct settings. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Using the NANA toolkit at home to predict older adults' future depression.

PubMed

Andrews, J A; Harrison, R F; Brown, L J E; MacLean, L M; Hwang, F; Smith, T; Williams, E A; Timon, C; Adlam, T; Khadra, H; Astell, A J

2017-04-15

Depression is currently underdiagnosed among older adults. As part of the Novel Assessment of Nutrition and Aging (NANA) validation study, 40 older adults self-reported their mood using a touchscreen computer over three, one-week periods. Here, we demonstrate the potential of these data to predict future depression status. We analysed data from the NANA validation study using a machine learning approach. We applied the least absolute shrinkage and selection operator with a logistic model to averages of six measures of mood, with depression status according to the Geriatric Depression Scale 10 weeks later as the outcome variable. We tested multiple values of the selection parameter in order to produce a model with low deviance. We used a cross-validation framework to avoid overspecialisation, and receiver operating characteristic (ROC) curve analysis to determine the quality of the fitted model. The model we report contained coefficients for two variables: sadness and tiredness, as well as a constant. The cross-validated area under the ROC curve for this model was 0.88 (CI: 0.69-0.97). While results are based on a small sample, the methodology for the selection of variables appears suitable for the problem at hand, suggesting promise for a wider study and ultimate deployment with older adults at increased risk of depression. We have identified self-reported scales of sadness and tiredness as sensitive measures which have the potential to predict future depression status in older adults, partially addressing the problem of underdiagnosis. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Body mass index, waist circumference and waist-to-hip-ratio in the prediction of obesity in Turkish teenagers.

PubMed

Kavak, Vatan; Pilmane, Mara; Kazoka, Dzintra

2014-06-01

The aim of this study was to identify the usefulness of body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) in screening for obesity in teenagers by using the receiver operating characteristic (ROC). To select the sample set in this cross-sectional study, a stratified random sampling approach was utilized. Weight, height, WC, hip circumference and body fat percentage (BFP) were measured in 1118 children of both genders (597 boys and 521 girls), aged from 10 to 15 years old. Percentiles of BMI and Centers for Disease Control and Prevention-United States (CDC-US)-growth chart for boys and girls aged from 10 to 15 years old were presented. ROC analyses were then used to evaluate the performances of three anthropometric indices; BMI, WC and WHR had strong positive correlations with BFP (r = 0.49-0.77) in both girls and boys within indicated age group. The area under the curves (AUCs) were high in both girls and boys for BMI, 0.795 and 0.893, respectively, and WC, 0.767 and 0.853, respectively, and were a little lower, 0.747 and 0.783, respectively, for WHR. In conclusion, this study demonstrates that the prevalence of being overweight and obese among teenagers of both sexes in our data set does not differ from CDC-US-growth chart. In addition, BMI and WC are two important predictors for teenagers to become overweight and obese, while WHR is less useful for this purpose.

Clinical utility of the Calgary Depression Scale for Schizophrenia in individuals at ultra-high risk of psychosis.

PubMed

Rekhi, Gurpreet; Ng, Wai Yee; Lee, Jimmy

2018-03-01

There is a pressing need for reliable and valid rating scales to assess and measure depression in individuals at ultra-high risk (UHR) of psychosis. The aim of this study was to examine the clinical utility of the Calgary Depression Scale for Schizophrenia (CDSS) in individuals at UHR of psychosis. 167 individuals at UHR of psychosis were included as participants in this study. The Structured Clinical Interview for DSM-IV Axis I Disorders, CDSS, Beck Anxiety Inventory and Global Assessment of Functioning were administered. A receiver operating characteristic (ROC) curve analysis and factor analyses were performed. Cronbach's alpha was computed. Correlations between CDSS factor scores and other clinical variables were examined. The median CDSS total score was 5.0 (IQR 1.0-9.0). The area under ROC curve was 0.886 and Cronbach's alpha was 0.855. A score of 7 on the CDSS yielded the highest sensitivity and specificity in detecting depression in UHR individuals. Exploratory factor analysis of the CDSS yielded two factors: depression-hopelessness and self depreciation-guilt, which was confirmed by confirmatory factor analysis. Further analysis showed that the depression-hopelessness factor predicted functioning; whereas the self depreciation-guilt factor was related to the severity of the attenuated psychotic symptoms. In conclusion, the CDSS demonstrates good psychometric properties when used to evaluate depression in individuals at UHR of psychosis. Our study results also support a two-factor structure of the CDSS in UHR individuals. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Signal detection in animal psychoacoustics: Analysis and simulation of sensory and decision-related influences

PubMed Central

Alves-Pinto, A.; Sollini, J.; Sumner, C.J.

2012-01-01

Signal detection theory (SDT) provides a framework for interpreting psychophysical experiments, separating the putative internal sensory representation and the decision process. SDT was used to analyse ferret behavioural responses in a (yes–no) tone-in-noise detection task. Instead of measuring the receiver-operating characteristic (ROC), we tested SDT by comparing responses collected using two common psychophysical data collection methods. These (Constant Stimuli, Limits) differ in the set of signal levels presented within and across behavioural sessions. The results support the use of SDT as a method of analysis: SDT sensory component was unchanged between the two methods, even though decisions depended on the stimuli presented within a behavioural session. Decision criterion varied trial-by-trial: a ‘yes’ response was more likely after a correct rejection trial than a hit trial. Simulation using an SDT model with several decision components reproduced the experimental observations accurately, leaving only ∼10% of the variance unaccounted for. The model also showed that trial-by-trial dependencies were unlikely to influence measured psychometric functions or thresholds. An additional model component suggested that inattention did not contribute substantially. Further analysis showed that ferrets were changing their decision criteria, almost optimally, to maximise the reward obtained in a session. The data suggest trial-by-trial reward-driven optimization of the decision process. Understanding the factors determining behavioural responses is important for correlating neural activity and behaviour. SDT provides a good account of animal psychoacoustics, and can be validated using standard psychophysical methods and computer simulations, without recourse to ROC measurements. PMID:22698686

Screening for alcohol use disorders and at-risk drinking in the general population: psychometric performance of three questionnaires.

PubMed

Rumpf, Hans-Jürgen; Hapke, Ulfert; Meyer, Christian; John, Ulrich

2002-01-01

Most screening questionnaires are developed in clinical settings and there are few data on their performance in the general population. This study provides data on the area under the receiver-operating characteristic (ROC) curve, sensitivity, specificity, and internal consistency of the Alcohol Use Disorders Identification Test (AUDIT), the consumption questions of the AUDIT (AUDIT-C) and the Lübeck Alcohol Dependence and Abuse Screening Test (LAST) among current drinkers (n = 3551) of a general population sample in northern Germany. Alcohol dependence and misuse according to DSM-IV and at-risk drinking served as gold standards to assess sensitivity and specificity and were assessed with the Munich-Composite Diagnostic Interview (M-CIDI). AUDIT and LAST showed insufficient sensitivity for at-risk drinking and alcohol misuse using standard cut-off scores, but satisfactory detection rates for alcohol dependence. The AUDIT-C showed low specificity in all criterion groups with standard cut-off. Adjusted cut-points are recommended. Among a subsample of individuals with previous general hospital admission in the last year, all questionnaires showed higher internal consistency suggesting lower reliability in non-clinical samples. In logistic regression analyses, having had a hospital admission increased the sensitivity in detecting any criterion group of the LAST, and the number of recent general practice visits increased the sensitivity of the AUDIT in detecting alcohol misuse. Women showed lower scores and larger areas under the ROC curves. It is concluded that setting specific instruments (e.g. primary care or general population) or adjusted cut-offs should be used.

Impact of different study populations on reader behavior and performance metrics: initial results

NASA Astrophysics Data System (ADS)

Gallas, Brandon D.; Pisano, Etta; Cole, Elodia; Myers, Kyle

2017-03-01

The FDA recently completed a study on design methodologies surrounding the Validation of Imaging Premarket Evaluation and Regulation called VIPER. VIPER consisted of five large reader sub-studies to compare the impact of different study populations on reader behavior as seen by sensitivity, specificity, and AUC, the area under the ROC curve (receiver operating characteristic curve). The study investigated different prevalence levels and two kinds of sampling of non-cancer patients: a screening population and a challenge population. The VIPER study compared full-field digital mammography (FFDM) to screenfilm mammography (SFM) for women with heterogeneously dense or extremely dense breasts. All cases and corresponding images were sampled from Digital Mammographic Imaging Screening Trial (DMIST) archives. There were 20 readers (American Board Certified radiologists) for each sub-study, and instead of every reader reading every case (fully-crossed study), readers and cases were split into groups to reduce reader workload and the total number of observations (split-plot study). For data collection, readers first decided whether or not they would recall a patient. Following that decision, they provided an ROC score for how close or far that patient was from the recall decision threshold. Performance results for FFDM show that as prevalence increases to 50%, there is a moderate increase in sensitivity and decrease in specificity, whereas AUC is mainly flat. Regarding precision, the statistical efficiency (ratio of variances) of sensitivity and specificity relative to AUC are 0.66 at best and decrease with prevalence. Analyses comparing modalities and the study populations (screening vs. challenge) are still ongoing.

Impact of Different Study Populations on Reader Behavior and Performance Metrics: Initial Results

PubMed Central

Gallas, Brandon D.; Pisano, Etta; Cole, Elodia; Myers, Kyle

2017-01-01

The FDA recently completed a study on design methodologies surrounding the Validation of Imaging Premarket Evaluation and Regulation called VIPER. VIPER consisted of five large reader sub-studies to compare the impact of different study populations on reader behavior as seen by sensitivity, specificity, and AUC, the area under the ROC curve (receiver operating characteristic curve). The study investigated different prevalence levels and two kinds of sampling of non-cancer patients: a screening population and a challenge population. The VIPER study compared full-field digital mammography (FFDM) to screen-film mammography (SFM) for women with heterogeneously dense or extremely dense breasts. All cases and corresponding images were sampled from Digital Mammographic Imaging Screening Trial (DMIST) archives. There were 20 readers (American Board Certified radiologists) for each sub-study, and instead of every reader reading every case (fully-crossed study), readers and cases were split into groups to reduce reader workload and the total number of observations (split-plot study). For data collection, readers first decided whether or not they would recall a patient. Following that decision, they provided an ROC score for how close or far that patient was from the recall decision threshold. Performance results for FFDM show that as prevalence increases to 50%, there is a moderate increase in sensitivity and decrease in specificity, whereas AUC is mainly flat. Regarding precision, the statistical efficiency (ratio of variances) of sensitivity and specificity relative to AUC are 0.66 at best and decrease with prevalence. Analyses comparing modalities and the study populations (screening vs. challenge) are still ongoing. PMID:28845078

Scene perception and memory revealed by eye movements and receiver-operating characteristic analyses: Does a cultural difference truly exist?

PubMed Central

Evans, Kris; Rotello, Caren M.; Li, Xingshan; Rayner, Keith

2009-01-01

Cultural differences have been observed in scene perception and memory: Chinese participants purportedly attend to the background information more than did American participants. We investigated the influence of culture by recording eye movements during scene perception and while participants made recognition memory judgements. Real-world pictures with a focal object on a background were shown to both American and Chinese participants while their eye movements were recorded. Later, memory for the focal object in each scene was tested, and the relationship between the focal object (studied, new) and the background context (studied, new) was manipulated. Receiver-operating characteristic (ROC) curves show that both sensitivity and response bias were changed when objects were tested in new contexts. However, neither the decrease in accuracy nor the response bias shift differed with culture. The eye movement patterns were also similar across cultural groups. Both groups made longer and more fixations on the focal objects than on the contexts. The similarity of eye movement patterns and recognition memory behaviour suggests that both Americans and Chinese use the same strategies in scene perception and memory. PMID:18785074

Comparing Postural Stability Entropy Analyses to Differentiate Fallers and Non-Fallers

PubMed Central

Fino, Peter C.; Mojdehi, Ahmad R.; Adjerid, Khaled; Habibi, Mohammad; Lockhart, Thurmon E.; Ross, Shane D.

2015-01-01

The health and financial cost of falls has spurred research to differentiate the characteristics of fallers and non-fallers. Postural stability has received much of the attention with recent studies exploring various measures of entropy. This study compared the discriminatory ability of several entropy methods at differentiating two paradigms in the center-of-pressure (COP) of elderly individuals: 1.) eyes open (EO) versus eyes closed (EC) and 2.) fallers (F) versus non-fallers (NF). Methods were compared using the area under the curve (AUC) of the receiver-operating characteristic (ROC) curves developed from logistic regression models. Overall, multiscale entropy (MSE) and composite multiscale entropy (CompMSE) performed the best with AUCs of 0.71 for EO/EC and 0.77 for F/NF. When methods were combined together to maximize the AUC, the entropy classifier had an AUC of for 0.91 the F/NF comparison. These results suggest researchers and clinicians attempting to create clinical tests to identify fallers should consider a combination of every entropy method when creating a classifying test. Additionally, MSE and CompMSE classifiers using polar coordinate data outperformed rectangular coordinate data, encouraging more research into the most appropriate time series for postural stability entropy analysis. PMID:26464267

Diagnostic Capability of Peripapillary Retinal Volume Measurements in Glaucoma.

PubMed

Simavli, Huseyin; Poon, Linda Yi-Chieh; Que, Christian J; Liu, Yingna; Akduman, Mustafa; Tsikata, Edem; de Boer, Johannes F; Chen, Teresa C

2017-06-01

To determine the diagnostic capability of spectral domain optical coherence tomography peripapillary retinal volume (RV) measurements. A total of 156 patients, 89 primary open-angle glaucoma and 67 normal subjects, were recruited. Spectral domain optical coherence tomography peripapillary RV was calculated for 4 quadrants using 3 annuli of varying scan circle diameters: outer circumpapillary annuli of circular grids 1, 2, and 3 (OCA1, OCA2, OCA3). Area under the receiver operating characteristic curves and pairwise comparisons of receiver operating characteristic (ROC) curves were performed to determine which quadrants were best for diagnosing primary open-angle glaucoma. The pairwise comparisons of the best ROC curves for RV and retinal nerve fiber layer (RNFL) were performed. The artifact rates were analyzed. Pairwise comparisons showed that the smaller annuli OCA1 and OCA2 had better diagnostic performance than the largest annulus OCA3 (P<0.05 for all quadrants). OCA1 and OCA2 had similar diagnostic performance, except for the inferior quadrant which was better for OCA1 (P=0.0033). The pairwise comparisons of the best ROC curves for RV and RNFL were not statistically significant. RV measurements had lower rates of artifacts at 7.4% while RNFL measurements had higher rates at 42.9%. Peripapillary RV measurements have excellent ability for diagnosing not only glaucoma patients but also a subset of early glaucoma patients. The inferior quadrant of peripapillary annulus OCA1 demonstrated the best diagnostic capability for both glaucoma and early glaucoma. The diagnostic ability of RV is comparable with that of RNFL parameters in glaucoma but with lower artifact rates.

Diagnostic Capability of Peripapillary Retinal Volume Measurements in Glaucoma

PubMed Central

Simavli, Huseyin; Poon, Linda Yi-Chieh; Que, Christian John; Liu, Yingna; Akduman, Mustafa; Tsikata, Edem; de Boer, Johannes F.; Chen, Teresa C.

2017-01-01

Purpose To determine the diagnostic capability of spectral domain optical coherence tomography (SD-OCT) peripapillary retinal volume (RV) measurements. Materials and Methods A total of 156 patients, 89 primary open angle (POAG) and 67 normal subjects, were recruited. SD-OCT peripapillary RV was calculated for four quadrants using 3 annuli of varying scan circle diameters: outer circumpapillary annuli of circular grids 1, 2, and 3 (OCA1, OCA2, OCA3). Area under the receiver operating characteristic (AUROC) curves and pairwise comparisons of receiver operating characteristic (ROC) curves were performed to determine which quadrants were best for diagnosing POAG. The pairwise comparisons of the best ROC curves for RV and RNFL were performed. The artifact rates were analyzed. Results Pairwise comparisons showed that the smaller annuli OCA1 and OCA2 had better diagnostic performance than the largest annulus OCA3 (p<0.05 for all quadrants). OCA1 and OCA2 had similar diagnostic performance, except for the inferior quadrant which was better for OCA1 (p=0.0033).The pairwise comparisons of the best ROC curves for RV and RNFL were not statistically significant. Retinal volume measurements had lower rates of artifacts at 7.4% while RNFL measurements had higher rates at 42.9%. Conclusion Peripapillary RV measurements have excellent ability for diagnosing not only glaucoma patients but also a subset of early glaucoma patients. The inferior quadrant of peripapillary annulus OCA1 demonstrated the best diagnostic capability for both glaucoma and early glaucoma. The diagnostic ability of RV is comparable to that of RNFL parameters in glaucoma but with lower artifact rates. PMID:28079657

Analysis of SEER Adenosquamous Carcinoma Data to Identify Cause Specific Survival Predictors and Socioeconomic Disparities.

PubMed

Cheung, Rex

2016-01-01

This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) adenosquamous carcinoma data to identify predictive models and potential disparities in outcome. This study analyzed socio-economic, staging and treatment factors available in the SEER database for adenosquamous carcinoma. For the risk modeling, each factor was fitted by a generalized linear model to predict the cause specific survival. An area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A total of 20,712 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 54.2 (78.4) months. Some 2/3 of the patients were female. The mean (S.D.) age was 63 (13.8) years. SEER stage was the most predictive factor of outcome (ROC area of 0.71). 13.9% of the patients were un-staged and had risk of cause specific death of 61.3% that was higher than the 45.3% risk for the regional disease and lower than the 70.3% for metastatic disease. Sex, site, radiotherapy, and surgery had ROC areas of about 0.55-0.65. Rural residence and race contributed to socioeconomic disparity for treatment outcome. Radiotherapy was underused even with localized and regional stages when the intent was curative. This under use was most pronounced in older patients. Anatomic stage was predictive and useful in treatment selection. Under-staging may have contributed to poor outcome.

Optimizing area under the ROC curve using semi-supervised learning

PubMed Central

Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M.

2014-01-01

Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two classes. Traditional AUC optimization techniques are supervised learning methods that utilize only labeled data (i.e., the true class is known for all data) to train the classifiers. In this work, inspired by semi-supervised and transductive learning, we propose two new AUC optimization algorithms hereby referred to as semi-supervised learning receiver operating characteristic (SSLROC) algorithms, which utilize unlabeled test samples in classifier training to maximize AUC. Unlabeled samples are incorporated into the AUC optimization process, and their ranking relationships to labeled positive and negative training samples are considered as optimization constraints. The introduced test samples will cause the learned decision boundary in a multidimensional feature space to adapt not only to the distribution of labeled training data, but also to the distribution of unlabeled test data. We formulate the semi-supervised AUC optimization problem as a semi-definite programming problem based on the margin maximization theory. The proposed methods SSLROC1 (1-norm) and SSLROC2 (2-norm) were evaluated using 34 (determined by power analysis) randomly selected datasets from the University of California, Irvine machine learning repository. Wilcoxon signed rank tests showed that the proposed methods achieved significant improvement compared with state-of-the-art methods. The proposed methods were also applied to a CT colonography dataset for colonic polyp classification and showed promising results.1 PMID:25395692

Using patient data similarities to predict radiation pneumonitis via a self-organizing map

NASA Astrophysics Data System (ADS)

Chen, Shifeng; Zhou, Sumin; Yin, Fang-Fang; Marks, Lawrence B.; Das, Shiva K.

2008-01-01

This work investigates the use of the self-organizing map (SOM) technique for predicting lung radiation pneumonitis (RP) risk. SOM is an effective method for projecting and visualizing high-dimensional data in a low-dimensional space (map). By projecting patients with similar data (dose and non-dose factors) onto the same region of the map, commonalities in their outcomes can be visualized and categorized. Once built, the SOM may be used to predict pneumonitis risk by identifying the region of the map that is most similar to a patient's characteristics. Two SOM models were developed from a database of 219 lung cancer patients treated with radiation therapy (34 clinically diagnosed with Grade 2+ pneumonitis). The models were: SOMall built from all dose and non-dose factors and, for comparison, SOMdose built from dose factors alone. Both models were tested using ten-fold cross validation and Receiver Operating Characteristics (ROC) analysis. Models SOMall and SOMdose yielded ten-fold cross-validated ROC areas of 0.73 (sensitivity/specificity = 71%/68%) and 0.67 (sensitivity/specificity = 63%/66%), respectively. The significant difference between the cross-validated ROC areas of these two models (p < 0.05) implies that non-dose features add important information toward predicting RP risk. Among the input features selected by model SOMall, the two with highest impact for increasing RP risk were: (a) higher mean lung dose and (b) chemotherapy prior to radiation therapy. The SOM model developed here may not be extrapolated to treatment techniques outside that used in our database, such as several-field lung intensity modulated radiation therapy or gated radiation therapy.

Receiver operating characteristic analysis of eyewitness memory: comparing the diagnostic accuracy of simultaneous versus sequential lineups.

PubMed

Mickes, Laura; Flowe, Heather D; Wixted, John T

2012-12-01

A police lineup presents a real-world signal-detection problem because there are two possible states of the world (the suspect is either innocent or guilty), some degree of information about the true state of the world is available (the eyewitness has some degree of memory for the perpetrator), and a decision is made (identifying the suspect or not). A similar state of affairs applies to diagnostic tests in medicine because, in a patient, the disease is either present or absent, a diagnostic test yields some degree of information about the true state of affairs, and a decision is made about the presence or absence of the disease. In medicine, receiver operating characteristic (ROC) analysis is the standard method for assessing diagnostic accuracy. By contrast, in the eyewitness memory literature, this powerful technique has never been used. Instead, researchers have attempted to assess the diagnostic performance of different lineup procedures using methods that cannot identify the better procedure (e.g., by computing a diagnosticity ratio). Here, we describe the basics of ROC analysis, explaining why it is needed and showing how to use it to measure the performance of different lineup procedures. To illustrate the unique advantages of this technique, we also report 3 ROC experiments that were designed to investigate the diagnostic accuracy of simultaneous versus sequential lineups. According to our findings, the sequential procedure appears to be inferior to the simultaneous procedure in discriminating between the presence versus absence of a guilty suspect in a lineup.

Unsupervised classification of cirrhotic livers using MRI data

NASA Astrophysics Data System (ADS)

Lee, Gobert; Kanematsu, Masayuki; Kato, Hiroki; Kondo, Hiroshi; Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Hoshi, Hiroaki

2008-03-01

Cirrhosis of the liver is a chronic disease. It is characterized by the presence of widespread nodules and fibrosis in the liver which results in characteristic texture patterns. Computerized analysis of hepatic texture patterns is usually based on regions-of-interest (ROIs). However, not all ROIs are typical representatives of the disease stage of the liver from which the ROIs originated. This leads to uncertainties in the ROI labels (diseased or non-diseased). On the other hand, supervised classifiers are commonly used in determining the assignment rule. This presents a problem as the training of a supervised classifier requires the correct labels of the ROIs. The main purpose of this paper is to investigate the use of an unsupervised classifier, the k-means clustering, in classifying ROI based data. In addition, a procedure for generating a receiver operating characteristic (ROC) curve depicting the classification performance of k-means clustering is also reported. Hepatic MRI images of 44 patients (16 cirrhotic; 28 non-cirrhotic) are used in this study. The MRI data are derived from gadolinium-enhanced equilibrium phase images. For each patient, 10 ROIs selected by an experienced radiologist and 7 texture features measured on each ROI are included in the MRI data. Results of the k-means classifier are depicted using an ROC curve. The area under the curve (AUC) has a value of 0.704. This is slightly lower than but comparable to that of LDA and ANN classifiers which have values 0.781 and 0.801, respectively. Methods in constructing ROC curve in relation to k-means clustering have not been previously reported in the literature.

Optimizing area under the ROC curve using semi-supervised learning.

PubMed

Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M

2015-01-01

Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two classes. Traditional AUC optimization techniques are supervised learning methods that utilize only labeled data (i.e., the true class is known for all data) to train the classifiers. In this work, inspired by semi-supervised and transductive learning, we propose two new AUC optimization algorithms hereby referred to as semi-supervised learning receiver operating characteristic (SSLROC) algorithms, which utilize unlabeled test samples in classifier training to maximize AUC. Unlabeled samples are incorporated into the AUC optimization process, and their ranking relationships to labeled positive and negative training samples are considered as optimization constraints. The introduced test samples will cause the learned decision boundary in a multidimensional feature space to adapt not only to the distribution of labeled training data, but also to the distribution of unlabeled test data. We formulate the semi-supervised AUC optimization problem as a semi-definite programming problem based on the margin maximization theory. The proposed methods SSLROC1 (1-norm) and SSLROC2 (2-norm) were evaluated using 34 (determined by power analysis) randomly selected datasets from the University of California, Irvine machine learning repository. Wilcoxon signed rank tests showed that the proposed methods achieved significant improvement compared with state-of-the-art methods. The proposed methods were also applied to a CT colonography dataset for colonic polyp classification and showed promising results.

Estimating the relative utility of screening mammography.

PubMed

Abbey, Craig K; Eckstein, Miguel P; Boone, John M

2013-05-01

The concept of diagnostic utility is a fundamental component of signal detection theory, going back to some of its earliest works. Attaching utility values to the various possible outcomes of a diagnostic test should, in principle, lead to meaningful approaches to evaluating and comparing such systems. However, in many areas of medical imaging, utility is not used because it is presumed to be unknown. In this work, we estimate relative utility (the utility benefit of a detection relative to that of a correct rejection) for screening mammography using its known relation to the slope of a receiver operating characteristic (ROC) curve at the optimal operating point. The approach assumes that the clinical operating point is optimal for the goal of maximizing expected utility and therefore the slope at this point implies a value of relative utility for the diagnostic task, for known disease prevalence. We examine utility estimation in the context of screening mammography using the Digital Mammographic Imaging Screening Trials (DMIST) data. We show how various conditions can influence the estimated relative utility, including characteristics of the rating scale, verification time, probability model, and scope of the ROC curve fit. Relative utility estimates range from 66 to 227. We argue for one particular set of conditions that results in a relative utility estimate of 162 (±14%). This is broadly consistent with values in screening mammography determined previously by other means. At the disease prevalence found in the DMIST study (0.59% at 365-day verification), optimal ROC slopes are near unity, suggesting that utility-based assessments of screening mammography will be similar to those found using Youden's index.

Validation of a Competitive Enzyme-Linked Immunosorbent Assay for Detection of Babesia bigemina Antibodies in Cattle

USDA-ARS?s Scientific Manuscript database

A competitive ELISA (cELISA) based on a broadly conserved, species-specific, B-cell epitope within the C-terminus of Babesia bigemina rhoptry-associated protein-1a was validated for international use. Receiver Operating Characteristic (ROC) analysis revealed 16% inhibition as the threshold for a neg...

Examining Classification Criteria: A Comparison of Three Cut Score Methods

ERIC Educational Resources Information Center

DiStefano, Christine; Morgan, Grant

2011-01-01

This study compared 3 different methods of creating cut scores for a screening instrument, T scores, receiver operating characteristic curve (ROC) analysis, and the Rasch rating scale method (RSM), for use with the Behavioral and Emotional Screening System (BESS) Teacher Rating Scale for Children and Adolescents (Kamphaus & Reynolds, 2007).…

Validation of a Brief PTSD Scale for Clients with Severe Mental Illnesses

ERIC Educational Resources Information Center

O'Hare, Thomas; Shen, Ce; Sherrer, Margaret

2012-01-01

Trauma and Posttraumatic Stress Disorder (PTSD) are more common in severe mental illnesses (SMI) clients than in the general population, yet brief screens for detecting probable PTSD in SMI clients are nonexistent. In a two-part study, the authors used correlation analysis and receiver operating characteristics (ROC) analysis to develop and…

Use of the Child Behavior Checklist as a Diagnostic Screening Tool in Community Mental Health

ERIC Educational Resources Information Center

Rishel, Carrie W.; Greeno, Catherine; Marcus, Steven C.; Shear, M. Katherine; Anderson, Carol

2005-01-01

Objective: This study examines whether the Child Behavior Checklist (CBCL) can be used as an accurate psychiatric screening tool for children in community mental health settings. Method: Associations, logistic regression models, and receiver operating characteristic (ROC) analysis were used to test the predictive relationship between the CBCL and…

Investigating Strength and Frequency Effects in Recognition Memory Using Type-2 Signal Detection Theory

ERIC Educational Resources Information Center

Higham, Philip A.; Perfect, Timothy J.; Bruno, Davide

2009-01-01

Criterion- versus distribution-shift accounts of frequency and strength effects in recognition memory were investigated with Type-2 signal detection receiver operating characteristic (ROC) analysis, which provides a measure of metacognitive monitoring. Experiment 1 demonstrated a frequency-based mirror effect, with a higher hit rate and lower…

International ring trial to detect anti-Trichinella IgG by ELISA on pig sera.

USDA-ARS?s Scientific Manuscript database

In the present study, the sensitivity and specificity of the ELISA assay determined by the CRLP validation was 100% and 98.29%, respectively. The assay was reproducible, moreover, based on the receiver-operator characteristic (ROC) curve, the sensitivity and specificity of the assay reached 97.5% an...

Classification of breast abnormalities using artificial neural network

NASA Astrophysics Data System (ADS)

Zaman, Nur Atiqah Kamarul; Rahman, Wan Eny Zarina Wan Abdul; Jumaat, Abdul Kadir; Yasiran, Siti Salmah

2015-05-01

Classification is the process of recognition, differentiation and categorizing objects into groups. Breast abnormalities are calcifications which are tumor markers that indicate the presence of cancer in the breast. The aims of this research are to classify the types of breast abnormalities using artificial neural network (ANN) classifier and to evaluate the accuracy performance using receiver operating characteristics (ROC) curve. The methods used in this research are ANN for breast abnormalities classifications and Canny edge detector as a feature extraction method. Previously the ANN classifier provides only the number of benign and malignant cases without providing information for specific cases. However in this research, the type of abnormality for each image can be obtained. The existing MIAS MiniMammographic database classified the mammogram images into three features only namely characteristic of background tissues, class of abnormality and radius of abnormality. However, in this research three other features are added-in. These three features are number of spots, area and shape of abnormalities. Lastly the performance of the ANN classifier is evaluated using ROC curve. It is found that ANN has an accuracy of 97.9% which is considered acceptable.

ROC Analysis of Chest Radiographs Using Computed Radiography and Conventional Analog Films

NASA Astrophysics Data System (ADS)

Morioka, Craig A.; Brown, Kathy; Hayrapetian, Alek S.; Kangarloo, Hooshang; Balter, Stephen; Huang, H. K.

1989-05-01

Receiver operating characteristic is used to compare the image quality of films obtained digitally using computed radiography (CR) and conventionally using analog film following fluoroscopic examination. Similar radiological views were obtained by both modalities. Twenty-four cases, some with a solitary noncalcified nodule and/or pneumothorax, were collected. Ten radiologists have been tested viewing analog and CR digital films separately. Final results indicate that there is no statistically significant difference in the ability to detect either a pneumothorax or a solitary noncalcified nodule when comparing CR digital film with conventional analog film. However, there is a trend that indicated the area under the ROC curves for detection of either a pneumothorax or solitary noncalcified nodule were greater for the analog film than for the digital film.

Fertility biomarkers to estimate metabolic risks in women with polycystic ovary syndrome.

PubMed

Detti, Laura; Jeffries-Boyd, Heather E; Williams, Lucy J; Diamond, Michael P; Uhlmann, Rebecca A

2015-12-01

We sought to evaluate the relationship between the polycystic ovary syndrome (PCOS)-defining characteristics and the risk of developing metabolic complications in women presenting with complaints of infertility and/or menstrual irregularities and subsequently diagnosed with PCOS. This was a cross-sectional study. Women presenting with complaints of infertility and/or irregular menses and diagnosed with PCOS by the Rotterdam criteria, underwent endocrine, metabolic, and ultrasound assessment in the early follicular phase. Reproductive and metabolic parameters were included in regression analysis models with the PCOS-defining characteristics; ROC curves were calculated for the significant predictors. Three hundred and seventy-four women with PCOS were included in our study. Oligo-anovulation, menstrual irregularities, and hirsutism were not predictive of any of the variables. Ovarian volume, follicle count, and biochemical hyperandrogenism were predictors for hormonal, metabolic, and endometrial complications. The relationships were independent of age and body mass index. ROC curves identified lower cut-off values of the PCOS-defining characteristics to predict patients' risks of hyperinsulinemia, dyslipidemia, and glucose intolerance. Adverse metabolic effects of PCOS are already present in women at the time they present complaining of infertility and/or irregular menses. Hyperandrogenism and ultrasound can assist in predicting the patients' concomitant metabolic abnormalities and can aid physicians in tailoring counseling for effective preventive strategies.

