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Sample records for predicting clinical response

  1. Brain Connectivity Predicts Placebo Response across Chronic Pain Clinical Trials

    PubMed Central

    Tétreault, Pascal; Mansour, Ali; Vachon-Presseau, Etienne; Schnitzer, Thomas J.; Apkarian, A. Vania

    2016-01-01

    Placebo response in the clinical trial setting is poorly understood and alleged to be driven by statistical confounds, and its biological underpinnings are questioned. Here we identified and validated that clinical placebo response is predictable from resting-state functional magnetic-resonance-imaging (fMRI) brain connectivity. This also led to discovering a brain region predicting active drug response and demonstrating the adverse effect of active drug interfering with placebo analgesia. Chronic knee osteoarthritis (OA) pain patients (n = 56) underwent pretreatment brain scans in two clinical trials. Study 1 (n = 17) was a 2-wk single-blinded placebo pill trial. Study 2 (n = 39) was a 3-mo double-blinded randomized trial comparing placebo pill to duloxetine. Study 3, which was conducted in additional knee OA pain patients (n = 42), was observational. fMRI-derived brain connectivity maps in study 1 were contrasted between placebo responders and nonresponders and compared to healthy controls (n = 20). Study 2 validated the primary biomarker and identified a brain region predicting drug response. In both studies, approximately half of the participants exhibited analgesia with placebo treatment. In study 1, right midfrontal gyrus connectivity best identified placebo responders. In study 2, the same measure identified placebo responders (95% correct) and predicted the magnitude of placebo’s effectiveness. By subtracting away linearly modeled placebo analgesia from duloxetine response, we uncovered in 6/19 participants a tendency of duloxetine enhancing predicted placebo response, while in another 6/19, we uncovered a tendency for duloxetine to diminish it. Moreover, the approach led to discovering that right parahippocampus gyrus connectivity predicts drug analgesia after correcting for modeled placebo-related analgesia. Our evidence is consistent with clinical placebo response having biological underpinnings and shows that the method can also reveal that active

  2. Brain Connectivity Predicts Placebo Response across Chronic Pain Clinical Trials.

    PubMed

    Tétreault, Pascal; Mansour, Ali; Vachon-Presseau, Etienne; Schnitzer, Thomas J; Apkarian, A Vania; Baliki, Marwan N

    2016-10-01

    Placebo response in the clinical trial setting is poorly understood and alleged to be driven by statistical confounds, and its biological underpinnings are questioned. Here we identified and validated that clinical placebo response is predictable from resting-state functional magnetic-resonance-imaging (fMRI) brain connectivity. This also led to discovering a brain region predicting active drug response and demonstrating the adverse effect of active drug interfering with placebo analgesia. Chronic knee osteoarthritis (OA) pain patients (n = 56) underwent pretreatment brain scans in two clinical trials. Study 1 (n = 17) was a 2-wk single-blinded placebo pill trial. Study 2 (n = 39) was a 3-mo double-blinded randomized trial comparing placebo pill to duloxetine. Study 3, which was conducted in additional knee OA pain patients (n = 42), was observational. fMRI-derived brain connectivity maps in study 1 were contrasted between placebo responders and nonresponders and compared to healthy controls (n = 20). Study 2 validated the primary biomarker and identified a brain region predicting drug response. In both studies, approximately half of the participants exhibited analgesia with placebo treatment. In study 1, right midfrontal gyrus connectivity best identified placebo responders. In study 2, the same measure identified placebo responders (95% correct) and predicted the magnitude of placebo's effectiveness. By subtracting away linearly modeled placebo analgesia from duloxetine response, we uncovered in 6/19 participants a tendency of duloxetine enhancing predicted placebo response, while in another 6/19, we uncovered a tendency for duloxetine to diminish it. Moreover, the approach led to discovering that right parahippocampus gyrus connectivity predicts drug analgesia after correcting for modeled placebo-related analgesia. Our evidence is consistent with clinical placebo response having biological underpinnings and shows that the method can also reveal that active

  3. Distinct Functional Connectivities Predict Clinical Response with Emotion Regulation Therapy.

    PubMed

    Fresco, David M; Roy, Amy K; Adelsberg, Samantha; Seeley, Saren; García-Lesy, Emmanuel; Liston, Conor; Mennin, Douglas S

    2017-01-01

    Despite the success of available medical and psychosocial treatments, a sizable subgroup of individuals with commonly co-occurring disorders, generalized anxiety disorder (GAD) and major depressive disorder (MDD), fail to make sufficient treatment gains thereby prolonging their deficits in life functioning and satisfaction. Clinically, these patients often display temperamental features reflecting heightened sensitivity to underlying motivational systems related to threat/safety and reward/loss (e.g., somatic anxiety) as well as inordinate negative self-referential processing (e.g., worry, rumination). This profile may reflect disruption in two important neural networks associated with emotional/motivational salience (e.g., salience network) and self-referentiality (e.g., default network, DN). Emotion Regulation Therapy (ERT) was developed to target this hypothesized profile and its neurobehavioral markers. In the present study, 22 GAD patients (with and without MDD) completed resting state MRI scans before receiving 16 sessions of ERT. To test study these hypotheses, we examined the associations between baseline patterns of intrinsic functional connectivity (iFC) of the insula and of hubs within the DN (anterior and dorsal medial prefrontal cortex [MPFC] and posterior cingulate cortex [PCC]) and treatment-related changes in worry, somatic anxiety symptoms and decentering. Results suggest that greater treatment linked reductions in worry were associated with iFC clusters in both the insular and parietal cortices. Greater treatment linked gains in decentering, a metacognitive process that involves the capacity to observe items that arise in the mind with healthy psychological distance that is targeted by ERT, was associated with iFC clusters in the anterior and posterior DN. The current study adds to the growing body of research implicating disruptions in the default and salience networks as promising targets of treatment for GAD with and without co-occurring MDD.

  4. Distinct Functional Connectivities Predict Clinical Response with Emotion Regulation Therapy

    PubMed Central

    Fresco, David M.; Roy, Amy K.; Adelsberg, Samantha; Seeley, Saren; García-Lesy, Emmanuel; Liston, Conor; Mennin, Douglas S.

    2017-01-01

    Despite the success of available medical and psychosocial treatments, a sizable subgroup of individuals with commonly co-occurring disorders, generalized anxiety disorder (GAD) and major depressive disorder (MDD), fail to make sufficient treatment gains thereby prolonging their deficits in life functioning and satisfaction. Clinically, these patients often display temperamental features reflecting heightened sensitivity to underlying motivational systems related to threat/safety and reward/loss (e.g., somatic anxiety) as well as inordinate negative self-referential processing (e.g., worry, rumination). This profile may reflect disruption in two important neural networks associated with emotional/motivational salience (e.g., salience network) and self-referentiality (e.g., default network, DN). Emotion Regulation Therapy (ERT) was developed to target this hypothesized profile and its neurobehavioral markers. In the present study, 22 GAD patients (with and without MDD) completed resting state MRI scans before receiving 16 sessions of ERT. To test study these hypotheses, we examined the associations between baseline patterns of intrinsic functional connectivity (iFC) of the insula and of hubs within the DN (anterior and dorsal medial prefrontal cortex [MPFC] and posterior cingulate cortex [PCC]) and treatment-related changes in worry, somatic anxiety symptoms and decentering. Results suggest that greater treatment linked reductions in worry were associated with iFC clusters in both the insular and parietal cortices. Greater treatment linked gains in decentering, a metacognitive process that involves the capacity to observe items that arise in the mind with healthy psychological distance that is targeted by ERT, was associated with iFC clusters in the anterior and posterior DN. The current study adds to the growing body of research implicating disruptions in the default and salience networks as promising targets of treatment for GAD with and without co-occurring MDD

  5. Predictive Factors of Clinical Response of Infliximab Therapy in Active Nonradiographic Axial Spondyloarthritis Patients

    PubMed Central

    Lin, Zhiming; Liao, Zetao; Huang, Jianlin; Ai, Maixing; Pan, Yunfeng; Wu, Henglian; Lu, Jun; Cao, Shuangyan; Li, Li; Wei, Qiujing; Tang, Deshen; Wei, Yanlin; Li, Tianwang; Wu, Yuqiong; Xu, Manlong; Li, Qiuxia; Jin, Ou; Yu, Buyun; Gu, Jieruo

    2015-01-01

    Objectives. To evaluate the efficiency and the predictive factors of clinical response of infliximab in active nonradiographic axial spondyloarthritis patients. Methods. Active nonradiographic patients fulfilling ESSG criteria for SpA but not fulfilling modified New York criteria were included. All patients received infliximab treatment for 24 weeks. The primary endpoint was ASAS20 response at weeks 12 and 24. The abilities of baseline parameters and response at week 2 to predict ASAS20 response at weeks 12 and 24 were assessed using ROC curve and logistic regression analysis, respectively. Results. Of 70 axial SpA patients included, the proportions of patients achieving an ASAS20 response at weeks 2, 6, 12, and 24 were 85.7%, 88.6%, 87.1%, and 84.3%, respectively. Baseline MRI sacroiliitis score (AUC = 0.791; P = 0.005), CRP (AUC = 0.75; P = 0.017), and ASDAS (AUC = 0.778, P = 0.007) significantly predicted ASAS20 response at week 12. However, only ASDAS (AUC = 0.696, P = 0.040) significantly predicted ASAS20 response at week 24. Achievement of ASAS20 response after the first infliximab infusion was a significant predictor of subsequent ASAS20 response at weeks 12 and 24 (wald χ2 = 6.87, P = 0.009, and wald χ2 = 5.171, P = 0.023). Conclusions. Infliximab shows efficiency in active nonradiographic axial spondyloarthritis patients. ASDAS score and first-dose response could help predicting clinical efficacy of infliximab therapy in these patients. PMID:26273654

  6. Residual β-Cell Function Predicts Clinical Response After Autologous Hematopoietic Stem Cell Transplantation.

    PubMed

    Xiang, Hang; Yang, Chao; Xiang, Tianyuan; Wang, Zheng; Ge, Xin; Li, Fan; Su, Yuehan; Chen, Haixu; Huang, Xianyong; Zeng, Qiang

    2016-05-01

    New strategies of autologous hematopoietic stem cell transplantation (auto-HSCT) have gained much interest for the treatment of type 1 diabetes mellitus. However, assessing the clinical response and residual β-cell function still has limitations. The aim of the study was to select the optimal quantitative index to assess pre-existing β-cell function and to explore its predictive function for clinical response after auto-HSCT therapy. In this study, all of the patients who had undergone auto-HSCT were clustered into a responder group (Δβ-score > 0) and a nonresponder group (Δβ-score ≤ 0). We compared their quantitative metabolic indexes at baseline and performed receiver-operating characteristic (ROC) analysis to analyze the correlations between the indexes and clinical response. Kaplan-Meier analysis was conducted to compare the cumulative response durations in each quartile of the selected indexes. In an average of 15.13 ± 6.15 months of follow-up, 44 of 112 patients achieved a clinical response. The responder group had lower levels of fasting plasma glucose and quantitative insulin sensitivity check index (QUICKI) but higher levels of fasting C-peptide, fasting insulin, and homeostasis model assessments for insulin resistance (HOMA-IR). ROC analysis showed that HOMA-IR had the largest area under the curve (0.756), which was similar to that of QUICKI. Kaplan-Meier analysis further confirmed that the third quartile (1.3371-1.7018) of HOMA-IR or the second quartile (0.3523-0.3657) of QUICKI was preferential for a prolonged response. In conclusion, HOMA-IR and QUICKI could be optimal measurements for β-cell reserves, and they were predictive for the clinical response after auto-HSCT. The β-score was comprehensive and reliable in evaluating clinical response after autologous hematopoietic stem cell transplantation (HSCT). The homeostasis model assessments for insulin resistance and the quantitative insulin sensitivity check index could serve as precise

  7. Pharmacogenomics of Methotrexate Membrane Transport Pathway: Can Clinical Response to Methotrexate in Rheumatoid Arthritis Be Predicted?

    PubMed

    Lima, Aurea; Bernardes, Miguel; Azevedo, Rita; Medeiros, Rui; Seabra, Vítor

    2015-06-16

    Methotrexate (MTX) is widely used for rheumatoid arthritis (RA) treatment. Single nucleotide polymorphisms (SNPs) could be used as predictors of patients' therapeutic outcome variability. Therefore, this study aims to evaluate the influence of SNPs in genes encoding for MTX membrane transport proteins in order to predict clinical response to MTX. Clinicopathological data from 233 RA patients treated with MTX were collected, clinical response defined, and patients genotyped for 23 SNPs. Genotype and haplotype analyses were performed using multivariate methods and a genetic risk index (GRI) for non-response was created. Increased risk for non-response was associated to SLC22A11 rs11231809 T carriers; ABCC1 rs246240 G carriers; ABCC1 rs3784864 G carriers; CGG haplotype for ABCC1 rs35592, rs2074087 and rs3784864; and CGG haplotype for ABCC1 rs35592, rs246240 and rs3784864. GRI demonstrated that patients with Index 3 were 16-fold more likely to be non-responders than those with Index 1. This study revealed that SLC22A11 and ABCC1 may be important to identify those patients who will not benefit from MTX treatment, highlighting the relevance in translating these results to clinical practice. However, further validation by independent studies is needed to develop the field of personalized medicine to predict clinical response to MTX treatment.

  8. Pharmacogenomics of Methotrexate Membrane Transport Pathway: Can Clinical Response to Methotrexate in Rheumatoid Arthritis Be Predicted?

    PubMed Central

    Lima, Aurea; Bernardes, Miguel; Azevedo, Rita; Medeiros, Rui; Seabra, Vitor

    2015-01-01

    Background: Methotrexate (MTX) is widely used for rheumatoid arthritis (RA) treatment. Single nucleotide polymorphisms (SNPs) could be used as predictors of patients’ therapeutic outcome variability. Therefore, this study aims to evaluate the influence of SNPs in genes encoding for MTX membrane transport proteins in order to predict clinical response to MTX. Methods: Clinicopathological data from 233 RA patients treated with MTX were collected, clinical response defined, and patients genotyped for 23 SNPs. Genotype and haplotype analyses were performed using multivariate methods and a genetic risk index (GRI) for non-response was created. Results: Increased risk for non-response was associated to SLC22A11 rs11231809 T carriers; ABCC1 rs246240 G carriers; ABCC1 rs3784864 G carriers; CGG haplotype for ABCC1 rs35592, rs2074087 and rs3784864; and CGG haplotype for ABCC1 rs35592, rs246240 and rs3784864. GRI demonstrated that patients with Index 3 were 16-fold more likely to be non-responders than those with Index 1. Conclusions: This study revealed that SLC22A11 and ABCC1 may be important to identify those patients who will not benefit from MTX treatment, highlighting the relevance in translating these results to clinical practice. However, further validation by independent studies is needed to develop the field of personalized medicine to predict clinical response to MTX treatment. PMID:26086825

  9. Artificial neural network prediction of clozapine response with combined pharmacogenetic and clinical data.

    PubMed

    Lin, Chao-Cheng; Wang, Ying-Chieh; Chen, Jen-Yeu; Liou, Ying-Jay; Bai, Ya-Mei; Lai, I-Ching; Chen, Tzu-Ting; Chiu, Hung-Wen; Li, Yu-Chuan

    2008-08-01

    Although one third to one half of refractory schizophrenic patients responds to clozapine, however, there are few evidences currently that could predict clozapine response before the use of the medication. The present study aimed to train and validate artificial neural networks (ANN), using clinical and pharmacogenetic data, to predict clozapine response in schizophrenic patients. Five pharmacogenetic variables and five clinical variables were collated from 93 schizophrenic patients taking clozapine, including 26 responders. ANN analysis was carried out by training the network with data from 75% of cases and subsequently testing with data from 25% of unseen cases to determine the optimal ANN architecture. Then the leave-one-out method was used to examine the generalization of the models. The optimal ANN architecture was found to be a standard feed-forward, fully-connected, back-propagation multilayer perceptron. The overall accuracy rate of ANN was 83.3%, which is higher than that of logistic regression (LR) (70.8%). By using the area under the receiver operating characteristics curve as a measure of performance, the ANN outperformed the LR (0.821+/-0.054 versus 0.579+/-0.068; p<0.001). The ANN with only genetic variables outperformed the ANN with only clinical variables (0.805+/-0.056 versus 0.647+/-0.066; p=0.046). The gene polymorphisms should play an important role in the prediction. Further validation of ANN analysis is likely to provide decision support for predicting individual response.