Change in end-tidal carbon dioxide outperforms other surrogates for change in cardiac output during fluid challenge.

PubMed

Lakhal, K; Nay, M A; Kamel, T; Lortat-Jacob, B; Ehrmann, S; Rozec, B; Boulain, T

2017-03-01

During fluid challenge, volume expansion (VE)-induced increase in cardiac output (Δ VE CO) is seldom measured. In patients with shock undergoing strictly controlled mechanical ventilation and receiving VE, we assessed minimally invasive surrogates for Δ VE CO (by transthoracic echocardiography): fluid-induced increases in end-tidal carbon dioxide (Δ VE E'CO2 ); pulse (Δ VE PP), systolic (Δ VE SBP), and mean systemic blood pressure (Δ VE MBP); and femoral artery Doppler flow (Δ VE FemFlow). In the absence of arrhythmia, fluid-induced decrease in heart rate (Δ VE HR) and in pulse pressure respiratory variation (Δ VE PPV) were also evaluated. Areas under the receiver operating characteristic curves (AUC ROC s) reflect the ability to identify a response to VE (Δ VE CO ≥15%). In 86 patients, Δ VE E'CO2 had an AUC ROC =0.82 [interquartile range 0.73-0.90], significantly higher than the AUC ROC for Δ VE PP, Δ VE SBP, Δ VE MBP, and Δ VE FemFlow (AUC ROC =0.61-0.65, all P  <0.05). A value of Δ VE E'CO2  >1 mm Hg (>0.13 kPa) had good positive (5.0 [2.6-9.8]) and fair negative (0.29 [0.2-0.5]) likelihood ratios. The 16 patients with arrhythmia had similar relationships between Δ VE E'CO2 and Δ VE CO to patients with regular rhythm ( r 2 =0.23 in both subgroups). In 60 patients with no arrhythmia, Δ VE E'CO2 (AUC ROC =0.84 [0.72-0.92]) outperformed Δ VE HR (AUC ROC =0.52 [0.39-0.66], P <0.05) and tended to outperform Δ VE PPV (AUC ROC =0.73 [0.60-0.84], P =0.21). In the 45 patients with no arrhythmia and receiving ventilation with tidal volume <8 ml kg -1 , Δ VE E'CO2 performed better than Δ VE PPV, with AUC ROC =0.86 [0.72-0.95] vs 0.66 [0.49-0.80], P =0.02. Δ VE E'CO2 outperformed Δ VE PP, Δ VE SBP, Δ VE MBP, Δ VE FemFlow, and Δ VE HR and, during protective ventilation, arrhythmia, or both, it also outperformed Δ VE PPV. A value of Δ VE E'CO2 >1 mm Hg (>0.13 kPa) indicated a likely response to VE. © The Author 2017. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Evaluation and simplification of the occupational slip, trip and fall risk-assessment test

PubMed Central

NAKAMURA, Takehiro; OYAMA, Ichiro; FUJINO, Yoshihisa; KUBO, Tatsuhiko; KADOWAKI, Koji; KUNIMOTO, Masamizu; ODOI, Haruka; TABATA, Hidetoshi; MATSUDA, Shinya

2016-01-01

Objective: The purpose of this investigation is to evaluate the efficacy of the occupational slip, trip and fall (STF) risk assessment test developed by the Japan Industrial Safety and Health Association (JISHA). We further intended to simplify the test to improve efficiency. Methods: A previous cohort study was performed using 540 employees aged ≥50 years who took the JISHA’s STF risk assessment test. We conducted multivariate analysis using these previous results as baseline values and answers to questionnaire items or score on physical fitness tests as variables. The screening efficiency of each model was evaluated based on the obtained receiver operating characteristic (ROC) curve. Results: The area under the ROC obtained in multivariate analysis was 0.79 when using all items. Six of the 25 questionnaire items were selected for stepwise analysis, giving an area under the ROC curve of 0.77. Conclusion: Based on the results of follow-up performed one year after the initial examination, we successfully determined the usefulness of the STF risk assessment test. Administering a questionnaire alone is sufficient for screening subjects at risk of STF during the subsequent one-year period. PMID:27021057

Predictive inference for best linear combination of biomarkers subject to limits of detection.

PubMed

Coolen-Maturi, Tahani

2017-08-15

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning and credit scoring. The receiver operating characteristic (ROC) curve is a useful tool to assess the ability of a diagnostic test to discriminate between two classes or groups. In practice, multiple diagnostic tests or biomarkers are combined to improve diagnostic accuracy. Often, biomarker measurements are undetectable either below or above the so-called limits of detection (LoD). In this paper, nonparametric predictive inference (NPI) for best linear combination of two or more biomarkers subject to limits of detection is presented. NPI is a frequentist statistical method that is explicitly aimed at using few modelling assumptions, enabled through the use of lower and upper probabilities to quantify uncertainty. The NPI lower and upper bounds for the ROC curve subject to limits of detection are derived, where the objective function to maximize is the area under the ROC curve. In addition, the paper discusses the effect of restriction on the linear combination's coefficients on the analysis. Examples are provided to illustrate the proposed method. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Iodine concentration: a new, important characteristic of the spot sign that predicts haematoma expansion.

PubMed

Fu, Fan; Sun, Shengjun; Liu, Liping; Li, Jianying; Su, Yaping; Li, Yingying

2018-04-19

The computed tomography angiography (CTA) spot sign is a validated predictor of haematoma expansion (HE) in spontaneous intracerebral haemorrhage (SICH). We investigated whether defining the iodine concentration (IC) inside the spot sign and the haematoma on Gemstone spectral imaging (GSI) would improve its sensitivity and specificity for predicting HE. From 2014 to 2016, we prospectively enrolled 65 SICH patients who underwent single-phase spectral CTA within 6 h. Logistic regression was performed to assess the risk factors for HE. The predictive performance of individual spot sign characteristics was examined via receiver operating characteristic (ROC) analysis. The spot sign was detected in 46.1% (30/65) of patients. ROC analysis indicated that IC inside the spot sign had the greatest area under the ROC curve for HE (0.858; 95% confidence interval, 0.727-0.989; p = 0.003). Multivariate analysis found that spot sign with higher IC (i.e. IC > 7.82 100 μg/ml) was an independent predictor of HE (odds ratio = 34.27; 95% confidence interval, 5.608-209.41; p < 0.001) with sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 0.81, 0.75, 0.90 and 0.60, respectively; while the spot sign showed sensitivity, specificity, PPV and NPV of 0.81, 0.79, 0.73 and 0.86. Logistic regression analysis indicated that the IC in haematomas was independently associated with HE (odds ratio = 1.525; 95% confidence interval, 1.041-2.235; p = 0.030). ICs in haematoma and in spot sign were all independently associated with HE. IC analysis in spectral imaging may help to identify SICH patients for targeted haemostatic therapy. • Iodine concentration in spot sign and haematoma can predict haematoma expansion • Spectral imaging could measure the IC inside the spot sign and haematoma • IC in spot sign improved the positive predictive value (PPV) cf. CTA.

The "surprise question" for predicting death in seriously ill patients: a systematic review and meta-analysis.

PubMed

Downar, James; Goldman, Russell; Pinto, Ruxandra; Englesakis, Marina; Adhikari, Neill K J

2017-04-03

The surprise question - "Would I be surprised if this patient died in the next 12 months?" - has been used to identify patients at high risk of death who might benefit from palliative care services. Our objective was to systematically review the performance characteristics of the surprise question in predicting death. We searched multiple electronic databases from inception to 2016 to identify studies that prospectively screened patients with the surprise question and reported on death at 6 to 18 months. We constructed models of hierarchical summary receiver operating characteristics (sROCs) to determine prognostic performance. Sixteen studies (17 cohorts, 11 621 patients) met the selection criteria. For the outcome of death at 6 to 18 months, the pooled prognostic characteristics were sensitivity 67.0% (95% confidence interval [CI] 55.7%-76.7%), specificity 80.2% (73.3%-85.6%), positive likelihood ratio 3.4 (95% CI 2.8-4.1), negative likelihood ratio 0.41 (95% CI 0.32-0.54), positive predictive value 37.1% (95% CI 30.2%-44.6%) and negative predictive value 93.1% (95% CI 91.0%-94.8%). The surprise question had worse discrimination in patients with noncancer illness (area under sROC curve 0.77 [95% CI 0.73-0.81]) than in patients with cancer (area under sROC curve 0.83 [95% CI 0.79-0.87; p = 0.02 for difference]). Most studies had a moderate to high risk of bias, often because they had a low or unknown participation rate or had missing data. The surprise question performs poorly to modestly as a predictive tool for death, with worse performance in noncancer illness. Further studies are needed to develop accurate tools to identify patients with palliative care needs and to assess the surprise question for this purpose. © 2017 Canadian Medical Association or its licensors.

Environmentally Adaptive UXO Detection and Classification Systems

DTIC Science & Technology

2016-04-01

probability of false alarm ( Pfa ), as well as Receiver Op- erating Characteristic (ROC) curve and confusion matrix characteristics. The results of these...techniques at a false alarm probability of Pfa = 1× 10−3. X̃ = g(X). In this case, the problem remains invariant to the group of transformations G = { g : g(X...and observed target responses as well as the probability of detection versus SNR for both detection techniques at Pfa = 1× 10−3. with N = 128 and M = 50

Analysis of injury patterns and roles of care in US and Israel militaries during recent conflicts: Two are better than one.

PubMed

Antebi, Ben; Benov, Avi; Mann-Salinas, Elizabeth A; Le, Tuan D; Cancio, Leopoldo C; Wenke, Joseph C; Paran, Haim; Yitzhak, Avraham; Tarif, Bader; Gross, Kirby R; Dagan, David; Glassberg, Elon

2016-11-01

As new conflicts emerge and enemies evolve, military medical organizations worldwide must adopt the "lessons learned." In this study, we describe roles of care (ROCs) deployed and injuries sustained by both US and Israeli militaries during recent conflicts. The purpose of this collaborative work is facilitate exchange of medical data among allied forces in order to advance military medicine and facilitate strategic readiness for future military engagements that may involve less predictable situations of evacuation and care, such as prolonged field care. This retrospective study was conducted for the periods of 2003 to 2014 from data retrieved from the Department of Defense Trauma Registry and the Israel Defense Force (IDF) Trauma Registry. Comparative analyses included ROC capabilities, casualties who died of wounds, as well as mechanism of injury, anatomical wound distribution, and Injury Severity Score of US and IDF casualties during recent conflicts. Although concept of ROCs was similar among militaries, the IDF supports increased capabilities at point of injury and Role 1 including the presence of physicians, but with limited deployment of other ROCs; conversely, the US maintains fewer capabilities at Role 1 but utilized the entire spectrum of care, including extensive deployment of Roles 2/2+, during recent conflicts. Casualties from US forces (n = 19,005) and IDF (n = 2,637) exhibited significant differences in patterns of injury with higher proportions of casualties who died of wounds in the US forces (4%) compared with the IDF (0.6%). As these data suggest deployed ROCs and injury patterns of US and Israeli militaries were both conflict and system specific. We envision that identification of discordant factors and common medical strategies of the two militaries will enable strategic readiness for future conflicts as well as foster further collaboration among allied forces with the overarching universal goal of eliminating preventable death on the battlefield.

Taxometric analyses and predictive accuracy of callous-unemotional traits regarding quality of life and behavior problems in non-conduct disorder diagnoses.

PubMed

Herpers, Pierre C M; Klip, Helen; Rommelse, Nanda N J; Taylor, Mark J; Greven, Corina U; Buitelaar, Jan K

2017-07-01

Callous-unemotional (CU) traits have mainly been studied in relation to conduct disorder (CD), but can also occur in other disorder groups. However, it is unclear whether there is a clinically relevant cut-off value of levels of CU traits in predicting reduced quality of life (QoL) and clinical symptoms, and whether CU traits better fit a categorical (taxonic) or dimensional model. Parents of 979 youths referred to a child and adolescent psychiatric clinic rated their child's CU traits on the Inventory of Callous-Unemotional traits (ICU), QoL on the Kidscreen-27, and clinical symptoms on the Child Behavior Checklist. Experienced clinicians conferred DSM-IV-TR diagnoses of ADHD, ASD, anxiety/mood disorders and DBD-NOS/ODD. The ICU was also used to score the DSM-5 specifier 'with limited prosocial emotions' (LPE) of Conduct Disorder. Receiver operating characteristic (ROC) analyses revealed that the predictive accuracy of the ICU and LPE regarding QoL and clinical symptoms was poor to fair, and similar across diagnoses. A clinical cut-off point could not be defined. Taxometric analyses suggested that callous-unemotional traits on the ICU best reflect a dimension rather than taxon. More research is needed on the impact of CU traits on the functional adaptation, course, and response to treatment of non-CD conditions. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Can we predict pneumococcal bacteremia in patients with severe community-acquired pneumonia?

PubMed

Pereira, José Manuel; Teixeira-Pinto, Armando; Basílio, Carla; Sousa-Dias, Conceição; Mergulhão, Paulo; Paiva, José Artur

2013-12-01

This study aimed to evaluate the role of biomarkers as markers of pneumococcal bacteremia in severe community-acquired pneumonia (SCAP). A prospective, single-center, observational cohort study of 108 patients with SCAP admitted to the intensive care department of a university hospital in Portugal was conducted. Leucocytes, C-reactive protein (CRP), lactate, procalcitonin (PCT), d-dimer, brain natriuretic peptide (BNP), and cortisol were measured within 12 hours after the first antibiotic dose. Fifteen patients (14%) had bacteremic pneumococcal pneumonia (BPP). They had significantly higher levels of median CRP (301 [interquartile range, or IQR], 230-350] mg/L vs 201 [IQR, 103-299] mg/L; P = .023), PCT (40 [IQR, 25-102] ng/mL vs 8 [IQR, 2-26] ng/mL; P < .001), BNP (568 [IQR, 478-2841] pg/mL vs 407 [IQR, 175-989] pg/mL; P = .027), and lactate (5.5 [IQR, 4.5-9.8] mmol/L vs 3.1 [IQR, 1.9-6.2] mmol/L; P = .009) than did patients without BPP. The discriminatory power evaluated by the area under the receiver operating characteristic curve (aROC) for PCT (aROC, 0.79) was superior to lactate (aROC, 0.71), BNP (aROC, 0.67), and CRP (aROC, 0.70). At a cutoff point of 17 ng/mL, PCT showed a sensitivity of 87%, a specificity of 67%, a positive predictive value of 30% and a negative predictive value of 97%, as a marker of pneumococcal bacteremia. In this cohort, significantly higher PCT, BNP, lactate, and CRP levels were found in BPP, and PCT presented the best ability to identify pneumococcal bacteremia. A PCT serum level lower than 17 ng/mL could identify patients with SCAP unlikely to have pneumococcal bacteremia. Copyright © 2013 Elsevier Inc. All rights reserved.

A comparative study of quantitative immunohistochemistry and quantum dot immunohistochemistry for mutation carrier identification in Lynch syndrome.

PubMed

Barrow, Emma; Evans, D Gareth; McMahon, Ray; Hill, James; Byers, Richard

2011-03-01

Lynch Syndrome is caused by mutations in DNA mismatch repair (MMR) genes. Mutation carrier identification is facilitated by immunohistochemical detection of the MMR proteins MHL1 and MSH2 in tumour tissue and is desirable as colonoscopic screening reduces mortality. However, protein detection by conventional immunohistochemistry (IHC) is subjective, and quantitative techniques are required. Quantum dots (QDs) are novel fluorescent labels that enable quantitative multiplex staining. This study compared their use with quantitative 3,3'-diaminobenzidine (DAB) IHC for the diagnosis of Lynch Syndrome. Tumour sections from 36 mutation carriers and six controls were obtained. These were stained with DAB on an automated platform using antibodies against MLH1 and MSH2. Multiplex QD immunofluorescent staining of the sections was performed using antibodies against MLH1, MSH2 and smooth muscle actin (SMA). Multispectral analysis of the slides was performed. The staining intensity of DAB and QDs was measured in multiple colonic crypts, and the mean intensity scores calculated. Receiver operating characteristic (ROC) curves of staining performance for the identification of mutation carriers were evaluated. For quantitative DAB IHC, the area under the MLH1 ROC curve was 0.872 (95% CI 0.763 to 0.981), and the area under the MSH2 ROC curve was 0.832 (95% CI 0.704 to 0.960). For quantitative QD IHC, the area under the MLH1 ROC curve was 0.812 (95% CI 0.681 to 0.943), and the area under the MSH2 ROC curve was 0.598 (95% CI 0.418 to 0.777). Despite the advantage of QD staining to enable several markers to be measured simultaneously, it is of lower utility than DAB IHC for the identification of MMR mutation carriers. Automated DAB IHC staining and quantitative slide analysis may enable high-throughput IHC.

Gender differences in the accuracy of time-dependent blood pressure indices for predicting coronary heart disease: A random-effects modeling approach.

PubMed

Brant, Larry J; Ferrucci, Luigi; Sheng, Shan L; Concin, Hans; Zonderman, Alan B; Kelleher, Cecily C; Longo, Dan L; Ulmer, Hanno; Strasak, Alexander M

2010-12-01

Previous studies on blood pressure (BP) indices as a predictor of coronary heart disease (CHD) have provided equivocal results and generally relied on Cox proportional hazards regression methodology, with age and sex accounting for most of the predictive capability of the model. The aim of the present study was to use serially collected BP measurements to examine age-and gender-related differences in BP indices for predicting CHD. The predictive accuracy of time-dependent BP indices for CHD was investigated using a method of risk prediction based on posterior probabilities calculated from mixed-effects regression to utilize intraindividual differences in serial BP measurements according to age changes within gender groups. Data were collected prospectively from 2 community-dwelling cohort studies in the United States (Baltimore Longitudinal Study of Aging [BLSA]) and Europe (Vorarlberg Health Monitoring and Promotion Program [VHM&PP]). The study comprised 152,633 participants (aged 30-74 years) and 610,061 BP measurements. During mean follow-up of 7.5 years, 2457 nonfatal and fatal CHD events were observed. In both study populations, pulse pressure (PP) and systolic blood pressure (SBP) performed best as individual predictors of CHD in women (area under the receiver operating characteristic curve [AUC(ROC)] was between 0.83 and 0.85 for PP, and between 0.77 and 0.81 for SBP). Mean arterial pressure (MAP) and diastolic blood pressure (DBP) performed better for men (AUC(ROC) = 0.67 and 0.65 for MAP and DBP, respectively, in the BLSA; AUC(ROC) = 0.77 and 0.75 in the VHM&PP) than for women (AUC(ROC) = 0.60 for both MAP and DBP in the BLSA; AUC(ROC) = 0.75 and 0.52, respectively, in the VHM&PP). The degree of discrimination in both populations was overall greater but more varied for all BP indices for women (AUC(ROC) estimates between 0.85 [PP in the VHM&PP] and 0.52 [DBP in the VHM&PP]) than for men (AUC(ROC) estimates between 0.78 [MAP + PP in the VHM&PP] and 0.63 [PP in the BLSA]). Our findings indicate differences in discrimination between women and men in the accuracy of longitudinally collected BP measurements for predicting CHD, implicating the usefulness of gender-specific BP indices to assess individual CHD risk. Copyright © 2010. Published by EM Inc USA.

Assessing Internalizing, Externalizing, and Attention Problems in Young Children: Validation of the MacArthur HBQ

ERIC Educational Resources Information Center

Lemery-Chalfant, Kathryn; Schreiber, Jane E.; Schmidt, Nicole L.; Van Hulle, Carol A.; Essex, Marilyn J.; Goldsmith, H. H.

2007-01-01

Objective: To test the validity of the MacArthur Health and Behavior Questionnaire (HBQ) using receiver operating characteristic (ROC) analysis to determine optimal thresholds for the HBQ in predicting Diagnostic Interview Schedule for Children Version-IV (DISC-IV)diagnoses. The roles of child sex, level of impairment, and physical health in…

Some Memories Are Odder than Others: Judgments of Episodic Oddity Violate Known Decision Rules

ERIC Educational Resources Information Center

O'Connor, Akira R.; Guhl, Emily N.; Cox, Justin C.; Dobbins, Ian G.

2011-01-01

Current decision models of recognition memory are based almost entirely on one paradigm, single item old/new judgments accompanied by confidence ratings. This task results in receiver operating characteristics (ROCs) that are well fit by both signal-detection and dual-process models. Here we examine an entirely new recognition task, the judgment…

Three Tests and Three Corrections: Comment on Koen and Yonelinas (2010)

ERIC Educational Resources Information Center

Jang, Yoonhee; Mickes, Laura; Wixted, John T.

2012-01-01

The slope of the z-transformed receiver-operating characteristic (zROC) in recognition memory experiments is usually less than 1, which has long been interpreted to mean that the variance of the target distribution is greater than the variance of the lure distribution. The greater variance of the target distribution could arise because the…

Can histogram analysis of MR images predict aggressiveness in pancreatic neuroendocrine tumors?

PubMed

De Robertis, Riccardo; Maris, Bogdan; Cardobi, Nicolò; Tinazzi Martini, Paolo; Gobbo, Stefano; Capelli, Paola; Ortolani, Silvia; Cingarlini, Sara; Paiella, Salvatore; Landoni, Luca; Butturini, Giovanni; Regi, Paolo; Scarpa, Aldo; Tortora, Giampaolo; D'Onofrio, Mirko

2018-06-01

To evaluate MRI derived whole-tumour histogram analysis parameters in predicting pancreatic neuroendocrine neoplasm (panNEN) grade and aggressiveness. Pre-operative MR of 42 consecutive patients with panNEN >1 cm were retrospectively analysed. T1-/T2-weighted images and ADC maps were analysed. Histogram-derived parameters were compared to histopathological features using the Mann-Whitney U test. Diagnostic accuracy was assessed by ROC-AUC analysis; sensitivity and specificity were assessed for each histogram parameter. ADC entropy was significantly higher in G2-3 tumours with ROC-AUC 0.757; sensitivity and specificity were 83.3 % (95 % CI: 61.2-94.5) and 61.1 % (95 % CI: 36.1-81.7). ADC kurtosis was higher in panNENs with vascular involvement, nodal and hepatic metastases (p= .008, .021 and .008; ROC-AUC= 0.820, 0.709 and 0.820); sensitivity and specificity were: 85.7/74.3 % (95 % CI: 42-99.2 /56.4-86.9), 36.8/96.5 % (95 % CI: 17.2-61.4 /76-99.8) and 100/62.8 % (95 % CI: 56.1-100/44.9-78.1). No significant differences between groups were found for other histogram-derived parameters (p >.05). Whole-tumour histogram analysis of ADC maps may be helpful in predicting tumour grade, vascular involvement, nodal and liver metastases in panNENs. ADC entropy and ADC kurtosis are the most accurate parameters for identification of panNENs with malignant behaviour. • Whole-tumour ADC histogram analysis can predict aggressiveness in pancreatic neuroendocrine neoplasms. • ADC entropy and kurtosis are higher in aggressive tumours. • ADC histogram analysis can quantify tumour diffusion heterogeneity. • Non-invasive quantification of tumour heterogeneity can provide adjunctive information for prognostication.

Cognitive Styles in Mood Disorders: Discriminative Ability of Unipolar and Bipolar Cognitive Profiles

PubMed Central

Shapero, Benjamin G.; Stange, Jonathan P.; Goldstein, Kim E.; Black, Chelsea L.; Molz, Ashleigh R.; Hamlat, Elissa J.; Black, Shimrit K.; Boccia, Angelo S.; Abramson, Lyn Y.; Alloy, Lauren B.

2015-01-01

Although previous research has identified cognitive styles that distinguish individuals with bipolar disorder (BD), individuals with major depressive disorder (MDD), and individuals without mood disorders from one another, findings have been inconsistent. The current study included 381 participants classified into a BD group, a MDD group, and a no mood disorder group. To differentiate between these groups, this study evaluated cognitive styles with a battery of traditional and more recently-developed measures. Receiver operating characteristics (ROC) analyses were used to determine the discriminate ability of variables with significant between group differences. Results supported that BD and MDD may be characterized by distinct cognitive styles. Given work showing that interventions for MDD may not be effective at treating BD, it is important to directly compare individuals with these disorders. By clarifying the overlapping and divergent cognitive styles characterizing BD and MDD, research can not only improve diagnostic validity, but also provide more efficacious and effective interventions. PMID:25893033

Inattention symptoms and the diagnosis of comorbid attention-deficit/hyperactivity disorder among youth with generalized anxiety disorder.

PubMed

Elkins, R Meredith; Carpenter, Aubrey L; Pincus, Donna B; Comer, Jonathan S

2014-12-01

Generalized anxiety disorder (GAD) and attention-deficit/hyperactivity disorder (ADHD) commonly co-occur in childhood. Inattention symptoms can be hallmarks of both conditions, however assessment tools of inattention may not effectively distinguish between the two conditions. The present study used receiver operating characteristic (ROC) analyses to examine the high-end specificity of the Attention Problems Scale of the Child Behavior Checklist (CBCL) for detecting comorbid ADHD among youth with GAD (N=46). Results support the utility of the Attention Problems Scale for accurately distinguishing between the two groups (AUC=.84, SE=.06). Specifically, a cut score of 63 achieved the most favorable values across diagnostic utility indices; 74% of GAD youth with ADHD scored above this cutoff and 91% of GAD youth without ADHD scored below this cutoff. Findings provide support for the use of the CBCL Attention Problems Scale to supplement diagnostic interviews and identify inattention associated with ADHD among GAD youth. Copyright © 2014 Elsevier Ltd. All rights reserved.

An examination of the MASC Social Anxiety Scale in a non-referred sample of adolescents.

PubMed

Anderson, Emily R; Jordan, Judith A; Smith, Ashley J; Inderbitzen-Nolan, Heidi M

2009-12-01

Social phobia is prevalent during adolescence and is associated with negative outcomes. Two self-report instruments are empirically validated to specifically assess social phobia symptomatology in youth: the Social Phobia and Anxiety Inventory for Children and the Social Anxiety Scale for Adolescents. The Multidimensional Anxiety Scale for Children is a broad-band measure of anxiety containing a scale assessing the social phobia construct. The present study investigated the MASC Social Anxiety Scale in relation to other well-established measures of social phobia and depression in a non-referred sample of adolescents. Results support the convergent validity of the MASC Social Anxiety Scale and provide some support for its discriminant validity, suggesting its utility in the initial assessment of social phobia. Receiver Operating Characteristics (ROCs) calculated the sensitivity and specificity of the MASC Social Anxiety Scale. Binary logistic regression analyses determined the predictive utility of the MASC Social Anxiety Scale. Implications for assessment are discussed.

Development of short-form measures to assess four types of elder mistreatment: Findings from an evidence-based study of APS elder abuse substantiation decisions.

PubMed

Beach, Scott R; Liu, Pi-Ju; DeLiema, Marguerite; Iris, Madelyn; Howe, Melissa J K; Conrad, Kendon J

2017-01-01

Improving the standardization and efficiency of adult protective services (APS) investigations is a top priority in APS practice. Using data from the Elder Abuse Decision Support System (EADSS), we developed short-form measures of four types of elder abuse: financial, emotional/psychological, physical, and neglect. The EADSS data set contains 948 elder abuse cases (age 60+) with yes/no abuse substantiation decisions for each abuse type following a 30-day investigation. Item sensitivity/specificity analyses were conducted on long-form items with the substantiation decision for each abuse type as the criterion. Validity was further tested using receiver-operator characteristic (ROC) curve analysis, correlation with long forms and internal consistency. The four resulting short-form measures, containing 36 of the 82 original items, have validity similar to the original long forms. These short forms can be used to standardize and increase efficiency of APS investigations, and may also offer researchers new options for brief elder abuse assessments.

Development of short-form measures to assess four types of elder mistreatment: Findings from an evidence-based study of APS elder abuse substantiation decisions

PubMed Central

Beach, Scott R.; Liu, Pi-Ju; DeLiema, Marguerite; Iris, Madelyn; Howe, Melissa J.K.; Conrad, Kendon J.

2018-01-01

Improving the standardization and efficiency of adult protective services (APS) investigations is a top priority in APS practice. Using data from the Elder Abuse Decision Support System (EADSS), we developed short-form measures of four types of elder abuse: financial, emotional/psychological, physical, and neglect. The EADSS data set contains 948 elder abuse cases (age 60+) with yes/no abuse substantiation decisions for each abuse type following a 30-day investigation. Item sensitivity/specificity analyses were conducted on long-form items with the substantiation decision for each abuse type as the criterion. Validity was further tested using receiver–operator characteristic (ROC) curve analysis, correlation with long forms and internal consistency. The four resulting short-form measures, containing 36 of the 82 original items, have validity similar to the original long forms. These short forms can be used to standardize and increase efficiency of APS investigations, and may also offer researchers new options for brief elder abuse assessments. PMID:28590799

Pediatric ocular trauma score as a prognostic tool in the management of pediatric traumatic cataracts.

PubMed

Shah, Mehul A; Agrawal, Rupesh; Teoh, Ryan; Shah, Shreya M; Patel, Kashyap; Gupta, Satyam; Gosai, Siddharth

2017-05-01

To introduce and validate the pediatric ocular trauma score (POTS) - a mathematical model to predict visual outcome trauma in children with traumatic cataract METHODS: In this retrospective cohort study, medical records of consecutive children with traumatic cataracts aged 18 and below were retrieved and analysed. Data collected included age, gender, visual acuity, anterior segment and posterior segment findings, nature of surgery, treatment for amblyopia, follow-up, and final outcome was recorded on a precoded data information sheet. POTS was derived based on the ocular trauma score (OTS), adjusting for age of patient and location of the injury. Visual outcome was predicted using the OTS and the POTS and using receiver operating characteristic (ROC) curves. POTS predicted outcomes were more accurate compared to that of OTS (p = 0.014). POTS is a more sensitive and specific score with more accurate predicted outcomes compared to OTS, and is a viable tool to predict visual outcomes of pediatric ocular trauma with traumatic cataract.

Analysis of confidence level scores from an ROC study: comparison of three mammographic systems for detection of simulated calcifications

NASA Astrophysics Data System (ADS)

Lai, Chao-Jen; Shaw, Chris C.; Whitman, Gary J.; Yang, Wei T.; Dempsey, Peter J.

2005-04-01

The purpose of this study is to compare the detection performance of three different mammography systems: screen/film (SF) combination, a-Si/CsI flat-panel (FP-), and charge-coupled device (CCD-) based systems. A 5-cm thick 50% adipose/50% glandular breast tissue equivalent slab phantom was used to provide an uniform background. Calcium carbonate grains of three different size groups were used to simulate microcalcifications (MCs): 112-125, 125-140, and 140-150 μm overlapping with the uniform background. Calcification images were acquired with the three mammography systems. Digital images were printed on hardcopy films. All film images were displayed on a mammographic viewer and reviewed by 5 mammographers. The visibility of the MC was rated with a 5-point confidence rating scale for each detection task, including the negative controls. Scores were averaged over all readers for various detectors and size groups. Receiver operating characteristic (ROC) analysis was performed and the areas under the ROC curves (Az"s) were computed for various imaging conditions. The results shows that (1) the FP-based system performed significantly better than the SF and CCD-based systems for individual size groups using ROC analysis (2) the FP-based system also performed significantly better than the SF and CCD-based systems for individual size groups using averaged confidence scale, and (3) the results obtained from the Az"s were largely correlated with these from confidence level scores. However, the correlation varied slightly among different imaging conditions.