  10. An Ex Vivo Platform for the Prediction of Clinical Response in Multiple Myeloma.

    PubMed

    Silva, Ariosto; Silva, Maria C; Sudalagunta, Praneeth; Distler, Allison; Jacobson, Timothy; Collins, Aunshka; Nguyen, Tuan; Song, Jinming; Chen, Dung-Tsa; Chen, Lu; Cubitt, Christopher; Baz, Rachid; Perez, Lia; Rebatchouk, Dmitri; Dalton, William; Greene, James; Gatenby, Robert; Gillies, Robert; Sontag, Eduardo; Meads, Mark B; Shain, Kenneth H

    2017-06-15

    Multiple myeloma remains treatable but incurable. Despite a growing armamentarium of effective agents, choice of therapy, especially in relapse, still relies almost exclusively on clinical acumen. We have developed a system, Ex vivo Mathematical Myeloma Advisor (EMMA), consisting of patient-specific mathematical models parameterized by an ex vivo assay that reverse engineers the intensity and heterogeneity of chemosensitivity of primary cells from multiple myeloma patients, allowing us to predict clinical response to up to 31 drugs within 5 days after bone marrow biopsy. From a cohort of 52 multiple myeloma patients, EMMA correctly classified 96% as responders/nonresponders and correctly classified 79% according to International Myeloma Working Group stratification of level of response. We also observed a significant correlation between predicted and actual tumor burden measurements (Pearson r = 0.5658, P < 0.0001). Preliminary estimates indicate that, among the patients enrolled in this study, 60% were treated with at least one ineffective agent from their therapy combination regimen, whereas 30% would have responded better if treated with another available drug or combination. Two in silico clinical trials with experimental agents ricolinostat and venetoclax, in a cohort of 19 multiple myeloma patient samples, yielded consistent results with recent phase I/II trials, suggesting that EMMA is a feasible platform for estimating clinical efficacy of drugs and inclusion criteria screening. This unique platform, specifically designed to predict therapeutic response in multiple myeloma patients within a clinically actionable time frame, has shown high predictive accuracy in patients treated with combinations of different classes of drugs. The accuracy, reproducibility, short turnaround time, and high-throughput potential of this platform demonstrate EMMA's promise as a decision support system for therapeutic management of multiple myeloma. Cancer Res; 77(12); 3336-51.

  11. Clinical utility of C-reactive protein to predict treatment response during cystic fibrosis pulmonary exacerbations

    PubMed Central

    Sharma, Ashutosh; Kirkpatrick, Gordon; Chen, Virginia; Skolnik, Kate; Hollander, Zsuzsanna; Wilcox, Pearce; Quon, Bradley S.

    2017-01-01

    Rationale C-reactive protein (CRP) is a systemic marker of inflammation that correlates with disease status in cystic fibrosis (CF). The clinical utility of CRP measurement to guide pulmonary exacerbation (PEx) treatment decisions remains uncertain. Objectives To determine whether monitoring CRP during PEx treatment can be used to predict treatment response. We hypothesized that early changes in CRP can be used to predict treatment response. Methods We reviewed all PEx events requiring hospitalization for intravenous (IV) antibiotics over 2 years at our institution. 83 PEx events met our eligibility criteria. CRP levels from admission to day 5 were evaluated to predict treatment non-response, using a modified version of a prior published composite definition. CRP was also evaluated to predict time until next exacerbation (TUNE). Measurements and main results 53% of 83 PEx events were classified as treatment non-response. Paradoxically, 24% of PEx events were characterized by a ≥ 50% increase in CRP levels within the first five days of treatment. Absolute change in CRP from admission to day 5 was not associated with treatment non-response (p = 0.58). Adjusted for FEV1% predicted, admission log10 CRP was associated with treatment non-response (OR: 2.39; 95% CI: 1.14 to 5.91; p = 0.03) and shorter TUNE (HR: 1.60; 95% CI: 1.13 to 2.27; p = 0.008). The area under the receiver operating characteristics (ROC) curve of admission CRP to predict treatment non-response was 0.72 (95% CI 0.61–0.83; p<0.001). 23% of PEx events were characterized by an admission CRP of > 75 mg/L with a specificity of 90% for treatment non-response. Conclusions Admission CRP predicts treatment non-response and time until next exacerbation. A very elevated admission CRP (>75mg/L) is highly specific for treatment non-response and might be used to target high-risk patients for future interventional studies aimed at improving exacerbation outcomes. PMID:28178305

  12. Clinical application of fluctuation dissipation theory - Prediction of heart rate response to spontaneous breathing trial

    NASA Astrophysics Data System (ADS)

    Niestemski, Liang R.; Chen, Man; Prevost, Robert; McRae, Michael; Cholleti, Sharath; Najarro, Gabriel; Buchman, Timothy G.; Deem, Michael W.

    2013-03-01

    Contrary to the traditional view of the healthy physiological state as being a single static state, variation in physiologic variables has more recently been suggested to be a key component of the healthy state. Indeed, aging and disease are characterized by a loss of such variability. We apply the conceptual framework of fluctuation-dissipation theory (FDT) to predict the response to a common clinical intervention from historical fluctuations in physiologic time series data. The non-equilibrium FDT relates the response of a system to a perturbation to natural fluctuations in the stationary state of the system. We seek to understand with the FDT a common clinical perturbation, the spontaneous breathing trial (SBT), in which mechanical ventilation is briefly suspended while the patient breathes freely for a period of time. As a stress upon the heart of the patient, the SBT can be characterized as a perturbation of heart rate dynamics. A non-equilibrium, but steady-state FDT allows us to predict the heart rate recovery after the SBT stress. We show that the responses of groups of similar patients to the spontaneous breathing trial can be predicted by this approach. This mathematical framework may serve as part of the basis for personalized critical care.

  13. Predictive cytokine biomarkers of clinical response to glatiramer acetate therapy in multiple sclerosis.

    PubMed

    Valenzuela, R M; Kaufman, M; Balashov, K E; Ito, K; Buyske, S; Dhib-Jalbut, S

    2016-11-15

    A prospective study of 62 patients with relapsing-remitting multiple sclerosis (RRMS) treated with Glatiramer acetate (GA) was conducted to evaluate the value of baseline and treatment-modulated cytokines in predicting the clinical response to the drug after 2years of therapy. There were 32 responders and 30 non-responders. GA upregulated Th2/regulatory cytokines and inhibited Th1 cytokines in sera or PBMC supernatants 3 and 6months into treatment. We found two prognostic models with clinical utility. A model based on IL-18 at baseline, the change in TNFa from baseline to 3months, the change in IL-4 from baseline to 6months, and the change in the log of the ratio of TNFa/IL-4 from baseline to 6months had an area under the curve (AUC) of 0.80. A high IL-18 level at baseline and a reduction of TNF-alpha over time are associated with a response to GA. Although the study identified predictive biomarkers of clinical response to GA, the results will need to be validated in other data sets. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Prediction of response to treatment in a randomized clinical trial of marital therapy.

    PubMed

    Atkins, David C; Berns, Sara B; George, William H; Doss, Brian D; Gattis, Krista; Christensen, Andrew

    2005-10-01

    This study investigated demographic, intrapersonal, and interpersonal predictors of treatment response in a randomized clinical trial of 134 distressed married couples, which examined traditional (N. S. Jacobson & G. Margolin, 1979) and integrative (N. S. Jacobson & A. Christensen, 1996) behavioral couple therapy. Results based on hierarchical linear modeling revealed that interpersonal variables were the strongest predictors, but their effects were largely limited to predicting initial marital dissatisfaction; greater individual mental health was also associated with less distress initially. Couples who were married longer demonstrated stronger treatment gains, and exploratory analyses suggested that sexually dissatisfied couples showed slower initial, but overall more consistent, gains in the integrative versus the traditional approach. Findings are considered in light of the previous literature on predicting response to marital therapy. ((c) 2005 APA, all rights reserved).

  15. Clinical Parameters Predicting Pathologic Tumor Response After Preoperative Chemoradiotherapy for Rectal Cancer

    SciTech Connect

    Yoon, Sang Min; Kim, Dae Yong Kim, Tae Hyun; Jung, Kyung Hae; Chang, Hee Jin; Koom, Woong Sub; Lim, Seok-Byung; Choi, Hyo Seong; Jeong, Seung-Yong; Park, Jae-Gahb

    2007-11-15

    Purpose: To identify pretreatment clinical parameters that could predict pathologic tumor response to preoperative chemoradiotherapy (CRT) for rectal cancer. Methods and Materials: The study involved 351 patients who underwent preoperative CRT followed by surgery between October 2001 and July 2006. Tumor responses to preoperative CRT were assessed in terms of tumor downstaging and tumor regression. Statistical analyses were performed to identify clinical factors associated with pathologic tumor response. Results: Tumor downstaging (defined as ypT2 or less) was observed in 167 patients (47.6%), whereas tumor regression (defined as Dworak's Regression Grades 3 or 4) was observed in 103 patients (29.3%) and complete regression in 51 patients (14.5%). Multivariate analysis found that predictors of downstaging were pretreatment hemoglobin level (p = 0.045), cN0 classification (p < 0.001), and serum carcinoembryonic antigen (CEA) level (p < 0.001), that predictors of tumor regression were cN0 classification (p = 0.044) and CEA level (p < 0.001), and that the predictor of complete regression was CEA level (p = 0.004). Conclusions: The data suggest that pretreatment CEA level is the most important clinical predictor of pathologic tumor response. It may be of benefit in the selection of treatment options as well as the assessment of individual prognosis.

  16. Can a Clinical Test of Reaction Time Predict a Functional Head-Protective Response?

    PubMed Central

    ECKNER, JAMES T.; LIPPS, DAVID B.; KIM, HOGENE; RICHARDSON, JAMES K.; ASHTON-MILLER, JAMES A.

    2015-01-01

    Purpose Reaction time is commonly prolonged after a sport-related concussion. Besides being a marker for injury, a rapid reaction time is necessary for protective maneuvers that can reduce the frequency and severity of additional head impacts. The purpose of this study was to determine whether a clinical test of simple visuomotor reaction time predicted the time taken to raise the hands to protect the head from a rapidly approaching ball. Methods Twenty-six healthy adult participants recruited from campus and community recreation and exercise facilities completed two experimental protocols during a single session: a manual visuomotor simple reaction time test (RTclin) and a sport-related head-protective response (RTsprt). RTclin measured the time required to catch a thin vertically oriented device on its release by the tester and was calculated from the distance the device fell before being arrested. RTsprt measured the time required to raise the hands from waist level to block a foam tennis ball fired toward the subject’s face from an air cannon and was determined using an optoelectronic camera system. A correlation coefficient was calculated between RTclin and RTsprt, with linear regression used to assess for effect modification by other covariates. Results A strong positive correlation was found between RTclin and RTsprt (r = 0.725, P < 0.001) independent of age, gender, height, or weight. Conclusions RTclin is predictive of a functional sport-related head-protective response. To our knowledge, this is the first demonstration of a clinical test predicting the ability to protect the head in a simulated sport environment. This correlation with a functional head-protective response is a relevant consideration for the potential use of RTclin as part of a multifaceted concussion assessment program. PMID:20689458

  17. Predictive event modelling in multicenter clinical trials with waiting time to response.

    PubMed

    Anisimov, Vladimir V

    2011-01-01

    A new analytic statistical technique for predictive event modeling in ongoing multicenter clinical trials with waiting time to response is developed. It allows for the predictive mean and predictive bounds for the number of events to be constructed over time, accounting for the newly recruited patients and patients already at risk in the trial, and for different recruitment scenarios. For modeling patient recruitment, an advanced Poisson-gamma model is used, which accounts for the variation in recruitment over time, the variation in recruitment rates between different centers and the opening or closing of some centers in the future. A few models for event appearance allowing for 'recurrence', 'death' and 'lost-to-follow-up' events and using finite Markov chains in continuous time are considered. To predict the number of future events over time for an ongoing trial at some interim time, the parameters of the recruitment and event models are estimated using current data and then the predictive recruitment rates in each center are adjusted using individual data and Bayesian re-estimation. For a typical scenario (continue to recruit during some time interval, then stop recruitment and wait until a particular number of events happens), the closed-form expressions for the predictive mean and predictive bounds of the number of events at any future time point are derived under the assumptions of Markovian behavior of the event progression. The technique is efficiently applied to modeling different scenarios for some ongoing oncology trials. Case studies are considered. Copyright © 2011 John Wiley & Sons, Ltd.

  18. Empirically and Clinically Useful Decision Making in Psychotherapy: Differential Predictions with Treatment Response Models

    ERIC Educational Resources Information Center

    Lutz, Wolfgang; Saunders, Stephen M.; Leon, Scott C.; Martinovich, Zoran; Kosfelder, Joachim; Schulte, Dietmar; Grawe, Klaus; Tholen, Sven

    2006-01-01

    In the delivery of clinical services, outcomes monitoring (i.e., repeated assessments of a patient's response to treatment) can be used to support clinical decision making (i.e., recurrent revisions of outcome expectations on the basis of that response). Outcomes monitoring can be particularly useful in the context of established practice research…

  19. Empirically and Clinically Useful Decision Making in Psychotherapy: Differential Predictions with Treatment Response Models

    ERIC Educational Resources Information Center

    Lutz, Wolfgang; Saunders, Stephen M.; Leon, Scott C.; Martinovich, Zoran; Kosfelder, Joachim; Schulte, Dietmar; Grawe, Klaus; Tholen, Sven

    2006-01-01

    In the delivery of clinical services, outcomes monitoring (i.e., repeated assessments of a patient's response to treatment) can be used to support clinical decision making (i.e., recurrent revisions of outcome expectations on the basis of that response). Outcomes monitoring can be particularly useful in the context of established practice research…

  20. Population pharmacokinetic–pharmacodynamic modelling in oncology: a tool for predicting clinical response

    PubMed Central

    Bender, Brendan C; Schindler, Emilie; Friberg, Lena E

    2015-01-01

    In oncology trials, overall survival (OS) is considered the most reliable and preferred endpoint to evaluate the benefit of drug treatment. Other relevant variables are also collected from patients for a given drug and its indication, and it is important to characterize the dynamic effects and links between these variables in order to improve the speed and efficiency of clinical oncology drug development. However, the drug-induced effects and causal relationships are often difficult to interpret because of temporal differences. To address this, population pharmacokinetic–pharmacodynamic (PKPD) modelling and parametric time-to-event (TTE) models are becoming more frequently applied. Population PKPD and TTE models allow for exploration towards describing the data, understanding the disease and drug action over time, investigating relevance of biomarkers, quantifying patient variability and in designing successful trials. In addition, development of models characterizing both desired and adverse effects in a modelling framework support exploration of risk-benefit of different dosing schedules. In this review, we have summarized population PKPD modelling analyses describing tumour, tumour marker and biomarker responses, as well as adverse effects, from anticancer drug treatment data. Various model-based metrics used to drive PD response and predict OS for oncology drugs and their indications are also discussed. PMID:24134068

  1. A clinical tool to predict failed response to therapy in children with severe pneumonia.

    PubMed

    Mamtani, Manju; Patel, Archana; Hibberd, Patricia L; Tuan, Tran Anh; Jeena, Prakash; Chisaka, Noel; Hassan, Mumtaz; Radovan, Irene Maulen; Thea, Donald M; Qazi, Shamim; Kulkarni, Hemant

    2009-04-01

    Severe pneumonia in children under 5 years of age continues to be an important clinical entity with treatment failure rates as high as 20%. Where severe pneumonias are common, predictive tools for treatment failure like chest radiography and pulse oximetry are not available or affordable. Thus, there is a need for development of simple, accurate and inexpensive clinical tools for prediction of treatment failure. Using clinical, chest radiographic and pulse oximetry data from 1702 children recruited in the Amoxicillin Penicillin Pneumonia International Study (APPIS) trial we developed and validated a simple clinical tool. For development, a randomly derived development sample (n = 889) was used. The tool which was based on the results of multivariate logistic regression models was validated on a separate sample of 813 children. The derived clinical tool in its final form contained three clinical predictors: age of child, excess age-specific respiratory rate at baseline and at 24 hr of hospitalization. This tool had a 70% and 66% predictive accuracy in the development and validation samples, respectively. The tool is presented as an easy-to-use nomogram. It is possible to predict the likelihood of treatment failure in children with severe pneumonia based on clinical features that are simple and inexpensive to measure.

  2. Prediction of response to treatment in a randomized clinical trial of couple therapy: a 2-year follow-up.

    PubMed

    Baucom, Brian R; Atkins, David C; Simpson, Lorelei E; Christensen, Andrew

    2009-02-01

    Many studies have examined pretreatment predictors of immediate posttreatment outcome, but few studies have examined prediction of long-term treatment response to couple therapies. Four groups of predictors (demographic, intrapersonal, communication, and other interpersonal) and 2 moderators (pretreatment severity and type of therapy) were explored as predictors of clinically significant change measured 2 years after treatment termination. Results demonstrated that power processes and expressed emotional arousal were the strongest predictors of 2-year response to treatment. Moderation analyses showed that these variables predicted differential treatment response to traditional versus integrative behavioral couple therapy and that more variables predicted 2-year response for couples who were less distressed when beginning treatment. Findings are discussed with regard to existing work on prediction of treatment response, and directions for further study are offered.

  3. Drug response in a genetically engineered mouse model of multiple myeloma is predictive of clinical efficacy

    PubMed Central

    Chesi, Marta; Matthews, Geoffrey M.; Garbitt, Victoria M.; Palmer, Stephen E.; Shortt, Jake; Lefebure, Marcus; Stewart, A. Keith; Johnstone, Ricky W.

    2012-01-01

    The attrition rate for anticancer drugs entering clinical trials is unacceptably high. For multiple myeloma (MM), we postulate that this is because of preclinical models that overemphasize the antiproliferative activity of drugs, and clinical trials performed in refractory end-stage patients. We validate the Vk*MYC transgenic mouse as a faithful model to predict single-agent drug activity in MM with a positive predictive value of 67% (4 of 6) for clinical activity, and a negative predictive value of 86% (6 of 7) for clinical inactivity. We identify 4 novel agents that should be prioritized for evaluation in clinical trials. Transplantation of Vk*MYC tumor cells into congenic mice selected for a more aggressive disease that models end-stage drug-resistant MM and responds only to combinations of drugs with single-agent activity in untreated Vk*MYC MM. We predict that combinations of standard agents, histone deacetylase inhibitors, bromodomain inhibitors, and hypoxia-activated prodrugs will demonstrate efficacy in the treatment of relapsed MM. PMID:22451422

  4. Baseline gut microbiota predicts clinical response and colitis in metastatic melanoma patients treated with ipilimumab.

    PubMed

    Chaput, N; Lepage, P; Coutzac, C; Soularue, E; Le Roux, K; Monot, C; Boselli, L; Routier, E; Cassard, L; Collins, M; Vaysse, T; Marthey, L; Eggermont, A; Asvatourian, V; Lanoy, E; Mateus, C; Robert, C; Carbonnel, F

    2017-03-27

    Ipilimumab, an immune checkpoint inhibitor targeting CTLA-4, prolongs survival in a subset of patients with metastatic melanoma but can induce immune-related adverse events, including enterocolitis. We hypothesized that baseline gut microbiota could predict ipilimumab anti-tumor response and/or intestinal toxicity.

  5. Predicting tumour response

    PubMed Central

    Law, W. Phillip; Miles, Kenneth A.

    2013-01-01

    Abstract Response prediction is an important emerging concept in oncologic imaging, with tailored, individualized treatment regimens increasingly becoming the standard of care. This review aims to define tumour response and illustrate the ways in which imaging techniques can demonstrate tumour biological characteristics that provide information on the likely benefit to be received by treatment. Two imaging approaches are described: identification of therapeutic targets and depiction of the treatment-resistant phenotype. The former approach is exemplified by the use of radionuclide imaging to confirm target expression before radionuclide therapy but with angiogenesis imaging and imaging correlates for genetic response predictors also demonstrating potential utility. Techniques to assess the treatment-resistant phenotype include demonstration of hypoperfusion with dynamic contrast-enhanced computed tomography and magnetic resonance imaging (MRI), depiction of necrosis with diffusion-weighted MRI, imaging of hypoxia and tumour adaption to hypoxia, and 99mTc-MIBI imaging of P-glycoprotein mediated drug resistance. To date, introduction of these techniques into clinical practice has often been constrained by inadequate cross-validation of predictive criteria and lack of verification against appropriate response end points such as survival. With further refinement, imaging predictors of response could play an important role in oncology, contributing to individualization of therapy based on the specific tumour phenotype. This ability to predict tumour response will have implications for improving efficacy of treatment, cost-effectiveness and omission of futile therapy. PMID:24061161

  6. Prediction of Response to Treatment in a Randomized Clinical Trial of Marital Therapy

    ERIC Educational Resources Information Center

    Atkins, David C.; Berns, Sara B.; George, William H.; Doss, Brian D.; Gattis, Krista; Christensen, Andrew

    2005-01-01

    This study investigated demographic, intrapersonal, and interpersonal predictors of treatment response in a randomized clinical trial of 134 distressed married couples, which examined traditional (N. S. Jacobson & G. Margolin, 1979) and integrative (N. S. Jacobson & A. Christensen, 1996) behavioral couple therapy. Results based on hierarchical…

  7. Prediction of Response to Treatment in a Randomized Clinical Trial of Marital Therapy

    ERIC Educational Resources Information Center

    Atkins, David C.; Berns, Sara B.; George, William H.; Doss, Brian D.; Gattis, Krista; Christensen, Andrew

    2005-01-01

    This study investigated demographic, intrapersonal, and interpersonal predictors of treatment response in a randomized clinical trial of 134 distressed married couples, which examined traditional (N. S. Jacobson & G. Margolin, 1979) and integrative (N. S. Jacobson & A. Christensen, 1996) behavioral couple therapy. Results based on hierarchical…

  8. Breast Cancer Subtype Influences the Accuracy of Predicting Pathologic Response by Imaging and Clinical Breast Exam After Neoadjuvant Chemotherapy.

    PubMed

    Waldrep, Ashley R; Avery, Eric J; Rose, Ferrill F; Midathada, Madhu V; Tilford, Joni A; Kolberg, Hans-Christian; Hutchins, Mark R

    2016-10-01

    Clinical response evaluation after neoadjuvant chemotherapy (NACT) for breast cancer could include various imaging methods, as well as clinical breast exam (CBE). We assessed the accuracy of CBE and imaging to predict pathologic response after NACT administration according to breast cancer subtype. This retrospective cohort study included 84 patients with records of NACT and subsequent primary breast surgery from 2003-2013. Patients were divided into 4 breast cancer subtypes according to hormone receptor (HR) status and human epidermal growth factor receptor-2 (HER2) status. Negative predictive value (NPV), false-negative rate (FNR), false-positive rate (FPR) and positive predictive value (PPV) were calculated for CBE and imaging post-NACT and prior to breast cancer surgery. NPV, FNR, FPR and PPV varied by breast cancer subtype and clinical response evaluation method. Imaging resulted in a higher NPV and a lower FNR than CBE among the entire cohort. There was a lower FPR with CBE. Clinical response evaluation by CBE was highly accurate for predicting pathologic residual disease in HR+ tumors (CBE PPV: 95.5% in HR+HER2-, 100.0% in HR+HER2+). In triple-negative breast cancer (TNBC), the imaging NPV was 100% and the imaging FNR was 0%. The use of imaging in HR+ tumors post-NACT may provide little to no additional value that is not already garnered by performance of a CBE. For TNBC, imaging may play a critical role in the prediction of pathologic complete response (pCR) post-NACT. Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  9. Does adenosine response predict clinical recurrence of atrial fibrillation after pulmonary vein isolation?

    PubMed

    Gula, Lorne J; Massel, David; Leong-Sit, Peter; Gray, Christopher; Fox, David J; Segal, Oliver R; Krahn, Andrew D; Yee, Raymond; Klein, George J; Skanes, Allan C

    2011-09-01

    Approximately 30% of patients undergoing pulmonary vein isolation (PVI) for atrial fibrillation (AF) have clinical recurrence of AF, and a great majority of these patients have recovery of vein conduction. Adenosine can be associated with acute recovery of conduction to the pulmonary veins immediately after isolation. However, it is not known whether this is prognostic for permanent recovery of conduction or recurrence of AF. Patients with paroxysmal AF underwent PVI, with administration of adenosine after electrical isolation. Those with transient conduction recovery (TCR+) underwent no further ablation and were compared to those without (TCR-) for clinical AF recurrence and conduction recovery at second procedure. Seventy-two consecutive PVI patients were studied (mean age 56.7 ± 9.2, 61 male). Twenty-five (35%) patients had transient recovery of conduction with adenosine. After 1 year, 18 patients (25%) had symptomatic recurrence of AF. In this group of 18 patients, 6 were TCR+ at initial ablation (sensitivity 33%, NPV = 74%). In the remaining group of 54 patients free from AF recurrence, 35 patients (65%) were TCR- at initial ablation (specificity 65%, PPV = 24%). All 18 patients with recurrent AF underwent repeat procedure and had at least 1 pulmonary vein with recurrent conduction. The initial adenosine test correctly predicted 13 out of 36 (36%) veins, with positive predictive value 90% and negative predictive value 15%. Adenosine testing for TCR does not appear to predict recurrence of clinical AF. TCR- veins remain susceptible to conduction recovery, as determined at the follow-up procedure.  © 2011 Wiley Periodicals, Inc.

  10. Predicting beneficial effects of atomoxetine and citalopram on response inhibition in Parkinson's disease with clinical and neuroimaging measures.

    PubMed

    Ye, Zheng; Rae, Charlotte L; Nombela, Cristina; Ham, Timothy; Rittman, Timothy; Jones, Peter Simon; Rodríguez, Patricia Vázquez; Coyle-Gilchrist, Ian; Regenthal, Ralf; Altena, Ellemarije; Housden, Charlotte R; Maxwell, Helen; Sahakian, Barbara J; Barker, Roger A; Robbins, Trevor W; Rowe, James B

    2016-03-01

    Recent studies indicate that selective noradrenergic (atomoxetine) and serotonergic (citalopram) reuptake inhibitors may improve response inhibition in selected patients with Parkinson's disease, restoring behavioral performance and brain activity. We reassessed the behavioral efficacy of these drugs in a larger cohort and developed predictive models to identify patient responders. We used a double-blind randomized three-way crossover design to investigate stopping efficiency in 34 patients with idiopathic Parkinson's disease after 40 mg atomoxetine, 30 mg citalopram, or placebo. Diffusion-weighted and functional imaging measured microstructural properties and regional brain activations, respectively. We confirmed that Parkinson's disease impairs response inhibition. Overall, drug effects on response inhibition varied substantially across patients at both behavioral and brain activity levels. We therefore built binary classifiers with leave-one-out cross-validation (LOOCV) to predict patients' responses in terms of improved stopping efficiency. We identified two optimal models: (1) a "clinical" model that predicted the response of an individual patient with 77-79% accuracy for atomoxetine and citalopram, using clinically available information including age, cognitive status, and levodopa equivalent dose, and a simple diffusion-weighted imaging scan; and (2) a "mechanistic" model that explained the behavioral response with 85% accuracy for each drug, using drug-induced changes of brain activations in the striatum and presupplementary motor area from functional imaging. These data support growing evidence for the role of noradrenaline and serotonin in inhibitory control. Although noradrenergic and serotonergic drugs have highly variable effects in patients with Parkinson's disease, the individual patient's response to each drug can be predicted using a pattern of clinical and neuroimaging features.

  11. Validation of biomarkers to predict response to immunotherapy in cancer: Volume II - clinical validation and regulatory considerations.

    PubMed

    Dobbin, Kevin K; Cesano, Alessandra; Alvarez, John; Hawtin, Rachael; Janetzki, Sylvia; Kirsch, Ilan; Masucci, Giuseppe V; Robbins, Paul B; Selvan, Senthamil R; Streicher, Howard Z; Zhang, Jenny; Butterfield, Lisa H; Thurin, Magdalena

    2016-01-01

    There is growing recognition that immunotherapy is likely to significantly improve health outcomes for cancer patients in the coming years. Currently, while a subset of patients experience substantial clinical benefit in response to different immunotherapeutic approaches, the majority of patients do not but are still exposed to the significant drug toxicities. Therefore, a growing need for the development and clinical use of predictive biomarkers exists in the field of cancer immunotherapy. Predictive cancer biomarkers can be used to identify the patients who are or who are not likely to derive benefit from specific therapeutic approaches. In order to be applicable in a clinical setting, predictive biomarkers must be carefully shepherded through a step-wise, highly regulated developmental process. Volume I of this two-volume document focused on the pre-analytical and analytical phases of the biomarker development process, by providing background, examples and "good practice" recommendations. In the current Volume II, the focus is on the clinical validation, validation of clinical utility and regulatory considerations for biomarker development. Together, this two volume series is meant to provide guidance on the entire biomarker development process, with a particular focus on the unique aspects of developing immune-based biomarkers. Specifically, knowledge about the challenges to clinical validation of predictive biomarkers, which has been gained from numerous successes and failures in other contexts, will be reviewed together with statistical methodological issues related to bias and overfitting. The different trial designs used for the clinical validation of biomarkers will also be discussed, as the selection of clinical metrics and endpoints becomes critical to establish the clinical utility of the biomarker during the clinical validation phase of the biomarker development. Finally, the regulatory aspects of submission of biomarker assays to the U.S. Food and

  12. Study of the prediction system for clinical response to M-VAC neoadjuvant chemotherapy for bladder cancer.

    PubMed

    Takata, R; Obara, W; Fujioka, T

    2010-01-01

    Neoadjuvant chemotherapy for invasive bladder cancer, involving a regimen of M-VAC, can manage micrometastasis and improve the prognosis. However, some patients suffer from severe adverse drug reactions without any effect, and no method yet exists for predicting the response of an individual patient to chemotherapy. Our purpose in this study is to establish a method for predicting the response to the M-VAC therapy. We analyzed gene-expression profiles of biopsy materials from 40 invasive bladder cancers using a cDNA microarray consisting of 27 648 genes, after populations of cancer cells had been purified by laser-microbeam microdissection. We identified 14 predictive genes that were expressed differently between nine responder and nine non-responder tumors and devised a prediction-scoring system that clearly separated the responder group from the non-responder group. This system accurately predicted the clinical response for 19 of the 22 additional test cases. The group of patients with positive predictive scores had significantly longer survival times than that with negative scores. As real-time RT-PCR data were highly concordant with the cDNA microarray data for those 14 genes, we developed a quantitative RT-PCR-based prediction system that could be feasible for routine clinical use. Taken together, our results suggest that the sensitivity of an invasive bladder cancer to the M-VAC neoadjuvant chemotherapy can be predicted by expression patterns in this set of genes, a step toward achievement of "personalized therapy" for treatment of this disease.

  13. Neurobiological markers predicting treatment response in anxiety disorders: A systematic review and implications for clinical application.

    PubMed

    Lueken, Ulrike; Zierhut, Kathrin C; Hahn, Tim; Straube, Benjamin; Kircher, Tilo; Reif, Andreas; Richter, Jan; Hamm, Alfons; Wittchen, Hans-Ulrich; Domschke, Katharina

    2016-07-01

    Anxiety disorders constitute the largest group of mental disorders with a high individual and societal burden. Neurobiological markers of treatment response bear potential to improve response rates by informing stratified medicine approaches. A systematic review was performed on the current evidence of the predictive value of genetic, neuroimaging and other physiological markers for treatment response (pharmacological and/or psychotherapeutic treatment) in anxiety disorders. Studies published until March 2015 were selected through search in PubMed, Web of Science, PsycINFO, Embase, and CENTRAL. Sixty studies were included, among them 27 on genetic, 17 on neuroimaging and 16 on other markers. Preliminary evidence was found for the functional 5-HTTLPR/rs25531 genotypes, anterior cingulate cortex function and cardiovascular flexibility to modulate treatment outcome. Studies varied considerably in methodological quality. Application of more stringent study methodology, predictions on the individual patient level and cross-validation in independent samples are recommended to set the next stage of biomarker research and to avoid flawed conclusions in the emerging field of "Mental Health Predictomics". Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Predicting beneficial effects of atomoxetine and citalopram on response inhibition in Parkinson's disease with clinical and neuroimaging measures

    PubMed Central

    Ye, Zheng; Rae, Charlotte L.; Nombela, Cristina; Ham, Timothy; Rittman, Timothy; Jones, Peter Simon; Rodríguez, Patricia Vázquez; Coyle‐Gilchrist, Ian; Regenthal, Ralf; Altena, Ellemarije; Housden, Charlotte R.; Maxwell, Helen; Sahakian, Barbara J.; Barker, Roger A.; Robbins, Trevor W.

    2016-01-01

    Abstract Recent studies indicate that selective noradrenergic (atomoxetine) and serotonergic (citalopram) reuptake inhibitors may improve response inhibition in selected patients with Parkinson's disease, restoring behavioral performance and brain activity. We reassessed the behavioral efficacy of these drugs in a larger cohort and developed predictive models to identify patient responders. We used a double‐blind randomized three‐way crossover design to investigate stopping efficiency in 34 patients with idiopathic Parkinson's disease after 40 mg atomoxetine, 30 mg citalopram, or placebo. Diffusion‐weighted and functional imaging measured microstructural properties and regional brain activations, respectively. We confirmed that Parkinson's disease impairs response inhibition. Overall, drug effects on response inhibition varied substantially across patients at both behavioral and brain activity levels. We therefore built binary classifiers with leave‐one‐out cross‐validation (LOOCV) to predict patients’ responses in terms of improved stopping efficiency. We identified two optimal models: (1) a “clinical” model that predicted the response of an individual patient with 77–79% accuracy for atomoxetine and citalopram, using clinically available information including age, cognitive status, and levodopa equivalent dose, and a simple diffusion‐weighted imaging scan; and (2) a “mechanistic” model that explained the behavioral response with 85% accuracy for each drug, using drug‐induced changes of brain activations in the striatum and presupplementary motor area from functional imaging. These data support growing evidence for the role of noradrenaline and serotonin in inhibitory control. Although noradrenergic and serotonergic drugs have highly variable effects in patients with Parkinson's disease, the individual patient's response to each drug can be predicted using a pattern of clinical and neuroimaging features. Hum Brain Mapp 37:1026–1037

  15. Early response predicts subsequent response to olanzapine long-acting injection in a randomized, double-blind clinical trial of treatment for schizophrenia

    PubMed Central

    2011-01-01

    Background In patients with schizophrenia, early non-response to oral antipsychotic therapy robustly predicts subsequent non-response to continued treatment with the same medication. This study assessed whether early response predicted later response when using a long-acting injection (LAI) antipsychotic. Methods Data were taken from an 8-week, randomized, double-blind, placebo-controlled study of olanzapine LAI in acutely ill patients with schizophrenia (n = 233). Early response was defined as ≥30% improvement from baseline to Week 4 in Positive and Negative Syndrome Scale (PANSS0-6) Total score. Subsequent response was defined as ≥40% baseline-to-endpoint improvement in PANSS0-6 Total score. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and predictive accuracy were calculated. Clinical and functional outcomes were compared between Early Responders and Early Non-responders. Results Early response/non-response to olanzapine LAI predicted later response/non-response with high sensitivity (85%), specificity (72%), PPV (78%), NPV (80%), and overall accuracy (79%). Compared to Early Non-responders, Early Responders had significantly greater improvement in PANSS0-6 Total scores at all time points and greater baseline-to-endpoint improvement in PANSS subscale scores, Quality of Life Scale scores, and Short Form-36 Health Survey scores (all p ≤ .01). Among Early Non-responders, 20% demonstrated response by Week 8. Patients who lacked early improvement (at Week 4) in Negative Symptoms and Disorganized Thoughts were more likely to continue being non-responders at Week 8. Conclusions Among acutely ill patients with schizophrenia, early response predicted subsequent response to olanzapine LAI. Early Responders experienced significantly better clinical and functional outcomes than Early Non-responders. Findings are consistent with previous research on oral antipsychotics. Clinical Trials Registry F1D-MC-HGJZ: Comparison of

  16. Prediction of clinical response based on pharmacokinetic/pharmacodynamic models of 5-hydroxytryptamine reuptake inhibitors in mice.