Basic concepts and development of an all-purpose computer interface for ROC/FROC observer study.

PubMed

Shiraishi, Junji; Fukuoka, Daisuke; Hara, Takeshi; Abe, Hiroyuki

2013-01-01

In this study, we initially investigated various aspects of requirements for a computer interface employed in receiver operating characteristic (ROC) and free-response ROC (FROC) observer studies which involve digital images and ratings obtained by observers (radiologists). Secondly, by taking into account these aspects, an all-purpose computer interface utilized for these observer performance studies was developed. Basically, the observer studies can be classified into three paradigms, such as one rating for one case without an identification of a signal location, one rating for one case with an identification of a signal location, and multiple ratings for one case with identification of signal locations. For these paradigms, display modes on the computer interface can be used for single/multiple views of a static image, continuous viewing with cascade images (i.e., CT, MRI), and dynamic viewing of movies (i.e., DSA, ultrasound). Various functions on these display modes, which include windowing (contrast/level), magnifications, and annotations, are needed to be selected by an experimenter corresponding to the purpose of the research. In addition, the rules of judgment for distinguishing between true positives and false positives are an important factor for estimating diagnostic accuracy in an observer study. We developed a computer interface which runs on a Windows operating system by taking into account all aspects required for various observer studies. This computer interface requires experimenters to have sufficient knowledge about ROC/FROC observer studies, but allows its use for any purpose of the observer studies. This computer interface will be distributed publicly in the near future.

Effect of Edge-Preserving Adaptive Image Filter on Low-Contrast Detectability in CT Systems: Application of ROC Analysis

PubMed Central

Okumura, Miwa; Ota, Takamasa; Kainuma, Kazuhisa; Sayre, James W.; McNitt-Gray, Michael; Katada, Kazuhiro

2008-01-01

Objective. For the multislice CT (MSCT) systems with a larger number of detector rows, it is essential to employ dose-reduction techniques. As reported in previous studies, edge-preserving adaptive image filters, which selectively eliminate only the noise elements that are increased when the radiation dose is reduced without affecting the sharpness of images, have been developed. In the present study, we employed receiver operating characteristic (ROC) analysis to assess the effects of the quantum denoising system (QDS), which is an edge-preserving adaptive filter that we have developed, on low-contrast resolution, and to evaluate to what degree the radiation dose can be reduced while maintaining acceptable low-contrast resolution. Materials and Methods. The low-contrast phantoms (Catphan 412) were scanned at various tube current settings, and ROC analysis was then performed for the groups of images obtained with/without the use of QDS at each tube current to determine whether or not a target could be identified. The tube current settings for which the area under the ROC curve (Az value) was approximately 0.7 were determined for both groups of images with/without the use of QDS. Then, the radiation dose reduction ratio when QDS was used was calculated by converting the determined tube current to the radiation dose. Results. The use of the QDS edge-preserving adaptive image filter allowed the radiation dose to be reduced by up to 38%. Conclusion. The QDS was found to be useful for reducing the radiation dose without affecting the low-contrast resolution in MSCT studies. PMID:19043565

The Impact of Magnetic Resonance Imaging on Prediction of Extraprostatic Extension and Prostatectomy Outcome in Patients with Low-, Intermediate- and High-Risk Prostate Cancer: Try to Find a Standard.

PubMed

Radtke, Jan Philipp; Hadaschik, Boris A; Wolf, Maya B; Freitag, Martin T; Schwab, Constantin; Alt, Celine; Roth, Wilfried; Duensing, Stefan; Pahernik, Sascha A; Roethke, Matthias C; Schlemmer, Heinz-Peter; Hohenfellner, Markus; Teber, Dogu

2015-12-01

To investigate the value of multiparametric magnetic resonance imaging (mpMRI) and to predict extracapsular extension (ECE), seminal vesicle (SV) infiltration, and a negative surgical margin (SM) status at radical prostatectomy (RP) for different prostate cancer (PC) risk groups. In the study, 805 men underwent 3 tesla mpMRI without endorectal coil before MRI/transrectal ultrasonography-fusion guided prostate biopsy. MRIs were analyzed using the prostate imaging reporting and data system. The cohort was classified into risk groups according to National Comprehensive Cancer Network (NCCN) criteria. Of 132 men who subsequently underwent RP, pathologic stage and SM status at RP were used as reference. Retrospectively, we investigated a European Society of Urogenital Radiology (ESUR) score for ECE and SV-infiltration. Statistical analyses included regression analyses, receiver operating characteristics (ROC), and Youden Index to assess an ESUR-score cutoff. Area under the curve in ROC curve analyses was 0.82 for ESUR-ECE score to detect pT(3a)-disease and 0.77 for ESUR-SV score for pT(3b). Using a cutoff of 4 for ECE and of 2 for SV, the positive predictive value of the ECE-score for harboring pT(3) was 50.0%, 90.0%, and 88.8% for the low-, intermediate- and high-risk cohort. Retrospectively, the use of the ESUR-ECE score preoperatively would have changed the initial surgical plan, according to NCCN criteria, in 31.1% of patients. In the high-risk subgroup, 9/35 (25.7%) patients were correctly assessed as not harboring pT(3) by imaging (ECE score <4), and would have allowed secure robot-assisted radical prostatectomy and nerve-sparing surgery (NSS). When T3 suspicion on preoperative MRI would be taken into account, intraoperative frozen-sections (IFS) might avoid positive SM in 12/18 high-risk patients and an oncologic secure NSS in 8/20 intermediate-risk patients. Prediction of pT(3) disease is crucial to plan NSS and to achieve negative SM in RP. Standardized ECE scoring on mpMRI is an independent predictor of pT(3) and may help to plan RP with oncologic security, even in high-risk patients. In addition, it allows more accurate selection of a subgroup of patients for systematic and MRI-guided IFS.

Identification of Warthin tumor: magnetic resonance imaging versus salivary scintigraphy with technetium-99m pertechnetate.

PubMed

Motoori, Ken; Ueda, Takuya; Uchida, Yoshitaka; Chazono, Hideaki; Suzuki, Homare; Ito, Hisao

2005-01-01

The aim of this study was to evaluate the accuracy of technetium-99m (Tc-99m) pertechnetate scintigraphy and magnetic resonance (MR) imaging in the diagnosis of Warthin tumor. Sixteen cases of Warthin tumor and 17 cases of non-Warthin tumor were examined by Tc-99m pertechnetate scintigraphy with lemon juice stimulation and MR imaging, including T1-weighted, T2-weighted, short inversion time inversion recovery, diffusion-weighted, and contrast-enhanced dynamic images. We used the receiver operating characteristic (ROC) curve to evaluate diagnostic accuracy. The mean area under the ROC curves of MR imaging in the diagnosis of Warthin tumor (0.97) was higher than that of Tc-99m pertechnetate scintigraphy (0.88). Magnetic resonance imaging is more useful in the evaluation of Warthin tumor than Tc-99m pertechnetate scintigraphy.

Spatiotemporal correlation of optical coherence tomography in-vivo images of rabbit airway for the diagnosis of edema

NASA Astrophysics Data System (ADS)

Kang, DongYel; Wang, Alex; Volgger, Veronika; Chen, Zhongping; Wong, Brian J. F.

2015-07-01

Detection of an early stage of subglottic edema is vital for airway management and prevention of stenosis, a life-threatening condition in critically ill neonates. As an observer for the task of diagnosing edema in vivo, we investigated spatiotemporal correlation (STC) of full-range optical coherence tomography (OCT) images acquired in the rabbit airway with experimentally simulated edema. Operating the STC observer on OCT images generates STC coefficients as test statistics for the statistical decision task. Resulting from this, the receiver operating characteristic (ROC) curves for the diagnosis of airway edema with full-range OCT in-vivo images were extracted and areas under ROC curves were calculated. These statistically quantified results demonstrated the potential clinical feasibility of the STC method as a means to identify early airway edema.

Comparison of radiologist performance with photon-counting full-field digital mammography to conventional full-field digital mammography.

PubMed

Cole, Elodia B; Toledano, Alicia Y; Lundqvist, Mats; Pisano, Etta D

2012-08-01

The purpose of this study was to assess the performance of a MicroDose photon-counting full-field digital mammography (PCM) system in comparison to full-field digital mammography (FFDM) for area under the receiver-operating characteristic (ROC) curve (AUC), sensitivity, specificity, and feature analysis of standard-view mammography for women presenting for screening mammography, diagnostic mammography, or breast biopsy. A total of 133 women were enrolled in this study at two European medical centers, with 67 women who had a pre-existing 10-36 months FFDM enrolled prospectively into the study and 66 women who underwent breast biopsy and had screening PCM and diagnostic FFDM, including standard craniocaudal and mediolateral oblique views of the breast with the lesion, enrolled retrospectively. The case mix consisted of 49 cancers, 17 biopsy-benign cases, and 67 normal cases. Sixteen radiologists participated in the reader study and interpreted all 133 cases in both conditions, separated by washout period of ≥4 weeks. ROC curve and free-response ROC curve analyses were performed for noninferiority of PCM compared to FFDM using a noninferiority margin Δ value of 0.10. Feature analysis of the 66 cases with lesions was conducted with all 16 readers at the conclusion of the blinded reads. Mean glandular dose was recorded for all cases. The AUC for PCM was 0.947 (95% confidence interval [CI], 0.920-0.974) and for FFDM was 0.931 (95% CI, 0.898-0.964). Sensitivity per case for PCM was 0.936 (95% CI, 0.897-0.976) and for FFDM was 0.908 (95% CI, 0.856-0.960). Specificity per case for PCM was 0.764 (95% CI, 0.688-0.841) and for FFDM was 0.749 (95% CI, 0.668-0.830). Free-response ROC curve figures of merit were 0.920 (95% CI, 0.881-0.959) and 0.903 (95% CI, 0.858-0.948) for PCM and FFDM, respectively. Sensitivity per lesion was 0.903 (95% CI, 0.846-0.960) and 0.883 (95% CI, 0.823-0.944) for PCM and FFDM, respectively. The average false-positive marks per image of noncancer cases were 0.265 (95% CI, 0.171-0.359) and 0.281 (95% CI, 0.188-0.374) for PCM and FFDM, respectively. Noninferiority P values for AUC, sensitivity (per case and per lesion), specificity, and average false-positive marks per image were all statistically significant (P < .001). The noninferiority P value for free-response ROC was <.025, from the 95% CI for the difference. Feature analysis resulted in PCM being preferred to FFDM by the readers for ≥70% of the cases. The average mean glandular dose for PCM was 0.74 mGy (95% CI, 0.722-0.759 mGy) and for FFDM was 1.23 mGy (95% CI, 1.199-1.262 mGy). In this study, radiologist performance with PCM was not inferior to that with conventional FFDM at an average 40% lower mean glandular dose. Copyright © 2012 AUR. Published by Elsevier Inc. All rights reserved.

Differentiation between microcystin contaminated and uncontaminated fish by determination of unconjugated MCs using an ELISA anti-Adda test based on receiver-operating characteristic curves threshold values: application to Tinca tinca from natural ponds.

PubMed

Moreno, Isabel María; Herrador, M Ángeles; Atencio, Loyda; Puerto, María; González, A Gustavo; Cameán, Ana María

2011-02-01

The aim of this study was to evaluate whether the enzyme-linked immunosorbent assay (ELISA) anti-Adda technique could be used to monitor free microcystins (MCs) in biological samples from fish naturally exposed to toxic cyanobacteria by using receiver operating characteristic (ROC) curve software to establish an optimal cut-off value for MCs. The cut-off value determined by ROC curve analysis in tench (Tinca tinca) exposed to MCs under laboratory conditions by ROC curve analysis was 5.90-μg MCs/kg tissue dry weight (d.w.) with a sensitivity of 93.3%. This value was applied in fish samples from natural ponds (Extremadura, Spain) in order to asses its potential MCs bioaccumulation by classifying samples as either true positive (TP), false positive (FP), true negative (TN), or false negative (FN). In this work, it has been demonstrated that toxic cyanobacteria, mainly Microcystis aeruginosa, Aphanizomenon issatchenkoi, and Anabaena spiroides, were present in two of these ponds, Barruecos de Abajo (BDown) and Barruecos de Arriba (BUp). The MCs levels were detected in waters from both ponds with an anti-MC-LR ELISA immunoassay and were of similar values (between 3.8-6.5-μg MC-LR equivalent/L in BDown pond and 4.8-6.0-μg MC-LR equivalent/L in BUp). The MCs cut-off values were applied in livers from fish collected from these two ponds using the ELISA anti-Adda technique. A total of 83% of samples from BDown pond and only 42% from BUp were TP with values of free MCs higher than 8.8-μg MCs/kg tissue (d.w.). Copyright © 2009 Wiley Periodicals, Inc.

Impact of FIB-4 index on hepatocellular carcinoma incidence during nucleos(t)ide analogue therapy in patients with chronic hepatitis B: An analysis using time-dependent receiver operating characteristic.

PubMed

Tada, Toshifumi; Kumada, Takashi; Toyoda, Hidenori; Tsuji, Kunihiko; Hiraoka, Atsushi; Tanaka, Junko

2017-02-01

Nucleos(t)ide analogue (NA) therapy has been reported to reduce the risk of hepatocellular carcinoma (HCC) development in patients with chronic hepatitis B (CHB). However, even during NA therapy, development of HCC has been observed in patients with CHB. Therefore, we clarified the predictive power of clinical factors for HCC incidence using receiver operating characteristic (ROC) analysis that takes time dependence into account. A total of 539 patients with CHB treated with NAs were enrolled. Univariate, multivariate, and time-dependent ROC curves for clinical factors associated with the development of HCC were analyzed. Eighty-one patients developed HCC during the follow-up period (median duration, 5.9 years). α-fetoprotein (AFP) and FIB-4 index at 24 weeks from the initiation of treatment and sex were significantly associated with HCC incidence according to the log-rank test. Cox proportional hazards models including the covariates of sex, hepatitis B genotype, basal core promoter mutations, AFP at 24 weeks, and FIB-4 index at 24 weeks showed that FIB-4 index >2.65 (HR, 5.03; 95% CI, 3.06-8.26; P < 0.001) and male sex were independently associated with HCC incidence. In addition, time-dependent ROC analysis showed that compared with AFP at 24 weeks, FIB-4 index at 24 weeks had higher predictive power for HCC incidence throughout the follow-up period. Elevated FIB-4 index at 24 weeks in patients with CHB receiving NA therapy is a risk factor for developing HCC. The FIB-4 index is an excellent predictor of HCC development. © 2016 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Validation of the modified Ranson versus Glasgow score for pancreatitis in a Singaporean population.

PubMed

Tan, Yong Hui Alvin; Rafi, Shumaila; Tyebally Fang, Mirriam; Hwang, Stephen; Lim, Ee Wen; Ngu, James; Tan, Su-Ming

2017-09-01

The characteristics of patients with acute pancreatitis in multi-ethnic Singapore differ from that of the populations used in formulating the modified Ranson and Glasgow scores. The use of these scoring systems has not previously been validated in the Singaporean setting. This study aims to validate and compare the prognostic use of the modified Ranson and Glasgow scores, and to determine the superiority of one score over the other in predicting the outcome for acute pancreatitis in the Singaporean population. This is a 3-year retrospective study of patients diagnosed with acute pancreatitis at our centre. Patients with chronic pancreatitis, acute on chronic pancreatitis, iatrogenic pancreatitis, pancreatic cancer as well as those with incomplete Ranson or Glasgow scores were excluded from the study. Case notes and computer records were reviewed for local complications of pancreatitis and organ failure. Receiver operator characteristic (ROC) curves of the Ranson and Glasgow scores were plotted for the prediction of severity and mortality. Between January 2010 and December 2012, 230 cases were diagnosed with acute pancreatitis. A majority of the patients had mild pancreatitis (n = 194, 84.3%), and the overall 30-day mortality rate was 3.5% (n = 8). ROC of the Ranson and Glasgow scoring systems for mortality showed an area under curve (AUC) of 0.854 (P = 0.001) and 0.776 (P = 0.008), respectively. For severity, the AUC for the modified Ranson and Glasgow score was calculated to be 0.694 and 0.668, respectively. The ROC curves of Ranson and Glasgow scores for mortality are comparable with that published in earlier studies. In a Singaporean population, the Ranson score is more accurate in the prediction of mortality. However, both scoring systems are poor predictors for severity of acute pancreatitis. © 2015 Royal Australasian College of Surgeons.

Cumulative lactate and hospital mortality in ICU patients

PubMed Central

2013-01-01

Background Both hyperlactatemia and persistence of hyperlactatemia have been associated with bad outcome. We compared lactate and lactate-derived variables in outcome prediction. Methods Retrospective observational study. Case records from 2,251 consecutive intensive care unit (ICU) patients admitted between 2001 and 2007 were analyzed. Baseline characteristics, all lactate measurements, and in-hospital mortality were recorded. The time integral of arterial blood lactate levels above the upper normal threshold of 2.2 mmol/L (lactate-time-integral), maximum lactate (max-lactate), and time-to-first-normalization were calculated. Survivors and nonsurvivors were compared and receiver operating characteristic (ROC) analysis were applied. Results A total of 20,755 lactate measurements were analyzed. Data are srpehown as median [interquartile range]. In nonsurvivors (n = 405) lactate-time-integral (192 [0–1881] min·mmol/L) and time-to-first normalization (44.0 [0–427] min) were higher than in hospital survivors (n = 1846; 0 [0–134] min·mmol/L and 0 [0–75] min, respectively; all p < 0.001). Normalization of lactate <6 hours after ICU admission revealed better survival compared with normalization of lactate >6 hours (mortality 16.6% vs. 24.4%; p < 0.001). AUC of ROC curves to predict in-hospital mortality was the largest for max-lactate, whereas it was not different among all other lactate derived variables (all p > 0.05). The area under the ROC curves for admission lactate and lactate-time-integral was not different (p = 0.36). Conclusions Hyperlactatemia is associated with in-hospital mortality in a heterogeneous ICU population. In our patients, lactate peak values predicted in-hospital mortality equally well as lactate-time-integral of arterial blood lactate levels above the upper normal threshold. PMID:23446002

Combining viscoelasticity, diffusivity and volume of the hippocampus for the diagnosis of Alzheimer's disease based on magnetic resonance imaging.

PubMed

Gerischer, Lea M; Fehlner, Andreas; Köbe, Theresa; Prehn, Kristin; Antonenko, Daria; Grittner, Ulrike; Braun, Jürgen; Sack, Ingolf; Flöel, Agnes

2018-01-01

Dementia due to Alzheimer's Disease (AD) is a neurodegenerative disease for which treatment strategies at an early stage are of great clinical importance. So far, there is still a lack of non-invasive diagnostic tools to sensitively detect AD in early stages and to predict individual disease progression. Magnetic resonance elastography (MRE) of the brain may be a promising novel tool. In this proof-of-concept study, we investigated whether multifrequency-MRE (MMRE) can detect differences in hippocampal stiffness between patients with clinical diagnosis of dementia due to AD and healthy controls (HC). Further, we analyzed if the combination of three MRI-derived parameters, i.e., hippocampal stiffness, hippocampal volume and mean diffusivity (MD), improves diagnostic accuracy. Diagnostic criteria for probable dementia due to AD were in line with the NINCDS-ADRDA criteria and were verified through history-taking (patient and informant), neuropsychological testing, routine blood results and routine MRI to exclude other medical causes of a cognitive decline. 21 AD patients and 21 HC (median age 75 years) underwent MMRE and structural MRI, from which hippocampal volume and MD were calculated. From the MMRE-images maps of the magnitude | G* | and phase angle φ of the complex shear modulus were reconstructed using multifrequency inversion. Median values of | G* | and φ were extracted within three regions of interest (hippocampus, thalamus and whole brain white matter). To test the predictive value of the main outcome parameters, we performed receiver operating characteristic (ROC) curve analyses. Hippocampal stiffness (| G* |) and viscosity ( φ ) were significantly lower in the patient group (both p  < 0.001). ROC curve analyses showed an area under the curve (AUC) for |  G* | of 0.81 [95%CI 0.68-0.94]; with sensitivity 86%, specificity 67% for cutoff at | G* | = 980 Pa) and for φ an AUC of 0.79 [95%CI 0.66-0.93]. In comparison, the AUC of MD and hippocampal volume were 0.83 [95%CI 0.71-0.95] and 0.86 [95%CI 0.74-0.97], respectively. A combined ROC curve of | G* |, MD and hippocampal volume yielded a significantly improved AUC of 0.90 [95%CI 0.81-0.99]. In conclusion, we demonstrated reduced hippocampal stiffness and reduced hippocampal viscosity, as determined by MMRE, in patients with clinical diagnosis of dementia of the AD type. Diagnostic sensitivity was further improved by the combination with two other MRI-based hippocampal parameters. These findings motivate further investigation whether MMRE can detect decreased brain stiffness already in pre-dementia stages, and whether these changes predict cognitive decline.

A Nomogram to Predict Anastomotic Leakage in Open Rectal Surgery-Hope or Hype?

PubMed

Klose, Johannes; Tarantino, Ignazio; von Fournier, Armin; Stowitzki, Moritz J; Kulu, Yakup; Bruckner, Thomas; Volz, Claudia; Schmidt, Thomas; Schneider, Martin; Büchler, Markus W; Ulrich, Alexis

2018-05-18

Anastomotic leakage is the most dreaded complication after rectal resection and total mesorectal excision, leading to increased morbidity and mortality. Formation of a diverting ileostomy is generally performed to protect anastomotic healing. Identification of variables predicting anastomotic leakage might help to select patients who are under increased risk for the development of anastomotic leakage prior to surgery. The objective of this study was to assess the applicability of a nomogram as prognostic model for the occurrence of anastomotic leakage after rectal resection in a cohort of rectal cancer patients. Nine hundred seventy-two consecutive patients who underwent surgery for rectal cancer were retrospectively analyzed. Univariate and multivariable Cox regression analyses were used to determine independent risk factors associated with anastomotic leakage. Receiver operating characteristics (ROC) curve analysis was performed to calculate the sensitivity, specificity, and overall model correctness of a recently published nomogram and an adopted risk score based on the variables identified in this study as a predictive model. Male sex (p = 0.042), obesity (p = 0.017), smoking (p = 0.012), postoperative bleeding (p = 0.024), and total protein level ≤ 5.6 g/dl (p = 0.007) were identified as independent risk factors for anastomotic leakage. The investigated nomogram and the adopted risk score failed to reach relevant areas under the ROC curve greater than 0.700 for the prediction of anastomotic leakage. The proposed nomogram and the adopted risk score failed to reliably predict the occurrence of anastomotic leakage after rectal resection. Risk scores as prognostic models for the prediction of anastomotic leakage, independently of the study population, still need to be identified.

Reader performance in visual assessment of breast density using visual analogue scales: Are some readers more predictive of breast cancer?

NASA Astrophysics Data System (ADS)

Rayner, Millicent; Harkness, Elaine F.; Foden, Philip; Wilson, Mary; Gadde, Soujanya; Beetles, Ursula; Lim, Yit Y.; Jain, Anil; Bundred, Sally; Barr, Nicky; Evans, D. Gareth; Howell, Anthony; Maxwell, Anthony; Astley, Susan M.

2018-03-01

Mammographic breast density is one of the strongest risk factors for breast cancer, and is used in risk prediction and for deciding appropriate imaging strategies. In the Predicting Risk Of Cancer At Screening (PROCAS) study, percent density estimated by two readers on Visual Analogue Scales (VAS) has shown a strong relationship with breast cancer risk when assessed against automated methods. However, this method suffers from reader variability. This study aimed to assess the performance of PROCAS readers using VAS, and to identify those most predictive of breast cancer. We selected the seven readers who had estimated density on over 6,500 women including at least 100 cancer cases, analysing their performance using multivariable logistic regression and Receiver Operator Characteristic (ROC) analysis. All seven readers showed statistically significant odds ratios (OR) for cancer risk according to VAS score after adjusting for classical risk factors. The OR was greatest for reader 18 at 1.026 (95% Cl 1.018-1.034). Adjusted Area Under the ROC Curves (AUCs) were statistically significant for all readers, but greatest for reader 14 at 0.639. Further analysis of the VAS scores for these two readers showed reader 14 had higher sensitivity (78.0% versus 42.2%), whereas reader 18 had higher specificity (78.0% versus 46.0%). Our results demonstrate individual differences when assigning VAS scores; one better identified those with increased risk, whereas another better identified low risk individuals. However, despite their different strengths, both readers showed similar predictive abilities overall. Standardised training for VAS may improve reader variability and consistency of VAS scoring.

Who to handover: a case-control study of a novel scoring system to prioritise handover of internal medicine inpatients.

PubMed

Bittman, Jesse; Tam, Penny; Little, Chris; Khan, Nadia

2017-06-01

Handover of patients between care providers is a critical event in patient care. There is, however, little evidence to guide the handover process, including determining which patients to handover. Compare the ability of gestalt-based handover with two structured scores, the modified early warning score (MEWS) and our novel iHAND clinical decision support system, to predict which patients will be assessed by a physician overnight. This case-control study included 90 inpatients, comprising 32 patients assessed overnight (cases) and 58 patients not assessed overnight (controls) at a teaching hospital in British Columbia, Canada (May 2012). Gestalt, MEWS and iHAND scores were analysed against patients seen overnight using logistic regression and receiver-operating characteristic (ROC) curves. Neither current gestalt-based handover practice (odds ratio (OR) 1.50, 95% CI 0.89 to 3.83) nor MEWS (OR 0.96, 95% CI 0.75 to 1.24, area under the ROC curve (AUC) 0.61, 95% CI 0.49 to 0.73) were significantly associated with need to be seen overnight. The iHAND score was associated with need to be seen (OR 1.93, 95% CI 1.24 to 3.02, AUC 0.70, 95% CI 0.60 to 0.81). The iHAND score had moderate ability to predict which patients required assessment overnight, while MEWS score and current gestalt approach correlated poorly, suggesting the iHAND score may help prioritisation of patients likely to be seen overnight for handover. 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/.

Discovery of serum biomarkers predicting development of a subsequent depressive episode in social anxiety disorder.

PubMed

Gottschalk, M G; Cooper, J D; Chan, M K; Bot, M; Penninx, B W J H; Bahn, S

2015-08-01

Although social anxiety disorder (SAD) is strongly associated with the subsequent development of a depressive disorder (major depressive disorder or dysthymia), no underlying biological risk factors are known. We aimed to identify biomarkers which predict depressive episodes in SAD patients over a 2-year follow-up period. One hundred sixty-five multiplexed immunoassay analytes were investigated in blood serum of 143 SAD patients without co-morbid depressive disorders, recruited within the Netherlands Study of Depression and Anxiety (NESDA). Predictive performance of identified biomarkers, clinical variables and self-report inventories was assessed using receiver operating characteristics curves (ROC) and represented by the area under the ROC curve (AUC). Stepwise logistic regression resulted in the selection of four serum analytes (AXL receptor tyrosine kinase, vascular cell adhesion molecule 1, vitronectin, collagen IV) and four additional variables (Inventory of Depressive Symptomatology, Beck Anxiety Inventory somatic subscale, depressive disorder lifetime diagnosis, BMI) as optimal set of patient parameters. When combined, an AUC of 0.86 was achieved for the identification of SAD individuals who later developed a depressive disorder. Throughout our analyses, biomarkers yielded superior discriminative performance compared to clinical variables and self-report inventories alone. We report the discovery of a serum marker panel with good predictive performance to identify SAD individuals prone to develop subsequent depressive episodes in a naturalistic cohort design. Furthermore, we emphasise the importance to combine biological markers, clinical variables and self-report inventories for disease course predictions in psychiatry. Following replication in independent cohorts, validated biomarkers could help to identify SAD patients at risk of developing a depressive disorder, thus facilitating early intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

Jaw-opening force test to screen for Dysphagia: preliminary results.

PubMed

Hara, Koji; Tohara, Haruka; Wada, Satoko; Iida, Takatoshi; Ueda, Koichiro; Ansai, Toshihiro

2014-05-01

To assess the jaw-opening force test (JOFT) for dysphagia screening. Criterion standard. University dental hospital. Patients complaining of dysphagia (N=95) and with symptoms of dysphagia with chronic underlying causes (mean age ± SD, 79.3±9.61y; range, 50-94y; men: n=49; mean age ± SD, 77.03±9.81y; range, 50-94y; women: n=46; mean age ± SD, 75.42±9.73y; range, 51-93y) admitted for treatment between May 2011 and December 2012 were included. None. All patients were administered the JOFT and underwent fiberoptic endoscopic evaluation of swallowing (FEES). The mean jaw-opening strength was compared with aspiration (ASP) and pharyngeal residue observations of the FEES, which was used as the criterion standard. A receiver operating characteristic (ROC) curve analysis was performed. Forces of ≤3.2kg for men and ≤4kg for women were appropriate cutoff values for predicting ASP with a sensitivity and specificity of .57 and .79 for men and .93 and .52 for women, respectively. Based on the ROC analyses for predicting pharyngeal residue, forces of ≤5.3kg in men and ≤3.9kg in women were appropriate cutoff values, with a sensitivity and specificity of .80 and .88 for men and .83 and .81 for women, respectively. The JOFT could be a useful screening tool for predicting pharyngeal residue and could provide useful information to aid in the referral of patients for further diagnostic imaging testing. However, given its low sensitivity to ASP the JOFT should be paired with other screening tests that predict ASP. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Articular cartilage degeneration classification by means of high-frequency ultrasound.

PubMed

Männicke, N; Schöne, M; Oelze, M; Raum, K

2014-10-01

To date only single ultrasound parameters were regarded in statistical analyses to characterize osteoarthritic changes in articular cartilage and the potential benefit of using parameter combinations for characterization remains unclear. Therefore, the aim of this work was to utilize feature selection and classification of a Mankin subset score (i.e., cartilage surface and cell sub-scores) using ultrasound-based parameter pairs and investigate both classification accuracy and the sensitivity towards different degeneration stages. 40 punch biopsies of human cartilage were previously scanned ex vivo with a 40-MHz transducer. Ultrasound-based surface parameters, as well as backscatter and envelope statistics parameters were available. Logistic regression was performed with each unique US parameter pair as predictor and different degeneration stages as response variables. The best ultrasound-based parameter pair for each Mankin subset score value was assessed by highest classification accuracy and utilized in receiver operating characteristics (ROC) analysis. The classifications discriminating between early degenerations yielded area under the ROC curve (AUC) values of 0.94-0.99 (mean ± SD: 0.97 ± 0.03). In contrast, classifications among higher Mankin subset scores resulted in lower AUC values: 0.75-0.91 (mean ± SD: 0.84 ± 0.08). Variable sensitivities of the different ultrasound features were observed with respect to different degeneration stages. Our results strongly suggest that combinations of high-frequency ultrasound-based parameters exhibit potential to characterize different, particularly very early, degeneration stages of hyaline cartilage. Variable sensitivities towards different degeneration stages suggest that a concurrent estimation of multiple ultrasound-based parameters is diagnostically valuable. In-vivo application of the present findings is conceivable in both minimally invasive arthroscopic ultrasound and high-frequency transcutaneous ultrasound. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Renal Atrophy Secondary to Chemoradiotherapy of Abdominal Malignancies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Gary Y., E-mail: Gary.Yang@RoswellPark.or; May, Kilian Salerno; Iyer, Renuka V.

2010-10-01

Purpose: To identify factors predictive of renal atrophy after chemoradiotherapy of gastrointestinal malignancies. Methods and Materials: Patients who received chemotherapy and abdominal radiotherapy (RT) between 2002 and 2008 were identified for this study evaluating change in kidney size and function after RT. Imaging and biochemical data were obtained before and after RT in 6-month intervals. Kidney size was defined by craniocaudal measurement on CT images. The primarily irradiated kidney (PK) was defined as the kidney that received the greater mean kidney dose. Receiver operating characteristic (ROC) curves were generated to predict risk for renal atrophy. Results: Of 130 patients, medianmore » age was 64 years, and 51.5% were male. Most primary disease sites were pancreas and periampullary tumors (77.7%). Median follow-up was 9.4 months. Creatinine clearance declined 20.89%, and size of the PK decreased 4.67% 1 year after completion of chemoradiation. Compensatory hypertrophy of the non-PK was not seen. Percentage volumes of the PK receiving {>=}10 Gy (V{sub 10}), 15 Gy (V{sub 15}), and 20 Gy (V{sub 20}) were significantly associated with renal atrophy 1 year after RT (p = 0.0030, 0.0029, and 0.0028, respectively). Areas under the ROC curves for V{sub 10}, V{sub 15}, and V{sub 20} to predict >5% decrease in PK size were 0.760, 0.760, and 0.762, respectively. Conclusions: Significant detriments in PK size and renal function were seen after abdominal RT. The V{sub 10}, V{sub 15}, and V{sub 20} were predictive of risk for PK atrophy 1 year after RT. Analyses suggest the association of lower-dose renal irradiation with subsequent development of renal atrophy.« less

Lipid accumulation product and insulin resistance in Iranian PCOS prevalence study.

PubMed

Hosseinpanah, Farhad; Barzin, Maryam; Erfani, Hadi; Serahati, Sara; Ramezani Tehrani, Fahimeh; Azizi, Fereidoun

2014-07-01

To evaluate diagnostic accuracy of lipid accumulation product (LAP) index as a marker of insulin resistance in a community-based population with polycystic ovary syndrome (PCOS), compared with healthy women. Anthropometric measurements, biochemical parameters, LAP index and insulin resistance (IR) were compared in 134 PCOS subjects and 414 healthy women recruited from 1126 reproductive aged women (18-45 years), participants of the Iranian PCOS Prevalence Study. LAP was defined as [WC (cm)-58] ×TG (mmol/l)]. PCOS was diagnosed using the Rotterdam criteria, and IR was defined using the homeostatic model assessment IR. LAP, body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) were compared using the two-tailed Spearman rank correlation test and analysing the receiver operating characteristic (ROC) curves for IR. Among the PCOS subjects, the mean ± SD age, BMI, WC and WHR were 32·2 ± 7·7 years, 26·8 ± 5·8 kg/m(2) , 85·2 ± 13·2 cm and 0·80 ± 0·06, respectively, and the median (IQ25-75) of LAP index was 34·03 (17·8-66·3). There was significant correlation between HOMA-IR index and LAP in patients with PCOS (r = 0·41; P < 0·001). Also, ROC curves analysis revealed that the optimal cut-off value for LAP to define the presence of IR was 34·1 (sensitivity: 75%; specificity: 58%). LAP showed the highest area under curve (AUC) (P < 0·001). Among PCOS subjects, LAP index has the strongest diagnostic accuracy for detection of IR in comparison with BMI, WC and WHR. © 2013 John Wiley & Sons Ltd.

Can non‐clinical repolarization assays predict the results of clinical thorough QT studies? Results from a research consortium

PubMed Central

Park, Eunjung; Gintant, Gary A; Bi, Daoqin; Kozeli, Devi; Pettit, Syril D; Skinner, Matthew; Willard, James; Wisialowski, Todd; Koerner, John; Valentin, Jean‐Pierre

2018-01-01

Background and Purpose Translation of non‐clinical markers of delayed ventricular repolarization to clinical prolongation of the QT interval corrected for heart rate (QTc) (a biomarker for torsades de pointes proarrhythmia) remains an issue in drug discovery and regulatory evaluations. We retrospectively analysed 150 drug applications in a US Food and Drug Administration database to determine the utility of established non‐clinical in vitro IKr current human ether‐à‐go‐go‐related gene (hERG), action potential duration (APD) and in vivo (QTc) repolarization assays to detect and predict clinical QTc prolongation. Experimental Approach The predictive performance of three non‐clinical assays was compared with clinical thorough QT study outcomes based on free clinical plasma drug concentrations using sensitivity and specificity, receiver operating characteristic (ROC) curves, positive (PPVs) and negative predictive values (NPVs) and likelihood ratios (LRs). Key Results Non‐clinical assays demonstrated robust specificity (high true negative rate) but poor sensitivity (low true positive rate) for clinical QTc prolongation at low‐intermediate (1×–30×) clinical exposure multiples. The QTc assay provided the most robust PPVs and NPVs (ability to predict clinical QTc prolongation). ROC curves (overall test accuracy) and LRs (ability to influence post‐test probabilities) demonstrated overall marginal performance for hERG and QTc assays (best at 30× exposures), while the APD assay demonstrated minimal value. Conclusions and Implications The predictive value of hERG, APD and QTc assays varies, with drug concentrations strongly affecting translational performance. While useful in guiding preclinical candidates without clinical QT prolongation, hERG and QTc repolarization assays provide greater value compared with the APD assay. PMID:29181850

Comparison of the results of intradermal test reactivity and serum allergen-specific IgE measurement for Malassezia pachydermatis in atopic dogs.

PubMed

Oldenhoff, Willam E; Frank, Glenn R; DeBoer, Douglas J

2014-12-01

Malassezia pachydermatis is part of the normal flora of canine skin. Malassezia hypersensitivity is recognized as a trigger for clinical signs of atopic dermatitis (AD) in some dogs. Determinations of Malassezia hypersensitivity are often made with intradermal testing (IDT), which may have limited availability in a first-opinion veterinary practice. The purpose of this study was to compare immediate IDT reactivity to M. pachydermatis with results of an enzyme-linked immunosorbent assay (ELISA) designed to detect anti-Malassezia IgE. Eighty-four dogs with a clinical diagnosis of AD. Multi-allergen IDT was performed on all dogs. Serum testing for allergen-specific IgE against a panel of common environmental allergens and M. pachydermatis was performed by ELISA using the FcεRIα receptor fragment as a detection reagent, with results reported as adjusted optical density (OD). A receiver operating characteristic (ROC) curve was used to analyse the results of the two tests. The median adjusted OD of the anti-Malassezia IgE ELISA for dogs reactive and nonreactive to M. pachydermatis on IDT was 0.137 and 0.024, respectively. Analysis of the ROC curve suggested a cut-off point for the anti-Malassezia ELISA that yielded a sensitivity of 77.0% and a specificity of 89% relative to IDT results. Substantial agreement was demonstrated between IDT reactivity and anti-Malassezia IgE as detected by the FcεRIα receptor reagent. Although correlation with a clinical diagnosis of Malassezia dermatitis was not attempted in this study, the results indicate that the ELISA may be used to demonstrate the presence of immediate-type Malassezia hypersensitivity in dogs with AD. © 2014 ESVD and ACVD.

Pelvic floor morphometry: a predictor of success of pelvic floor muscle training for women with stress and mixed urinary incontinence.

PubMed

Dumoulin, Chantale; Tang, An; Pontbriand-Drolet, Stéphanie; Madill, Stephanie J; Morin, Mélanie

2017-08-01

The aim of this study was to determine if pelvic floor muscle (PFM) morphometry at baseline, as measured by MRI, can predict response to PFM training in women with stress or mixed urinary incontinence (UI). This study was a prospective quasi-experimental pre-test, post-test cohort study of women with UI, aged 60 years and older. All participants completed a baseline assessment of UI severity and impact, using the 72-h bladder diary and the Incontinence Impact Questionnaire. They underwent a pelvic MRI examination to assess the PFM anatomy. Women then participated in a 12-week PFM training program. Finally, they attended a post intervention assessment of UI severity and impact. The association between morphometry and PFM training response was assessed by univariate analysis, multivariate analysis, and receiver operating characteristic (ROC) curve analysis. The urethro-vesical junction height at rest, as measured by MRI before treatment, was associated with response to PFM training both on univariate (p ≤ 0.005) and multivariate analyses (p = 0.007). The area under the ROC curve was 0.82 (95% confidence interval [CI]: 0.67-0.96). Using a cut-off point of 11.4 mm, participants' response to PFM training was predicted with a sensitivity of 77% and a specificity of 83%. Incontinent women with a urethro-vesical junction height above this threshold were 35% more likely to respond to PFM training (OR 1.35; 95% CI: 1.08-1.67). In older women with UI, a urethro-vesical junction height at rest of at least 11.4 mm appears to be predictive of PFM training response.

Comparison of the Nosocomial Pneumonia Mortality Prediction (NPMP) model with standard mortality prediction tools.

PubMed

Srinivasan, M; Shetty, N; Gadekari, S; Thunga, G; Rao, K; Kunhikatta, V

2017-07-01

Severity or mortality prediction of nosocomial pneumonia could aid in the effective triage of patients and assisting physicians. To compare various severity assessment scoring systems for predicting intensive care unit (ICU) mortality in nosocomial pneumonia patients. A prospective cohort study was conducted in a tertiary care university-affiliated hospital in Manipal, India. One hundred patients with nosocomial pneumonia, admitted in the ICUs who developed pneumonia after >48h of admission, were included. The Nosocomial Pneumonia Mortality Prediction (NPMP) model, developed in our hospital, was compared with Acute Physiology and Chronic Health Evaluation II (APACHE II), Mortality Probability Model II (MPM 72  II), Simplified Acute Physiology Score II (SAPS II), Multiple Organ Dysfunction Score (MODS), Sequential Organ Failure Assessment (SOFA), Clinical Pulmonary Infection Score (CPIS), Ventilator-Associated Pneumonia Predisposition, Insult, Response, Organ dysfunction (VAP-PIRO). Data and clinical variables were collected on the day of pneumonia diagnosis. The outcome for the study was ICU mortality. The sensitivity and specificity of the various scoring systems was analysed by plotting receiver operating characteristic (ROC) curves and computing the area under the curve for each of the mortality predicting tools. NPMP, APACHE II, SAPS II, MPM 72  II, SOFA, and VAP-PIRO were found to have similar and acceptable discrimination power as assessed by the area under the ROC curve. The AUC values for the above scores ranged from 0.735 to 0.762. CPIS and MODS showed least discrimination. NPMP is a specific tool to predict mortality in nosocomial pneumonia and is comparable to other standard scores. Copyright © 2017 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Thrombospondin-2 predicts response to treatment with intravenous immunoglobulin in children with Kawasaki disease.

PubMed

Yang, Shuai; Song, Ruixia; Li, Xiaohui; Zhang, Ting; Fu, Jin; Cui, Xiaodai

2018-01-01

To investigate the predictive value of thrombospondin-2 (TSP-2) in assessing the response to intravenous immunoglobulin (IVIG) in children with acute Kawasaki disease (KD). This was a cohort study with controls. 71 children with KD were recruited as the case group, including IVIG non-responder (n=17) and IVIG responder (n=54), and healthy children (n=27) and febrile children (n=30) were used as control groups. ELISA was used to measure plasma TSP-2 and TSP-1 levels. The rank-sum test was used to compare groups of non-normally distributed data. Predictive value was evaluated through the receiver operating characteristic (ROC) curve. Compared with the control groups, the plasma TSP-2 levels in acute KD were significantly elevated (TSP-2: 31.00 (24.02, 39.28) vs 21.93 (17.00, 24.73) vs 16.23 (14.00, 19.64) ng/mL, P<0.001). The plasma TSP-2 level in the IVIG non-responder was significantly higher than the responder group (37.58 (31.86, 43.98) vs 27.84 (21.88, 33.48) ng/mL, P=0.002). When using an ROC curve to analyse the predictive effect of TSP-2 on non-responsiveness to IVIG treatment, the area under the curve was 0.752 (0.630, 0.875) (P=0.002). When the cut-off value for TSP-2 was 31.50 ng/mL, the sensitivity was 82.35%, the specificity was 64.81%. The plasma TSP-2 level was elevated in acute KD and it might be a novel predictor for IVIG resistance, which could help guide clinicians to choose individualised initial therapeutic regimens.

The Italian version of the 92-item Prodromal Questionnaire: Concurrent validity with the SIPS and factor analysis in a sample of 258 outpatients aged 11-36years.

PubMed

Kotzalidis, Georgios D; Solfanelli, Andrea; Piacentino, Daria; Savoja, Valeria; Fiori Nastro, Paolo; Curto, Martina; Lindau, Juliana Fortes; Masillo, Alice; Brandizzi, Martina; Fagioli, Francesca; Raballo, Andrea; Gebhardt, Eva; Preti, Antonio; D'Alema, Marco; Fucci, Maria Rosa; Miletto, Roberto; Andropoli, Daniela; Leccisi, Donato; Girardi, Paolo; Loewy, Rachel L; Schultze-Lutter, Frauke

2017-11-01

Current early screeners for psychosis-risk states have still to prove ability in identifying at-risk individuals. Among screeners, the 92-item Prodromal Questionnaire (PQ-92) is often used. We aimed to assess the validity of its Italian translation in a large Italian adolescent and young adult help-seeking sample. We included all individuals aged 12-36years seeking help at psychiatric mental health services in a large semirural Roman area (534,600 population) who accepted to participate. Participants completed the Italian version of the PQ-92 and were subsequently assessed with the Structured Interview of Prodromal/Psychosis-Risk Syndromes (SIPS). We examined diagnostic accuracy (sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios) and content, concurrent, and convergent validity between PQ-92 and SIPS using Cronbach's alpha, Cohen's kappa, and Spearman's rho, respectively. We tested the validity of adopted cut-offs through Receiver Operating Characteristic (ROC) curves plotted against SIPS diagnoses and the instrument's factor-structure through Principal Component Analysis. PQ-92 showed high internal consistency, acceptable diagnostic accuracy and concurrent validity, and excellent convergent validity. ROC analyses pointed to scores of 18 on the Positive subscale and 36 on the total PQ-92 as best cut-offs. The Scree-test identified a four-factor solution as fitting best. Psychometric properties of Italian PQ-92 were satisfactory. Optimal cut-offs were confirmed at ≥18 on the positive subscale, but at ≥36 on the total scale was able to identify more SIPS-positive cases. Copyright © 2017 Elsevier B.V. All rights reserved.

Efficient screening for COPD using three steps: a cross-sectional study in Mexico City.

PubMed

Franco-Marina, Francisco; Fernandez-Plata, Rosario; Torre-Bouscoulet, Luis; García-Sancho, Cecilia; Sanchez-Gallen, Elisa; Martinez, David; Perez-Padilla, Rogelio

2014-05-20

Underdiagnosis of chronic obstructive pulmonary disease (COPD) in primary care can be improved by a more efficient screening strategy. To evaluate a three-step method of screening for COPD consisting of an initial short questionnaire followed by measurement of forced expiratory volume in 1s/forced expiratory volume in 6s (FEV1/FEV6) using an inexpensive pocket spirometer in those with high risk, and diagnostic quality spirometry in those with a low FEV1/FEV6. We analysed two related Mexico City cross-sectional samples. The 2003 Mexico City PLATINO survey (n=542) was used to develop a short questionnaire to determine the risk of COPD and a 2010 survey (n=737) additionally used a pocket spirometer. The discriminatory power of the two instruments was assessed with receiver operator characteristic (ROC) curves using three COPD definitions. The developed COPD scale included two variables from a simple questionnaire and, in ROC analysis, an area under the curve (AUC) between 0.64 and 0.77 was found to detect COPD. The pocket spirometer had an AUC between 0.85 and 0.88 to detect COPD. Using the COPD scale as a first screening step excluded 35-48% of the total population from further testing at the cost of not detecting 8-18% of those with COPD. Using the pocket spirometer and sending those with a FEV1/FEV6<0.80 for diagnostic quality spirometry is very efficient, and substantially improved the positive predictive value at the cost of not detecting one-third of COPD cases. A three-step screening strategy for COPD substantially reduces the need for spirometry testing when only a COPD scale is used for screening.

Risk factors for radiation pneumonitis after stereotactic radiation therapy for lung tumours: clinical usefulness of the planning target volume to total lung volume ratio.

PubMed

Ueyama, Tomoko; Arimura, Takeshi; Takumi, Koji; Nakamura, Fumihiko; Higashi, Ryutaro; Ito, Soichiro; Fukukura, Yoshihiko; Umanodan, Tomokazu; Nakajo, Masanori; Koriyama, Chihaya; Yoshiura, Takashi

2018-06-01

To identify risk factors for symptomatic radiation pneumonitis (RP) after stereotactic radiation therapy (SRT) for lung tumours. We retrospectively evaluated 68 lung tumours in 63 patients treated with SRT between 2011 and 2015. RP was graded according to the National Cancer Institute-Common Terminology Criteria for Adverse Events version 4.0. SRT was delivered at 7.0-12.0 Gy per each fraction, once daily, to a total of 48-64 Gy (median, 50 Gy). Univariate analysis was performed to assess patient- and treatment-related factors, including age, sex, smoking index (SI), pulmonary function, tumour location, serum Krebs von den Lungen-6 value (KL-6), dose-volume metrics (V5, V10, V20, V30, V40 and VS5), homogeneity index of the planning target volume (PTV), PTV dose, mean lung dose (MLD), contralateral MLD and V2, PTV volume, lung volume and the PTV/lung volume ratio (PTV/Lung). Performance of PTV/Lung in predicting symptomatic RP was also analysed using receiver operating characteristic (ROC) analysis. The median follow-up period was 21 months. 10 of 63 patients (15.9%) developed symptomatic RP after SRT. On univariate analysis, V10, V20, PTV volume and PTV/Lung were significantly associated with occurrence of RP  ≥Grade 2. ROC curves indicated that symptomatic RP could be predicted using PTV/Lung [area under curve (AUC): 0.88, confidence interval (CI: 0.78-0.95), cut-off value: 1.09, sensitivity: 90.0% and specificity: 72.4%]. PTV/Lung is a good predictor of symptomatic RP after SRT. Advances in knowledge: The cases with high PTV/Lung should be carefully monitored with caution for the occurrence of RP after SRT.

Clinical utility of EMSE and STESS in predicting hospital mortality for status epilepticus.

PubMed

Zhang, Yu; Chen, Deng; Xu, Da; Tan, Ge; Liu, Ling

2018-05-25

To explore the applicability of the epidemiology-based mortality score in status epilepticus (EMSE) and the status epilepticus severity score (STESS) in predicting hospital mortality in patients with status epilepticus (SE) in western China. Furthermore, we sought to compare the abilities of the two scales to predict mortality from convulsive status epilepticus (CSE) and non-convulsive status epilepticus (NCSE). Patients with epilepsy (n = 253) were recruited from the West China Hospital of Sichuan University from January 2012 to January 2016. The EMSE and STESS for all patients were calculated immediately after admission. The main outcome was in-hospital death. The predicted values were analysed using SPSS 22.0 receiver operating characteristic (ROC) curves. Of the 253 patients with SE who were included in the study, 39 (15.4%) died in the hospital. Using STESS ≥4 points to predict SE mortality, the area under the ROC curve (AUC) was 0.724 (P < 0.05). Using EMSE ≥79 points, the AUC was 0.776 (P < 0.05). To predict mortality in NCSE, STESS ≥2 points was used and resulted in an AUC of 0.632 (P > 0.05), while EMSE ≥90 points gave an AUC of 0.666 (P > 0.05). The hospital mortality rate from SE in this study was 15.4%. Those with STESS ≥4 points or EMSE ≥79 points had higher rates of SE mortality. Both STESS and EMSE are less useful predicting in-hospital mortality in NCSE compared to CSE. Furthermore, the EMSE has some advantages over the STESS. Copyright © 2018 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Lower Quarter Y-Balance Test Scores and Lower Extremity Injury in NCAA Division I Athletes.

PubMed

Lai, Wilson C; Wang, Dean; Chen, James B; Vail, Jeremy; Rugg, Caitlin M; Hame, Sharon L

2017-08-01

Functional movement tests that are predictive of injury risk in National Collegiate Athletic Association (NCAA) athletes are useful tools for sports medicine professionals. The Lower Quarter Y-Balance Test (YBT-LQ) measures single-leg balance and reach distances in 3 directions. To assess whether the YBT-LQ predicts the laterality and risk of sports-related lower extremity (LE) injury in NCAA athletes. Case-control study; Level of evidence, 3. The YBT-LQ was administered to 294 NCAA Division I athletes from 21 sports during preparticipation physical examinations at a single institution. Athletes were followed prospectively over the course of the corresponding season. Correlation analysis was performed between the laterality of reach asymmetry and composite scores (CS) versus the laterality of injury. Receiver operating characteristic (ROC) analysis was used to determine the optimal asymmetry cutoff score for YBT-LQ. A multivariate regression analysis adjusting for sex, sport type, body mass index, and history of prior LE surgery was performed to assess predictors of earlier and higher rates of injury. Neither the laterality of reach asymmetry nor the CS correlated with the laterality of injury. ROC analysis found optimal cutoff scores of 2, 9, and 3 cm for anterior, posteromedial, and posterolateral reach, respectively. All of these potential cutoff scores, along with a cutoff score of 4 cm used in the majority of prior studies, were associated with poor sensitivity and specificity. Furthermore, none of the asymmetric cutoff scores were associated with earlier or increased rate of injury in the multivariate analyses. YBT-LQ scores alone do not predict LE injury in this collegiate athlete population. Sports medicine professionals should be cautioned against using the YBT-LQ alone to screen for injury risk in collegiate athletes.

Developing the Thai Siriraj Psoriatic Arthritis Screening Tool and validating the Thai Psoriasis Epidemiology Screening Tool and the Early Arthritis for Psoriatic Patients questionnaire.

PubMed

Chiowchanwisawakit, Praveena; Wattanamongkolsil, Luksame; Srinonprasert, Varalak; Petcharat, Chonachan; Siriwanarangsun, Palanan; Katchamart, Wanruchada

2016-10-01

To validate the Thai language version of the Psoriasis Epidemiology Screening Tool (PEST) and the Early Arthritis for Psoriatic Patients Questionnaire (EARP), as well as also to develop a new tool for screening psoriatic arthritis (PsA) among psoriasis (Ps) patients. This was a cross-sectional study. Ps patients visiting the psoriasis clinic at Siriraj Hospital were recruited. They completed the EARP and PEST. Full musculoskeletal history, examination, and radiography were evaluated. PsA was diagnosed by a rheumatologist's evaluation and fulfillment of the classification criteria for psoriatic arthritis. Receiver operator characteristic (ROC) curves, sensitivity, and specificity were used to evaluate the performances of the tools. The Siriraj Psoriatic Arthritis Screening Tool (SiPAT) contained questions most relevant to peripheral arthritis, axial inflammation, and enthesitis, selected from multivariate analysis. Of a total of 159 patients, the prevalence of PsA was 78.6 %. The ROC curve analyses of Thai EARP, PEST, and SiPAT were 0.90 (95 % CI 0.84, 0.96), 0.85 (0.78, 0.92), and 0.89 (0.83, 0.95), respectively. The sensitivities of SiPAT, Thai EARP, and PEST were 91.0, 83.0, and 72.0 %, respectively, while the specificities were 69.0, 79.3, and 89.7 %, respectively. All screening questionnaires showed good diagnostic performances. SiPAT could be considered as a screening tool with its desirable properties: higher sensitivity and taking less time. Thai PEST and EARP could possibly be sequentially administered for people with a positive test from SiPAT to reduce the number of false positives.

Indoor versus outdoor time in preschoolers at child care.

PubMed

Tandon, Pooja S; Saelens, Brian E; Zhou, Chuan; Kerr, Jacqueline; Christakis, Dimitri A

2013-01-01

Being outdoors may have health benefits including being more physically active. Understanding the relationship between outdoor time and health is hampered by the difficulty of measuring outdoor time. To examine the accuracy and validity of light-sensor and GPS methods for quantifying outdoor time among those aged 3-5 years at child care. A total of 45 children (mean age 4.5 years, 64% boys) from five child care centers wore portable accelerometers with built-in light sensors and a separate GPS device around their waists during child care, providing 80,648 episodes (15 seconds each) for analysis. Direct observation (gold standard) of children being outdoors versus indoors was conducted for 2 days at each center. GPS signal-to-noise ratios, processed through the Personal Activity and Location Measurement System were used to define indoor versus outdoor locations. Receiver operating characteristic (ROC) analyses were used to determine thresholds for defining being indoors versus outdoors. Data were collected in Fall 2011, analyzed in 2012. Mean observed outdoor time was 63 [±44; range: 18-152] minutes/day. Mean light-sensor levels were significantly higher outdoors. The area under the ROC curve for location based on light sensor for all weather conditions was 0.82 (range: 0.70 on partly cloudy days to 0.97 on sunny days); for GPS, it was 0.89. The light sensor had a sensitivity of 74% and specificity of 86%. GPS had a sensitivity of 82% and specificity of 88%. A light sensor and a GPS device both distinguish indoor from outdoor time for preschoolers with moderate to high levels of accuracy. These devices can increase the feasibility and lower the cost of measuring outdoor time in studies of preschool children. Copyright © 2013 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Value of amino-terminal pro B-natriuretic peptide in diagnosing Kawasaki disease.

PubMed

McNeal-Davidson, Ariane; Fournier, Anne; Spigelblatt, Linda; Saint-Cyr, Claire; Mir, Thomas S; Nir, Amiram; Dallaire, Frédéric; Cousineau, Jocelyne; Delvin, Edgard; Dahdah, Nagib

2012-10-01

The aim of the present study was to investigate the diagnostic value of the N-terminal B-type natriuretic peptide (NT-proBNP) in acute Kawasaki disease (KD) given that the clinical criteria and the current basic laboratory tests lack the necessary specificity for accurate diagnosis. Basic biological tests and serum NT-proBNP levels obtained from acute KD patients were compared to that of febrile controls. NT-proBNP was considered abnormal based on the following definitions: above a cut-off determined on receiver operator characteristic (ROC) analysis, above the upper limit for age, or above 2 SD calculated from healthy children. Analyses were also performed for KD cases with complete or incomplete criteria combined and separately. There were 81 patients and 49 controls aged 3.60 ± 2.77 versus 4.25 ± 3.88 years (P= 0.69). ROC analysis yielded significant area under the curve for NT-proBNP. The sensitivity, specificity, positive and negative predictive values were 70.4-88.9%, 69.4-91.8%, 82.8-93.4%, and 65.2-79.1%. The odds ratios based on NT-proBNP definitions varied between 18.13 (95% confidence interval [CI]: 7.21-45.57), 20.82 (95%CI: 8.18-53.0), and 26.71 (95%CI: 8.64-82.57; P < 0.001). Results were reproducible for cases with complete or incomplete criteria separately. NT-proBNP is a reliable marker for the diagnosis of KD. Prospective clinical studies with emphasis on NT-proBNP in a diagnostic algorithm are needed. © 2012 The Authors. Pediatrics International © 2012 Japan Pediatric Society.

Impact of the integration of proton magnetic resonance imaging spectroscopy to PI-RADS 2 for prediction of high grade and high stage prostate cancer.

PubMed

Leapman, Michael S; Wang, Zhen J; Behr, Spencer C; Kurhanewicz, John; Zagoria, Ronald J; Carroll, Peter R; Westphalen, Antonio C

2017-01-01

To compare the predictions of dominant Gleason pattern ≥ 4 or non-organ confined disease with Prostate Imaging Reporting and Data System (PI-RADS v2) with or without proton magnetic resonance spectroscopic imaging ( 1 H-MRSI). Thirty-nine men underwent 3-tesla endorectal multiparametric MRI including 1 H-MRSI and prostatectomy. Two radiologists assigned PI-RADS v2 and 1 H-MRSI scores to index lesions. Statistical analyses used logistic regressions, receiver operating characteristic (ROC) curves, and 2x2 tables for diagnostic accuracies. The sensitivity and specificity of 1 H-MRSI and PI-RADS v2 for high-grade prostate cancer (PCa) were 85.7% (57.1%) and 92.9% (100%), and 56% (68.0%) and 24.0% (24.0%). The sensitivity and specificity of 1 H-MRSI and PI-RADS v2 for extra-prostatic extension (EPE) were 64.0% (40%) and 20.0% (48%), and 50.0% (57.1%) and 71.4% (64.3%). The area under the ROC curves (AUC) for prediction of high-grade prostate cancer were 0.65 and 0.61 for PI-RADS v2 and 0.72 and 0.70 when combined with 1 H-MRSI (readers 1 and 2, p = 0.04 and 0.21). For prediction of EPE the AUC were 0.54 and 0.60 for PI-RADS v2 and 0.55 and 0.61 when combined with 1 H-MRSI ( p > 0.05). 1 H-MRSI might improve the discrimination of high-grade prostate cancer when combined to PI-RADS v2, particularly for PI-RADS v2 score 4 lesions, but it does not affect the prediction of EPE.

The role of IGF-1 and the distribution of body fat in decreasing the number of prostate rebiopsies.

PubMed

Morán, E; Martínez, M; Budía, A; Broseta, E; Cámara, R; Boronat, F

2017-03-01

To assess the usefulness of IGF-1 and internal organ fat measured by bioelectrical impedance audiometry to avoid rebiopsies in patients with persistently high prostate-specific antigen (PSA) levels. A prospective study was conducted with 92 patients who underwent prostate rebiopsy due to high PSA levels with negative results in the rectal examination and a lack of preneoplastic lesions. The patients previously had their IGF-1 levels measured and had undergone an impedance audiometry test using the abdominal Fat Analyser AB-140 TANITA system. We calculated the receiver operating characteristic (ROC) curves for the PSA levels, %PSA, internal organ fat and IGF-1 and PSA density. Twenty-five patients were diagnosed with prostate cancer. These patients had significantly higher PSA, PSAd and IGF-1 values and a tendency towards higher internal organ fat levels and lower %PSA readings (p=.001, p=.003, p=.001, p=.24 and P=0.28, respectively). The ROC curve showed an area under the curve for IGF-1 and PSA of .82 and .81, respectively. Using the cutoff points for 95% sensitivity and using the 3 criteria as an indication of rebiopsy, 74% of the biopsies would have been spared, leaving undiagnosed only 1 patient with clinically significant cancer -Gleason score>7 (4+3)-. The positive and negative predictive values for the set of variables were higher than for each one separately (PPV: 66/NPV: 63). The cost of both determinations was 82 euros. Our results suggest that measuring IGF-1 could significantly decrease the number of unnecessary rebiopsies in an inexpensive and safe manner. Copyright © 2016 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

Interpreting SF-12 mental component score: an investigation of its convergent validity with CESD-10.

PubMed

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.

Meta-analysis of oral water-soluble contrast agent in the management of adhesive small bowel obstruction.

PubMed

Abbas, S M; Bissett, I P; Parry, B R

2007-04-01

Adhesions are the leading cause of small bowel obstruction. Identification of patients who require surgery is difficult. This review analyses the role of Gastrografin as a diagnostic and therapeutic agent in the management of adhesive small bowel obstruction. A systematic search of Medline, Embase and Cochrane databases was performed to identify studies of the use of Gastrografin in adhesive small bowel obstruction. Studies that addressed the diagnostic role of water-soluble contrast agent were appraised, and data presented as sensitivity, specificity, and positive and negative likelihood ratios. Results were pooled and a summary receiver-operator characteristic (ROC) curve was constructed. A meta-analysis of the data from six therapeutic studies was performed using the Mantel-Haenszel test and both fixed- and random-effect models. The appearance of water-soluble contrast agent in the colon on an abdominal radiograph within 24 h of its administration predicted resolution of obstruction with a pooled sensitivity of 97 per cent and specificity of 96 per cent. The area under the summary ROC curve was 0.98. Water-soluble contrast agent did not reduce the need for surgical intervention (odds ratio 0.81, P = 0.300), but it did reduce the length of hospital stay for patients who did not require surgery compared with placebo (weighted mean difference--1.84 days; P < 0.001). Published data strongly support the use of water-soluble contrast medium as a predictive test for non-operative resolution of adhesive small bowel obstruction. Although Gastrografin does not reduce the need for operation, it appears to shorten the hospital stay for those who do not require surgery.