    PubMed

    Kreilgaard, M; Smith, D G; Brennum, L T; Sánchez, C

    2008-09-01

    Bridging the gap between preclinical research and clinical trials is vital for drug development. Predicting clinically relevant steady-state drug concentrations (Css) in serum from preclinical animal models may facilitate this transition. Here we used a pharmacokinetic/pharmacodynamic (PK/PD) modelling approach to evaluate the predictive validity of 5-hydroxytryptamine (5-HT; serotonin) transporter (SERT) occupancy and 5-hydroxytryptophan (5-HTP)-potentiated behavioral syndrome induced by 5-HT reuptake inhibitor (SRI) antidepressants in mice. Serum and whole brain drug concentrations, cortical SERT occupancy and 5-HTP-potentiated behavioral syndrome were measured over 6 h after a single subcutaneous injection of escitalopram, paroxetine or sertraline. [(3)H]2-(2-dimethylaminomethylphenylsulphanyl)-5-methyl-phenylamine ([(3)H]MADAM) was used to assess SERT occupancy. For PK/PD modelling, an effect-compartment model was applied to collapse the hysteresis and predict the steady-state relationship between drug exposure and PD response. The predicted Css for escitalopram, paroxetine and sertraline at 80% SERT occupancy in mice are 18 ng mL(-1), 18 ng mL(-1) and 24 ng mL(-1), respectively, with corresponding responses in the 5-HTP behavioral model being between 20-40% of the maximum. Therapeutically effective SERT occupancy for SRIs in depressed patients is approximately 80%, and the corresponding plasma Css are 6-21 ng mL(-1), 21-95 ng mL(-1) and 20-48 ng mL(-1) for escitalopram, paroxetine and sertraline, respectively. Thus, PK/PD modelling using SERT occupancy and 5-HTP-potentiated behavioral syndrome as response markers in mice may be a useful tool to predict clinically relevant plasma Css values.

  17. Predicting Clinical and Echocardiographic Response After Cardiac Resynchronization Therapy With a Score Combining Clinical, Electrocardiographic, and Echocardiographic Parameters.

    PubMed

    Bernard, Anne; Menet, Aymeric; Marechaux, Sylvestre; Fournet, Maxime; Schnell, Frederic; Guyomar, Yves; Leclercq, Christophe; Mabo, Philippe; Fauchier, Laurent; Donal, Erwan

    2017-06-01

    The L2ANDS2 score was previously found to be able to assess the probability of left ventricular (LV) remodeling. We sought to evaluate this score in terms of clinical outcomes: 275 patients with heart failure, from 2 centers, implanted with a cardiac resynchronization therapy (CRT) device were followed at least 2 years after implantation. Baseline clinical, electrocardiographic, and echocardiographic characteristics including left bundle branch block, age >70 years, nonischemic etiology, LV end-diastolic diameter <40 mm/m(2), and septal flash by echocardiography were integrated in 4 scoring systems. Nonresponse to CRT was LV reverse remodeling <15% at 6 months' follow-up and/or occurrence of major cardiovascular event (cardiovascular death or transplantation or assistance) during a clinical follow-up of at least 2 years. Ninety-seven patients (36%) demonstrated nonresponse to CRT. The L2ANDS2 score demonstrated the best predictive value (C statistic of 0.783) for predicting absence of LV reverse remodeling and/or occurrence of major cardiovascular event during the 2 years follow-up compared with other scoring systems that do not include septal flash. A L2ANDS2 score ≤4 was associated with a worse outcome (38% survival vs 81% survival, hazard ratio 4.19, 95% CI 2.70 to 6.48, p <0.0001). In conclusion, the L2ANDS2 score is able to assess the probability of nonresponse to CRT in terms of no reverse LV remodeling and/or major cardiovascular event at long-term follow-up. Integrating septal flash in a scoring system adds value over left bundle branch block only. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. A Prediction Algorithm for Drug Response in Patients with Mesial Temporal Lobe Epilepsy Based on Clinical and Genetic Information.

    PubMed

    Silva-Alves, Mariana S; Secolin, Rodrigo; Carvalho, Benilton S; Yasuda, Clarissa L; Bilevicius, Elizabeth; Alvim, Marina K M; Santos, Renato O; Maurer-Morelli, Claudia V; Cendes, Fernando; Lopes-Cendes, Iscia

    2017-01-01

    Mesial temporal lobe epilepsy is the most common form of adult epilepsy in surgical series. Currently, the only characteristic used to predict poor response to clinical treatment in this syndrome is the presence of hippocampal sclerosis. Single nucleotide polymorphisms (SNPs) located in genes encoding drug transporter and metabolism proteins could influence response to therapy. Therefore, we aimed to evaluate whether combining information from clinical variables as well as SNPs in candidate genes could improve the accuracy of predicting response to drug therapy in patients with mesial temporal lobe epilepsy. For this, we divided 237 patients into two groups: 75 responsive and 162 refractory to antiepileptic drug therapy. We genotyped 119 SNPs in ABCB1, ABCC2, CYP1A1, CYP1A2, CYP1B1, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, and CYP3A5 genes. We used 98 additional SNPs to evaluate population stratification. We assessed a first scenario using only clinical variables and a second one including SNP information. The random forests algorithm combined with leave-one-out cross-validation was used to identify the best predictive model in each scenario and compared their accuracies using the area under the curve statistic. Additionally, we built a variable importance plot to present the set of most relevant predictors on the best model. The selected best model included the presence of hippocampal sclerosis and 56 SNPs. Furthermore, including SNPs in the model improved accuracy from 0.4568 to 0.8177. Our findings suggest that adding genetic information provided by SNPs, located on drug transport and metabolism genes, can improve the accuracy for predicting which patients with mesial temporal lobe epilepsy are likely to be refractory to drug treatment, making it possible to identify patients who may benefit from epilepsy surgery sooner.

  19. A Prediction Algorithm for Drug Response in Patients with Mesial Temporal Lobe Epilepsy Based on Clinical and Genetic Information

    PubMed Central

    Carvalho, Benilton S.; Bilevicius, Elizabeth; Alvim, Marina K. M.; Lopes-Cendes, Iscia

    2017-01-01

    Mesial temporal lobe epilepsy is the most common form of adult epilepsy in surgical series. Currently, the only characteristic used to predict poor response to clinical treatment in this syndrome is the presence of hippocampal sclerosis. Single nucleotide polymorphisms (SNPs) located in genes encoding drug transporter and metabolism proteins could influence response to therapy. Therefore, we aimed to evaluate whether combining information from clinical variables as well as SNPs in candidate genes could improve the accuracy of predicting response to drug therapy in patients with mesial temporal lobe epilepsy. For this, we divided 237 patients into two groups: 75 responsive and 162 refractory to antiepileptic drug therapy. We genotyped 119 SNPs in ABCB1, ABCC2, CYP1A1, CYP1A2, CYP1B1, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, and CYP3A5 genes. We used 98 additional SNPs to evaluate population stratification. We assessed a first scenario using only clinical variables and a second one including SNP information. The random forests algorithm combined with leave-one-out cross-validation was used to identify the best predictive model in each scenario and compared their accuracies using the area under the curve statistic. Additionally, we built a variable importance plot to present the set of most relevant predictors on the best model. The selected best model included the presence of hippocampal sclerosis and 56 SNPs. Furthermore, including SNPs in the model improved accuracy from 0.4568 to 0.8177. Our findings suggest that adding genetic information provided by SNPs, located on drug transport and metabolism genes, can improve the accuracy for predicting which patients with mesial temporal lobe epilepsy are likely to be refractory to drug treatment, making it possible to identify patients who may benefit from epilepsy surgery sooner. PMID:28052106

  20. Baseline factors predicting placebo response to treatment in children and adolescents with autism spectrum disorders: a multisite randomized clinical trial.

    PubMed

    King, Bryan H; Dukes, Kimberly; Donnelly, Craig L; Sikich, Linmarie; McCracken, James T; Scahill, Lawrence; Hollander, Eric; Bregman, Joel D; Anagnostou, Evdokia; Robinson, Fay; Sullivan, Lisa; Hirtz, Deborah

    2013-11-01

    The finding of factors that differentially predict the likelihood of response to placebo over that of an active drug could have a significant impact on study design in this population. To identify possible nonspecific, baseline predictors of response to intervention in a large randomized clinical trial of children and adolescents with autism spectrum disorders. Randomized clinical trial of citalopram hydrobromide for children and adolescents with autism spectrum disorders and prominent repetitive behavior. Baseline data at study entry were examined with respect to final outcome to determine if response predictors could be identified. A total of 149 children and adolescents 5 to 17 years of age (mean [SD] age, 9.4 [3.1] years) from 6 academic centers were randomly assigned to citalopram (n = 73) or placebo (n = 76). Participants had autistic disorder, Asperger syndrome, or pervasive developmental disorder, not otherwise specified; had illness severity ratings that were moderate or more than moderate on the Clinical Global Impression-Severity scale; and scored moderate or more than moderate on compulsive behaviors measured with the modified Children's Yale-Brown Obsessive-Compulsive Scale. Twelve weeks of treatment with citalopram (10 mg/5 mL) or placebo. The mean (SD) maximum dose of citalopram was 16.5 (6.5) mg by mouth daily (maximum dose, 20 mg/d). A positive response was defined as having a score of at least much improved on the Clinical Global Impression-Improvement scale at week 12. Baseline measures included demographic (sex, age, weight, and pubertal status), clinical, and family measures. Clinical variables included baseline illness severity ratings (the Aberrant Behavior Checklist, the Child and Adolescent Symptom Inventory, the Vineland Adaptive Behavior Scales, the Repetitive Behavior Scale-Revised, and the Children's Yale-Brown Obsessive-Compulsive Scale). Family measures included the Caregiver Strain Questionnaire. Several baseline predictors of

  1. Rapid response predicts 12-month post-treatment outcomes in binge-eating disorder: theoretical and clinical implications

    PubMed Central

    Grilo, C. M.; White, M. A.; Wilson, G. T.; Gueorguieva, R.; Masheb, R. M.

    2011-01-01

    Background We examined rapid response in obese patients with binge-eating disorder (BED) in a clinical trial testing cognitive behavioral therapy (CBT) and behavioral weight loss (BWL). Method Altogether, 90 participants were randomly assigned to CBT or BWL. Assessments were performed at baseline, throughout and post-treatment and at 6- and 12-month follow-ups. Rapid response, defined as ≥70% reduction in binge eating by week four, was determined by receiver operating characteristic curves and used to predict outcomes. Results Rapid response characterized 57% of participants (67% of CBT, 47% of BWL) and was unrelated to most baseline variables. Rapid response predicted greater improvements across outcomes but had different prognostic significance and distinct time courses for CBT versus BWL. Patients receiving CBT did comparably well regardless of rapid response in terms of reduced binge eating and eating disorder psychopathology but did not achieve weight loss. Among patients receiving BWL, those without rapid response failed to improve further. However, those with rapid response were significantly more likely to achieve binge-eating remission (62% v. 13%) and greater reductions in binge-eating frequency, eating disorder psychopathology and weight loss. Conclusions Rapid response to treatment in BED has prognostic significance through 12-month follow-up, provides evidence for treatment specificity and has clinical implications for stepped-care treatment models for BED. Rapid responders who receive BWL benefit in terms of both binge eating and short-term weight loss. Collectively, these findings suggest that BWL might be a candidate for initial intervention in stepped-care models with an evaluation of progress after 1 month to identify non-rapid responders who could be advised to consider a switch to a specialized treatment. PMID:21923964

  2. Near-infrared spectroscopy in schizophrenia: a possible biomarker for predicting clinical outcome and treatment response.

    PubMed

    Koike, Shinsuke; Nishimura, Yukika; Takizawa, Ryu; Yahata, Noriaki; Kasai, Kiyoto

    2013-01-01

    Functional near-infrared spectroscopy (fNIRS) is a relatively new technique that can measure hemoglobin changes in brain tissues, and its use in psychiatry has been progressing rapidly. Although it has several disadvantages (e.g., relatively low spatial resolution and the possibility of shallow coverage in the depth of brain regions) compared with other functional neuroimaging techniques (e.g., functional magnetic resonance imaging and positron emission tomography), fNIRS may be a candidate instrument for clinical use in psychiatry, as it can measure brain activity in naturalistic position easily and non-invasively. fNIRS instruments are also small and work silently, and can be moved almost everywhere including schools and care units. Previous fNIRS studies have shown that patients with schizophrenia have impaired activity and characteristic waveform patterns in the prefrontal cortex during the letter version of the verbal fluency task, and part of these results have been approved as one of the Advanced Medical Technologies as an aid for the differential diagnosis of depressive symptoms by the Ministry of Health, Labor and Welfare of Japan in 2009, which was the first such approval in the field of psychiatry. Moreover, previous studies suggest that the activity in the frontopolar prefrontal cortex is associated with their functions in chronic schizophrenia and is its next candidate biomarker. Future studies aimed at exploring fNIRS differences in various clinical stages, longitudinal changes, drug effects, and variations during different task paradigms will be needed to develop more accurate biomarkers that can be used to aid differential diagnosis, the comprehension of the present condition, the prediction of outcome, and the decision regarding treatment options in schizophrenia. Future fNIRS researches will require standardized measurement procedures, probe settings, analytical methods and tools, manuscript description, and database systems in an fNIRS community.

  3. Clinical baseline factors predict response to natalizumab: their usefulness in patient selection

    PubMed Central

    2014-01-01

    Background Optimal patient selection would improve the risk-benefit ratio of natalizumab treatment for relapsing-remitting multiple sclerosis (RR MS). Clinical features of subjects responding to natalizumab have not been univocally recognized. Methods Longitudinal data on RR MS patients treated with natalizumab in Liguria, Italy are reported. Predictors of relapse occurrence and disability improvement were analyzed with a logistic regression method in subjects treated for one year (N = 62). A new score, called “Better EDSS Trend (BET)”, was devised to describe the impact of the treatment on disability. Changes in annualized relapse rate (ARR) and Expanded Disability Status Scale (EDSS) after one and two years and proportion of disease-free patients were evaluated. Results Previous EDSS worsening plus ARR ≥ 2 increased the risk of relapse during the treatment [Odds Ratio (OR) 4.12, P = 0.04], but this was not associated with an increase in disability at one year. EDSS 3.0-3.5 or high disease activity were associated with neurological improvement in the first year of treatment (respectively OR 5.78, P = 0.05 and OR 4.80, P = 0.05). Positive BET score, i.e. improvement in the disability trend, was observed in 40.3% of patients, and correlated with high ARR in the year before treatment (OR 1.69, P = 0.03). Conclusion Subjects with EDSS 3.0-3.5 and those with very active disease in the year before treatment are most likely to improve in neurological function under natalizumab. A relapse in the first year of treatment is associated to high pre-treatment disease activity; however, since the occurrence of a relapse did not have a negative impact on clinical improvement at one year, we suggest that it should not lead to treatment discontinuation. We propose BET as an additional endpoint of treatment response in MS. PMID:24885703

  4. Pre-treatment SNOT-22 Score Predicts Response to Endoscopic Polypectomy in Clinic (EPIC) Our experience in 30 adults.

    PubMed

    Caulley, Lisa; Lasso, Andrea; Rudmik, Luke; Kilty, Shaun J

    2016-01-23

    Endoscopic polypectomy in clinic (EPIC) has demonstrated substantial short-term improvement in patient reported quality of life measures and a pilot economic analysis of EPIC confirmed its cost-effectiveness in comparison to endoscopic sinus surgery. The purpose of this study was to evaluate if pre-treatment Sino Nasal Outcome Tests-22 (SNOT-22) score predicts response to EPIC treatment in parallel to the results found for endoscopic sinus surgery. Depending on the baseline SNOT-22 group the probability of achieving minimal clinically important difference was 75-100% post-EPIC. The relative improvement in quality of life on average was 62% with 90% realising a minimal clinically important difference in their SNOT-22 score. These results are comparable to what has been found for endoscopic sinus surgery. The results of this study reflect the published results of the effect of endoscopic sinus surgery on SNOT-22 scores 6 months post-intervention which themselves have been shown to predict SNOT-22 scores at 18 months post-endoscopic sinus surgery. In select patients with chronic rhinosinusitis with nasal polyps the EPIC procedure may provide SNOT-22 score improvements similar to those seen with patients who undergo endoscopic sinus surgery This article is protected by copyright. All rights reserved.

  5. Clinical trials for predictive medicine.

    PubMed

    Simon, Richard

    2012-11-10

    Developments in biotechnology and genomics are providing a biological basis for the heterogeneity of clinical course and response to treatment that have long been apparent to clinicians. The ability to molecularly characterize human diseases presents new opportunities to develop more effective treatments and new challenges for the design and analysis of clinical trials. In oncology, treatment of broad populations with regimens that benefit a minority of patients is less economically sustainable with expensive molecularly targeted therapeutics. The established molecular heterogeneity of human diseases requires the development of new paradigms for the design and analysis of randomized clinical trials as a reliable basis for predictive medicine. We review prospective designs for the development of new therapeutics and predictive biomarkers to inform their use. We cover designs for a wide range of settings. At one extreme is the development of a new drug with a single candidate biomarker and strong biological evidence that marker negative patients are unlikely to benefit from the new drug. At the other extreme are Phase III clinical trials involving both genome-wide discovery of a predictive classifier and internal validation of that classifier. We have outlined a prediction-based approach to the analysis of randomized clinical trials that both preserves the Type I error and provides a reliable internally validated basis for predicting which patients are most likely or unlikely to benefit from the new regimen.

  6. Cultural Responsivity in Clinical Psychology Graduate Students: A Developmental Approach to the Prediction of Learning

    ERIC Educational Resources Information Center

    Berrin, Sebastian Everett

    2010-01-01

    This study used a mixed-method approach to examine students' experiences in multicultural training and their opinions about various aspects of their course(s). A developmental model of learning was employed to analyze results. More specifically, this study explored the relationship between clinical psychology doctoral students' self-reported…

  7. A Review of Modeling Approaches to Predict Drug Response in Clinical Oncology

    PubMed Central

    2017-01-01

    Model-based approaches have emerged as important tools for quantitatively understanding temporal relationships between drug dose, concentration, and effect over the course of treatment, and have now become central to optimal drug development and tailored drug treatment. In oncology, the therapeutic index of a chemotherapeutic drug is typically narrow and a full dose–response relationship is not available, often because of treatment failure. Noting the benefits of model-based approaches and the low therapeutic index of oncology drugs, in recent years, modeling approaches have been increasingly used to streamline oncologic drug development through early identification and quantification of dose–response relationships. With this background, this report reviews publications that used model-based approaches to evaluate drug treatment outcome variables in oncology therapeutics, ranging from tumor size dynamics to tumor/biomarker time courses and survival response. PMID:27873489

  8. Immune contexture and histological response after neoadjuvant chemotherapy predict clinical outcome of lung cancer patients.

    PubMed

    Remark, Romain; Lupo, Audrey; Alifano, Marco; Biton, Jerome; Ouakrim, Hanane; Stefani, Alessandro; Cremer, Isabelle; Goc, Jeremy; Régnard, Jean-Francois; Dieu-Nosjean, Marie-Caroline; Damotte, Diane

    2016-01-01

    There is now growing evidence that the immune contexture influences cancer progression and clinical outcome of patients with non-small cell lung cancer (NSCLC). If chemotherapy is widely used to treat patients with advanced-stage NSCLC, it remains unclear how it could modify the immune contexture and impact its prognostic value. Here, we analyzed two retrospective cohorts, respectively composed of 122 stage III-N2 NSCLC patients treated with chemotherapy before surgery and 39 stage-matched patients treated by surgery only. In patients treated with neoadjuvant chemotherapy, the histological characteristics, the expression of PD-L1 protein, and the tumor immune microenvironment (CD8(+) T cells, DC-LAMP(+) mature dendritic cells, and CD68(+) macrophages) were evaluated and their prognostic value assessed together with standard clinical parameters. By analyzing pre- and post-treatment specimens, we did not find any changes in the PD-L1 expression. We also found that the tumor immune contexture in patients treated with neoadjuvant chemotherapy exhibited a similar pattern that the one found in chemotherapy-naive patients, with comparable densities of tumor-infiltrating CD8(+) and DC-LAMP(+) cells and a similar spatial organization. The percentage of residual viable tumor cells and the immune pattern (CD8(+) and DC-LAMP(+) cell densities) were significantly associated with the clinical outcome and allowed the identification of short- and long-term survivors, respectively. In multivariate analysis, the immune pattern was found to be the strongest independent prognostic factor. In conclusion, this study decrypts the complex interplay between cancer and immune cells in patients undergoing chemotherapy and supports potential beneficial synergistic effect of immunotherapy and chemotherapy.

  9. Can clinical response to cyclosporin in chronic severe asthma be predicted by an in vitro T-lymphocyte proliferation assay?

    PubMed

    Alexander, A G; Barnes, N C; Kay, A B; Corrigan, C J

    1996-07-01

    This study tests the hypothesis that the clinical response to cyclosporin therapy of patients with chronic severe asthma is related to the sensitivity of their T-lymphocytes to the antiproliferative effects of cyclosporin in vitro. In a previous study, we observed such a relationship with glucocorticoids and the same lectin-driven proliferation assay was used in the present study. Peripheral blood mononuclear cells were obtained from 33 patients participating in a cross-over trial of oral cyclosporin therapy during both cyclosporin and placebo treatment periods, and cultured in the presence of phytohaemagglutinin and serial dilutions of cyclosporin and dexamethasone. Proliferation was measured by tritiated thymidine uptake. Both cyclosporin and dexamethasone inhibited T-lymphocyte proliferation in a concentration-dependent manner in vitro at concentrations encompassing those achieved in peripheral blood during therapy in vivo. T-lymphocytes from the asthmatic patients showed a range of sensitivity to the antiproliferative effects of cyclosporin, but this could not be correlated with improvements in peak expiratory flow rate (PEFR) or forced expiratory volume in one second (FEV1) during cyclosporin therapy as compared with placebo. In contrast to previous observations with glucocorticoids, this in vitro T-lymphocyte proliferation assay is not predictive of clinical response to cyclosporin therapy in chronic severe asthmatics.

  10. [Clinical prediction in medical oncology].

    PubMed

    González Barón, Manuel

    2003-01-01

    Predictive factors (PF) are variables that give information about survival, treatment response or toxicity and future complications on cancer patients. The foremost utility of PF takes root in the possibility to furnish an individualized treatment schedule with higher succeeding options. They include clinical characteristics of the patient, tumour features, treatment administrated, classical pathological and new molecular data obtained from patients clinical samples. Clinical parameters comprise age, sex, underlying diseases and performance status among others, and in concurrence with tumour pathology and clinical stage (TNM) usually define the best treatment options. Also, chemotherapy response can modify natural history of several tumours, and thus is a PF. Modifications in evolving PF typically induce a variation in patient outcome. Hence, surgical tumour size reduction or neoadjuvant down-staging improve survival in several cancers. In the other side, treatment adjustment to steady PF should offers better outcome than "standard therapies". Recent advances on cancer research have generated a great deal of biological data that help us to search new treatment and diagnostic modalities. Biotechnology offers a great amount of possibilities in the next future and probably a true individualized therapy. Conversely, there are a small amount of molecular evidences that imply a creal variation in current clinical practice. Hence, more scientific and financial efforts are necessary to exploit to the full knowledge spurting up from basic science. In summary, the prediction in oncology is a hard task derived from clinical observation, tumour behaviour, treatment schedules and biological evidences that must offer realistic predictions on a concrete cancer patient. Oncologists have a duty to know all these variables to accomplish this thorny assignment. This review will focus on classical and recent biological PF in cancer.

  11. Predicting response to epigenetic therapy

    PubMed Central

    Treppendahl, Marianne B.; Kristensen, Lasse S.; Grønbæk, Kirsten

    2014-01-01

    Drugs targeting the epigenome are new promising cancer treatment modalities; however, not all patients receive the same benefit from these drugs. In contrast to conventional chemotherapy, responses may take several months after the initiation of treatment to occur. Accordingly, identification of good pretreatment predictors of response is of great value. Many clinical parameters and molecular targets have been tested in preclinical and clinical studies with varying results, leaving room for optimization. Here we provide an overview of markers that may predict the efficacy of FDA- and EMA-approved epigenetic drugs. PMID:24382389

  12. Prediction of conductive hearing loss based on acoustic ear-canal response using a multivariate clinical decision theory.

    PubMed

    Piskorski, P; Keefe, D H; Simmons, J L; Gorga, M P

    1999-03-01

    This study evaluated the accuracy of acoustic response tests in predicting conductive hearing loss in 161 ears of subjects from the age of 2 to 10 yr, using as a "gold standard" the air-bone gap to classify ears as normal or impaired. The acoustic tests included tympanometric peak-compensated static admittance magnitude (SA) and tympanometric gradient at 226 Hz, and admittance-reflectance (YR) measurements from 0.5 to 8 kHz. The performance of individual, frequency-specific, YR test variables as predictors was assessed. By applying logistic regression (LR) and discriminant analysis (DA) techniques to the multivariate YR response, two univariate functions were calculated as the linear combinations of YR variables across frequency that best separated normal and impaired ears. The tympanometric and YR tests were also combined in a multivariate manner to test whether predictive efficacy improved when 226-Hz tympanometry was added to the predictor set. Conductive hearing loss was predicted based on air-bone gap thresholds at 0.5 and 2 kHz, and on a maximum air-bone gap at any octave frequency from 0.5 to 4 kHz. Each air-bone gap threshold ranged from 5 to 30 dB in 5-dB steps. Areas under the relative operating characteristic curve for DA and LR were larger than for reflectance at 2 kHz, SA and Gr. For constant hit rates of 80% and 90%, both DA and LR scores had lower false-alarm rates than tympanometric tests-LR achieved a false-alarm rate of 6% for a sensitivity of 90%. In general, LR outperformed DA as the multivariate technique of choice. In predicting an impairment at 0.5 kHz, the reflectance scores at 0.5 kHz were less accurate predictors than reflectance at 2 and 4 kHz. This supports the hypothesis that the 2-4-kHz range is a particularly sensitive indicator of middle-ear status, in agreement with the spectral composition of the output predictor from the multivariate analyses. When tympanometric and YR tests were combined, the resulting predictor performed

  13. Early Clinical Response after 2 Weeks of Sorafenib Therapy Predicts Outcomes and Anti-Tumor Response in Patients with Advanced Hepatocellular Carcinoma

    PubMed Central

    Kuzuya, Teiji; Ishigami, Masatoshi; Ishizu, Yoji; Honda, Takashi; Hayashi, Kazuhiko; Katano, Yoshiaki; Hirooka, Yoshiki; Ishikawa, Tetsuya; Nakano, Isao; Goto, Hidemi

    2015-01-01

    Background & Aims We evaluated the relationship between the early clinical response after 2 weeks of sorafenib therapy and the outcomes and anti-tumor response in patients with advanced hepatocellular carcinoma. Methods Fifty-seven patients who had intrahepatic hypervascular hepatocellular carcinoma and Child-Pugh (CP) class A disease at baseline were enrolled in this prospective, multicenter, observational, non-interventional study. As an early clinical response after 2 weeks of sorafenib therapy, changes in intra-tumor blood flow on contrast-enhanced computed tomography (CE-CT), alpha-fetoprotein (AFP) levels, and remnant liver function were investigated. Results After 2 weeks of sorafenib therapy, there were 26 patients (45.6%) without disappearance of arterial tumor enhancement on CE-CT, 15 patients (26.3%) with an AFP ratio of >1.2, and seven patients (12.3%) with two or more increments in the CP score. Multivariate analysis showed that the absence of disappearance of arterial tumor enhancement on CE-CT, AFP ratio of >1.2, and two or more increments in the CP score after 2 weeks of sorafenib therapy were significant and independent predictors of worse survival. Upon scoring these three variables as "poor prognostic factors", patients with poor prognostic score 4, 3 or 2 (n = 17) had significantly worse outcomes and a significantly higher progressive disease (PD) rate based on modified Response Evaluation Criteria in Solid Tumors at 6 weeks after sorafenib therapy than those with poor prognostic score 1 or 0 (n = 40) (median overall survival: 194 days vs. 378 days; p = 0.0010, PD rate: 70.6% vs. 20.0%; p = 0.0003, respectively). Conclusions Changes in intra-tumor blood flow on CE-CT, AFP levels, and remnant liver function after 2 weeks of sorafenib therapy may be useful for predicting the outcomes and anti-tumor response to sorafenib in patients with advanced hepatocellular carcinoma. PMID:26421430

  14. Activation of c-Jun predicts a poor response to sorafenib in hepatocellular carcinoma: Preliminary Clinical Evidence

    PubMed Central

    Chen, Wei; Xiao, Weikai; Zhang, Kunsong; Yin, Xiaoyu; Lai, Jiaming; Liang, Lijian; Chen, Dong

    2016-01-01

    We determined the mitogen-activated protein kinase (MAPK) gene expression profile of acquired resistance in sorafenib-sensitive hepatocellular carcinoma (HCC) cells and aimed to identify c-Jun as an important molecule mediating the efficacy of sorafenib. Differences in gene expression of the MAPK signaling between untreated and sorafenib-treated HCC cell lines were investigated using real-time polymerase chain reaction array. Western blot and real-time PCR further evaluated the expression of c-Jun. Pathological specimens from 50 patients with advanced HCC were collected to measure p-c-Jun expression. Sorafenib-resistant HCC cells demonstrated greater levels of basal c-Jun mRNA and protein compared with sorafenib-sensitive HCC cells. Sorafenib activated p-c-Jun in a dose- and time-dependent manner in PLC/PRF/5 and MHCC97H cell lines. Decreased expression levels of 6 genes after sorafenib treatment suggested a robust inhibitory impact of sorafenib on MAPK signaling in HCC cells. c-Jun and p-c-Jun expression levels were inversely correlated with the efficacy of sorafenib; a high expression level of p-c-Jun was associated with resistance to sorafenib and poor overall survival in patients with clinical HCC. p-c-Jun may act as a biomarker for predicting responses of sorafenib treatment, thus advocating targeting of JNK/c-Jun signaling as an optimal therapeutic strategy in a subset of HCC. PMID:26964667

  15. Short term response is predictive of long term response to acetylcholinesterase inhibitors in Alzheimer’s disease: A starting point to explore Bayesian approximation in clinical practice

    PubMed Central

    Rota, Eugenia; Ferrero, Patrizia; Ursone, Rita; Migliaretti, Giuseppe

    2007-01-01

    This study was aimed at identifying, in 203 patients with Alzheimer's disease followed during long-term treatment with Acetylcholinesterase inhibitors (ChEIs), the predictive factors of the clinical response among cognition (MMSE), functioning (BADL and IADL) measures and age and gender at the baseline (T0). The ANCOVA test showed a significant association between MMSE scores at time T0 and T3, and the variation T9 to T0, T15 to T0 and T21 to T0 of the MMSE scores, using also gender, age and drug as covariates. The significance was higher for the patients affected by mild dementia. Regarding functional activities, a significant relationship was detected, by the ANCOVA test, only between the scores at T3 and the variation T15 to T0 for BADL, and the variation T9 to T0, T15 to T0 for IADL, respectively. Our results confirm, in a real world setting, that ChEIs provide long-term cognitive benefit, which is correlated to, and predictable by, the short-term response (within the third month) as well as the cognitive status (evaluated by means of the MMSE) at the beginning of the treatment. These factors should be the basis of any cost/effectiveness algorithm in health economic decision models. PMID:18188418

  16. Incremental Value of Cystatin C Over Conventional Renal Metrics for Predicting Clinical Response and Outcomes in Cardiac Resynchronization Therapy: The BIOCRT Study

    PubMed Central

    Chatterjee, Neal A.; Singh, Jagmeet P.; Szymonifka, Jackie; Deaño, Roderick C.; Thai, Wai-ee; Wai, Bryan; Min, James K.; Januzzi, James L.; Truong, Quynh A.

    2015-01-01

    Background Despite the benefit of CRT in select patients with heart failure (HF), there remains significant need for predicting those at risk for adverse outcomes for this effective but costly therapy. CysC, an emerging marker of renal function, is predictive of worsening symptoms and mortality in patients with HF. This study assessed the utility of baseline and serial measures of cystatin C (CysC), compared to conventional creatinine-based measures of renal function (estimated glomerular filtration rate, eGFR), in predicting clinical outcomes following cardiac resynchronization therapy (CRT). Methods In 133 patients, we measured peripheral venous (PV) and coronary sinus (CS) CysC concentrations and peripheral creatinine levels at the time of CRT implant. Study endpoints included clinical response to CRT at 6 months and major adverse cardiac events (MACE) at 2 years. Results While all 3 renal metrics were predictive of MACE (all adjusted p≤0.02), only CysC was associated with CRT non-response at 6 months (adjusted odds ratio 3.6, p=0.02). CysC improved prediction of CRT non-response (p≤0.003) in net reclassification index analysis compared to models utilizing standard renal metrics. Serial CysC >1mg/L was associated with 6-month CRT non-response and reduced 6-minute walk distance as well as 2-year MACE (all p≤0.04). Conclusion In patients undergoing CRT, CysC demonstrated incremental benefit in the prediction of CRT non-response when compared to standard metrics of renal function. Baseline and serial measures of elevated CysC were predictive of CRT non-response and functional status at 6 months as well as long term clinical outcomes. PMID:26710332

  17. Prediction of Response to Treatment in a Randomized Clinical Trial of Couple Therapy: A 2-Year Follow-Up

    ERIC Educational Resources Information Center

    Baucom, Brian R.; Atkins, David C.; Simpson, Lorelei E.; Christensen, Andrew

    2009-01-01

    Many studies have examined pretreatment predictors of immediate posttreatment outcome, but few studies have examined prediction of long-term treatment response to couple therapies. Four groups of predictors (demographic, intrapersonal, communication, and other interpersonal) and 2 moderators (pretreatment severity and type of therapy) were…

  18. Circulating B-cell activating factor level predicts clinical response of chronic graft-versus-host disease to extracorporeal photopheresis.