Anterior Chamber Angle Measurements Using Schwalbe's Line with High Resolution Fourier-Domain Optical Coherence Tomography

PubMed Central

Qin, Bing; Francis, Brian A.; Li, Yan; Tang, Maolong; Zhang, Xinbo; Jiang, Chunhui; Cleary, Catherine; Huang, David

2012-01-01

Purpose To use Fourier-domain optical coherence tomography (OCT) to measure the angle opening distance at Schwalbe's line (AOD-SL) and determine its value in anterior chamber angle assessment. Methods Horizontal scans of the nasal and temporal anterior chamber angles in glaucoma subjects were performed by 830 nm wavelength Fourier-domain OCT. Images were graded by two ophthalmologists who assessed the visibility of Schwalbe’s line (SL), anterior limbus (AL), scleral spur (SS), and angle recess (AR). AOD-SL was measured with computer calipers. SL was manually identified by the termination of the corneal endothelium. Gonioscopy was used to classify anterior chamber angles according to a modified Shaffer system. Spearman's rho analysis was performed to assess correlation between AOD-SL and modified Shaffer grade. A cut-off value of AOD-SL for diagnosing occludable angles (modified Shaffer grade ≤1) was determined by receiver operating characteristic (ROC) analyses. Results Thirty-five glaucoma subjects (65 eyes) were enrolled. SL, AL, AR, and SS were visible by OCT in 97.7%, 99.2%, 87.3%, and 80.8% of eyes, respectively. Nasal and temporal AOD-SLs were 322.6 ± 200.2 µm and 341.4 ± 197.4 µm, respectively. Correlation coefficients between AOD-SL and modified Shaffer grade were 0.80 (nasal) and 0.81 (temporal). The diagnostic cut-off value of AOD-SL for occludable angles was 290 µm. The areas under the ROC curve, sensitivity, specificity values were 0.90, 0.80, 0.87 (nasal) and 0.90, 0.85, 0.77 (temporal). Conclusions The measurement of AOD-SL by Fourier-domain OCT is highly correlated with gonioscopy and may be a useful noncontact method of assessing angle closure risk. PMID:22827999

Evaluation of glioblastomas and lymphomas with whole-brain CT perfusion: Comparison between a delay-invariant singular-value decomposition algorithm and a Patlak plot.

PubMed

Hiwatashi, Akio; Togao, Osamu; Yamashita, Koji; Kikuchi, Kazufumi; Yoshimoto, Koji; Mizoguchi, Masahiro; Suzuki, Satoshi O; Yoshiura, Takashi; Honda, Hiroshi

2016-07-01

Correction of contrast leakage is recommended when enhancing lesions during perfusion analysis. The purpose of this study was to assess the diagnostic performance of computed tomography perfusion (CTP) with a delay-invariant singular-value decomposition algorithm (SVD+) and a Patlak plot in differentiating glioblastomas from lymphomas. This prospective study included 17 adult patients (12 men and 5 women) with pathologically proven glioblastomas (n=10) and lymphomas (n=7). CTP data were analyzed using SVD+ and a Patlak plot. The relative tumor blood volume and flow compared to contralateral normal-appearing gray matter (rCBV and rCBF derived from SVD+, and rBV and rFlow derived from the Patlak plot) were used to differentiate between glioblastomas and lymphomas. The Mann-Whitney U test and receiver operating characteristic (ROC) analyses were used for statistical analysis. Glioblastomas showed significantly higher rFlow (3.05±0.49, mean±standard deviation) than lymphomas (1.56±0.53; P<0.05). There were no statistically significant differences between glioblastomas and lymphomas in rBV (2.52±1.57 vs. 1.03±0.51; P>0.05), rCBF (1.38±0.41 vs. 1.29±0.47; P>0.05), or rCBV (1.78±0.47 vs. 1.87±0.66; P>0.05). ROC analysis showed the best diagnostic performance with rFlow (Az=0.871), followed by rBV (Az=0.771), rCBF (Az=0.614), and rCBV (Az=0.529). CTP analysis with a Patlak plot was helpful in differentiating between glioblastomas and lymphomas, but CTP analysis with SVD+ was not. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Predicting Voice Disorder Status From Smoothed Measures of Cepstral Peak Prominence Using Praat and Analysis of Dysphonia in Speech and Voice (ADSV).

PubMed

Sauder, Cara; Bretl, Michelle; Eadie, Tanya

2017-09-01

The purposes of this study were to (1) determine and compare the diagnostic accuracy of a single acoustic measure, smoothed cepstral peak prominence (CPPS), to predict voice disorder status from connected speech samples using two software systems: Analysis of Dysphonia in Speech and Voice (ADSV) and Praat; and (2) to determine the relationship between measures of CPPS generated from these programs. This is a retrospective cross-sectional study. Measures of CPPS were obtained from connected speech recordings of 100 subjects with voice disorders and 70 nondysphonic subjects without vocal complaints using commercially available ADSV and freely downloadable Praat software programs. Logistic regression and receiver operating characteristic (ROC) analyses were used to evaluate and compare the diagnostic accuracy of CPPS measures. Relationships between CPPS measures from the programs were determined. Results showed acceptable overall accuracy rates (75% accuracy, ADSV; 82% accuracy, Praat) and area under the ROC curves (area under the curve [AUC] = 0.81, ADSV; AUC = 0.91, Praat) for predicting voice disorder status, with slight differences in sensitivity and specificity. CPPS measures derived from Praat were uniquely predictive of disorder status above and beyond CPPS measures from ADSV (χ 2 (1) = 40.71, P < 0.001). CPPS measures from both programs were significantly and highly correlated (r = 0.88, P < 0.001). A single acoustic measure of CPPS was highly predictive of voice disorder status using either program. Clinicians may consider using CPPS to complement clinical voice evaluation and screening protocols. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Intelligence test at preschool-age predicts reading difficulty among school-aged very low birth weight infants in Japan.

PubMed

Takeuchi, Akihito; Ogino, Tatsuya; Koeda, Tatsuya; Oka, Makio; Yorifuji, Takashi; Takayanagi, Toshimitsu; Sato, Kazuo; Sugino, Noriko; Bonno, Motoki; Nakamura, Makoto; Kageyama, Misao

2018-05-21

To elucidate whether the results of an intelligence test at preschool age are predictive of reading difficulty (RD) at school age among very low birth weight infants (VLBWI). Subjects were 48 Japanese children whose birth weight was <1500 g and who regularly visited a follow-up clinic. All subjects completed the Wechsler Intelligence Scale for Children-III (WISC-III) during the last grade of kindergarten, and four reading tasks during the second to fourth grade of elementary school. All participants had a full-scale intelligence quotient score of 85 or higher. Subjects with a standard deviation reading time score greater than 2.0 in two or more tasks were considered to have RD. We evaluated the associations between each WISC-III score and RD using logistic regression analyses. Furthermore, we performed receiver operating characteristic (ROC) analysis to determine a cutoff WISC-III score predictive of RD. In the mutually-adjusted model, the adjusted odds ratio per 1 score increase of freedom from distractibility (FD) was 0.832 (95% confidence interval: 0.720-0.962). In the ROC analysis, an FD score of <95.5 was chosen as the cutoff value for predicting RD (sensitivity, 0.77; specificity, 0.74). The present study indicated that a lower FD score at preschool age, which was associated with deficits in verbal working memory and attention, is a risk factor for RD at school age among Japanese VLBWI. Further investigation is desired to clarify the cognitive deficits underlying RD in Japanese-speaking preterm children, and to establish appropriate interventions for these children. Copyright © 2018 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Do cravings predict smoking cessation in smokers calling a national quit line: secondary analyses from a randomised trial for the utility of 'urges to smoke' measures.

PubMed

Taggar, Jaspal S; Lewis, Sarah; Docherty, Graeme; Bauld, Linda; McEwen, Andy; Coleman, Tim

2015-04-14

Single-item urges to smoke measures have been contemplated as important measures of nicotine dependence This study aimed to prospectively determine the relationships between measures of craving to smoke and smoking cessation, and compare their ability to predict cessation with the Heaviness of Smoking Index, an established measure of nicotine dependence. We conducted a secondary analysis of data from the randomised controlled PORTSSS trial. Measures of nicotine dependence, ascertained before making a quit attempt, were the HSI, frequency of urges to smoke (FUTS) and strength of urges to smoke (SUTS). Self-reported abstinence at six months after quitting was the primary outcome measure. Multivariate logistic regression and Receiver Operating Characteristic (ROC) analysis were used to assess associations and abilities of the nicotine dependence measures to predict smoking cessation. Of 2,535 participants, 53.5% were female; the median (Interquartile range) age was 38 (28-50) years. Both FUTS and HSI were inversely associated with abstinence six months after quitting; for each point increase in HSI score, participants were 16% less likely to have stopped smoking (OR 0.84, 95% C.I 0.78-0.89, p < 0.0001). Compared to participants with the lowest possible FUTS scores, those with greater scores had generally lower odds of cessation (p across frequency of urges categories=0.0026). SUTS was not associated with smoking cessation. ROC analysis suggested the HSI and FUTS had similar predictive validity for cessation. Higher FUTS and HSI scores were inversely associated with successful smoking cessation six months after quit attempts began and both had similar validity for predicting cessation.

Individual MRI and radiographic features of knee OA in subjects with unilateral knee pain: Health ABC study

PubMed Central

Javaid, MK; Kiran, A; Guermazi, A; Kwoh, K; Zaim, S; Carbone, L; Harris, T.; McCulloch, C.E.; Arden, NK; Lane, NE; Felson, D; Nevitt, M

2012-01-01

Strong associations between radiographic features of knee OA and pain have been demonstrated in persons with unilateral knee symptoms. Our objectives were to compare radiographic with MRI features of knee OA and assess the discrimination between painful and non-painful knees in persons with unilateral symptoms. 283 individuals with unilateral knee pain aged 71 to 80 years from Health ABC, a study of weight-related diseases and mobility, had bilateral knee radiographs, read for KL grade and individual radiographic features, and 1.5T MRIs, read using WORMS. The association of structural features with pain was assessed using a within-person case/control design and conditional logistic regression. Receiver operator characteristics (ROC) were then used to test the discriminatory performance of structural features. In conditional logistic analyses, knee pain was significantly associated with both radiographic (any JSN grade >=1: OR 3.20 (1.79 – 5.71) and MRI (any cartilage defect:>=2: OR 3.67 (1.49 – 9.04)) features. However, most subjects had MR detected osteophytes, cartilage and bone marrow lesions in both knees and no individual structural feature discriminated well between painful and non-painful knees using ROC. The best performing MRI feature (synovitis/effusion) was not significantly more informative than KL grade >=2 (p=0.42). In persons with unilateral knee pain, MR and radiographic features were associated with knee pain confirming an important role in the etiology of pain. However, no single MRI or radiographic finding performed well in discriminating painful from non-painful knees. Further work is needed to examine how structural and non-structural factors influence knee pain. PMID:22736267

Validation study of Polar V800 accelerometer.

PubMed

Hernández-Vicente, Adrián; Santos-Lozano, Alejandro; De Cocker, Katrien; Garatachea, Nuria

2016-08-01

The correct quantification of physical activity (PA) and energy expenditure (EE) in daily life is an important target for researchers and professionals. The objective of this paper is to study the validity of the Polar V800 for the quantification of PA and the estimation of EE against the ActiGraph (ActiTrainer) in healthy young adults. Eighteen Caucasian active people (50% women) aged between 19-23 years wore an ActiTrainer on the right hip and a Polar V800 on the preferred wrist during 7 days. Paired samples t-tests were used to analyze differences in outcomes between devices, and Pearson's correlation coefficients to examine the correlation between outcomes. The agreement was studied using the Bland-Altman method. Also, the association between the difference and the magnitude of the measurement (heteroscedasticity) was examined. Sensitivity, specificity and area under the receiver operating characteristic curve (ROC-AUC value) were calculated to evaluate the ability of the devices to accurately define a person who fulfills the recommendation of 10,000 daily steps. The devices significantly differed from each other on all outcomes (P<0.05), except for Polar V800's alerts vs. ActiTrainer's 1 hour sedentary bouts (P=0.595) and Polar V800's walking time vs. ActiTrainer's lifestyle time (P=0.484). Heteroscedasticity analyses were significant for all outcomes, except for Kcal and sitting time. The ROC-AUC value was fair (0.781±0.048) and the sensitivity and specificity was 98% and 58%, respectively. The Polar V800 accelerometer has a comparable validity to the accelerometer in free-living conditions, regarding "1 hour sedentary bouts" and "V800's walking time vs. ActiTrainer's lifestyle time" in young adults.

How valuable is P-wave dispersion in the determination of carboxyhemoglobin levels?

PubMed

Sener, M T; Anci, Y; Kalkan, K; Kir, M Z; Emet, M

2014-05-01

To determine whether or not wave/interval dispersions in electrocardiography (ECG) are increased, and to define whether wave and interval dispersions are correlated with carboxyhemoglobin (COHb) levels. ECG, complete blood count, and biochemical parameters were taken from 87 patients with carbon monoxide (CO) poisoning as well as 90 control patients with similar age, gender, and body mass index distribution. COHb levels were recorded in CO-poisoning patients. The COHb levels and the relationships with ECG parameters were studied. Pmax, Pmin, Pd, PRmax, PRmin, PRd, QTmax, QTmin, QTd, cQTmax, cQTmin, cQTd, Tmax, Tmin, and Td in ECG were higher in intoxicated patients than the control group (p < 0.05 for all). Pearson's correlation analyses showed moderately significant positive correlations between COHb level and Pmax (r = 0.224; p = 0.037) and Pd (r = 0.222; p = 0.039). The receiver-operator characteristic (ROC) curve showed that a Pd value of 38 ms determined by ECG separates patients with a COHb ≥ 20% with area under the ROC curve of 0.78 (95%CI = 0.71-0.83), a sensitivity of 67.9% (95%CI = 59.4-75.6), a specificity of 95% (95%CI = 83.0-99.2], a positive predictive value of 97.9% (95%CI = 92.5-99.7), and a negative predictive value of 46.3% (95%CI = 35.3-57.7.) A significant increase in wave/interval dispersions in the ECG of CO-poisoning patients compared with controls may show that not only a part is affected but both atrium and the ventricles as a whole are affected by hypoxic ischemia. When COHb levels of the patients are unavailable, P dispersion on ECG may show CO poisoning level of the patient.

MRI differentiation of low-grade from high-grade appendicular chondrosarcoma.

PubMed

Douis, Hassan; Singh, Leanne; Saifuddin, Asif

2014-01-01

To identify magnetic resonance imaging (MRI) features which differentiate low-grade chondral lesions (atypical cartilaginous tumours/grade 1 chondrosarcoma) from high-grade chondrosarcomas (grade 2, grade 3 and dedifferentiated chondrosarcoma) of the major long bones. We identified all patients treated for central atypical cartilaginous tumours and central chondrosarcoma of major long bones (humerus, femur, tibia) over a 13-year period. The MRI studies were assessed for the following features: bone marrow oedema, soft tissue oedema, bone expansion, cortical thickening, cortical destruction, active periostitis, soft tissue mass and tumour length. The MRI-features were compared with the histopathological tumour grading using univariate, multivariate logistic regression and receiver operating characteristic curve (ROC) analyses. One hundred and seventy-nine tumours were included in this retrospective study. There were 28 atypical cartilaginous tumours, 79 grade 1 chondrosarcomas, 36 grade 2 chondrosarcomas, 13 grade 3 chondrosarcomas and 23 dedifferentiated chondrosarcomas. Multivariate analysis demonstrated that bone expansion (P = 0.001), active periostitis (P = 0.001), soft tissue mass (P < 0.001) and tumour length (P < 0.001) were statistically significant differentiating factors between low-grade and high-grade chondral lesions with an area under the ROC curve of 0.956. On MRI, bone expansion, active periostitis, soft tissue mass and tumour length can reliably differentiate high-grade chondrosarcomas from low-grade chondral lesions of the major long bones. • Accurate differentiation of low-grade from high-grade chondrosarcomas is essential before surgery • MRI can reliably differentiate high-grade from low-grade chondrosarcomas of long bone • Differentiating features are bone expansion, periostitis, soft tissue mass and tumour length • Presence of these four MRI features demonstrated a diagnostic accuracy (AUC) of 95.6 % • The findings may result in more accurate diagnosis before definitive surgery.

Aneurysms of the anterior and posterior cerebral circulation: comparison of the morphometric features.

PubMed

Tykocki, Tomasz; Kostkiewicz, Bogusław

2014-09-01

Intracranial aneurysms (IAs) located in the posterior circulation are considered to have higher annual bleed rates than those in the anterior circulation. The aim of the study was to compare the morphometric factors differentiating between IAs located in the anterior and posterior cerebral circulation. A total number of 254 IAs diagnosed between 2009 and 2012 were retrospectively analyzed. All patients qualified for diagnostic, three-dimensional rotational angiography. IAs were assigned to either the anterior or posterior cerebral circulation subsets for the analysis. Means were compared with a t-test. The univariate and stepwise logistic regression analyses were used to determine the predictors of morphometric differences between the groups. For the defined predictors, ROC (receiver-operating characteristic) curves and interactive dot diagrams were calculated with the cutoff values of the morphometric factors. The number of anterior cerebral circulation IAs was 179 (70.5 %); 141 (55.5 %) aneurysms were ruptured. Significant differences between anterior and posterior circulation IAs were found for: the parent artery size (5.08 ± 1.8 mm vs. 3.95 ± 1.5 mm; p < 0.05), size ratio (2.22 ± 0.9 vs. 3.19 ± 1.8; p < 0.045) and aspect ratio (AR) (1.91 ± 0.8 vs. 2.75 ± 1.8; p = 0.02). Predicting factors differentiating anterior and posterior circulation IAs were: the AR (OR = 2.20; 95 % CI 1.80-270; Is 270 correct or should it be 2.70 and parent artery size (OR = 0.44; 95 % CI 0.38-0.54). The cutoff point in the ROC curve was 2.185 for the AR and 4.89 mm for parent artery size. Aspect ratio and parent artery size were found to be predictive morphometric factors in differentiating between anterior and posterior cerebral IAs.

Quantitative evaluation of diffusion-kurtosis imaging for grading endometrial carcinoma: a comparative study with diffusion-weighted imaging.

PubMed

Chen, T; Li, Y; Lu, S-S; Zhang, Y-D; Wang, X-N; Luo, C-Y; Shi, H-B

2017-11-01

To evaluate the diagnostic performance of histogram analysis of diffusion kurtosis magnetic resonance imaging (DKI) and standard diffusion-weighted imaging (DWI) in discriminating tumour grades of endometrial carcinoma (EC). Seventy-three patients with EC were included in this study. The apparent diffusion coefficient (ADC) value from standard DWI, apparent diffusion for Gaussian distribution (D app ), and apparent kurtosis coefficient (K app ) from DKI were acquired using a 3 T magnetic resonance imaging (MRI) system. The measurement was based on an entire-tumour analysis. Histogram parameters (D app , K app , and ADC) were compared between high-grade (grade 3) and low-grade (grade 1 and 2) tumours. The diagnostic performance of imaging parameters for discriminating high- from low-grade tumours was analysed using a receiver operating characteristic curve (ROC). The area under the ROC curve (AUC) of the 10th percentile of D app , 90th percentile of K app and 10th percentile of ADC were higher than other parameters in distinguishing high-grade tumours from low-grade tumours (AUC=0.821, 0.891 and 0.801, respectively). The combination of 10th percentile of D app and 90th percentile of K app improved the AUC to 0.901, which was significantly higher than that of the 10th percentile of ADC (0.810, p=0.0314) in differentiating high- from low-grade EC. Entire-tumour volume histogram analysis of DKI and standard DWI were feasible for discriminating histological tumour grades of EC. DKI was relatively better than DWI in distinguishing high-grade from low-grade tumour in EC. Copyright © 2017. Published by Elsevier Ltd.

Prediction of challenge test results by flour-specific IgE and skin prick test in symptomatic bakers.

PubMed

van Kampen, V; Rabstein, S; Sander, I; Merget, R; Brüning, T; Broding, H C; Keller, C; Müsken, H; Overlack, A; Schultze-Werninghaus, G; Walusiak, J; Raulf-Heimsoth, M

2008-07-01

Wheat and rye flours are among the most important allergens causing occupational asthma. Usually, the diagnosis of baker's asthma is based on inhalation challenge tests with flours. To evaluate the relevance of flour-specific serum immunoglobulin E (IgE) and skin prick test (SPT) in the diagnosis of baker's asthma and to define flour-specific IgE concentrations and wheal sizes that allow a prediction of the outcome of challenge testing. Bronchial and nasal challenge tests with wheat (rye) flour were performed in 71 (95) symptomatic bakers. Determinations of flour-specific IgE as well as SPTs were performed in all subjects. Analyses included the calculation of sensitivity, specificity, positive (PPV) and negative predictive values (NPV) at different IgE concentrations and different wheal sizes, and receiver-operating characteristics (ROC) plots with the challenge result as gold standard. Thirty-seven bakers were positive in the challenge with wheat flour, while 63 were positive with rye flour. Depending on the flour-specific IgE concentrations (wheal size), PPV was 74-100% (74-100%) for wheat and 82-100% (91-100%) for rye flour, respectively. The minimal cut-off values with a PPV of 100% were 2.32 kU/l (5.0 mm) for wheat flour and 9.64 kU/l (4.5 mm) for rye flour. The shapes of the ROC plots were similar for wheat and rye flour. High concentrations of flour-specific IgE and clear SPT results in symptomatic bakers are good predictors for a positive challenge test. Challenge tests with flours may be avoided in strongly sensitized bakers.

Feasibility of histogram analysis of susceptibility-weighted MRI for staging of liver fibrosis

PubMed Central

Yang, Zhao-Xia; Liang, He-Yue; Hu, Xin-Xing; Huang, Ya-Qin; Ding, Ying; Yang, Shan; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-01-01

PURPOSE We aimed to evaluate whether histogram analysis of susceptibility-weighted imaging (SWI) could quantify liver fibrosis grade in patients with chronic liver disease (CLD). METHODS Fifty-three patients with CLD who underwent multi-echo SWI (TEs of 2.5, 5, and 10 ms) were included. Histogram analysis of SWI images were performed and mean, variance, skewness, kurtosis, and the 1st, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared. For significant parameters, further receiver operating characteristic (ROC) analyses were performed to evaluate the potential diagnostic performance for differentiating liver fibrosis stages. RESULTS The number of patients in each pathologic fibrosis grade was 7, 3, 5, 5, and 33 for F0, F1, F2, F3, and F4, respectively. The results of variance (TE: 10 ms), 90th percentile (TE: 10 ms), and 99th percentile (TE: 10 and 5 ms) in F0–F3 group were significantly lower than in F4 group, with areas under the ROC curves (AUCs) of 0.84 for variance and 0.70–0.73 for the 90th and 99th percentiles, respectively. The results of variance (TE: 10 and 5 ms), 99th percentile (TE: 10 ms), and skewness (TE: 2.5 and 5 ms) in F0–F2 group were smaller than those of F3/F4 group, with AUCs of 0.88 and 0.69 for variance (TE: 10 and 5 ms, respectively), 0.68 for 99th percentile (TE: 10 ms), and 0.73 and 0.68 for skewness (TE: 2.5 and 5 ms, respectively). CONCLUSION Magnetic resonance histogram analysis of SWI, particularly the variance, is promising for predicting advanced liver fibrosis and cirrhosis. PMID:27113421

Utility of serum lipid ratios for predicting incident type 2 diabetes: the Isfahan Diabetes Prevention Study.

PubMed

Janghorbani, Mohsen; Amini, Masoud

2016-09-01

In this study, we evaluate the association between triglyceride to high-density lipoprotein cholesterol (TG/HDL) ratio and total cholesterol (TC) to HDL (TC/HDL) ratio and the risks of type 2 diabetes (T2D) in an Iranian high-risk population. We analysed 7-year follow-up data (n = 1771) in non-diabetic first-degree relatives of consecutive patients with T2D 30-70 years old. The primary outcome was the diagnosis of T2D based on repeated oral glucose tolerance tests. We used Cox proportional hazard models to estimate hazard ratio for incident T2D across tertiles of TG/HDL and TC/HDL ratios and plotted a receiver operating characteristic (ROC) curve to assess discrimination. The highest tertile of TG/HDL and TC/HDL ratios compared with the lowest tertile was not associated with T2D in age- and gender-adjusted models (HR 0.99, 95% CI: 0.88, 1.11 for TG/HDL ratio and 1.10, 95% CI: 0.97, 1.23 for TC/HDL ratio). Further adjustment for waist circumference or body mass index, fasting plasma glucose, and low-density lipoprotein cholesterol did not appreciably alter the hazard ratio compared with the age- and gender-adjusted model. The area under the ROC curve for TG/HDL ratio was 57.7% (95% CI: 54.0, 61.5) and for TC/HDL ratio was 55.1% (95% CI: 51.2, 59.0). TG/HDL and TC/HDL ratios were not robust predictors of T2D in high-risk individuals in Iran. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Predicting Ovarian Activity in Women Affected by Early Breast Cancer: A Meta-Analysis-Based Nomogram.

PubMed

Barnabei, Agnese; Strigari, Lidia; Marchetti, Paolo; Sini, Valentina; De Vecchis, Liana; Corsello, Salvatore Maria; Torino, Francesco

2015-10-01

The assessment of ovarian reserve in premenopausal women requiring anticancer gonadotoxic therapy can help clinicians address some challenging issues, including the probability of future pregnancies after the end of treatment. Anti-Müllerian hormone (AMH) and age can reliably estimate ovarian reserve. A limited number of studies have evaluated AMH and age as predictors of residual ovarian reserve following cytotoxic chemotherapy in breast cancer patients. To conduct a meta-analysis of published data on this topic, we searched the medical literature using the key MeSH terms "amenorrhea/chemically induced," "ovarian reserve," "anti-Mullerian hormone/blood," and "breast neoplasms/drug therapy." Preferred Reporting Items for Systematic Reviews and Meta-Analyses statements guided the search strategy. U.K. National Health Service guidelines were used in abstracting data and assessing data quality and validity. Area under the receiver operating characteristic curve (ROC/AUC) analysis was used to evaluate the predictive utility of baseline AMH and age model. The meta-analysis of data pooled from the selected studies showed that both age and serum AMH are reliable predictors of post-treatment ovarian activity in breast cancer patients. Importantly, ROC/AUC analysis indicated AMH was a more reliable predictor of post-treatment ovarian activity in patients aged younger than 40 years (0.753; 95% confidence interval [CI]: 0.602-0.904) compared with those older than 40 years (0.678; 95% CI: 0.491-0.866). We generated a nomogram describing the correlations among age, pretreatment AMH serum levels, and ovarian activity at 1 year from the end of chemotherapy. After the ongoing validation process, the proposed nomogram may help clinicians discern premenopausal women requiring cytotoxic chemotherapy who should be considered high priority for fertility preservation counseling and procedures. ©AlphaMed Press.

Assessment of under nutrition of Bangladeshi adults using anthropometry: can body mass index be replaced by mid-upper-arm-circumference?

PubMed

Sultana, Tania; Karim, Md Nazmul; Ahmed, Tahmeed; Hossain, Md Iqbal

2015-01-01

Body-mass-index (BMI) is widely accepted as an indicator of nutritional status in adults. Mid-upper-arm-circumference (MUAC) is another anthropometric-measure used primarily among children. The present study attempted to evaluate the use of MUAC as a simpler alternative to BMI cut-off <18.5 to detect adult undernutrition, and thus to suggest a suitable cut-off value. A cross-sectional study in 650 adult attendants of the patients of Dhaka-Hospital, of the International Centre for Diarrheal Disease Research, Bangladesh (icddr,b) was conducted during 2012. Height, weight and MUAC of 260 male and 390 female aged 19-60 years were measured. Curve estimation was done to assess the linearity and correlation of BMI and MUAC. Sensitivity and specificity of MUAC against BMI<18.5 was determined. Separate Receiver-operating-characteristic (ROC) analyses were performed for male and female. Area under ROC curve and Youden's index were generated to aid selection of the most suitable cut-off value of MUAC for undernutrition. A value with highest Youden's index was chosen for cut-off. Our data shows strong significant positive correlation (linear) between MUAC and BMI, for males r = 0.81, (p<0.001) and for females r = 0.828, (p<0.001). MUAC cut-off <25.1 cm in males (AUC 0.930) and <23.9 cm in females (AUC 0.930) were chosen separately based on highest corresponding Youden's index. These values best correspond with BMI cut-off for under nutrition (BMI <18.5) in either gender. MUAC correlates closely with BMI. For the simplicity and easy to remember MUAC <25 cm for male and <24 cm for female may be considered as a simpler alternative to BMI cut-off <18.5 to detect adult undernutrition.

Thymidine kinase 1 combined with CEA, CYFRA21-1 and NSE improved its diagnostic value for lung cancer.

PubMed

Jiang, Z F; Wang, M; Xu, J L

2018-02-01

Thymidine kinase 1 (TK1) is a tumor biomarker in human malignancies. The purpose of this study was to evaluate the diagnostic efficiency of this marker for lung cancer using the combined analysis of carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA21-1), neuron specific enolase (NSE) and TK1. From 2013 to 2014, 147 patients with lung cancer and 228 patients with lung benign diseases who were admitted to our hospital were reviewed. Peripheral blood samples were collected for the detection of TK1, CEA, CYFRA21-1 and NSE. The diagnostic value of each marker was analyzed using receiver operating characteristic (ROC) curves and logistic regression equations. The serum levels of TK1, CEA, CYFRA21-1 and NSE were significantly higher than those in patients with lung benign diseases (all P<0.05). The TK1 concentration was dependent on TNM stage (P=0.005). The ROC curve analyses showed that the diagnostic value of TK1 combined with CEA, CYFRA21-1 and NSE in lung cancer was significantly higher than that of each biomarker alone (all P<0.0001). In addition, TK1 combined with CEA, CYFRA21-1, or NSE could also improve the diagnosis of the squamous cell carcinoma, adenocarcinoma and small cell lung cancer subtypes, respectively. The combined detection of TK1 and the other three markers significantly improved the diagnosis of lung cancer. Furthermore, the detection of TK1 combined with that of CYFRA21-1, CEA or NSE increased the diagnostic value of TK1 for lung squamous cell carcinoma, adenocarcinoma and SCLC, respectively. Copyright © 2017 Elsevier Inc. All rights reserved.

Role of BMI, airflow obstruction, St George's Respiratory Questionnaire and age index in prognostication of Asian COPD.

PubMed

Chan, Hiang Ping; Mukhopadhyay, Amartya; Chong, Pauline Lee Poh; Chin, Sally; Wong, Xue Yun; Ong, Venetia; Chan, Yiong Huak; Lim, Tow Keang; Phua, Jason

2017-01-01

COPD is a complex condition with a heavy burden of disease. Many multidimensional tools have been studied for their prognostic utility but none has been universally adopted as each has its own limitations. We hypothesize that a multidimensional tool examining four domains, health-related quality of life, disease severity, systemic effects of disease and patient factors, would better categorize and prognosticate these patients. We first evaluated 300 patients and found four factors that predicted mortality: BMI, airflow obstruction, St George's Respiratory Questionnaire and age (BOSA). A 10-point index (BOSA index) was constructed and prospectively validated in a cohort of 772 patients with all-cause mortality as the primary outcome. Patients were categorized into their respective BOSA quartile group based on their BOSA score. Multivariate survival analyses and receiver operator characteristic (ROC) curves were used to assess the BOSA index. Patients in BOSA Group 4 were at higher risk of death compared with their counterparts in Group 1 (hazard ratio (HR): 0.29, 95% CI: 0.16-0.51, P < 0.001) and Group 2 (HR: 0.53, 95% CI: 0.34-0.82, P = 0.005). Race and gender did not affect mortality. The area under the ROC curve for BOSA index was 0.690 ± 0.025 while that for Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2011 was 0.641 ± 0.025 (P = 0.17). The BOSA index predicts mortality well and it has at least similar prognostic utility as GOLD 2011 in Asian patients. The BOSA index is a simple tool that does not require complex equipment or testing. It has the potential to be used widely. © 2016 Asian Pacific Society of Respirology.