    PubMed

    Whittle, Robert; Taylor, Peter C

    2011-12-08

    Extracorporeal photopheresis (ECP) is an important therapeutic option in steroid-refractory chronic graft-versus-host disease (cGVHD). Few biomarkers predicting response exist. We measured serum B-cell activating factor (BAFF) in 46 cGVHD patients receiving ECP before and during treatment course. BAFF level at 1 month of ECP predicted 3- and 6-month skin disease response, with BAFF less than 4 ng/mL associated with significant skin improvement and complete resolution in 11 of 20 patients. High BAFF at 1-month ECP associated with a worsening median 6-month skin score and resolution in 1 of 10 patients. BAFF level at 3 months also predicted the likelihood of maintaining skin disease improvement at 6 months. BAFF level was not correlated directly with extracutaneous cGVHD response, although full cutaneous responders exhibited improved extracutaneous organ response rates compared with skin nonresponders (65% vs 35%). This study suggests that early BAFF measurement during ECP for cGVHD represents a potentially useful biomarker in prediction of treatment outcome.

  19. Tumor-associated gastroparesis with esophageal carcinoma. Use of intravenous metoclopramide during radionuclide gastric emptying studies to predict clinical response

    SciTech Connect

    Choe, A.I.; Ziessman, H.A.; Fleischer, D.E.

    1989-07-01

    This case report describes a patient with esophageal carcinoma and tumor-associated gastroparesis. The radionuclide gastric emptying study diagnosed very delayed liquid and solid gastric emptying. Metoclopramide was administered intravenously during the study and was able to predict a good response to oral therapy.

  20. Predicting stimulant medication response in ADHD: evidence from an integrated profile of neuropsychological, psychophysiological and clinical factors.

    PubMed

    Hermens, Daniel F; Cooper, Nicholas J; Kohn, Michael; Clarke, Simon; Gordon, Evian

    2005-03-01

    There have been significant advances in understanding the neurobiology of Attention-Deficit/Hyperactivity Disorder (ADHD) and it is timely to examine the ability of biological and psychological markers to predict medication response in this disorder. We evaluated prediction of medication response in adolescent ADHD using neuropsychological testing and psychophysiological measures of central and autonomic function. Fifty ADHD adolescents participated in pre- and post-stimulant medication testing. Separately ranked performance in auditory oddball and visual Working Memory (WM) tasks determined 20 "responders" and 20 "non-responders" with 10 "neutrals" excluded from the discriminant function analyses (DFA). For both oddball and WM performance rankings, the two groups did not differ in age, sex, or handedness. However, responders did have higher levels of symptomatology than non-responders at baseline. Pre-stimulant medication psychophysiology variables were used as predictors in each DFA. Oddball performance correctly classified 85.0% of responders and 95.0% of non-responders. Better response was associated with increased resting beta power (left posteriorly), delayed oddball target N1 (frontally), decreased oddball target P2 (left posteriorly) and decreased WM distractor P3 (right frontally). Working memory performance classified 80.0% of responders and 90.0% of non-responders, with a broadly similar profile of psychophysiological predictors. These finding indicate the value of integrating neuropsychological and psychophysiological data in predicting medication response in ADHD.

  1. Usefulness of clinical findings, nerve conduction studies and ultrasonography to predict response to surgical release in idiopathic carpal tunnel syndrome.

    PubMed

    Naranjo, A; Ojeda, S; Araña, V; Baeta, P; Fernández-Palacios, J; García-Duque, O; Rodríguez-Lozano, C; Carmona, L

    2009-01-01

    To assess the usefulness of clinical findings, nerve conduction studies and ultrasonography performed by a rheumatologist to predict success in patients with idiopathic carpal tunnel syndrome (CTS) undergoing median nerve release. Ninety consecutive patients with CTS (112 wrists) completed a specific CTS questionnaire and underwent physical examination and nerve conduction studies. Ultrasound examination was performed by a rheumatologist who was blind to any patient's data. Outcome variables were improvement >25% in symptoms of the CTS questionnaire and patient's overall satisfaction (5-point Likert scale) at 3 months postoperatively. Success was defined as improvement in both outcome variables. Receiver operating characteristics (ROC) curves and logistic regression analyses were used to assess the best predictive combination of preoperative findings. Success was achieved in 63% of the operated wrists. Utility parameters and area under the ROC curve (AUC) for individual findings was poor, ranging from 0.481 of the nerve conduction study to 0.634 of the cross-sectional area at tunnel outlet. Logistic regression identified the preoperative US parameters as the best predictive variables for success after 3 months. The best predictive combination (AUC=0.708) included a negative Phalen maneuver, plus absence of thenar atrophy, plus less than moderately abnormalities on nerve conduction studies plus a large maximal cross-sectional area along the tunnel by ultrasonography. Although cross-sectional area of the median nerve was the only predictor of success after three months of surgical release, isolated preoperative findings are not reliable predictors of success in patients with idiopathic CTS. A combination of findings that include ultrasound improves prediction.

  2. [A prospective clinical study of pleth variability index in prediction of volume responsiveness in patients with septic shock].

    PubMed

    Lu, Nianfang; Zheng, Ruiqiang; Lin, Hua; Yu, Jiangquan; Shao, Jun; Wu, Xiaoyan; Wang, Haixia

    2015-01-01

    To evaluate the role of pleth variability index ( PVI ) by passive leg raising ( PLR ) test in volume responsiveness and volume status prediction in patients with septic shock. A prospective randomized controlled trial ( RCT ) was conducted. Eighty-seven patients suffering from septic shock undergoing mechanical ventilation in Department of Critical Care Medicine of Subei People's Hospital from June 2012 to September 2014 were enrolled. The hemodynamic changes before and after PLR were monitored by pulse indicated continuous cardiac output ( PiCCO ) and PVI monitoring. Responsive group: positive fluid response was defined as an increase in cardiac index ( CI )≥10% after PLR. Unresponsive group: negative fluid response was defined as an increase in CI<10% after PLR. The hemodynamic parameters, including heart rate ( HR ), mean arterial pressure ( MAP ), central venous pressure ( CVP ), stroke volume variation ( SVV ), CI and PVI, and the changes in cardiac parameters (ΔHR, ΔMAP, ΔCVP, ΔSVV, ΔCI, and ΔPVI ) before and after PLR were determined. The relations between hemodynamic parameters and their changes with ΔCI were analyzed by the Pearson analysis. The role of the parameters for volume responsiveness prediction was evaluated by receiver operating characteristic ( ROC ) curves. 145 PLRs in 87 patients with septic shock were conducted, with 67 in responsive group and 78 in unresponsive group. There were no statistically significant differences in HR, MAP, CVP and CI before PLR between the responsive and unresponsive groups. SVV and PVI in responsive group were significantly higher than those in the unresponsive group [ SVV: ( 16.9±3.1 )% vs. ( 8.4±2.2 ) %, t = 9.078, P = 0.031; PVI: ( 20.6±4.3 )% vs. ( 11.1±3.2 )%, t = 19.189, P = 0.022 ]. There were no statistically significant differences in HR, MAP, CVP, SVV, and PVI after PLR between the responsive group and unresponsive group. CI in the responsive group was significantly higher than that in the

  3. Does clinical presentation predict response to a nonsurgical chronic disease management program for endstage hip and knee osteoarthritis?

    PubMed

    Eyles, Jillian P; Lucas, Barbara R; Patterson, Jillian A; Williams, Matthew J; Weeks, Kate; Fransen, Marlene; Hunter, David J

    2014-11-01

    To identify baseline characteristics of participants who will respond favorably following 6 months of participation in a chronic disease management program for hip and knee osteoarthritis (OA). This prospective cohort study assessed 559 participants at baseline and following 6 months of participation in the Osteoarthritis Chronic Care Program. Response was defined as the minimal clinically important difference of an 18% and 9-point absolute improvement in the Western Ontario and McMaster Universities Arthritis Index global score. Multivariate logistic regression modeling was used to identify predictors of response. Complete data were available for 308 participants. Those who withdrew within the study period were imputed as nonresponders. Three variables were independently associated with response: signal joint (knee vs hip), sex, and high level of comorbidity. Index joint and sex were significant in the multivariate model, but the model was not a sensitive predictor of response. Strong predictors of response to a chronic disease management program for hip and knee OA were not identified. The significant predictors that were found should be considered in future studies.

  4. Prediction of Treatment Response at 5-year Follow-up in a Randomized Clinical Trial of Behaviorally Based Couple Therapies

    PubMed Central

    Baucom, Brian R.; Atkins, David C.; Rowe, Lorelei Simpson; Doss, Brian D.; Christensen, Andrew

    2014-01-01

    Objective Building on earlier work examining predictors of short- and moderate-term treatment response, demographic, intrapersonal, communication, and interpersonal variables were examined as predictors of clinically significant outcomes five years after couples completed one of two behaviorally based couple therapies. Method One hundred and thirty-four couples were randomly assigned to Integrative Behavioral Couple Therapy (IBCT; Jacobson & Christensen, 1998) or Traditional Behavioral Couple Therapy (TBCT; Jacobson & Margolin, 1979) and followed for 5 years after treatment. Outcomes include clinically significant change categories of relationship satisfaction and marital status at 5-year follow-up. Optimal subsets of predictors were selected using an automated, bootstrapped selection procedure based on Bayesian Information Criterion. Results Higher levels of commitment and being married for a longer period of time were associated with decreased likelihood of divorce/separation (Odds Ratio [OR] = 1.39, p = .004; OR = 0.91, p = .015). Being married for a longer period of time was also associated with increased likelihood of positive, clinically significant change (OR = 1.12, p = .029). Finally, higher levels of wife desired closeness were associated with increased odds of positive, clinically significant change and decreased odds of divorce for moderately distressed, IBCT couples (OR = 1.16, p = 0.002; OR = 0.85, p = 0.007, respectively) whereas the opposite was true for moderately distressed, TBCT couples (OR = 0.77, p < 0.001; OR = 1.17, p = 0.002, respectively). Conclusions Commitment-related variables are associated with clinically significant outcomes at 5-year follow-up as well as at termination and moderate-term follow-up. Public health significance This study indicates that couples who begin marital therapy with higher levels of commitment are least likely to get divorced and most likely to report improvements in relationship satisfaction five years after

  5. Prediction of treatment response at 5-year follow-up in a randomized clinical trial of behaviorally based couple therapies.

    PubMed

    Baucom, Brian R; Atkins, David C; Rowe, Lorelei Simpson; Doss, Brian D; Christensen, Andrew

    2015-02-01

    Building on earlier work examining predictors of short- and moderate-term treatment response, demographic, intrapersonal, communication, and interpersonal variables were examined as predictors of clinically significant outcomes 5 years after couples completed 1 of 2 behaviorally based couple therapies. One hundred and thirty-four couples were randomly assigned to Integrative Behavioral Couple Therapy (IBCT; Jacobson & Christensen, 1998) or Traditional Behavioral Couple Therapy (TBCT; Jacobson & Margolin, 1979) and followed for 5 years after treatment. Outcomes include clinically significant change categories of relationship satisfaction and marital status at 5-year follow-up. Optimal subsets of predictors were selected using an automated, bootstrapped selection procedure based on Bayesian information criterion. Higher levels of commitment and being married for a longer period of time were associated with decreased likelihood of divorce or separation (odds ratio [OR] = 1.39, p = .004; OR = 0.91, p = .015). Being married for a longer period of time was also associated with increased likelihood of positive, clinically significant change (OR = 1.12, p = .029). Finally, higher levels of wife-desired closeness were associated with increased odds of positive, clinically significant change and decreased odds of divorce for moderately distressed, IBCT couples (OR = 1.16, p = .002; OR = 0.85, p = .007, respectively), whereas the opposite was true for moderately distressed, TBCT couples (OR = 0.77, p < .001; OR = 1.17, p = .002, respectively). Commitment-related variables are associated with clinically significant outcomes at 5-year follow-up as well as at termination and moderate-term follow-up. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  6. Clinical Model for Predicting Hepatocellular Carcinomas in Patients with Post-Sustained Virologic Responses of Chronic Hepatitis C: A Case Control Study

    PubMed Central

    Zeng, Qing-Lei; Li, Bing; Zhang, Xue-Xiu; Chen, Yan; Fu, Yan-Ling; Lv, Jun; Liu, Yan-Min; Yu, Zu-Jiang

    2016-01-01

    Background/Aims No clinical model exists to predict the occurrence of hepatocellular carcinoma in sustained virologic response-achieving (HCC after SVR) patients with chronic hepatitis C (CHC). Methods We performed a case-control study using a clinical database to research the risk factors for HCC after SVR. A predictive model based on risk factors was established, and the area under the receiver operating characteristic curve (AUC) was calculated. Results In the multivariate model, an initial diagnosis of compensated cirrhosis and post-SVR albumin reductions of 1 g/L were associated with 21.7-fold (95% CI, 4.2 to 112.3; p<0.001) and 1.3-fold (95% CI, 1.1 to 1.7; p=0.004) increases in the risk of HCC after SVR, respectively. A predictive model based on an initial diagnosis of compensated cirrhosis (yes, +1; no, 0) and post-SVR albumin ≤36.0 g/L (yes, +1; not, 0) predicted the occurrence of HCC after SVR with a cutoff value of >0, an AUC of 0.880, a sensitivity of 0.833, a specificity of 0.896, and a negative predictive value of 0.956. Conclusions An initial diagnosis of compensated cirrhosis combined with a post-SVR albumin value of ≤36.0 g/L predicts the occurrence of HCC after SVR in patients with CHC. PMID:27257023

  7. Clinical value of serum anti-mullerian hormone and inhibin B in prediction of ovarian response in patients with polycystic ovary syndrome.

    PubMed

    Zhang, Fan; Liu, Xiao-Ling; Rong, Nan; Huang, Xiao-Wen

    2017-02-01

    The present study aimed to investigate the clinical value of serum anti-mullerian hormone (AMH) and inhibin B (INHB) in predicting the ovarian response of patients with polycystic ovary syndrome (PCOS). A total of 120 PCOS patients were enrolled and divided into three groups in terms of the ovarian response: a low-response group (n=36), a normal-response group (n=44), and a high-response group (n=40). The serum AMH and INHB levels were measured by enzyme-linked immunosorbent assay (ELISA). The follicle stimulating hormone (FSH), luteinizing hormone (LH), and estradiol (E2) levels were determined by chemiluminescence microparticle immunoassay. The correlation of the serum AMH and INHB levels with other indicators was analyzed. A receiver operating characteristic (ROC) curve was established to analyze the prediction of ovarian response by AMH and INHB. The results showed that there were significant differences in age, body mass index (BMI), FSH, total gonadotropin-releasing hormone (GnRH), LH, E2, and antral follicle counts (AFCs) between the groups (P<0.05). The serum AMH and INHB levels were increased significantly with the ovarian response of PCOS patients increasing (P<0.05). The serum AMH and INHB levels were negatively correlated with the age, BMI, FSH level, Gn, and E2 levels (P<0.05). They were positively correlated with the LH levels and AFCs (P<0.05). ROC curve analysis of serum AMH and INHB in prediction of a low ovarian response showed that the area under the ROC curve (AUC) value of the serum AMH level was 0.817, with a cut-off value of 1.29 ng/mL. The sensitivity and specificity were 71.2% and 79.6%, respectively. The AUC value of serum INHB was 0.674, with a cut-off value of 38.65 ng/mL, and the sensitivity and specificity were 50.7% and 74.5%, respectively. ROC curve analysis showed when the serum AMH and INHB levels were used to predict a high ovarian response, the AUC value of the serum AMH level was 0.742, with a cut-off value of 2.84 ng/mL, and

  8. Prediction of Methotrexate Clinical Response in Portuguese Rheumatoid Arthritis Patients: Implication of MTHFR rs1801133 and ATIC rs4673993 Polymorphisms

    PubMed Central

    Lima, Aurea; Monteiro, Joaquim; Bernardes, Miguel; Sousa, Hugo; Azevedo, Rita; Seabra, Vitor; Medeiros, Rui

    2014-01-01

    Objective. Methotrexate (MTX), the most used drug in rheumatoid arthritis (RA) treatment, showing variability in clinical response, is often associated with genetic polymorphisms. This study aimed to elucidate the role of methylenetetrahydrofolate reductase (MTHFR) C677T and aminoimidazole carboxamide adenosine ribonucleotide transformylase (ATIC) T675C polymorphisms and clinicopathological variables in clinical response to MTX in Portuguese RA patients. Methods. Study included 233 RA patients treated with MTX for at least six months. MTHFR C677T and ATIC T675C polymorphisms were genotyped and clinicopathological variables were collected. Statistical analyses were performed and binary logistic regression method adjusted to possible confounding variables. Results. Multivariate analyses demonstrated that MTHFR 677TT (OR = 4.63; P = 0.013) and ATIC 675T carriers (OR = 5.16; P = 0.013) were associated with over 4-fold increased risk for nonresponse. For clinicopathological variables, noncurrent smokers (OR = 7.98; P = 0.001), patients positive to anti-cyclic citrullinated peptide (OR = 3.53; P = 0.004) and antinuclear antibodies (OR = 2.28; P = 0.045), with higher health assessment questionnaire score (OR = 2.42; P = 0.007), and nonsteroidal anti-inflammatory drug users (OR = 2.77; P = 0.018) were also associated with nonresponse. Contrarily, subcutaneous administration route (OR = 0.11; P < 0.001) was associated with response. Conclusion. Our study suggests that MTHFR C677T and ATIC T675C genotyping combined with clinicopathological data may help to identify patients whom will not benefit from MTX treatment and, therefore, assist clinicians in personalizing RA treatment. PMID:24967362

  9. A study of predictive validity, responsiveness, and minimal clinically important difference of arm accelerometer in real-world activity of patients with chronic stroke.

    PubMed

    Chen, Hao-Ling; Lin, Keh-Chung; Hsieh, Yu-Wei; Wu, Ching-Yi; Liing, Rong-Jiuan; Chen, Chia-Ling

    2017-06-01

    To investigate the predictive validity, responsiveness, and minimal clinically important difference of arm accelerometer in real-world activity of patients with chronic stroke. Validation and psychometric study. Three medical centers. Patients with chronic stroke came from three separated randomized controlled trials. Patients with stroke received upper extremity rehabilitation programs for four weeks. Real-world arm movements were measured by an arm accelerometer and three clinical measurement tools-the Motor Activity Log, Stroke Impact Scale, and Nottingham Extended Activities of Daily Living-administered before and after treatment. A total of 82 subjects were recruited in the study (mean age: 55.32 years; mean score of Fugl-Meyer Assessment: 39.91). Correlations between the arm accelerometer and three clinical measurement tools were fair to moderate (Pearson's r = 0.47, 0.42, and 0.34, respectively). The correlation between the arm accelerometer and the quality of use of Motor Activity Log subscale was moderate to good (Pearson's r = 0.57). The responsiveness of the arm accelerometer from pretreatment to posttreatment was medium (standardized response mean = 0.72). The minimal clinically important difference range for the arm accelerometer was 547-751 mean counts. The arm accelerometer demonstrated acceptable predictive validity and responsiveness in patients with chronic stroke. The affected arm activity measured by the arm accelerometer was sensitive to change. The change score of a patient with chronic stroke on the arm accelerometer should reach 574-751 mean counts to be regarded as a minimal clinically important difference.

  10. Single-dose effects on the P3no-go ERP component predict clinical response to stimulants in pediatric ADHD.

    PubMed

    Ogrim, Geir; Aasen, Ida Emilia; Brunner, Jan Ferenc

    2016-10-01

    Approximately 30% of children and adolescents diagnosed with attention-deficit/hyperactivity disorder (ADHD) and treated with stimulants are considered non-responders (non-REs). Reliable predictors of response are missing. We examined changes in Event-Related Potentials (ERPs) induced by a single dose of stimulant medication in order to predict later clinical response. ERPs were registered twice during performance of a visual cued go/no-go task in 87 ADHD patients (27 girls) aged 8-18years; the second recording on a single dose of stimulant medication, followed by a systematic medication trial lasting 4weeks. Based on the four-week trial, participants were categorized as responders (REs, N=62) or non-REs (N=25). Changes among REs and non-REs in ERP components (cueP3, CNV, P3go, N2no-go, P3no-go) and behavioral-test variables were then compared. REs and non-REs differed significantly in medication-induced changes in P3no-go, cue-P3, CNV, omission errors, reaction time, and reaction-time variability. The largest effect size was found for P3no-go amplitude (p<.001; d=1.76). Changes in P3no-go and omission errors correctly classified 90% of the REs and 76% of the non-REs, when controlling for the age of the participants. Clinical response to stimulants can be predicted by assessing single-dose changes in the P3no-go ERP component amplitude. Changes in P3no-go may be a clinically useful marker of response to stimulants. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  11. Response in bone turnover markers during therapy predicts overall survival in patients with metastatic prostate cancer: analysis of three clinical trials.

    PubMed

    Som, A; Tu, S-M; Liu, J; Wang, X; Qiao, W; Logothetis, C; Corn, P G

    2012-10-23

    The bone-forming metastases of prostate cancer result from complex stromal-epithelial interactions within the tumour microenvironment. Autocrine-paracrine signalling pathways between prostate cancer epithelial cells, osteoblasts, and osteoclasts stimulate aberrant bone remodelling, and the activity of these three cell populations can be quantitatively measured using prostate-specific antigen (PSA), bone-specific alkaline phosphatase (BAP) and urine N-telopeptide (uNTx), respectively. The purpose of the present study was to test the hypothesis that serial measurements of BAP and uNTx during therapy would facilitate monitoring of disease activity and predict the overall survival (OS) in patients with metastatic prostate cancer receiving therapy. Radionuclide bone scan, PSA, BAP, and uNTx data were retrospectively analysed from three clinical trials in patients with metastatic prostate cancer conducted at our institution. Qualitative changes in bone scans and quantitative changes in PSA, BAP, and uNTx concentrations during therapy were correlated with OS. Baseline levels of BAP, but not PSA, were prognostic for OS in both androgen-dependent and castrate-resistant disease. A reduction in PSA, BAP, uNTx, or BAP/uNTx on therapy was predictive of improved OS in both patient groups. Conversely, an increase in PSA, or BAP on therapy was predictive of worse OS in both patient groups. Baseline number of lesions and response on bone scan during therapy were neither prognostic nor predictive of OS in either patient group. These observations support the concept that serial measurements of bone turnover metabolites during therapy function as clinically informative predictive biomarkers in patients with advanced prostate cancer and skeletal metastases. PSA measurements and bone scans remain essential to monitor the overall disease activity and determine the anatomic distribution of skeletal metastases.

  12. The good EULAR response at the first year is strongly predictive of clinical remission in rheumatoid arthritis: results from the TARAC cohort.

    PubMed

    Darawankul, Budsakorn; Chaiamnuay, Sumapa; Pakchotanon, Rattapol; Asavatanabodee, Paijit; Narongroeknawin, Pongthorn

    2015-01-01

    The purpose of this study was to identify the prevalence and prognostic factors of clinical remission in patients with rheumatoid arthritis (RA). The Thai Army Rheumatoid Arthritis Cohort (TARAC) patients were included if baseline data were available. Clinical remission was defined as 28-joint count disease activity scores (DAS28) <2.6 in the last two consecutive visits, at least 3 months apart. Three hundred and thirty-five patients were enrolled, and 89.9 % were female. Mean (SD) age was 61 years (11.4), and mean disease duration was 145.9 months (93.7). Rheumatoid factor (RF) and anti-citrullinated protein antibody (ACPA) were positive in 69.9 and 67.8 %, respectively. Eighty-nine percent of patients were treated with synthetic DMARDs, of which 29 % received monotherapy. The combination of biologic and synthetic DMARDs was used in 10.4 % of the patients. Clinical remission was observed in 49 patients (14.6 %). Early diagnosis and treatment within 12 months of onset (odds ratio (OR) 1.95, 95 % confidence interval (CI) 1.02-3.74, p = 0.04), rheumatoid factor negativity (OR 2.10, 95 % CI 1.04-4.21, p = 0.04) and good EULAR response at the end of the first year of treatment (OR 2.75, 95 % CI 1.08-6.99, p = 0.03) were associated with clinical remission in univariate analysis. In multivariate regression analysis, only a good EULAR response at the first year was significantly correlated with clinical remission in this study (OR 3.1, 95 % CI 1.15-8.36, p = 0.03). Although remission is currently a treatment goal in patients with RA, only one-seventh of patients have achieved sustained clinical remission in clinical practice. The good EULAR response at the end of the first year was an independent predictive factor of clinical remission.

  13. Biomarkers to Predict Antidepressant Response

    PubMed Central

    Cook, Ian A.; Hamilton, Steven P.; Narr, Katherine L.; Toga, Arthur; Hunter, Aimee M.; Faull, Kym; Whitelegge, Julian; Andrews, Anne M.; Loo, Joseph; Way, Baldwin; Nelson, Stanley F.; Horvath, Steven; Lebowitz, Barry D.

    2010-01-01

    During the past several years, we have achieved a deeper understanding of the etiology/pathophysiology of major depressive disorder (MDD). However, this improved understanding has not translated to improved treatment outcome. Treatment often results in symptomatic improvement, but not full recovery. Clinical approaches are largely trial-and-error, and when the first treatment does not result in recovery for the patient, there is little proven scientific basis for choosing the next. One approach to enhancing treatment outcomes in MDD has been the use of standardized sequential treatment algorithms and measurement-based care. Such treatment algorithms stand in contrast to the personalized medicine approach, in which biomarkers would guide decision making. Incorporation of biomarker measurements into treatment algorithms could speed recovery from MDD by shortening or eliminating lengthy and ineffective trials. Recent research results suggest several classes of physiologic biomarkers may be useful for predicting response. These include brain structural or functional findings, as well as genomic, proteomic, and metabolomic measures. Recent data indicate that such measures, at baseline or early in the course of treatment, may constitute useful predictors of treatment outcome. Once such biomarkers are validated, they could form the basis of new paradigms for antidepressant treatment selection. PMID:20963521

  14. Clinical response after two cycles compared to HER2, Ki-67, p53, and bcl-2 in independently predicting a pathological complete response after preoperative chemotherapy in patients with operable carcinoma of the breast

    PubMed Central

    von Minckwitz, Gunter; Sinn, Hans-Peter; Raab, Günter; Loibl, Sibylle; Blohmer, Jens-Uwe; Eidtmann, Holger; Hilfrich, Jörn; Merkle, Elisabeth; Jackisch, Christian; Costa, Serban D; Caputo, Angelika; Kaufmann, Manfred

    2008-01-01

    Introduction To investigate the predictive value of clinical and biological markers for a pathological complete remission after a preoperative dose-dense regimen of doxorubicin and docetaxel, with or without tamoxifen, in primary operable breast cancer. Methods Patients with a histologically confirmed diagnosis of previously untreated, operable, and measurable primary breast cancer (tumour (T), nodes (N) and metastases (M) score: T2-3(≥ 3 cm) N0-2 M0) were treated in a prospectively randomised trial with four cycles of dose-dense (bi-weekly) doxorubicin and docetaxel (ddAT) chemotherapy, with or without tamoxifen, prior to surgery. Clinical and pathological parameters (menopausal status, clinical tumour size and nodal status, grade, and clinical response after two cycles) and a panel of biomarkers (oestrogen and progesterone receptors, Ki-67, human epidermal growth factor receptor 2 (HER2), p53, bcl-2, all detected by immunohistochemistry) were correlated with the detection of a pathological complete response (pCR). Results A pCR was observed in 9.7% in 248 patients randomised in the study and in 8.6% in the subset of 196 patients with available tumour tissue. Clinically negative axillary lymph nodes, poor tumour differentiation, negative oestrogen receptor status, negative progesterone receptor status, and loss of bcl-2 were significantly predictive for a pCR in a univariate logistic regression model, whereas in a multivariate analysis only the clinical nodal status and hormonal receptor status provided significantly independent information. Backward stepwise logistic regression revealed a response after two cycles, with hormone receptor status and lymph-node status as significant predictors. Patients with a low percentage of cells stained positive for Ki-67 showed a better response when treated with tamoxifen, whereas patients with a high percentage of Ki-67 positive cells did not have an additional benefit when treated with tamoxifen. Tumours overexpressing

  15. Whole-blood RNA transcript-based models can predict clinical response in two large independent clinical studies of patients with advanced melanoma treated with the checkpoint inhibitor, tremelimumab.

    PubMed

    Friedlander, Philip; Wassmann, Karl; Christenfeld, Alan M; Fisher, David; Kyi, Chrisann; Kirkwood, John M; Bhardwaj, Nina; Oh, William K

    2017-08-15

    Tremelimumab is an antibody that blocks CTLA-4 and demonstrates clinical efficacy in a subset of advanced melanoma patients. An unmet clinical need exists for blood-based response-predictive gene signatures to facilitate clinically effective and cost-efficient use of such immunotherapeutic interventions. Peripheral blood samples were collected in PAXgene® tubes from 210 treatment-naïve melanoma patients receiving tremelimumab in a worldwide, multicenter phase III study (discovery dataset). A central panel of radiologists determined objective response using RECIST criteria. Gene expression for 169 mRNA transcripts was measured using quantitative PCR. A 15-gene pre-treatment response-predictive classifier model was identified. An independent population (N = 150) of refractory melanoma patients receiving tremelimumab after chemotherapy enrolled in a worldwide phase II study (validation dataset). The classifier model, using the same genes, coefficients and constants for objective response and one-year survival after treatment, was applied to the validation dataset. A 15-gene pre-treatment classifier model (containing ADAM17, CDK2, CDKN2A, DPP4, ERBB2, HLA-DRA, ICOS, ITGA4, LARGE, MYC, NAB2, NRAS, RHOC, TGFB1, and TIMP1) achieved an area under the curve (AUC) of 0.86 (95% confidence interval 0.81 to 0.91, p < 0.0001) for objective response and 0.6 (95% confidence interval 0.54 to 0.67, p = 0.0066) for one-year survival in the discovery set. This model was validated in the validation set with AUCs of 0.62 (95% confidence interval 0.54 to 0.70 p = 0.0455) for objective response and 0.68 for one-year survival (95% confidence interval 0.59 to 0.75 p = 0.0002). To our knowledge, this is the largest blood-based biomarker study of a checkpoint inhibitor, tremelimumab, which demonstrates a validated pre-treatment mRNA classifier model that predicts clinical response. The data suggest that the model captures a biological signature representative of genes needed for a

  16. Whole-blood RNA transcript-based models can predict clinical response in two large independent clinical studies of patients with advanced melanoma treated with the checkpoint inhibitor, tremelimumab.

    PubMed

    Friedlander, Philip; Wassmann, Karl; Christenfeld, Alan M; Fisher, David; Kyi, Chrisann; Kirkwood, John M; Bhardwaj, Nina; Oh, William K

    2017-01-01

    Tremelimumab is an antibody that blocks CTLA-4 and demonstrates clinical efficacy in a subset of advanced melanoma patients. An unmet clinical need exists for blood-based response-predictive gene signatures to facilitate clinically effective and cost-efficient use of such immunotherapeutic interventions. Peripheral blood samples were collected in PAXgene® tubes from 210 treatment-naïve melanoma patients receiving tremelimumab in a worldwide, multicenter phase III study (discovery dataset). A central panel of radiologists determined objective response using RECIST criteria. Gene expression for 169 mRNA transcripts was measured using quantitative PCR. A 15-gene pre-treatment response-predictive classifier model was identified. An independent population (N = 150) of refractory melanoma patients receiving tremelimumab after chemotherapy enrolled in a worldwide phase II study (validation dataset). The classifier model, using the same genes, coefficients and constants for objective response and one-year survival after treatment, was applied to the validation dataset. A 15-gene pre-treatment classifier model (containing ADAM17, CDK2, CDKN2A, DPP4, ERBB2, HLA-DRA, ICOS, ITGA4, LARGE, MYC, NAB2, NRAS, RHOC, TGFB1, and TIMP1) achieved an area under the curve (AUC) of 0.86 (95% confidence interval 0.81 to 0.91, p < 0.0001) for objective response and 0.6 (95% confidence interval 0.54 to 0.67, p = 0.0066) for one-year survival in the discovery set. This model was validated in the validation set with AUCs of 0.62 (95% confidence interval 0.54 to 0.70 p = 0.0455) for objective response and 0.68 for one-year survival (95% confidence interval 0.59 to 0.75 p = 0.0002). To our knowledge, this is the largest blood-based biomarker study of a checkpoint inhibitor, tremelimumab, which demonstrates a validated pre-treatment mRNA classifier model that predicts clinical response. The data suggest that the model captures a biological signature representative of genes needed for a

  17. Clinical Utility of Fractional exhaled Nitric Oxide (FeNO) as a Biomarker to Predict Severity of Disease and Response to Inhaled Corticosteroid (ICS) in Asthma Patients.