Clinical Significance of Tissue Factor Pathway Inhibitor 2, a Serum Biomarker Candidate for Ovarian Clear Cell Carcinoma

PubMed Central

Arakawa, Noriaki; Kobayashi, Hiroshi; Yonemoto, Naohiro; Masuishi, Yusuke; Ino, Yoko; Shigetomi, Hiroshi; Furukawa, Naoto; Ohtake, Norihisa; Miyagi, Yohei; Hirahara, Fumiki; Hirano, Hisashi; Miyagi, Etsuko

2016-01-01

Background There is currently no reliable serum biomarker for ovarian clear cell carcinoma (CCC), a highly lethal histological subtype of epithelial ovarian cancer (EOC). Previously, using a proteome-based approach, we identified tissue factor pathway inhibitor 2 (TFPI2) as a candidate serum biomarker for CCC. In this study, we sought to evaluate the clinical diagnostic performance of TFPI2 in preoperative prediction of CCC. Methods Serum TFPI2 levels were measured in serum samples from a retrospective training set consisting of patients with benign and borderline ovarian tumors, EOC subtypes, and uterine diseases. Via receiver operating characteristic (ROC) analyses, we compared the diagnostic performance of TFPI2 with that of CA125 in discrimination of patients with ovarian CCC from other patient groups. The observed diagnostic performances were examined in a prospective validation set. Results The 268-patient training set included 29 patients with ovarian CCC. Unlike CA125, which was also elevated in patients with endometriosis and several EOC subtypes, serum TFPI2 levels were specifically elevated only in ovarian CCC patients, consistent with the mRNA expression pattern in tumor tissues. The area under the ROC curve (AUC) of serum TFPI2 was obviously higher than that of CA125 for discrimination of CCC from other ovarian diseases (AUC = 0.891 versus 0.595). Applying a cut-off value of 280 pg/mL, TFPI2 could distinguish early-stage (FIGO I and II) CCC from endometriosis with 72.2% sensitivity, 93.3% specificity, and 88.8% accuracy. Similar results were confirmed in an independent 156-patient prospective validation set. Conclusions TFPI2 is a useful serum biomarker for preoperative clinical diagnosis of CCC. PMID:27798689

Clinical Significance of Tissue Factor Pathway Inhibitor 2, a Serum Biomarker Candidate for Ovarian Clear Cell Carcinoma.

PubMed

Arakawa, Noriaki; Kobayashi, Hiroshi; Yonemoto, Naohiro; Masuishi, Yusuke; Ino, Yoko; Shigetomi, Hiroshi; Furukawa, Naoto; Ohtake, Norihisa; Miyagi, Yohei; Hirahara, Fumiki; Hirano, Hisashi; Miyagi, Etsuko

2016-01-01

There is currently no reliable serum biomarker for ovarian clear cell carcinoma (CCC), a highly lethal histological subtype of epithelial ovarian cancer (EOC). Previously, using a proteome-based approach, we identified tissue factor pathway inhibitor 2 (TFPI2) as a candidate serum biomarker for CCC. In this study, we sought to evaluate the clinical diagnostic performance of TFPI2 in preoperative prediction of CCC. Serum TFPI2 levels were measured in serum samples from a retrospective training set consisting of patients with benign and borderline ovarian tumors, EOC subtypes, and uterine diseases. Via receiver operating characteristic (ROC) analyses, we compared the diagnostic performance of TFPI2 with that of CA125 in discrimination of patients with ovarian CCC from other patient groups. The observed diagnostic performances were examined in a prospective validation set. The 268-patient training set included 29 patients with ovarian CCC. Unlike CA125, which was also elevated in patients with endometriosis and several EOC subtypes, serum TFPI2 levels were specifically elevated only in ovarian CCC patients, consistent with the mRNA expression pattern in tumor tissues. The area under the ROC curve (AUC) of serum TFPI2 was obviously higher than that of CA125 for discrimination of CCC from other ovarian diseases (AUC = 0.891 versus 0.595). Applying a cut-off value of 280 pg/mL, TFPI2 could distinguish early-stage (FIGO I and II) CCC from endometriosis with 72.2% sensitivity, 93.3% specificity, and 88.8% accuracy. Similar results were confirmed in an independent 156-patient prospective validation set. TFPI2 is a useful serum biomarker for preoperative clinical diagnosis of CCC.

Automated analysis of heidelberg retina tomograph optic disc images by glaucoma probability score.

PubMed

Coops, Annemiek; Henson, David Barry; Kwartz, Anna J; Artes, Paul Habib

2006-12-01

To compare the diagnostic performance of the Heidelberg Retinal Tomograph's (HRT; Heidelberg Engineering GmbH, Dossenheim, Germany) glaucoma probability score (GPS), an automated, contour line-independent method of optic disc analysis with that of the Moorfields regression analysis (MRA). HRT images were obtained from one eye of 121 patients with glaucoma (median age, 70.2 years; median mean deviation [MD], -3.6 dB, range, +2.0 to -9.9 dB) and 95 healthy control subjects (median age, 59.7 years; median MD -0.1 dB, range +2.5 to -3.7). The diagnostic performances of GPS and MRA were evaluated by including borderline classifications, either as test negatives (most specific criteria) or as test positives (least specific criteria). Agreement between global and sectoral data of both analyses was established. Logistic regression analyses were performed to evaluate the effect of covariates such as optic disc size and age on the classification outcomes of both the GPS and the MRA. In 8 (7%) patients with glaucoma and 10 (11%) control subjects, the GPS failed to provide a complete global and sectoral optic disc classification. Although we could not identify a single distinct cause of this failure in the glaucoma group, failures in the control subjects occurred most often (7/10) with small and crowded optic discs. In subjects who were successfully classified at least globally by the GPS (117 patients with glaucoma, 88 control subjects), the diagnostic performances of GPS and MRA were similar (areas under the receiver operating characteristic [ROC] curve of 0.78 and 0.77, respectively; P > 0.1). With the GPS, sensitivity and specificity were 59% and 91% (most specific criteria) and 78% and 63% (least specific criteria), respectively. Combining GPS and MRA did not increase diagnostic performance significantly (ROC area of combined classifiers, 0.81). Both GPS and MRA were affected by disc size. In patients with glaucoma as well as healthy control subjects, the odds of a positive GPS classification (borderline or outside normal limits) increased by 21% (95% confidence interval [CI], 12%-30%) for each 0.1 mm2 increase in optic disc area. With the MRA, the corresponding increase was 15% (95% CI, 7%-23%). Optic disc area alone accounted for approximately 30% and 22% of the explained variance with the GPS and MRA, respectively (P < 0.001). The proportional-odds logistic regression confirmed that optic disc size affected mainly the tradeoff between true- and false-positive classifications (criterion) rather than the absolute performance of the analyses (area under the ROC curve). There was some evidence of an age effect with the MRA, which showed a 53% (95% CI, 16%-102%) increase in the odds of a positive test (borderline or outside normal limits) associated with each decade of age (P = 0.002), but no age effects were observed with the GPS (P > 0.1). The diagnostic performance of the contour line-independent GPS analysis is similar to that of the MRA. However, clinicians should be aware of the strong size dependence of both GPS and MRA. In large optic discs, both GPS and MRA are likely to produce many false-positive classifications. Correspondingly, the sensitivity to early damage is likely to be low in small optic discs. There is a need for automated classification systems that explicitly address the size dependence of current analyses.

Computed Tomography Angiography Evaluation of Risk Factors for Unstable Intracranial Aneurysms.

PubMed

Wang, Guang-Xian; Gong, Ming-Fu; Wen, Li; Liu, Lan-Lan; Yin, Jin-Bo; Duan, Chun-Mei; Zhang, Dong

2018-03-19

To evaluate risk factors for instability in intracranial aneurysms (IAs) using computed tomography angiography (CTA). A total of 614 consecutive patients diagnosed with 661 IAs between August 2011 and February 2016 were reviewed. Patients and IAs were divided into stable and unstable groups. Along with clinical characteristics, IA characteristics were evaluated by CTA. Multiple logistic regression analysis was used to identify the independent risk factors associated with unstable IAs. Receiver operating characteristic (ROC) curve analysis was performed on the final model, and optimal thresholds were obtained. Patient age (odds ratio [OR], 0.946), cerebral atherosclerosis (CA; OR, 0.525), and IAs located at the middle cerebral artery (OR, 0.473) or internal carotid artery (OR, 0.512) were negatively correlated with instability, whereas IAs with irregular shape (OR, 2.157), deep depth (OR, 1.557), or large flow angle (FA; OR, 1.015) were more likely to be unstable. ROC analysis revealed threshold values of age, depth, and FA of 59.5 years, 4.25 mm, and 87.8°, respectively. The stability of IAs is significantly affected by several factors, including patient age and the presence of CA. IA shape and location also have an impact on the stability of IAs. Growth into an irregular shape, with a deep depth, and a large FA are risk factors for a change in IAs from stable to unstable. Copyright © 2018 Elsevier Inc. All rights reserved.

Discriminating Famous from Fictional Names Based on Lifetime Experience: Evidence in Support of a Signal-Detection Model Based on Finite Mixture Distributions

ERIC Educational Resources Information Center

Bowles, Ben; Harlow, Iain M.; Meeking, Melissa M.; Kohler, Stefan

2012-01-01

It is widely accepted that signal-detection mechanisms contribute to item-recognition memory decisions that involve discriminations between targets and lures based on a controlled laboratory study episode. Here, the authors employed mathematical modeling of receiver operating characteristics (ROC) to determine whether and how a signal-detection…

Receiver Operating Characteristic Analysis for Classification Based on Various Prior Probabilities of Groups with an Application to Breath Analysis

NASA Astrophysics Data System (ADS)

Cimermanová, K.

2009-01-01

In this paper we illustrate the influence of prior probabilities of diseases on diagnostic reasoning. For various prior probabilities of classified groups characterized by volatile organic compounds of breath profile, smokers and non-smokers, we constructed the ROC curve and the Youden index with related asymptotic pointwise confidence intervals.

Assessing the Belief Bias Effect with ROCs: Reply to Dube, Rotello, and Heit (2010)

ERIC Educational Resources Information Center

Klauer, Karl Christoph; Kellen, David

2011-01-01

Dube, Rotello, and Heit (2010) argued (a) that the so-called receiver operating characteristic is nonlinear for data on belief bias in syllogistic reasoning; (b) that their data are inconsistent with Klauer, Musch, and Naumer's (2000) model of belief bias; (c) that their data are inconsistent with any of the existing accounts of belief bias and…

Objective Assessment of Image Quality VI: Imaging in Radiation Therapy

PubMed Central

Barrett, Harrison H.; Kupinski, Matthew A.; Müeller, Stefan; Halpern, Howard J.; Morris, John C.; Dwyer, Roisin

2015-01-01

Earlier work on Objective Assessment of Image Quality (OAIQ) focused largely on estimation or classification tasks in which the desired outcome of imaging is accurate diagnosis. This paper develops a general framework for assessing imaging quality on the basis of therapeutic outcomes rather than diagnostic performance. By analogy to Receiver Operating Characteristic (ROC) curves and their variants as used in diagnostic OAIQ, the method proposed here utilizes the Therapy Operating Characteristic or TOC curves, which are plots of the probability of tumor control vs. the probability of normal-tissue complications as the overall dose level of a radiotherapy treatment is varied. The proposed figure of merit is the area under the TOC curve, denoted AUTOC. This paper reviews an earlier exposition of the theory of TOC and AUTOC, which was specific to the assessment of image-segmentation algorithms, and extends it to other applications of imaging in external-beam radiation treatment as well as in treatment with internal radioactive sources. For each application, a methodology for computing the TOC is presented. A key difference between ROC and TOC is that the latter can be defined for a single patient rather than a population of patients. PMID:24200954

A comparison of the validity of GHQ-12 and CHQ-12 in Chinese primary care patients in Manchester.

PubMed

Pan, P C; Goldberg, D P

1990-11-01

The present study compares the efficacy of the GHQ-12 and the Chinese Health Questionnaire (CHQ-12) in Cantonese speaking Chinese primary-care patients living in Greater Manchester, using relative operating characteristic (ROC) analysis. We did not find that the Chinese version offered any advantage over the conventional version of the GHQ in this population. Stepwise discriminant analysis however confirmed the value of individual items in the former pertaining to specific somatic symptoms and interpersonal relationships in differentiating cases from non-cases. Information biases, arising from the lack of a reliability study on the second-stage case identifying interview and the unique linguistic characteristics of the Chinese language may have affected the overall validity indices of the questionnaires. The study also examines the effects of using different criteria to define a case, and shows that with increasing levels of severity, there is an improvement in the diagnostic performance of the two questionnaires as reflected by areas under ROC curves and traditional validity indices. Possible explanations of these findings are discussed. The scoring method proposed by Goodchild & Duncan-Jones (1985) when used on these questionnaires had no demonstrable advantage over the conventional scoring method.

Vertical or horizontal orientation of foot radiographs does not affect image interpretation

PubMed Central

Ferran, Nicholas Antonio; Ball, Luke; Maffulli, Nicola

2012-01-01

Summary This study determined whether the orientation of dorsoplantar and oblique foot radiographs has an effect on radiograph interpretation. A test set of 50 consecutive foot radiographs were selected (25 with fractures, and 25 normal), and duplicated in the horizontal orientation. The images were randomly arranged, numbered 1 through 100, and analysed by six image interpreters. Vertical and horizontal area under the ROC curve, accuracy, sensitivity and specificity were calculated for each image interpreter. There was no significant difference in the area under the ROC curve, accuracy, sensitivity or specificity of image interpretation between images viewed in the vertical or horizontal orientation. While conventions for display of radiographs may help to improve the development of an efficient visual search strategy in trainees, and allow for standardisation of publication of radiographic images, variation from the convention in clinical practice does not appear to affect the sensitivity or specificity of image interpretation. PMID:23738310

What is an ROC curve?

PubMed

Hoo, Zhe Hui; Candlish, Jane; Teare, Dawn

2017-06-01

The paper by Body et al is concerned with the evaluation of decision aids, which can be used to identify potential acute coronary syndromes (ACS) in the ED. The authors previously developed the Manchester Acute Coronary Syndromes model (MACS) decision aid, which uses several clinical variables and two biomarkers to 'rule in' and 'rule out' ACS. However, one of the two biomarkers (heart-type fatty acid bindingprotein, H-FABP) is not widely used so a revised decision aid has been developed (Troponin-only Manchester Acute Coronary Syndromes, T-MACS), which include a single biomarker hs-cTnT. In this issue, the authors show how they derive a revised decision aid and describe its performance in a number of independent diagnostic cohort studies. Decision aids (as well as other types of 'diagnostic tests') are often evaluated in terms of diagnostic testing parameters such as the area under the receiver operating characteristic (ROC) curve, sensitivity and specificity. In this article, we explain how the ROC analysis is conducted and why it is an essential step towards developing a test with the desirable levels of sensitivity and specificity. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Anatomy-Based Algorithms for Detecting Oral Cancer Using Reflectance and Fluorescence Spectroscopy

PubMed Central

McGee, Sasha; Mardirossian, Vartan; Elackattu, Alphi; Mirkovic, Jelena; Pistey, Robert; Gallagher, George; Kabani, Sadru; Yu, Chung-Chieh; Wang, Zimmern; Badizadegan, Kamran; Grillone, Gregory; Feld, Michael S.

2010-01-01

Objectives We used reflectance and fluorescence spectroscopy to noninvasively and quantitatively distinguish benign from dysplastic/malignant oral lesions. We designed diagnostic algorithms to account for differences in the spectral properties among anatomic sites (gingiva, buccal mucosa, etc). Methods In vivo reflectance and fluorescence spectra were collected from 71 patients with oral lesions. The tissue was then biopsied and the specimen evaluated by histopathology. Quantitative parameters related to tissue morphology and biochemistry were extracted from the spectra. Diagnostic algorithms specific for combinations of sites with similar spectral properties were developed. Results Discrimination of benign from dysplastic/malignant lesions was most successful when algorithms were designed for individual sites (area under the receiver operator characteristic curve [ROC-AUC], 0.75 for the lateral surface of the tongue) and was least accurate when all sites were combined (ROC-AUC, 0.60). The combination of sites with similar spectral properties (floor of mouth and lateral surface of the tongue) yielded an ROC-AUC of 0.71. Conclusions Accurate spectroscopic detection of oral disease must account for spectral variations among anatomic sites. Anatomy-based algorithms for single sites or combinations of sites demonstrated good diagnostic performance in distinguishing benign lesions from dysplastic/malignant lesions and consistently performed better than algorithms developed for all sites combined. PMID:19999369

Ultrasound bladder wall thickness measurement in diagnosis of recurrent urinary tract infections and cystitis cystica in prepubertal girls.

PubMed

Milošević, Danko; Trkulja, Vladimir; Turudić, Daniel; Batinić, Danica; Spajić, Borislav; Tešović, Goran

2013-12-01

To evaluate urinary bladder wall thickness (BWT) assessed by ultrasound as a diagnostic tool for cystitis cystica. This was a 9-year prospective study comprising 120 prepubertal girls. Sixty subjects of whom half underwent cystoscopy represented cases while the other 60 (those with a single urinary tract infection and healthy subjects) represented controls. Based on receiver operating characteristics (ROC) analysis, BWT discriminated very well between cases and controls with area under the ROC curve close to 1.0. At the optimum cut-off defined at 3.9 mm, negative predictive value (NPV) was 100% leaving no probability of cystic cystitis with BWT <3.9 mm. Positive predictive value (PPV) was also very high (95.2%), indicating only around 4.82% probability of no cystic cystitis in patients with BWT values ≥3.9 mm. BWT could also distinguish between healthy subjects and those with a cured single urinary tract infection, although discriminatory properties were moderate (area under ROC 86.7%, PPV 78.8%, NPV 85.2%). Ultrasound mucosal bladder wall measurement is a non-invasive, simple and quite reliable method in diagnosis of cystitis cystica in prepubertal girls with recurrent urinary tract infections. Copyright © 2013 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.

A Comparison between Decision Tree and Random Forest in Determining the Risk Factors Associated with Type 2 Diabetes.

PubMed

Esmaily, Habibollah; Tayefi, Maryam; Doosti, Hassan; Ghayour-Mobarhan, Majid; Nezami, Hossein; Amirabadizadeh, Alireza

2018-04-24

We aimed to identify the associated risk factors of type 2 diabetes mellitus (T2DM) using data mining approach, decision tree and random forest techniques using the Mashhad Stroke and Heart Atherosclerotic Disorders (MASHAD) Study program. A cross-sectional study. The MASHAD study started in 2010 and will continue until 2020. Two data mining tools, namely decision trees, and random forests, are used for predicting T2DM when some other characteristics are observed on 9528 subjects recruited from MASHAD database. This paper makes a comparison between these two models in terms of accuracy, sensitivity, specificity and the area under ROC curve. The prevalence rate of T2DM was 14% among these subjects. The decision tree model has 64.9% accuracy, 64.5% sensitivity, 66.8% specificity, and area under the ROC curve measuring 68.6%, while the random forest model has 71.1% accuracy, 71.3% sensitivity, 69.9% specificity, and area under the ROC curve measuring 77.3% respectively. The random forest model, when used with demographic, clinical, and anthropometric and biochemical measurements, can provide a simple tool to identify associated risk factors for type 2 diabetes. Such identification can substantially use for managing the health policy to reduce the number of subjects with T2DM .

Is the MARS questionnaire a reliable measure of medication adherence in childhood asthma?

PubMed

Garcia-Marcos, Patricia W; Brand, Paul L P; Kaptein, Adrian A; Klok, Ted

2016-12-01

To assess the reliability of the Medication Adherence Report Scale (MARS-5) for assessing adherence in clinical practice and research. Prospective cohort study following electronically measured inhaled corticosteroids (ICS) adherence for 1 year in 2-13-year-old children with persistent asthma. The relationship between electronically measured adherence and MARS-5 scores (ranging from 5 to 25) was assessed by Spearman's rank correlation coefficient. A ROC (receiver operating characteristic) curve was performed testing MARS-5 against electronically measured adherence. Sensitivity, specificity, positive and negative likelihood ratios of the closest MARS-5 cut-off values to the top left-hand corner of the ROC curve were calculated. High MARS scores were obtained (median 24, interquartile range 22-24). Despite a statistically significant correlation between MARS-5 and electronically assessed adherence (Spearman's rho = 0.47; p < 0.0001), there was considerable variation of adherence rates at every MARS-5 score. The area under the ROC curve was 0.7188. A MARS-5 score ≥23 had the best predictive ability for electronically assessed adherence, but positive and negative likelihood ratios were too small to be useful (1.65 and 0.27, respectively). Self-report using MARS-5 is too inaccurate to be a useful measure of adherence in children with asthma, both in clinical practice and in research.

Star Tracker Performance Estimate with IMU

NASA Technical Reports Server (NTRS)

Aretskin-Hariton, Eliot D.; Swank, Aaron J.

2015-01-01

A software tool for estimating cross-boresight error of a star tracker combined with an inertial measurement unit (IMU) was developed to support trade studies for the Integrated Radio and Optical Communication project (iROC) at the National Aeronautics and Space Administration Glenn Research Center. Typical laser communication systems, such as the Lunar Laser Communication Demonstration (LLCD) and the Laser Communication Relay Demonstration (LCRD), use a beacon to locate ground stations. iROC is investigating the use of beaconless precision laser pointing to enable laser communication at Mars orbits and beyond. Precision attitude knowledge is essential to the iROC mission to enable high-speed steering of the optical link. The preliminary concept to achieve this precision attitude knowledge is to use star trackers combined with an IMU. The Star Tracker Accuracy (STAcc) software was developed to rapidly assess the capabilities of star tracker and IMU configurations. STAcc determines the overall cross-boresight error of a star tracker with an IMU given the characteristic parameters: quantum efficiency, aperture, apparent star magnitude, exposure time, field of view, photon spread, detector pixels, spacecraft slew rate, maximum stars used for quaternion estimation, and IMU angular random walk. This paper discusses the supporting theory used to construct STAcc, verification of the program and sample results.

A transfer of technology from engineering: use of ROC curves from signal detection theory to investigate information processing in the brain during sensory difference testing.

PubMed

Wichchukit, Sukanya; O'Mahony, Michael

2010-01-01

This article reviews a beneficial effect of technology transfer from Electrical Engineering to Food Sensory Science. Specifically, it reviews the recent adoption in Food Sensory Science of the receiver operating characteristic (ROC) curve, a tool that is incorporated in the theory of signal detection. Its use allows the information processing that takes place in the brain during sensory difference testing to be studied and understood. The review deals with how Signal Detection Theory, also called Thurstonian modeling, led to the adoption of a more sophisticated way of analyzing the data from sensory difference tests, by introducing the signal-to-noise ratio, d', as a fundamental measure of perceived small sensory differences. Generally, the method of computation of d' is a simple matter for some of the better known difference tests like the triangle, duo-trio and 2-AFC. However, there are occasions when these tests are not appropriate and other tests like the same-different and the A Not-A test are more suitable. Yet, for these, it is necessary to understand how the brain processes information during the test before d' can be computed. It is for this task that the ROC curve has a particular use. © 2010 Institute of Food Technologists®

Efficient cost-sensitive human-machine collaboration for offline signature verification

NASA Astrophysics Data System (ADS)

Coetzer, Johannes; Swanepoel, Jacques; Sabourin, Robert

2012-01-01

We propose a novel strategy for the optimal combination of human and machine decisions in a cost-sensitive environment. The proposed algorithm should be especially beneficial to financial institutions where off-line signatures, each associated with a specific transaction value, require authentication. When presented with a collection of genuine and fraudulent training signatures, produced by so-called guinea pig writers, the proficiency of a workforce of human employees and a score-generating machine can be estimated and represented in receiver operating characteristic (ROC) space. Using a set of Boolean fusion functions, the majority vote decision of the human workforce is combined with each threshold-specific machine-generated decision. The performance of the candidate ensembles is estimated and represented in ROC space, after which only the optimal ensembles and associated decision trees are retained. When presented with a questioned signature linked to an arbitrary writer, the system first uses the ROC-based cost gradient associated with the transaction value to select the ensemble that minimises the expected cost, and then uses the corresponding decision tree to authenticate the signature in question. We show that, when utilising the entire human workforce, the incorporation of a machine streamlines the authentication process and decreases the expected cost for all operating conditions.

Morphological and wavelet features towards sonographic thyroid nodules evaluation.

PubMed

Tsantis, Stavros; Dimitropoulos, Nikos; Cavouras, Dionisis; Nikiforidis, George

2009-03-01

This paper presents a computer-based classification scheme that utilized various morphological and novel wavelet-based features towards malignancy risk evaluation of thyroid nodules in ultrasonography. The study comprised 85 ultrasound images-patients that were cytological confirmed (54 low-risk and 31 high-risk). A set of 20 features (12 based on nodules boundary shape and 8 based on wavelet local maxima located within each nodule) has been generated. Two powerful pattern recognition algorithms (support vector machines and probabilistic neural networks) have been designed and developed in order to quantify the power of differentiation of the introduced features. A comparative study has also been held, in order to estimate the impact speckle had onto the classification procedure. The diagnostic sensitivity and specificity of both classifiers was made by means of receiver operating characteristics (ROC) analysis. In the speckle-free feature set, the area under the ROC curve was 0.96 for the support vector machines classifier whereas for the probabilistic neural networks was 0.91. In the feature set with speckle, the corresponding areas under the ROC curves were 0.88 and 0.86 respectively for the two classifiers. The proposed features can increase the classification accuracy and decrease the rate of missing and misdiagnosis in thyroid cancer control.

Factors predicting work outcome in Japanese patients with schizophrenia: role of multiple functioning levels.

PubMed

Sumiyoshi, Chika; Harvey, Philip D; Takaki, Manabu; Okahisa, Yuko; Sato, Taku; Sora, Ichiro; Nuechterlein, Keith H; Subotnik, Kenneth L; Sumiyoshi, Tomiki

2015-09-01

Functional outcomes in individuals with schizophrenia suggest recovery of cognitive, everyday, and social functioning. Specifically improvement of work status is considered to be most important for their independent living and self-efficacy. The main purposes of the present study were 1) to identify which outcome factors predict occupational functioning, quantified as work hours, and 2) to provide cut-offs on the scales for those factors to attain better work status. Forty-five Japanese patients with schizophrenia and 111 healthy controls entered the study. Cognition, capacity for everyday activities, and social functioning were assessed by the Japanese versions of the MATRICS Cognitive Consensus Battery (MCCB), the UCSD Performance-based Skills Assessment-Brief (UPSA-B), and the Social Functioning Scale Individuals' version modified for the MATRICS-PASS (Modified SFS for PASS), respectively. Potential factors for work outcome were estimated by multiple linear regression analyses (predicting work hours directly) and a multiple logistic regression analyses (predicting dichotomized work status based on work hours). ROC curve analyses were performed to determine cut-off points for differentiating between the better- and poor work status. The results showed that a cognitive component, comprising visual/verbal learning and emotional management, and a social functioning component, comprising independent living and vocational functioning, were potential factors for predicting work hours/status. Cut-off points obtained in ROC analyses indicated that 60-70% achievements on the measures of those factors were expected to maintain the better work status. Our findings suggest that improvement on specific aspects of cognitive and social functioning are important for work outcome in patients with schizophrenia.

Reference values for anxiety questionnaires: the Leiden Routine Outcome Monitoring Study.

PubMed

Schulte-van Maaren, Yvonne W M; Giltay, Erik J; van Hemert, Albert M; Zitman, Frans G; de Waal, Margot W M; Carlier, Ingrid V E

2013-09-25

The monitoring of patients with an anxiety disorder can benefit from Routine Outcome Monitoring (ROM). As anxiety disorders differ in phenomenology, several anxiety questionnaires are included in ROM: Brief Scale for Anxiety (BSA), PADUA Inventory Revised (PI-R), Panic Appraisal Inventory (PAI), Penn State Worry Questionnaire (PSWQ), Worry Domains Questionnaire (WDQ), Social Interaction, Anxiety Scale (SIAS), Social Phobia Scale (SPS), and the Impact of Event Scale-Revised (IES-R). We aimed to generate reference values for both 'healthy' and 'clinically anxious' populations for these anxiety questionnaires. We included 1295 subjects from the general population (ROM reference-group) and 5066 psychiatric outpatients diagnosed with a specific anxiety disorder (ROM patient-group). The MINI was used as diagnostic device in both the ROM reference group and the ROM patient group. To define limits for one-sided reference intervals (95th percentile; P95) the outermost 5% of observations were used. Receiver Operating Characteristics (ROC) analyses were used to yield alternative cut-off values for the anxiety questionnaires. For the ROM reference-group the mean age was 40.3 years (SD=12.6), and for the ROM patient-group it was 36.5 years (SD=11.9). Females constituted 62.8% of the reference-group and 64.4% of the patient-group. P95 ROM reference group cut-off values for reference versus clinically anxious populations were 11 for the BSA, 43 for the PI-R, 37 for the PAI Anticipated Panic, 47 for the PAI Perceived Consequences, 65 for the PAI Perceived Self-efficacy, 66 for the PSWQ, 74 for the WDQ, 32 for the SIAS, 19 for the SPS, and 36 for IES-R. ROC analyses yielded slightly lower reference values. The discriminative power of all eight anxiety questionnaires was very high. Substantial non-response and limited generalizability. For eight anxiety questionnaires a comprehensive set of reference values was provided. Reference values were generally higher in women than in men, implying the use of gender-specific cut-off values. Each instrument can be offered to every patient with MAS disorders to make responsible decisions about continuing, changing or terminating therapy. © 2013 Elsevier B.V. All rights reserved.

Lower NIH stroke scale scores are required to accurately predict a good prognosis in posterior circulation stroke.

PubMed

Inoa, Violiza; Aron, Abraham W; Staff, Ilene; Fortunato, Gilbert; Sansing, Lauren H

2014-01-01

The NIH stroke scale (NIHSS) is an indispensable tool that aids in the determination of acute stroke prognosis and decision making. Patients with posterior circulation (PC) strokes often present with lower NIHSS scores, which may result in the withholding of thrombolytic treatment from these patients. However, whether these lower initial NIHSS scores predict better long-term prognoses is uncertain. We aimed to assess the utility of the NIHSS at presentation for predicting the functional outcome at 3 months in anterior circulation (AC) versus PC strokes. This was a retrospective analysis of a large prospectively collected database of adults with acute ischemic stroke. Univariate and multivariate analyses were conducted to identify factors associated with outcome. Additional analyses were performed to determine the receiver operating characteristic (ROC) curves for NIHSS scores and outcomes in AC and PC infarctions. Both the optimal cutoffs for maximal diagnostic accuracy and the cutoffs to obtain >80% sensitivity for poor outcomes were determined in AC and PC strokes. The analysis included 1,197 patients with AC stroke and 372 with PC stroke. The median initial NIHSS score for patients with AC strokes was 7 and for PC strokes it was 2. The majority (71%) of PC stroke patients had baseline NIHSS scores ≤4, and 15% of these 'minor' stroke patients had a poor outcome at 3 months. ROC analysis identified that the optimal NIHSS cutoff for outcome prediction after infarction in the AC was 8 and for infarction in the PC it was 4. To achieve >80% sensitivity for detecting patients with a subsequent poor outcome, the NIHSS cutoff for infarctions in the AC was 4 and for infarctions in the PC it was 2. The NIHSS cutoff that most accurately predicts outcomes is 4 points higher in AC compared to PC infarctions. There is potential for poor outcomes in patients with PC strokes and low NIHSS scores, suggesting that thrombolytic treatment should not be withheld from these patients based solely on the NIHSS. © 2014 S. Karger AG, Basel. © 2014 S. Karger AG, Basel.

Assessment of Minimum Important Difference and Substantial Clinical Benefit with the Vascular Quality of Life Questionnaire-6 when Evaluating Revascularisation Procedures in Peripheral Arterial Disease.

PubMed

Nordanstig, J; Pettersson, M; Morgan, M; Falkenberg, M; Kumlien, C

2017-09-01

Patient reported outcomes are increasingly used to assess outcomes after peripheral arterial disease (PAD) interventions. VascuQoL-6 (VQ-6) is a PAD specific health-related quality of life (HRQoL) instrument for routine clinical practice and clinical research. This study assessed the minimum important difference for the VQ-6 and determined thresholds for the minimum important difference and substantial clinical benefit following PAD revascularisation. This was a population-based observational cohort study. VQ-6 data from the Swedvasc Registry (January 2014 to September 2016) was analysed for revascularised PAD patients. The minimum important difference was determined using a combination of a distribution based and an anchor-based method, while receiver operating characteristic curve analysis (ROC) was used to determine optimal thresholds for a substantial clinical benefit following revascularisation. A total of 3194 revascularised PAD patients with complete VQ-6 baseline recordings (intermittent claudication (IC) n = 1622 and critical limb ischaemia (CLI) n = 1572) were studied, of which 2996 had complete VQ-6 recordings 30 days and 1092 a year after the vascular intervention. The minimum important difference 1 year after revascularisation for IC patients ranged from 1.7 to 2.2 scale steps, depending on the method of analysis. Among CLI patients, the minimum important difference after 1 year was 1.9 scale steps. ROC analyses demonstrated that the VQ-6 discriminative properties for a substantial clinical benefit was excellent for IC patients (area under curve (AUC) 0.87, sensitivity 0.81, specificity 0.76) and acceptable in CLI (AUC 0.736, sensitivity 0.63, specificity 0.72). An optimal VQ-6 threshold for a substantial clinical benefit was determined at 3.5 scale steps among IC patients and 4.5 in CLI patients. The suggested thresholds for minimum important difference and substantial clinical benefit could be used when evaluating VQ-6 outcomes following different interventions in PAD and in the design of clinical trials. Copyright © 2017 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

Surrogacy of progression free survival for overall survival in metastatic breast cancer studies: Meta-analyses of published studies.

PubMed

Kundu, Madan G; Acharyya, Suddhasatta

2017-02-01

PFS is often used as a surrogate endpoint for OS in metastatic breast cancer studies. We have evaluated the association of treatment effect on PFS with significant HR OS (and how this association is affected by other factors) in published prospective metastatic breast cancer studies. A systematic literature search in PubMed identified prospective metastatic breast cancer studies. Treatment effects on PFS were determined using hazard ratio (HR PFS ), increase in median PFS (ΔMED PFS ) and % increase in median PFS (%ΔMED PFS ). Diagnostic accuracy of PFS measures (HR PFS , ΔMED PFS and %ΔMED PFS ) in predicting significant HR OS was assessed using receiver operating characteristic (ROC) curves and classification tree approach (CART). Seventy-four cases (i.e., treatment to control comparisons) from 65 individual publications were identified for the analyses. Of these, 16 cases reported significant treatment effect on HR OS at 5% level of significance. Median number of deaths reported in these cases were 153. Area under the ROC curve (AUC) for diagnostic measures as HR PFS , ΔMED PFS and %ΔMED PFS were 0.69, 0.70 and 0.75, respectively. Classification tree results identified %ΔMED PFS and number of deaths as diagnostic measure for significant HR OS . Only 7.9% (3/39) cases with ΔMED PFS shorter than 48.27% reported significant HR OS . There were 7 cases with ΔMED PFS of 48.27% or more and number of deaths reported as 227 or more - of these 5 cases reported significant HR OS . %ΔMED PFS was found to be a better diagnostic measure for predicting significant HR OS . Our analysis results also suggest that consideration of total number of deaths may further improve its diagnostic performance. Based on our study results, the studies with 50% improvement in median PFS are more likely to produce significant HR OS if the total number of OS events at the time of analysis is 227 or more. Copyright © 2016 Elsevier Inc. All rights reserved.

The verbal facilitation effect: re-reading person descriptions as a system variable to improve identification performance.

PubMed

Sporer, Siegfried L; Kaminski, Kristina S; Davids, Maike C; McQuiston, Dawn

2016-11-01

When witnesses report a crime, police usually ask for a description of the perpetrator. Several studies suggested that verbalising faces leads to a detriment in identification performance (verbal overshadowing effect [VOE]) but the effect has been difficult to replicate. Here, we sought to reverse the VOE by inducing context reinstatement as a system variable through re-reading one's own description before an identification task. Participants (N = 208) watched a video film and were then dismissed (control group), only described the perpetrator, or described and later re-read their own descriptions before identification in either target-present or target-absent lineups after a 2-day or a 5-week delay. Identification accuracy was significantly higher after re-reading (85.0%) than in the no description control group (62.5%) irrespective of target presence. Data were internally replicated using a second target and corroborated by several small meta-analyses. Identification accuracy was related to description quality. Moreover, there was a tendency towards a verbal facilitation effect (VFE) rather than a VOE. Receiver operating characteristic (ROC) curve analyses confirm that our findings are not due to a shift in response bias but truly reflect improvement of recognition performance. Differences in the ecological validity of study paradigms are discussed.

Preliminary performance assessment of biotoxin detection for UWS applications using a MicroChemLab device.

DOE Office of Scientific and Technical Information (OSTI.GOV)

VanderNoot, Victoria A.; Haroldsen, Brent L.; Renzi, Ronald F.

2010-03-01

In a multiyear research agreement with Tenix Investments Pty. Ltd., Sandia has been developing field deployable technologies for detection of biotoxins in water supply systems. The unattended water sensor or UWS employs microfluidic chip based gel electrophoresis for monitoring biological analytes in a small integrated sensor platform. This instrument collects, prepares, and analyzes water samples in an automated manner. Sample analysis is done using the {mu}ChemLab{trademark} analysis module. This report uses analysis results of two datasets collected using the UWS to estimate performance of the device. The first dataset is made up of samples containing ricin at varying concentrations andmore » is used for assessing instrument response and detection probability. The second dataset is comprised of analyses of water samples collected at a water utility which are used to assess the false positive probability. The analyses of the two sets are used to estimate the Receiver Operating Characteristic or ROC curves for the device at one set of operational and detection algorithm parameters. For these parameters and based on a statistical estimate, the ricin probability of detection is about 0.9 at a concentration of 5 nM for a false positive probability of 1 x 10{sup -6}.« less

Validation of the sperm class analyser CASA system for sperm counting in a busy diagnostic semen analysis laboratory.

PubMed

Dearing, Chey G; Kilburn, Sally; Lindsay, Kevin S

2014-03-01

Sperm counts have been linked to several fertility outcomes making them an essential parameter of semen analysis. It has become increasingly recognised that Computer-Assisted Semen Analysis (CASA) provides improved precision over manual methods but that systems are seldom validated robustly for use. The objective of this study was to gather the evidence to validate or reject the Sperm Class Analyser (SCA) as a tool for routine sperm counting in a busy laboratory setting. The criteria examined were comparison with the Improved Neubauer and Leja 20-μm chambers, within and between field precision, sperm concentration linearity from a stock diluted in semen and media, accuracy against internal and external quality material, assessment of uneven flow effects and a receiver operating characteristic (ROC) analysis to predict fertility in comparison with the Neubauer method. This work demonstrates that SCA CASA technology is not a standalone 'black box', but rather a tool for well-trained staff that allows rapid, high-number sperm counting providing errors are identified and corrected. The system will produce accurate, linear, precise results, with less analytical variance than manual methods that correlate well against the Improved Neubauer chamber. The system provides superior predictive potential for diagnosing fertility problems.

Short versions of two specific phobia measures: The snake and the spider questionnaires.

PubMed

Zsido, Andras N; Arato, Nikolett; Inhof, Orsolya; Janszky, Jozsef; Darnai, Gergely

2018-03-01

Zoophobias are the most prevalent form of specific phobia worldwide. Two of the most widely used measures, the Snake Questionnaire (SNAQ) and Spider Questionnaire (SPQ) are good indicators of specific fears, but researchers have recognised that shorter, yet nevertheless reliable measures are needed. Hence the aims of this research were to develop short forms of the SNAQ and SPQ using item response theory and to use receiver operating characteristic (ROC) curve analyses to determine cut-offs for use in future research. Twelve-item versions of both scales (SNAQ-12 and SPQ-12) demonstrated excellent discrimination along the latent continuum in a sample of 1354 people. The SNAQ-12 and SPQ-12 showed excellent reliability and were highly correlated with the corresponding full-length scale. The scales discriminated between participants who reported snake (3.25%) or spider (8.05%) phobia and those who did not. Further analyses revealed that non-phobic women report higher fear of both snakes and spiders than do men, but this difference was not present in phobics. These findings suggest that the SNAQ-12 and SPQ-12 have considerable strengths, including shorter assessment and scoring times, whilst retaining high reliability and potential utility as a clinical screening tool. Copyright © 2017 Elsevier Ltd. All rights reserved.

Correlation between model observer and human observer performance in CT imaging when lesion location is uncertain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leng, Shuai; Yu, Lifeng; Zhang, Yi

2013-08-15

Purpose: The purpose of this study was to investigate the correlation between model observer and human observer performance in CT imaging for the task of lesion detection and localization when the lesion location is uncertain.Methods: Two cylindrical rods (3-mm and 5-mm diameters) were placed in a 35 × 26 cm torso-shaped water phantom to simulate lesions with −15 HU contrast at 120 kV. The phantom was scanned 100 times on a 128-slice CT scanner at each of four dose levels (CTDIvol = 5.7, 11.4, 17.1, and 22.8 mGy). Regions of interest (ROIs) around each lesion were extracted to generate imagesmore » with signal-present, with each ROI containing 128 × 128 pixels. Corresponding ROIs of signal-absent images were generated from images without lesion mimicking rods. The location of the lesion (rod) in each ROI was randomly distributed by moving the ROIs around each lesion. Human observer studies were performed by having three trained observers identify the presence or absence of lesions, indicating the lesion location in each image and scoring confidence for the detection task on a 6-point scale. The same image data were analyzed using a channelized Hotelling model observer (CHO) with Gabor channels. Internal noise was added to the decision variables for the model observer study. Area under the curve (AUC) of ROC and localization ROC (LROC) curves were calculated using a nonparametric approach. The Spearman's rank order correlation between the average performance of the human observers and the model observer performance was calculated for the AUC of both ROC and LROC curves for both the 3- and 5-mm diameter lesions.Results: In both ROC and LROC analyses, AUC values for the model observer agreed well with the average values across the three human observers. The Spearman's rank order correlation values for both ROC and LROC analyses for both the 3- and 5-mm diameter lesions were all 1.0, indicating perfect rank ordering agreement of the figures of merit (AUC) between the average performance of the human observers and the model observer performance.Conclusions: In CT imaging of different sizes of low-contrast lesions (−15 HU), the performance of CHO with Gabor channels was highly correlated with human observer performance for the detection and localization tasks with uncertain lesion location in CT imaging at four clinically relevant dose levels. This suggests the ability of Gabor CHO model observers to meaningfully assess CT image quality for the purpose of optimizing scan protocols and radiation dose levels in detection and localization tasks for low-contrast lesions.« less

Head-to-head comparison of procalcitonin and presepsin for the diagnosis of sepsis in critically ill adult patients: a protocol for a systematic review and meta-analysis.

PubMed

Hayashida, Kei; Kondo, Yutaka; Hara, Yoshitaka; Aihara, Morio; Yamakawa, Kazuma

2017-03-06

Early diagnosis and immediate therapeutic intervention, including appropriate antibiotic therapy and goal-directed resuscitation, are necessary to reduce mortality in patients with sepsis. However, a single clinical or biological marker indicative of sepsis has not been adopted unanimously. Although procalcitonin and presepsin are promising biomarkers that can effectively differentiate between sepsis/infection and systemic inflammatory response syndrome of non-infectious origin, little is known about which marker is superior. We will conduct a systematic review and meta-analysis of procalcitonin and presepsin for the diagnosis of sepsis/infection in critically ill adult patients. The primary objective is to evaluate the diagnostic accuracy of these 2 biomarkers to a reference standard of sepsis/infection and to compare the diagnostic accuracy with each other. We will search electronic bibliographic databases such as MEDLINE, EMBASE and Cochrane Central Register of Controlled Trials for retrospective and prospective diagnostic test studies. We will assign 2 reviewers to review all collected titles and associated abstracts, review full articles, and extract study data. We will use the Quality of Diagnostic Accuracy Studies-II tool to report study characteristics and to evaluate methodological quality. If pooling is possible, we will use bivariate random effects and hierarchical summary receiver operating characteristic (ROC) models to calculate parameter estimates to output summary ROCs, pooled sensitivity and specificity data, and 95% CIs around the summary operating point. We will also assess heterogeneity via clinical and methodological subgroup and sensitivity analyses. This systematic review will provide guidance on the triage of these tests, help to determine whether existing tests should be revised or replaced, and may also identify knowledge gaps in sepsis diagnosis that could direct further research in the field. Research ethics is not required for this review. The findings will be reported at conferences and in peer-reviewed publications. CRD42016035784. 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/.

Towards real-time topical detection and characterization of FDG dose infiltration prior to PET imaging.

PubMed

Williams, Jason M; Arlinghaus, Lori R; Rani, Sudheer D; Shone, Martha D; Abramson, Vandana G; Pendyala, Praveen; Chakravarthy, A Bapsi; Gorge, William J; Knowland, Joshua G; Lattanze, Ronald K; Perrin, Steven R; Scarantino, Charles W; Townsend, David W; Abramson, Richard G; Yankeelov, Thomas E

2016-12-01

To dynamically detect and characterize 18 F-fluorodeoxyglucose (FDG) dose infiltrations and evaluate their effects on positron emission tomography (PET) standardized uptake values (SUV) at the injection site and in control tissue. Investigational gamma scintillation sensors were topically applied to patients with locally advanced breast cancer scheduled to undergo limited whole-body FDG-PET as part of an ongoing clinical study. Relative to the affected breast, sensors were placed on the contralateral injection arm and ipsilateral control arm during the resting uptake phase prior to each patient's PET scan. Time-activity curves (TACs) from the sensors were integrated at varying intervals (0-10, 0-20, 0-30, 0-40, and 30-40 min) post-FDG and the resulting areas under the curve (AUCs) were compared to SUVs obtained from PET. In cases of infiltration, observed in three sensor recordings (30 %), the injection arm TAC shape varied depending on the extent and severity of infiltration. In two of these cases, TAC characteristics suggested the infiltration was partially resolving prior to image acquisition, although it was still apparent on subsequent PET. Areas under the TAC 0-10 and 0-20 min post-FDG were significantly different in infiltrated versus non-infiltrated cases (Mann-Whitney, p < 0.05). When normalized to control, all TAC integration intervals from the injection arm were significantly correlated with SUV peak and SUV max measured over the infiltration site (Spearman ρ ≥ 0.77, p < 0.05). Receiver operating characteristic (ROC) analyses, testing the ability of the first 10 min of post-FDG sensor data to predict infiltration visibility on the ensuing PET, yielded an area under the ROC curve of 0.92. Topical sensors applied near the injection site provide dynamic information from the time of FDG administration through the uptake period and may be useful in detecting infiltrations regardless of PET image field of view. This dynamic information may also complement the static PET image to better characterize the true extent of infiltrations.

The development and testing of a skin tear risk assessment tool.

PubMed

Newall, Nelly; Lewin, Gill F; Bulsara, Max K; Carville, Keryln J; Leslie, Gavin D; Roberts, Pam A

2017-02-01

The aim of the present study is to develop a reliable and valid skin tear risk assessment tool. The six characteristics identified in a previous case control study as constituting the best risk model for skin tear development were used to construct a risk assessment tool. The ability of the tool to predict skin tear development was then tested in a prospective study. Between August 2012 and September 2013, 1466 tertiary hospital patients were assessed at admission and followed up for 10 days to see if they developed a skin tear. The predictive validity of the tool was assessed using receiver operating characteristic (ROC) analysis. When the tool was found not to have performed as well as hoped, secondary analyses were performed to determine whether a potentially better performing risk model could be identified. The tool was found to have high sensitivity but low specificity and therefore have inadequate predictive validity. Secondary analysis of the combined data from this and the previous case control study identified an alternative better performing risk model. The tool developed and tested in this study was found to have inadequate predictive validity. The predictive validity of an alternative, more parsimonious model now needs to be tested. © 2015 Medicalhelplines.com Inc and John Wiley & Sons Ltd.

Russian Orthodox Culture or Russian Orthodox Teaching? Reflections on the Textbooks in Religious Education in Contemporary Russia

ERIC Educational Resources Information Center

Shnirelman, Victor A.

2012-01-01

A new textbook in religious education is analysed, first, in comparison to earlier ones, and, second, with respect to its content and goals. The aim of the Russian Orthodox Church (ROC) is threefold--to educate into religion, to foster the ethnic Russian identity and to make youngsters loyal to the state. Actually, the state rather than society is…

Groundwater potential mapping using C5.0, random forest, and multivariate adaptive regression spline models in GIS.

PubMed

Golkarian, Ali; Naghibi, Seyed Amir; Kalantar, Bahareh; Pradhan, Biswajeet

2018-02-17

Ever increasing demand for water resources for different purposes makes it essential to have better understanding and knowledge about water resources. As known, groundwater resources are one of the main water resources especially in countries with arid climatic condition. Thus, this study seeks to provide groundwater potential maps (GPMs) employing new algorithms. Accordingly, this study aims to validate the performance of C5.0, random forest (RF), and multivariate adaptive regression splines (MARS) algorithms for generating GPMs in the eastern part of Mashhad Plain, Iran. For this purpose, a dataset was produced consisting of spring locations as indicator and groundwater-conditioning factors (GCFs) as input. In this research, 13 GCFs were selected including altitude, slope aspect, slope angle, plan curvature, profile curvature, topographic wetness index (TWI), slope length, distance from rivers and faults, rivers and faults density, land use, and lithology. The mentioned dataset was divided into two classes of training and validation with 70 and 30% of the springs, respectively. Then, C5.0, RF, and MARS algorithms were employed using R statistical software, and the final values were transformed into GPMs. Finally, two evaluation criteria including Kappa and area under receiver operating characteristics curve (AUC-ROC) were calculated. According to the findings of this research, MARS had the best performance with AUC-ROC of 84.2%, followed by RF and C5.0 algorithms with AUC-ROC values of 79.7 and 77.3%, respectively. The results indicated that AUC-ROC values for the employed models are more than 70% which shows their acceptable performance. As a conclusion, the produced methodology could be used in other geographical areas. GPMs could be used by water resource managers and related organizations to accelerate and facilitate water resource exploitation.

A new method to predict anatomical outcome after idiopathic macular hole surgery.

PubMed

Liu, Peipei; Sun, Yaoyao; Dong, Chongya; Song, Dan; Jiang, Yanrong; Liang, Jianhong; Yin, Hong; Li, Xiaoxin; Zhao, Mingwei

2016-04-01

To investigate whether a new macular hole closure index (MHCI) could predict anatomic outcome of macular hole surgery. A vitrectomy with internal limiting membrane peeling, air-fluid exchange, and gas tamponade were performed on all patients. The postoperative anatomic status of the macular hole was defined by spectral-domain OCT. MHCI was calculated as (M+N)/BASE based on the preoperative OCT status. M and N were the curve lengths of the detached photoreceptor arms, and BASE was the length of the retinal pigment epithelial layer (RPE layer) detaching from the photoreceptors. Postoperative anatomical outcomes were divided into three grades: A (bridge-like closure), B (good closure), and C (poor closure or no closure). Correlation analysis was performed between anatomical outcomes and MHCI. Receiver operating characteristic (ROC) curves were derived for MHCI, indicating good model discrimination. ROC curves were also assessed by the area under the curve, and cut-offs were calculated. Other predictive parameters reported previously, which included the MH minimum, the MH height, the macular hole index (MHI), the diameter hole index (DHI), and the tractional hole index (THI) had been compared as well. MHCI correlated significantly with postoperative anatomical outcomes (r = 0.543, p = 0.000), but other predictive parameters did not. The areas under the curves indicated that MHCI could be used as an effective predictor of anatomical outcome. Cut-off values of 0.7 and 1.0 were obtained for MHCI from ROC curve analysis. MHCI demonstrated a better predictive effect than other parameters, both in the correlation analysis and ROC analysis. MHCI could be an easily measured and accurate predictive index for postoperative anatomical outcomes.

Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity

PubMed Central

Bosch-Bayard, Jorge; Galán-García, Lídice; Fernandez, Thalia; Lirio, Rolando B.; Bringas-Vega, Maria L.; Roca-Stappung, Milene; Ricardo-Garcell, Josefina; Harmony, Thalía; Valdes-Sosa, Pedro A.

2018-01-01

In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to) different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS) disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia), Mathematics (Dyscalculia), or Writing (Dysgraphia). By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented. PMID:29379411

Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity.

PubMed

Bosch-Bayard, Jorge; Galán-García, Lídice; Fernandez, Thalia; Lirio, Rolando B; Bringas-Vega, Maria L; Roca-Stappung, Milene; Ricardo-Garcell, Josefina; Harmony, Thalía; Valdes-Sosa, Pedro A

2017-01-01

In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to) different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS) disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia), Mathematics (Dyscalculia), or Writing (Dysgraphia). By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented.

Digital mammography: observer performance study of the effects of pixel size on radiologists' characterization of malignant and benign microcalcifications

NASA Astrophysics Data System (ADS)

Chan, Heang-Ping; Helvie, Mark A.; Petrick, Nicholas; Sahiner, Berkman; Adler, Dorit D.; Blane, Caroline E.; Joynt, Lynn K.; Paramagul, Chintana; Roubidoux, Marilyn A.; Wilson, Todd E.; Hadjiiski, Lubomir M.; Goodsitt, Mitchell M.

1999-05-01

A receiver operating characteristic (ROC) experiment was conducted to evaluate the effects of pixel size on the characterization of mammographic microcalcifications. Digital mammograms were obtained by digitizing screen-film mammograms with a laser film scanner. One hundred twelve two-view mammograms with biopsy-proven microcalcifications were digitized at a pixel size of 35 micrometer X 35 micrometer. A region of interest (ROI) containing the microcalcifications was extracted from each image. ROI images with pixel sizes of 70 micrometers, 105 micrometers, and 140 micrometers were derived from the ROI of 35 micrometer pixel size by averaging 2 X 2, 3 X 3, and 4 X 4 neighboring pixels, respectively. The ROI images were printed on film with a laser imager. Seven MQSA-approved radiologists participated as observers. The likelihood of malignancy of the microcalcifications was rated on a 10-point confidence rating scale and analyzed with ROC methodology. The classification accuracy was quantified by the area, Az, under the ROC curve. The statistical significance of the differences in the Az values for different pixel sizes was estimated with the Dorfman-Berbaum-Metz (DBM) method for multi-reader, multi-case ROC data. It was found that five of the seven radiologists demonstrated a higher classification accuracy with the 70 micrometer or 105 micrometer images. The average Az also showed a higher classification accuracy in the range of 70 to 105 micrometer pixel size. However, the differences in A(subscript z/ between different pixel sizes did not achieve statistical significance. The low specificity of image features of microcalcifications an the large interobserver and intraobserver variabilities may have contributed to the relatively weak dependence of classification accuracy on pixel size.

Influences on emergency department length of stay for older people.

PubMed

Street, Maryann; Mohebbi, Mohammadreza; Berry, Debra; Cross, Anthony; Considine, Julie

2018-02-14

The aim of this study was to examine the influences on emergency department (ED) length of stay (LOS) for older people and develop a predictive model for an ED LOS more than 4 h. This retrospective cohort study used organizational data linkage at the patient level from a major Australian health service. The study population was aged 65 years or older, attending an ED during the 2013/2014 financial year. We developed and internally validated a clinical prediction rule. Discriminatory performance of the model was evaluated by receiver operating characteristic (ROC) curve analysis. An integer-based risk score was developed using multivariate logistic regression. The risk score was evaluated using ROC analysis. There were 33 926 ED attendances: 57.5% (n=19 517) had an ED LOS more than 4 h. The area under ROC for age, usual accommodation, triage category, arrival by ambulance, arrival overnight, imaging, laboratory investigations, overcrowding, time to be seen by doctor, ED visits with admission and access block relating to ED LOS more than 4 h was 0.796, indicating good performance. In the validation set, area under ROC was 0.80, P-value was 0.36 and prediction mean square error was 0.18, indicating good calibration. The risk score value attributed to each risk factor ranged from 2 to 68 points. The clinical prediction rule stratified patients into five levels of risk on the basis of the total risk score. Objective identification of older people at intermediate and high risk of an ED LOS more than 4 h early in ED care enables targeted approaches to streamline the patient journey, decrease ED LOS and optimize emergency care for older people.

Analytical and clinical performance of thyroglobulin autoantibody assays in thyroid cancer follow-up.

PubMed

Katrangi, Waddah; Grebe, Stephan K G; Algeciras-Schimnich, Alicia

2017-10-26

While thyroglobulin autoantibodies (TgAb) can result in false low serum thyroglobulin (Tg) immunoassay (IA) measurements, they might also be indicators of disease persistence/recurrence. Hence, accurate TgAb measurement, in addition to Tg quantification, is crucial for thyroid cancer monitoring. We compared the analytical and clinical performance of four commonly used TgAb IAs. We measured Tg by mass spectrometry (Tg-MS) and by four pairs of Tg and TgAb IAs (Beckman, Roche, Siemens, Thermo) in 576 samples. Limit of quantitation (LOQ) and manufacturers' upper reference interval cut-off (URI) were used for comparisons. Clinical performance was assessed by receiving operator characteristics (ROC) curve analysis. Quantitative and qualitative agreement between TgAb-IAs was moderate with R2 of 0.20-0.70 and κ from 0.41-0.66 using LOQ and 0.47-0.71 using URI. In samples with TgAb interference, detection rates of TgAb were similar using LOQ and URI for Beckman, Siemens, and Thermo, but much lower for the Roche TgAb-IA when the URI was used. In TgAb positive cases, the ROC areas under the curve (AUC) for the TgAb-IAs were 0.59 (Beckman), 0.62 (Siemens), 0.59 (Roche), and 0.59 (Thermo), similar to ROC AUCs achieved with Tg. Combining Tg and TgAb measurements improved the ROC AUCs compared to Tg or TgAb alone. TgAb-IAs show significant qualitative and quantitative differences. For 2 of the 4 TgAb-IAs, using the LOQ improves the detection of interfering TgAbs. All assays showed suboptimal clinical performance when used as surrogate markers of disease, with modest improvements when Tg and TgAb were combined.

A comparison of confidence/credible interval methods for the area under the ROC curve for continuous diagnostic tests with small sample size.

PubMed

Feng, Dai; Cortese, Giuliana; Baumgartner, Richard

2017-12-01

The receiver operating characteristic (ROC) curve is frequently used as a measure of accuracy of continuous markers in diagnostic tests. The area under the ROC curve (AUC) is arguably the most widely used summary index for the ROC curve. Although the small sample size scenario is common in medical tests, a comprehensive study of small sample size properties of various methods for the construction of the confidence/credible interval (CI) for the AUC has been by and large missing in the literature. In this paper, we describe and compare 29 non-parametric and parametric methods for the construction of the CI for the AUC when the number of available observations is small. The methods considered include not only those that have been widely adopted, but also those that have been less frequently mentioned or, to our knowledge, never applied to the AUC context. To compare different methods, we carried out a simulation study with data generated from binormal models with equal and unequal variances and from exponential models with various parameters and with equal and unequal small sample sizes. We found that the larger the true AUC value and the smaller the sample size, the larger the discrepancy among the results of different approaches. When the model is correctly specified, the parametric approaches tend to outperform the non-parametric ones. Moreover, in the non-parametric domain, we found that a method based on the Mann-Whitney statistic is in general superior to the others. We further elucidate potential issues and provide possible solutions to along with general guidance on the CI construction for the AUC when the sample size is small. Finally, we illustrate the utility of different methods through real life examples.

Magnetic Resonance Imaging of Intracranial Hypotension: Diagnostic Value of Combined Qualitative Signs and Quantitative Metrics.

PubMed

Aslan, Kerim; Gunbey, Hediye Pinar; Tomak, Leman; Ozmen, Zafer; Incesu, Lutfi

The aim of this study was to investigate whether the use of combination quantitative metrics (mamillopontine distance [MPD], pontomesencephalic angle, and mesencephalon anterior-posterior/medial-lateral diameter ratios) with qualitative signs (dural enhancement, subdural collections/hematoma, venous engorgement, pituitary gland enlargements, and tonsillar herniations) provides a more accurate diagnosis of intracranial hypotension (IH). The quantitative metrics and qualitative signs of 34 patients and 34 control subjects were assessed by 2 independent observers. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of quantitative metrics and qualitative signs, and for the diagnosis of IH, optimum cutoff values of quantitative metrics were found with ROC analysis. Combined ROC curve was measured for the quantitative metrics, and qualitative signs combinations in determining diagnostic accuracy and sensitivity, specificity, and positive and negative predictive values were found, and the best model combination was formed. Whereas MPD and pontomesencephalic angle were significantly lower in patients with IH when compared with the control group (P < 0.001), mesencephalon anterior-posterior/medial-lateral diameter ratio was significantly higher (P < 0.001). For qualitative signs, the highest individual distinctive power was dural enhancement with area under the ROC curve (AUC) of 0.838. For quantitative metrics, the highest individual distinctive power was MPD with AUC of 0.947. The best accuracy in the diagnosis of IH was obtained by combination of dural enhancement, venous engorgement, and MPD with an AUC of 1.00. This study showed that the combined use of dural enhancement, venous engorgement, and MPD had diagnostic accuracy of 100 % for the diagnosis of IH. Therefore, a more accurate IH diagnosis can be provided with combination of quantitative metrics with qualitative signs.

Diagnostic accuracy of routine blood examinations and CSF lactate level for post-neurosurgical bacterial meningitis.

PubMed

Zhang, Yang; Xiao, Xiong; Zhang, Junting; Gao, Zhixian; Ji, Nan; Zhang, Liwei

2017-06-01

To evaluate the diagnostic accuracy of routine blood examinations and Cerebrospinal Fluid (CSF) lactate level for Post-neurosurgical Bacterial Meningitis (PBM) at a large sample-size of post-neurosurgical patients. The diagnostic accuracies of routine blood examinations and CSF lactate level to distinguish between PAM and PBM were evaluated with the values of the Area Under the Curve of the Receiver Operating Characteristic (AUC -ROC ) by retrospectively analyzing the datasets of post-neurosurgical patients in the clinical information databases. The diagnostic accuracy of routine blood examinations was relatively low (AUC -ROC <0.7). The CSF lactate level achieved rather high diagnostic accuracy (AUC -ROC =0.891; CI 95%, 0.852-0.922). The variables of patient age, operation duration, surgical diagnosis and postoperative days (the interval days between the neurosurgery and examinations) were shown to affect the diagnostic accuracy of these examinations. The variables were integrated with routine blood examinations and CSF lactate level by Fisher discriminant analysis to improve their diagnostic accuracy. As a result, the diagnostic accuracy of blood examinations and CSF lactate level was significantly improved with an AUC -ROC value=0.760 (CI 95%, 0.737-0.782) and 0.921 (CI 95%, 0.887-0.948) respectively. The PBM diagnostic accuracy of routine blood examinations was relatively low, whereas the accuracy of CSF lactate level was high. Some variables that are involved in the incidence of PBM can also affect the diagnostic accuracy for PBM. Taking into account the effects of these variables significantly improves the diagnostic accuracies of routine blood examinations and CSF lactate level. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Tumor necrosis factor receptor 1 (TNFRI) for ventilator-associated pneumonia diagnosis by cytokine multiplex analysis.

PubMed

Martin-Loeches, Ignacio; Bos, Lieuwe D; Povoa, Pedro; Ramirez, Paula; Schultz, Marcus J; Torres, Antoni; Artigas, Antonio

2015-12-01

The diagnosis of ventilator-associated pneumonia (VAP) is challenging. An important aspect to improve outcome is early recognition of VAP and the initiation of the appropriate empirical treatment. We hypothesized that biological markers in plasma can rule out VAP at the moment of clinical suspicion and could rule in VAP before the diagnosis can be made clinically. In this prospective study, patients with VAP (n = 24, microbiology confirmed) were compared to controls (n = 19) with a similar duration of mechanical ventilation. Blood samples from the day of VAP diagnosis and 1 and 3 days before were analyzed with a multiplex array for markers of inflammation, coagulation, and apoptosis. The best biomarker combination was selected and the diagnostic accuracy was given by the area under the receiver operating characteristic curve (ROC-AUC). TNF-receptor 1 (TNFRI) and granulocyte colony-stimulating factor (GCSF) were selected as optimal biomarkers at the day of VAP diagnosis, which resulted in a ROC-AUC of 0.96, with excellent sensitivity. Three days before the diagnosis TNFRI and plasminogen activator inhibitor-1 (PAI-1) levels in plasma predicted VAP with a ROC-AUC of 0.79. The slope of IL-10 and PAI-1 resulted in a ROC-AUC of 0.77. These biomarkers improved the classification of the clinical pulmonary infection score when combined. Concentration of TNFRI and PAI-1 and the slope of PAI-1 and IL-10 may be used to predict the development of VAP as early as 3 days before the diagnosis made clinically. TNFRI and GCSF may be used to exclude VAP at the moment of clinical suspicion. Especially TNFRI seems to be a promising marker for the prediction and diagnosis of VAP.

MYC and Human Telomerase Gene (TERC) Copy Number Gain in Early-stage Non–small Cell Lung Cancer

PubMed Central

Flacco, Antonella; Ludovini, Vienna; Bianconi, Fortunato; Ragusa, Mark; Bellezza, Guido; Tofanetti, Francesca R.; Pistola, Lorenza; Siggillino, Annamaria; Vannucci, Jacopo; Cagini, Lucio; Sidoni, Angelo; Puma, Francesco; Varella-Garcia, Marileila; Crinò, Lucio

2015-01-01

Objectives We investigated the frequency of MYC and TERC increased gene copy number (GCN) in early-stage non–small cell lung cancer (NSCLC) and evaluated the correlation of these genomic imbalances with clinicopathologic parameters and outcome. Materials and Methods Tumor tissues were obtained from 113 resected NSCLCs. MYC and TERC GCNs were tested by fluorescence in situ hybridization (FISH) according to the University of Colorado Cancer Center (UCCC) criteria and based on the receiver operating characteristic (ROC) classification. Results When UCCC criteria were applied, 41 (36%) cases for MYC and 41 (36%) cases for TERC were considered FISH-positive. MYC and TERC concurrent FISH-positive was observed in 12 cases (11%): 2 (17%) cases with gene amplification and 10 (83%) with high polysomy. By using the ROC analysis, high MYC (mean ≥2.83 copies/cell) and TERC (mean ≥2.65 copies/cell) GCNs were observed in 60 (53.1%) cases and 58 (51.3%) cases, respectively. High TERC GCN was associated with squamous cell carcinoma (SCC) histology (P = 0.001). In univariate analysis, increased MYC GCN was associated with shorter overall survival (P = 0.032 [UCCC criteria] or P = 0.02 [ROC classification]), whereas high TERC GCN showed no association. In multivariate analysis including stage and age, high MYC GCN remained significantly associated with worse overall survival using both the UCCC criteria (P = 0.02) and the ROC classification (P = 0.008). Conclusions Our results confirm MYC as frequently amplified in early-stage NSCLC and increased MYC GCN as a strong predictor of worse survival. Increased TERC GCN does not have prognostic impact but has strong association with squamous histology. PMID:25806711

Pulse Oximetry for the Detection of Obstructive Sleep Apnea Syndrome: Can the Memory Capacity of Oxygen Saturation Influence Their Diagnostic Accuracy?

PubMed Central

Nigro, Carlos A.; Dibur, Eduardo; Rhodius, Edgardo

2011-01-01

Objective. To assess the diagnostic ability of WristOx 3100 using its three different recording settings in patients with suspected obstructive sleep apnea syndrome (OSAS). Methods. All participants (135) performed the oximetry (three oximeters WristOx 3100) and polysomnography (PSG) simultaneously in the sleep laboratory. Both recordings were interpreted blindly. Each oximeter was set to one of three different recording settings (memory capabilities 0.25, 0.5, and 1 Hz). The software (nVision 5.1) calculated the adjusted O2 desaturation index-mean number of O2 desaturation per hour of analyzed recording ≥2, 3, and 4% (ADI2, 3, and 4). The ADI2, 3, and 4 cutoff points that better discriminated between subjects with or without OSAS arose from the receiver-operator characteristics (ROCs) curve analysis. OSAS was defined as a respiratory disturbance index (RDI) ≥ 5. Results. 101 patients were included (77 men, mean age 52, median RDI 22.6, median BMI 27.4 kg/m2). The area under the ROCs curves (AUC-ROCs) of ADI2, 3, and 4 with different data storage rates were similar (AUC-ROCs with data storage rates of 0.25/0.5/1 Hz: ADI2: 0.958/0.948/0.965, ADI3: 0.961/0.95/0.966, and ADI4: 0.957/0.949/0.963, P NS). Conclusions. The ability of WristOx 3100 to detect patients with OSAS was not affected by the data storage rate of the oxygen saturation signal. Both memory capacity of 0.25, 0.5, or 1 Hz showed a similar performance for the diagnosis of OSAS. PMID:23471171

Plateletpheresis efficiency and mathematical correction of software-derived platelet yield prediction: A linear regression and ROC modeling approach.

PubMed

Jaime-Pérez, José Carlos; Jiménez-Castillo, Raúl Alberto; Vázquez-Hernández, Karina Elizabeth; Salazar-Riojas, Rosario; Méndez-Ramírez, Nereida; Gómez-Almaguer, David

2017-10-01

Advances in automated cell separators have improved the efficiency of plateletpheresis and the possibility of obtaining double products (DP). We assessed cell processor accuracy of predicted platelet (PLT) yields with the goal of a better prediction of DP collections. This retrospective proof-of-concept study included 302 plateletpheresis procedures performed on a Trima Accel v6.0 at the apheresis unit of a hematology department. Donor variables, software predicted yield and actual PLT yield were statistically evaluated. Software prediction was optimized by linear regression analysis and its optimal cut-off to obtain a DP assessed by receiver operating characteristic curve (ROC) modeling. Three hundred and two plateletpheresis procedures were performed; in 271 (89.7%) occasions, donors were men and in 31 (10.3%) women. Pre-donation PLT count had the best direct correlation with actual PLT yield (r = 0.486. P < .001). Means of software machine-derived values differed significantly from actual PLT yield, 4.72 × 10 11 vs.6.12 × 10 11 , respectively, (P < .001). The following equation was developed to adjust these values: actual PLT yield= 0.221 + (1.254 × theoretical platelet yield). ROC curve model showed an optimal apheresis device software prediction cut-off of 4.65 × 10 11 to obtain a DP, with a sensitivity of 82.2%, specificity of 93.3%, and an area under the curve (AUC) of 0.909. Trima Accel v6.0 software consistently underestimated PLT yields. Simple correction derived from linear regression analysis accurately corrected this underestimation and ROC analysis identified a precise cut-off to reliably predict a DP. © 2016 Wiley Periodicals, Inc.

Prediction of missing common genes for disease pairs using network based module separation on incomplete human interactome.

PubMed

Akram, Pakeeza; Liao, Li

2017-12-06

Identification of common genes associated with comorbid diseases can be critical in understanding their pathobiological mechanism. This work presents a novel method to predict missing common genes associated with a disease pair. Searching for missing common genes is formulated as an optimization problem to minimize network based module separation from two subgraphs produced by mapping genes associated with disease onto the interactome. Using cross validation on more than 600 disease pairs, our method achieves significantly higher average receiver operating characteristic ROC Score of 0.95 compared to a baseline ROC score 0.60 using randomized data. Missing common genes prediction is aimed to complete gene set associated with comorbid disease for better understanding of biological intervention. It will also be useful for gene targeted therapeutics related to comorbid diseases. This method can be further considered for prediction of missing edges to complete the subgraph associated with disease pair.

The new powder diffractometer D1B of the Institut Laue Langevin

NASA Astrophysics Data System (ADS)

Puente Orench, I.; Clergeau, J. F.; Martínez, S.; Olmos, M.; Fabelo, O.; Campo, J.

2014-11-01

D1B is a medium resolution high flux powder diffractometer located at the Institut Laue Langevin, ILL. D1B a suitable instrument for studying a large variety of polycrystalline materials. D1B runs since 1998 as a CRG (collaborating research group) instrument, being exploited by the CNRS (Centre National de la Recherche Scientifique, France) and CSIC (Consejo Superior de Investigaciones Cientificas, Spain). In 2008 the Spanish CRG started an updating program which included a new detector and a radial oscillating collimator (ROC). The detector, which has a sensitive height of 100mm, covers an angular range of 128°. Its 1280 gold wires provide a neutron detection point every 0.1°. The ROC is made of 198 gadolinium- based absorbing collimation blades, regular placed every 0.67°. Here the present characteristics of D1B are reviewed and the different experimental performances will be presented.

Artificial neural network study on organ-targeting peptides

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Kim, Junhyoung; Choi, Seung-Hoon; Kim, Minkyoung; Rhee, Hokyoung; Shin, Jae-Min; Choi, Kihang; Kang, Sang-Kee; Lee, Nam Kyung; Choi, Yun-Jaie; Jung, Dong Hyun

2010-01-01

We report a new approach to studying organ targeting of peptides on the basis of peptide sequence information. The positive control data sets consist of organ-targeting peptide sequences identified by the peroral phage-display technique for four organs, and the negative control data are prepared from random sequences. The capacity of our models to make appropriate predictions is validated by statistical indicators including sensitivity, specificity, enrichment curve, and the area under the receiver operating characteristic (ROC) curve (the ROC score). VHSE descriptor produces statistically significant training models and the models with simple neural network architectures show slightly greater predictive power than those with complex ones. The training and test set statistics indicate that our models could discriminate between organ-targeting and random sequences. We anticipate that our models will be applicable to the selection of organ-targeting peptides for generating peptide drugs or peptidomimetics.

Nonparametric EROC analysis for observer performance evaluation on joint detection and estimation tasks

NASA Astrophysics Data System (ADS)

Wunderlich, Adam; Goossens, Bart

2014-03-01

The majority of the literature on task-based image quality assessment has focused on lesion detection tasks, using the receiver operating characteristic (ROC) curve, or related variants, to measure performance. However, since many clinical image evaluation tasks involve both detection and estimation (e.g., estimation of kidney stone composition, estimation of tumor size), there is a growing interest in performance evaluation for joint detection and estimation tasks. To evaluate observer performance on such tasks, Clarkson introduced the estimation ROC (EROC) curve, and the area under the EROC curve as a summary figure of merit. In the present work, we propose nonparametric estimators for practical EROC analysis from experimental data, including estimators for the area under the EROC curve and its variance. The estimators are illustrated with a practical example comparing MRI images reconstructed from different k-space sampling trajectories.

A concordance index for matched case-control studies with applications in cancer risk.

PubMed

Brentnall, Adam R; Cuzick, Jack; Field, John; Duffy, Stephen W

2015-02-10

In unmatched case-control studies, the area under the receiver operating characteristic (ROC) curve (AUC) may be used to measure how well a variable discriminates between cases and controls. The AUC is sometimes used in matched case-control studies by ignoring matching, but it lacks interpretation because it is not based on an estimate of the ROC for the population of interest. We introduce an alternative measure of discrimination that is the concordance of risk factors conditional on the matching factors. Parametric and non-parametric estimators are given for different matching scenarios, and applied to real data from breast and lung cancer case-control studies. Diagnostic plots to verify the constancy of discrimination over matching factors are demonstrated. The proposed simple measure is easy to use, interpret, more efficient than unmatched AUC statistics and may be applied to compare the conditional discrimination performance of risk factors. Copyright © 2014 John Wiley & Sons, Ltd.

Signal Detection Theory Applied to Helicopter Transmission Diagnostic Thresholds

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Keller, Jonathan A.; Wade, Daniel R.

2008-01-01

Helicopter Health Usage Monitoring Systems (HUMS) have potential for providing data to support increasing the service life of a dynamic mechanical component in the transmission of a helicopter. Data collected can demonstrate the HUMS condition indicator responds to a specific component fault with appropriate alert limits and minimal false alarms. Defining thresholds for specific faults requires a tradeoff between the sensitivity of the condition indicator (CI) limit to indicate damage and the number of false alarms. A method using Receiver Operating Characteristic (ROC) curves to assess CI performance was demonstrated using CI data collected from accelerometers installed on several UH60 Black Hawk and AH64 Apache helicopters and an AH64 helicopter component test stand. Results of the analysis indicate ROC curves can be used to reliably assess the performance of commercial HUMS condition indicators to detect damaged gears and bearings in a helicopter transmission.

Diagnosis of focal liver lesions suspected of metastases by diffusion-weighted imaging (DWI): systematic comparison favors free-breathing technique.

PubMed

Baltzer, Pascal A T; Schelhorn, Juliane; Benndorf, Matthias; Dietzel, Matthias; Kaiser, Werner A

2013-01-01

Two echo planar imaging diffusion-weighted imaging (DWI) techniques [one breath hold (DWI(bh)), repetition time/echo time (TR/TE) 2100/62 ms; one at free breathing (DWI(fb)), TR/TE 2000/65 ms] were compared regarding diagnosis of focal liver lesions (FLLs) in 45 patients with suspected liver metastasis without prior treatment. Apparent diffusion coefficient values of 46 benign and 67 malignant FLLs were analyzed by receiver operating characteristics (ROC) analysis. DWI(fb) detected more malignant lesions than DWI(bh) (P=.002). Lesion size ≤10 mm was associated with FLLs missed by DWI(bh) (P=.018). Area under the ROC curve of DWI(fb) (0.801) was higher compared to that of DWI(bh) (0.669, P<.0113), demonstrating the diagnostic superiority of DWI(fb). Copyright © 2013 Elsevier Inc. All rights reserved.

Turbidity of mouthrinsed water as a screening index for oral malodor.

PubMed

Ueno, Masayuki; Takeuchi, Susumu; Samnieng, Patcharaphol; Morishima, Seiji; Shinada, Kayoko; Kawaguchi, Yoko

2013-08-01

The objectives of this research were to examine the relationship between turbidity of mouthrinsed water and oral malodor, and to evaluate whether the turbidity could be used to screen oral malodor. The subjects were 165 oral malodor patients. Gas chromatography and organoleptic test (OT) were used for oral malodor measurement. Oral examination along with collection of saliva and quantification of bacteria was conducted. Turbidity of mouthrinsed water was measured with turbidimeter. Logistic regression with oral malodor status by OT as the dependent variable and receiver operating characteristic (ROC) analysis were performed. Turbidity had a significant association with oral malodor status. In addition, ROC analysis showed that the turbidity had an ability to screen for presence or absence of oral malodor. Turbidity could reflect or represent other influential variables of oral malodor and may be useful as a screening method for oral malodor. Copyright © 2013 Elsevier Inc. All rights reserved.

Aedes aegypti Larval Indices and Risk for Dengue Epidemics

PubMed Central

Sanchez, Lizet; Vanlerberghe, Veerle; Alfonso, Lázara; Marquetti, María del Carmen; Guzman, María Guadalupe; Bisset, Juan; van der Stuyft, Patrick

2006-01-01

We assessed in a case-control study the test-validity of Aedes larval indices for the 2000 Havana outbreak. "Cases" were blocks where a dengue fever patient lived during the outbreak. "Controls" were randomly sampled blocks. Before, during, and after the epidemic, we calculated Breteau index (BI) and house index at the area, neighborhood, and block level. We constructed receiver operating characteristic (ROC) curves to determine their performance as predictors of dengue transmission. We observed a pronounced effect of the level of measurement. The BImax (maximum block BI in a radius of 100 m) at 2-month intervals had an area under the ROC curve of 71%. At a cutoff of 4.0, it significantly (odds ratio 6.00, p<0.05) predicted transmission with 78% sensitivity and 63% specificity. Analysis of BI at the local level, with human-defined boundaries, could be introduced in control programs to identify neighborhoods at high risk for dengue transmission. PMID:16704841

Signal Detection Theory Applied to Helicopter Transmission Diagnostic Thresholds

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Keller, Jonathan A.; Wade, Daniel R.

2009-01-01

Helicopter Health Usage Monitoring Systems (HUMS) have potential for providing data to support increasing the service life of a dynamic mechanical component in the transmission of a helicopter. Data collected can demonstrate the HUMS condition indicator responds to a specific component fault with appropriate alert limits and minimal false alarms. Defining thresholds for specific faults requires a tradeoff between the sensitivity of the condition indicator (CI) limit to indicate damage and the number of false alarms. A method using Receiver Operating Characteristic (ROC) curves to assess CI performance was demonstrated using CI data collected from accelerometers installed on several UH60 Black Hawk and AH64 Apache helicopters and an AH64 helicopter component test stand. Results of the analysis indicate ROC curves can be used to reliably assess the performance of commercial HUMS condition indicators to detect damaged gears and bearings in a helicopter transmission.

Characteristics of the group of radiologists that benefits the most using Breast Screen Reader Assessment Strategy (BREAST)

NASA Astrophysics Data System (ADS)

Ganesan, A.; Alakhras, M.; Brennan, P. C.; Lee, W.; Tapia, K.; Mello-Thoms, C.

2018-03-01

Purpose: To determine the impact of Breast Screen Reader Assessment Strategy (BREAST) over time in improving radiologists' breast cancer detection performance, and to identify the group of radiologists that benefit the most by using BREAST as a training tool. Materials and Methods: Thirty-six radiologists who completed three case-sets offered by BREAST were included in this study. The case-sets were arranged in radiologists' chronological order of completion and five performance measures (sensitivity, specificity, location sensitivity, receiver operating characteristics area under the curve (ROC AUC) and jackknife alternative free-response receiver operating characteristic (JAFROC) figure-of-merit (FOM)), available from BREAST, were compared between case-sets to determine the level of improvement achieved. The radiologists were then grouped based on their characteristics and the above performance measures between the case-sets were compared. Paired t-tests or Wilcoxon signed-rank tests with statistical significance set at p < 0.05 were used to compare the performance measures. Results: Significant improvement was demonstrated in radiologists' case-set performance in terms of location sensitivity and JAFROC FOM over the years, and radiologists' location sensitivity and JAFROC FOM showed significant improvement irrespective of their characteristics. In terms of ROC AUC, significant improvement was shown for radiologists who were reading screen mammograms for more than 7 years and spent more than 9 hours per week reading mammograms. Conclusion: Engaging with case-sets appears to enhance radiologists' performance suggesting the important value of initiatives such as BREAST. However, such performance enhancement was not shown for everyone, highlighting the need to tailor the BREAST platform to benefit all radiologists.

A semiparametric separation curve approach for comparing correlated ROC data from multiple markers

PubMed Central

Tang, Liansheng Larry; Zhou, Xiao-Hua

2012-01-01

In this article we propose a separation curve method to identify the range of false positive rates for which two ROC curves differ or one ROC curve is superior to the other. Our method is based on a general multivariate ROC curve model, including interaction terms between discrete covariates and false positive rates. It is applicable with most existing ROC curve models. Furthermore, we introduce a semiparametric least squares ROC estimator and apply the estimator to the separation curve method. We derive a sandwich estimator for the covariance matrix of the semiparametric estimator. We illustrate the application of our separation curve method through two real life examples. PMID:23074360

TU-AB-303-06: Does Online Adaptive Radiation Therapy Mean Zero Margin for Intermediate-Risk Prostate Cancer? An Intra-Fractional Seminal Vesicles Motion Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheng, Y; Li, T; Lee, W

Purpose: To provide benchmark for seminal vesicles (SVs) margin selection to account for intra-fractional motion; and to investigate the effectiveness of two motion surrogates in predicting intra-fractional SV underdosage. Methods: 9 prostate SBRT patients were studied; each has five pairs of pre-treatment and post-treatment cone-beam CTs (CBCTs). Each pair of CBCTs was registered based on fiducial markers in the prostate. To provide “ground truth” for coverage evaluation, all pre-treatment SVs were expanded with isotropic margin of 1,2,3,5 and 8mm, and their overlap with post-treatment SVs were used to quantify intra-fractional coverage. Two commonly used motion surrogates, the center-of-mass (COM) andmore » the border of contour (the most distal points in SI/AP/LR directions) were evaluated using Receiver-Operating Characteristic (ROC) analyses for predicting SV underdosage due to intra-fractional motion. Action threshold of determining underdosage for each surrogate was calculated by selecting the optimal balancing between sensitivity and specificity. For comparison, margin for each surrogate was also calculated based on traditional margin recipe. Results: 90% post-treatment SV coverage can be achieved in 47%, 82%, 91%, 98% and 98% fractions for 1,2,3,5 and 8mm margins. 3mm margin ensured the 90% intra-fractional SV coverage in 90% fractions when prostate was aligned. The ROC analysis indicated the AUC for COM and border were 0.88 and 0.72. The underdosage threshold was 2.9mm for COM and 4.1mm for border. The Van Herk’s margin recipe recommended 0.5, 0 and 1.8mm margin in LR, AP and SI direction based on COM and for border, the corresponding margin was 2.1, 4.5 and 3mm. Conclusion: 3mm isotropic margin is the minimum required to mitigate the intra-fractional SV motion when prostate is aligned. ROC analysis reveals that both COM and border are acceptable predictors for SV underdosage with 2.9mm and 4.1mm action threshold. Traditional margin calculation is less reliable for this application. This work is partially supported a master research grant from Varian Medical Systems.« less

Design and performance evaluation of a 20-aperture multipinhole collimator for myocardial perfusion imaging applications.

PubMed

Bowen, Jason D; Huang, Qiu; Ellin, Justin R; Lee, Tzu-Cheng; Shrestha, Uttam; Gullberg, Grant T; Seo, Youngho

2013-10-21

Single photon emission computed tomography (SPECT) myocardial perfusion imaging remains a critical tool in the diagnosis of coronary artery disease. However, after more than three decades of use, photon detection efficiency remains poor and unchanged. This is due to the continued reliance on parallel-hole collimators first introduced in 1964. These collimators possess poor geometric efficiency. Here we present the performance evaluation results of a newly designed multipinhole collimator with 20 pinhole apertures (PH20) for commercial SPECT systems. Computer simulations and numerical observer studies were used to assess the noise, bias and diagnostic imaging performance of a PH20 collimator in comparison with those of a low energy high resolution (LEHR) parallel-hole collimator. Ray-driven projector/backprojector pairs were used to model SPECT imaging acquisitions, including simulation of noiseless projection data and performing MLEM/OSEM image reconstructions. Poisson noise was added to noiseless projections for realistic projection data. Noise and bias performance were investigated for five mathematical cardiac and torso (MCAT) phantom anatomies imaged at two gantry orbit positions (19.5 and 25.0 cm). PH20 and LEHR images were reconstructed with 300 MLEM iterations and 30 OSEM iterations (ten subsets), respectively. Diagnostic imaging performance was assessed by a receiver operating characteristic (ROC) analysis performed on a single MCAT phantom; however, in this case PH20 images were reconstructed with 75 pixel-based OSEM iterations (four subsets). Four PH20 projection views from two positions of a dual-head camera acquisition and 60 LEHR projections were simulated for all studies. At uniformly-imposed resolution of 12.5 mm, significant improvements in SNR and diagnostic sensitivity (represented by the area under the ROC curve, or AUC) were realized when PH20 collimators are substituted for LEHR parallel-hole collimators. SNR improves by factors of 1.94-2.34 for the five patient anatomies and two orbital positions studied. For the ROC analysis the PH20 AUC is larger than the LEHR AUC with a p-value of 0.0067. Bias performance, however, decreases with the use of PH20 collimators. Systematic analyses showed PH20 collimators present improved diagnostic imaging performance over LEHR collimators, requiring only collimator exchange on existing SPECT cameras for their use.

Design and performance evaluation of a 20-aperture multipinhole collimator for myocardial perfusion imaging applications

NASA Astrophysics Data System (ADS)

Bowen, Jason D.; Huang, Qiu; Ellin, Justin R.; Lee, Tzu-Cheng; Shrestha, Uttam; Gullberg, Grant T.; Seo, Youngho

2013-10-01

Single photon emission computed tomography (SPECT) myocardial perfusion imaging remains a critical tool in the diagnosis of coronary artery disease. However, after more than three decades of use, photon detection efficiency remains poor and unchanged. This is due to the continued reliance on parallel-hole collimators first introduced in 1964. These collimators possess poor geometric efficiency. Here we present the performance evaluation results of a newly designed multipinhole collimator with 20 pinhole apertures (PH20) for commercial SPECT systems. Computer simulations and numerical observer studies were used to assess the noise, bias and diagnostic imaging performance of a PH20 collimator in comparison with those of a low energy high resolution (LEHR) parallel-hole collimator. Ray-driven projector/backprojector pairs were used to model SPECT imaging acquisitions, including simulation of noiseless projection data and performing MLEM/OSEM image reconstructions. Poisson noise was added to noiseless projections for realistic projection data. Noise and bias performance were investigated for five mathematical cardiac and torso (MCAT) phantom anatomies imaged at two gantry orbit positions (19.5 and 25.0 cm). PH20 and LEHR images were reconstructed with 300 MLEM iterations and 30 OSEM iterations (ten subsets), respectively. Diagnostic imaging performance was assessed by a receiver operating characteristic (ROC) analysis performed on a single MCAT phantom; however, in this case PH20 images were reconstructed with 75 pixel-based OSEM iterations (four subsets). Four PH20 projection views from two positions of a dual-head camera acquisition and 60 LEHR projections were simulated for all studies. At uniformly-imposed resolution of 12.5 mm, significant improvements in SNR and diagnostic sensitivity (represented by the area under the ROC curve, or AUC) were realized when PH20 collimators are substituted for LEHR parallel-hole collimators. SNR improves by factors of 1.94-2.34 for the five patient anatomies and two orbital positions studied. For the ROC analysis the PH20 AUC is larger than the LEHR AUC with a p-value of 0.0067. Bias performance, however, decreases with the use of PH20 collimators. Systematic analyses showed PH20 collimators present improved diagnostic imaging performance over LEHR collimators, requiring only collimator exchange on existing SPECT cameras for their use.

Responsiveness and Minimal Important Changes of the Scoliosis Research Society-22 Patient Questionnaire in Subjects With Mild Adolescent and Moderate Adult Idiopathic Scoliosis Undergoing Multidisciplinary Rehabilitation.

PubMed

Monticone, Marco; Ambrosini, Emilia; Rocca, Barbara; Foti, Calogero; Ferrante, Simona

2017-06-01

Single-center, prospective study. Evaluating the responsiveness and minimal important changes (MICs) for the Scoliosis Research Society-22 Patient Questionnaire (SRS-22) in adolescent idiopathic scoliosis (AIS) and adult idiopathic scoliosis (AS). Despite the SRS-22 properties have been investigated in various different languages, there is still a lack of information concerning responsiveness and MIC, limiting the use of SRS-22 for clinical and research purposes. At the beginning and end of multidisciplinary rehabilitation programs, 149 subjects with mild AIS (Cobb angle <25°) and 140 subjects with moderate AS (Cobb angle <35°) completed the SRS-22. Upon completing the programs, subjects also performed the global perceived effect (GPE) scales test, which was divided to produce a dichotomous outcome (improved vs. stable). Responsiveness was calculated for all SRS-22 domains but satisfaction with management by distribution (effect size; standardized response mean) and anchor-based methods (receiver operating characteristic [ROC] curves; correlations between change scores of the SRS-22 and GPE). ROC curves were also used to compute the MICs. The effect size ranged from 1.23 to 1.50 in AIS and from 1.02 to 1.37 in AS. The standardized response mean ranged from 0.95 to 1.27 in AIS and from 0.66 to 0.90 in AS. The ROC analyses revealed the following MIC values (area under the curve; sensitivity; specificity): function, 0.70 (0.739;66;70) for AIS and 0.60 (0.842;84;76) for AS; pain, 0.70 (0.731;71;70) for AIS and 0.40 (0.817;81;70) for AS; mental health, 0.50 (0.708;83;58) for AIS and 0.55 (0.750;69;78) for AS; self-perceived image, 0.40 (0.609;79;42) for AIS and 0.60 (0.751;61;82) for AS. Correlations between change scores of the SRS-22 domains and GPE were low to moderate, ranging from -0.347 to -0.667. The SRS-22 was sensitive in detecting clinical changes in subjects with adolescent and adult scoliosis. We recommend taking the MICs provided into account when assessing patients' improvement or planning studies in these clinical contexts. 3.

CSmetaPred: a consensus method for prediction of catalytic residues.

PubMed

Choudhary, Preeti; Kumar, Shailesh; Bachhawat, Anand Kumar; Pandit, Shashi Bhushan

2017-12-22

Knowledge of catalytic residues can play an essential role in elucidating mechanistic details of an enzyme. However, experimental identification of catalytic residues is a tedious and time-consuming task, which can be expedited by computational predictions. Despite significant development in active-site prediction methods, one of the remaining issues is ranked positions of putative catalytic residues among all ranked residues. In order to improve ranking of catalytic residues and their prediction accuracy, we have developed a meta-approach based method CSmetaPred. In this approach, residues are ranked based on the mean of normalized residue scores derived from four well-known catalytic residue predictors. The mean residue score of CSmetaPred is combined with predicted pocket information to improve prediction performance in meta-predictor, CSmetaPred_poc. Both meta-predictors are evaluated on two comprehensive benchmark datasets and three legacy datasets using Receiver Operating Characteristic (ROC) and Precision Recall (PR) curves. The visual and quantitative analysis of ROC and PR curves shows that meta-predictors outperform their constituent methods and CSmetaPred_poc is the best of evaluated methods. For instance, on CSAMAC dataset CSmetaPred_poc (CSmetaPred) achieves highest Mean Average Specificity (MAS), a scalar measure for ROC curve, of 0.97 (0.96). Importantly, median predicted rank of catalytic residues is the lowest (best) for CSmetaPred_poc. Considering residues ranked ≤20 classified as true positive in binary classification, CSmetaPred_poc achieves prediction accuracy of 0.94 on CSAMAC dataset. Moreover, on the same dataset CSmetaPred_poc predicts all catalytic residues within top 20 ranks for ~73% of enzymes. Furthermore, benchmarking of prediction on comparative modelled structures showed that models result in better prediction than only sequence based predictions. These analyses suggest that CSmetaPred_poc is able to rank putative catalytic residues at lower (better) ranked positions, which can facilitate and expedite their experimental characterization. The benchmarking studies showed that employing meta-approach in combining residue-level scores derived from well-known catalytic residue predictors can improve prediction accuracy as well as provide improved ranked positions of known catalytic residues. Hence, such predictions can assist experimentalist to prioritize residues for mutational studies in their efforts to characterize catalytic residues. Both meta-predictors are available as webserver at: http://14.139.227.206/csmetapred/ .

A predictive model for diagnosing bipolar disorder based on the clinical characteristics of major depressive episodes in Chinese population.

PubMed

Gan, Zhaoyu; Diao, Feici; Wei, Qinling; Wu, Xiaoli; Cheng, Minfeng; Guan, Nianhong; Zhang, Ming; Zhang, Jinbei

2011-11-01

A correct timely diagnosis of bipolar depression remains a big challenge for clinicians. This study aimed to develop a clinical characteristic based model to predict the diagnosis of bipolar disorder among patients with current major depressive episodes. A prospective study was carried out on 344 patients with current major depressive episodes, with 268 completing 1-year follow-up. Data were collected through structured interviews. Univariate binary logistic regression was conducted to select potential predictive variables among 19 initial variables, and then multivariate binary logistic regression was performed to analyze the combination of risk factors and build a predictive model. Receiver operating characteristic (ROC) curve was plotted. Of 19 initial variables, 13 variables were preliminarily selected, and then forward stepwise exercise produced a final model consisting of 6 variables: age at first onset, maximum duration of depressive episodes, somatalgia, hypersomnia, diurnal variation of mood, irritability. The correct prediction rate of this model was 78% (95%CI: 75%-86%) and the area under the ROC curve was 0.85 (95%CI: 0.80-0.90). The cut-off point for age at first onset was 28.5 years old, while the cut-off point for maximum duration of depressive episode was 7.5 months. The limitations of this study include small sample size, relatively short follow-up period and lack of treatment information. Our predictive models based on six clinical characteristics of major depressive episodes prove to be robust and can help differentiate bipolar depression from unipolar depression. Copyright © 2011 Elsevier B.V. All rights reserved.