    PubMed

    Neelamegan, Revathy; Saka, Vinodkumar; Tamilarasu, Kadhiravan; Rajaram, Manju; Selvarajan, Sandhiya; Chandrasekaran, Adithan

    2016-12-01

    Bronchial asthma is a common chronic inflammatory airway disease diagnosed and is based on symptomatic history and Pulmonary Function Tests (PFT). Fractional exhaled Nitric Oxide (FeNO) is exclusively a non-invasive biomarker of on-going eosinophilic airway inflammation which remains unpredictable only with PFTs. FeNO measurement is recommended in predicting asthma severity and Inhaled Corticosteroid (ICS) response but further research is required to understand its clinical utility and agreement with current recommendations in a specific population. To estimate FeNO levels in Tamilian patients with mild-to-moderate persistent asthma and to correlate with disease severity and ICS response. The study was a prospective cohort with a single group of 102 persistent asthma patients under standard ICS regimen for 8 weeks (follow-up period). PFT and FeNO were measured using portable spirometry and chemiluminescence based exhaled breath analyser, at baseline and during follow-up visits. Based on PFT and FeNO parameters, the study population was sub-grouped with respect to asthma severity (as mild, moderate and moderately severe), FeNO cut-off (> or < 50ppb) and ICS response classification (good vs poor ICS responders). Significant decrease in mean FeNO levels were found in mild, moderate and moderately severe asthmatic groups following ICS treatment (90.15±27.36, 75.74±31.98 and 77.18±32.79 ppb) compared to similar baseline FeNO levels (103.03±34.08, 91.38±37.60 and 97.90±43.84 ppb) in all the above groups. Similarly, significant decrease in mean FeNO levels was found - FeNO>50ppb, good and poor ICS responders groups, in post- ICS treatment (89.63±24.04, 77.90±31.12 and 86.49±32.57 ppb) compared to baseline levels (110.183±1.23, 97.12±42.04 and 99.68±34.71 ppb). The observed baseline FeNO values in all groups as stated above did not show significant difference to differentiate asthma severity or ICS responders groups. The present study results do not support the

  18. Clinical Utility of Fractional exhaled Nitric Oxide (FeNO) as a Biomarker to Predict Severity of Disease and Response to Inhaled Corticosteroid (ICS) in Asthma Patients

    PubMed Central

    Saka, Vinodkumar; Tamilarasu, Kadhiravan; Rajaram, Manju; Selvarajan, Sandhiya; Chandrasekaran, Adithan

    2016-01-01

    Introduction Bronchial asthma is a common chronic inflammatory airway disease diagnosed and is based on symptomatic history and Pulmonary Function Tests (PFT). Fractional exhaled Nitric Oxide (FeNO) is exclusively a non-invasive biomarker of on-going eosinophilic airway inflammation which remains unpredictable only with PFTs. FeNO measurement is recommended in predicting asthma severity and Inhaled Corticosteroid (ICS) response but further research is required to understand its clinical utility and agreement with current recommendations in a specific population. Aim To estimate FeNO levels in Tamilian patients with mild-to-moderate persistent asthma and to correlate with disease severity and ICS response. Materials and Methods The study was a prospective cohort with a single group of 102 persistent asthma patients under standard ICS regimen for 8 weeks (follow-up period). PFT and FeNO were measured using portable spirometry and chemiluminescence based exhaled breath analyser, at baseline and during follow-up visits. Based on PFT and FeNO parameters, the study population was sub-grouped with respect to asthma severity (as mild, moderate and moderately severe), FeNO cut-off (> or < 50ppb) and ICS response classification (good vs poor ICS responders). Results Significant decrease in mean FeNO levels were found in mild, moderate and moderately severe asthmatic groups following ICS treatment (90.15±27.36, 75.74±31.98 and 77.18±32.79 ppb) compared to similar baseline FeNO levels (103.03±34.08, 91.38±37.60 and 97.90±43.84 ppb) in all the above groups. Similarly, significant decrease in mean FeNO levels was found - FeNO>50ppb, good and poor ICS responders groups, in post- ICS treatment (89.63±24.04, 77.90±31.12 and 86.49±32.57 ppb) compared to baseline levels (110.183±1.23, 97.12±42.04 and 99.68±34.71 ppb). Conclusion The observed baseline FeNO values in all groups as stated above did not show significant difference to differentiate asthma severity or ICS

  19. Efficacy of saxagliptin as an add-on to oral monotherapy in the phase 3 clinical development program: predictive factors of the treatment response in type 2 diabetes.

    PubMed

    Gautier, J-F; Sauvanet, J-P

    2011-09-01

    Saxagliptin, a dipeptidyl peptidase-4 inhibitor, has been the focus of a large clinical development programme, including Phase 3 randomized vs placebo-controlled clinical trials as add-on therapy in patients with type 2 diabetes (T2D) with inadequate glycemic control using initial monotherapy (metformin, glibenclamide, thiazolidinedione). This clinical programme has shown saxagliptin to be effective in the control of fasting and postprandial glycemic parameters, in addition to a good overall safety profile. The present paper aims at reviewing the overall short-term and long-term efficacy of saxagliptin in its Phase 3 development program and tries to pinpoint some factors that may be more predictive of treatment response in clinical practice. In individual and pooled analyses of the three pivotal add-on to monotherapy trials, saxagliptin (5mg once daily) led to significant reductions in HbA(1c) from baseline to 24 weeks. Additional analyses showed that reductions in HbA(1c) were maintained in the long-term, notably for 102 weeks, in combination with metformin. Data have also shown that the absolute reduction in HbA(1c) seen with saxagliptine from baseline to Week 24 was numerically greater with an elevated baseline HbA(1c). In these recently published pooled analyses, clinically pertinent reductions in HbA(1c) were also obtained with saxagliptin across a wide range of subgroups of T2D patients when examined either by specific baseline demographic characteristics or by β-cell function indices such as the HOMA-β. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

  20. Biomarkers of Host Response Predict Primary End-Point Radiological Pneumonia in Tanzanian Children with Clinical Pneumonia: A Prospective Cohort Study.

    PubMed

    Erdman, Laura K; D'Acremont, Valérie; Hayford, Kyla; Rajwans, Nimerta; Kilowoko, Mary; Kyungu, Esther; Hongoa, Philipina; Alamo, Leonor; Streiner, David L; Genton, Blaise; Kain, Kevin C

    2015-01-01

    Diagnosing pediatric pneumonia is challenging in low-resource settings. The World Health Organization (WHO) has defined primary end-point radiological pneumonia for use in epidemiological and vaccine studies. However, radiography requires expertise and is often inaccessible. We hypothesized that plasma biomarkers of inflammation and endothelial activation may be useful surrogates for end-point pneumonia, and may provide insight into its biological significance. We studied children with WHO-defined clinical pneumonia (n = 155) within a prospective cohort of 1,005 consecutive febrile children presenting to Tanzanian outpatient clinics. Based on x-ray findings, participants were categorized as primary end-point pneumonia (n = 30), other infiltrates (n = 31), or normal chest x-ray (n = 94). Plasma levels of 7 host response biomarkers at presentation were measured by ELISA. Associations between biomarker levels and radiological findings were assessed by Kruskal-Wallis test and multivariable logistic regression. Biomarker ability to predict radiological findings was evaluated using receiver operating characteristic curve analysis and Classification and Regression Tree analysis. Compared to children with normal x-ray, children with end-point pneumonia had significantly higher C-reactive protein, procalcitonin and Chitinase 3-like-1, while those with other infiltrates had elevated procalcitonin and von Willebrand Factor and decreased soluble Tie-2 and endoglin. Clinical variables were not predictive of radiological findings. Classification and Regression Tree analysis generated multi-marker models with improved performance over single markers for discriminating between groups. A model based on C-reactive protein and Chitinase 3-like-1 discriminated between end-point pneumonia and non-end-point pneumonia with 93.3% sensitivity (95% confidence interval 76.5-98.8), 80.8% specificity (72.6-87.1), positive likelihood ratio 4.9 (3.4-7.1), negative likelihood ratio 0.083 (0

  1. Biomarkers of Host Response Predict Primary End-Point Radiological Pneumonia in Tanzanian Children with Clinical Pneumonia: A Prospective Cohort Study

    PubMed Central

    Erdman, Laura K.; D’Acremont, Valérie; Hayford, Kyla; Kilowoko, Mary; Kyungu, Esther; Hongoa, Philipina; Alamo, Leonor; Streiner, David L.; Genton, Blaise; Kain, Kevin C.

    2015-01-01

    Background Diagnosing pediatric pneumonia is challenging in low-resource settings. The World Health Organization (WHO) has defined primary end-point radiological pneumonia for use in epidemiological and vaccine studies. However, radiography requires expertise and is often inaccessible. We hypothesized that plasma biomarkers of inflammation and endothelial activation may be useful surrogates for end-point pneumonia, and may provide insight into its biological significance. Methods We studied children with WHO-defined clinical pneumonia (n = 155) within a prospective cohort of 1,005 consecutive febrile children presenting to Tanzanian outpatient clinics. Based on x-ray findings, participants were categorized as primary end-point pneumonia (n = 30), other infiltrates (n = 31), or normal chest x-ray (n = 94). Plasma levels of 7 host response biomarkers at presentation were measured by ELISA. Associations between biomarker levels and radiological findings were assessed by Kruskal-Wallis test and multivariable logistic regression. Biomarker ability to predict radiological findings was evaluated using receiver operating characteristic curve analysis and Classification and Regression Tree analysis. Results Compared to children with normal x-ray, children with end-point pneumonia had significantly higher C-reactive protein, procalcitonin and Chitinase 3-like-1, while those with other infiltrates had elevated procalcitonin and von Willebrand Factor and decreased soluble Tie-2 and endoglin. Clinical variables were not predictive of radiological findings. Classification and Regression Tree analysis generated multi-marker models with improved performance over single markers for discriminating between groups. A model based on C-reactive protein and Chitinase 3-like-1 discriminated between end-point pneumonia and non-end-point pneumonia with 93.3% sensitivity (95% confidence interval 76.5–98.8), 80.8% specificity (72.6–87.1), positive likelihood ratio 4.9 (3.4–7

  2. Predicting and measuring fluid responsiveness with echocardiography.

    PubMed

    Miller, Ashley; Mandeville, Justin

    2016-06-01

    Echocardiography is ideally suited to guide fluid resuscitation in critically ill patients. It can be used to assess fluid responsiveness by looking at the left ventricle, aortic outflow, inferior vena cava and right ventricle. Static measurements and dynamic variables based on heart-lung interactions all combine to predict and measure fluid responsiveness and assess response to intravenous fluid resuscitation. Thorough knowledge of these variables, the physiology behind them and the pitfalls in their use allows the echocardiographer to confidently assess these patients and in combination with clinical judgement manage them appropriately.

  3. Predicting and measuring fluid responsiveness with echocardiography

    PubMed Central

    Mandeville, Justin

    2016-01-01

    Echocardiography is ideally suited to guide fluid resuscitation in critically ill patients. It can be used to assess fluid responsiveness by looking at the left ventricle, aortic outflow, inferior vena cava and right ventricle. Static measurements and dynamic variables based on heart–lung interactions all combine to predict and measure fluid responsiveness and assess response to intravenous fluid resuscitation. Thorough knowledge of these variables, the physiology behind them and the pitfalls in their use allows the echocardiographer to confidently assess these patients and in combination with clinical judgement manage them appropriately. PMID:27249550

  4. Physiotherapy clinical educators' perceptions and experiences of clinical prediction rules.

    PubMed

    Knox, Grahame M; Snodgrass, Suzanne J; Rivett, Darren A

    2015-12-01

    Clinical prediction rules (CPRs) are widely used in medicine, but their application to physiotherapy practice is more recent and less widespread, and their implementation in physiotherapy clinical education has not been investigated. This study aimed to determine the experiences and perceptions of physiotherapy clinical educators regarding CPRs, and whether they are teaching CPRs to students on clinical placement. Cross-sectional observational survey using a modified Dillman method. Clinical educators (n=211, response rate 81%) supervising physiotherapy students from 10 universities across 5 states and territories in Australia. Half (48%) of respondents had never heard of CPRs, and a further 25% had never used CPRs. Only 27% reported using CPRs, and of these half (51%) were rarely if ever teaching CPRs to students in the clinical setting. However most respondents (81%) believed CPRs assisted in the development of clinical reasoning skills and few (9%) were opposed to teaching CPRs to students. Users of CPRs were more likely to be male (p<0.001), have post-professional qualifications (p=0.020), work in private practice (p<0.001), and work in the area of musculoskeletal physiotherapy (p<0.001) compared with non-users. The CPRs most commonly known, used and taught were the Ottawa Ankle Rule, the Ottawa Knee Rule, and Wells' Rule for Deep Vein Thrombosis. Students are unlikely to be learning about CPRs on clinical placement, as few clinical educators use them. Clinical educators will require training in CPRs and assistance in teaching them if students are to better learn about implementing CPRs in physiotherapy clinical practice. Copyright © 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

  5. Clinical Predictive Modeling Development and Deployment through FHIR Web Services

    PubMed Central

    Khalilia, Mohammed; Choi, Myung; Henderson, Amelia; Iyengar, Sneha; Braunstein, Mark; Sun, Jimeng

    2015-01-01

    Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction. PMID:26958207

  6. Predicting clinically significant response to cognitive behavior therapy for chronic insomnia in general medical practice: analysis of outcome data at 12 months posttreatment.

    PubMed

    Espie, C A; Inglis, S J; Harvey, L

    2001-02-01

    The clinical efficacy of cognitive behavior therapy (CBT) for chronic insomnia has been established, yet clinical effectiveness is less clear. This study presents data on 109 patients from general practice during a formal evaluation of clinical effectiveness. Two thirds achieved normative values of < or =30 min for sleep latency and wakefulness during the night after CBT. Furthermore, almost half of the sample reduced sleeplessness by > or =50%. Logistic regression revealed that initial severity did not contraindicate good outcome. Rather, greater sleep disturbance was positively associated with large symptom reduction, although lower endpoint scores were less likely. Similarly, symptoms of anxiety, depression, and thinking errors positively predicted good outcome. Hypnotic using patients responded equally well to CBT, and demographic factors were of no significant predictive value. It is concluded that CBT is clinically and durably effective for persistent insomnia in routine practice.

  7. Clinical ethics revisited: responses

    PubMed Central

    Benatar, Solomon R; Bhutta, Zulfiqar A; Daar, Abdallah S; Hope, Tony; MacRae, Sue; Roberts, Laura W; Sharpe, Virginia A

    2001-01-01

    This series of responses was commissioned to accompany the article by Singer et al, which can be found at . If you would like to comment on the article by Singer et al or any of the responses, please email us on editorial@biomedcentral.com. PMID:11346457

  8. Is an instrumented spasticity assessment an improvement over clinical spasticity scales in assessing and predicting the response to integrated botulinum toxin type a treatment in children with cerebral palsy?

    PubMed

    Bar-On, Lynn; Van Campenhout, Anja; Desloovere, Kaat; Aertbeliën, Erwin; Huenaerts, Catherine; Vandendoorent, Britt; Nieuwenhuys, Angela; Molenaers, Guy

    2014-03-01

    To compare responsiveness and predictive ability of clinical and instrumented spasticity assessments after botulinum toxin type A (BTX) treatment combined with casting in the medial hamstrings (MEHs) in children with spastic cerebral palsy (CP). Prospective cohort study. Hospital. Consecutive sample of children (N=31; 40 MEH muscles) with CP requiring BTX injections. Clinical and instrumented spasticity assessments before and on average ± SD 53±14 days after BTX. Clinical spasticity scales included the Modified Ashworth Scale and the Modified Tardieu Scale. The instrumented spasticity assessment integrated biomechanical (position and torque) and electrophysiological (surface electromyography) signals during manually performed low- and high-velocity passive stretches of the MEHs. Signals were compared between both stretch velocities and were examined pre- and post-BTX. Responsiveness of clinical and instrumented assessments was compared by percentage exact agreement. Prediction ability was assessed with a logistic regression and the area under the receiver operating characteristic (ROC) curves of the baseline parameters of responders versus nonresponders. Both clinical and instrumented parameters improved post-BTX (P≤.005); however, they showed a low percentage exact agreement. The baseline Modified Tardieu Scale was the only clinical scale predictive for response (area under the ROC curve=0.7). For the instrumented assessment, baseline values of root mean square (RMS) electromyography and torque were better predictors for a positive response (area under the ROC curve=.82). Baseline RMS electromyography remained an important predictor in the logistic regression. The instrumented spasticity assessment showed higher responsiveness than the clinical scales. The amount of RMS electromyography is considered a promising parameter to predict treatment response. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights

  9. Motion Predicts Clinical Callus Formation

    PubMed Central

    Elkins, Jacob; Marsh, J. Lawrence; Lujan, Trevor; Peindl, Richard; Kellam, James; Anderson, Donald D.; Lack, William

    2016-01-01

    Background: Mechanotransduction is theorized to influence fracture-healing, but optimal fracture-site motion is poorly defined. We hypothesized that three-dimensional (3-D) fracture-site motion as estimated by finite element (FE) analysis would influence callus formation for a clinical series of supracondylar femoral fractures treated with locking-plate fixation. Methods: Construct-specific FE modeling simulated 3-D fracture-site motion for sixty-six supracondylar femoral fractures (OTA/AO classification of 33A or 33C) treated at a single institution. Construct stiffness and directional motion through the fracture were investigated to assess the validity of construct stiffness as a surrogate measure of 3-D motion at the fracture site. Callus formation was assessed radiographically for all patients at six, twelve, and twenty-four weeks postoperatively. Univariate and multivariate linear regression analyses examined the effects of longitudinal motion, shear (transverse motion), open fracture, smoking, and diabetes on callus formation. Construct types were compared to determine whether their 3-D motion profile was associated with callus formation. Results: Shear disproportionately increased relative to longitudinal motion with increasing bridge span, which was not predicted by our assessment of construct stiffness alone. Callus formation was not associated with open fracture, smoking, or diabetes at six, twelve, or twenty-four weeks. However, callus formation was associated with 3-D fracture-site motion at twelve and twenty-four weeks. Longitudinal motion promoted callus formation at twelve and twenty-four weeks (p = 0.017 for both). Shear inhibited callus formation at twelve and twenty-four weeks (p = 0.017 and p = 0.022, respectively). Titanium constructs with a short bridge span demonstrated greater longitudinal motion with less shear than did the other constructs, and this was associated with greater callus formation (p < 0.001). Conclusions: In this study of

  10. How to Establish Clinical Prediction Models.

    PubMed

    Lee, Yong Ho; Bang, Heejung; Kim, Dae Jung

    2016-03-01

    A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice.

  11. Searching for clinical prediction rules in MEDLINE.

    PubMed

    Ingui, B J; Rogers, M A

    2001-01-01

    Clinical prediction rules have been advocated as a possible mechanism to enhance clinical judgment in diagnostic, therapeutic, and prognostic assessment. Despite renewed interest in the their use, inconsistent terminology makes them difficult to index and retrieve by computerized search systems. No validated approaches to locating clinical prediction rules appear in the literature. The objective of this study was to derive and validate an optimal search filter for retrieving clinical prediction rules, using the National Library of Medicine's MEDLINE database. A comparative, retrospective analysis was conducted. The "gold standard" was established by a manual search of all articles from select print journals for the years 1991 through 1998, which identified articles covering various aspects of clinical prediction rules such as derivation, validation, and evaluation. Search filters were derived, from the articles in the July through December issues of the journals (derivation set), by analyzing the textwords (words in the title and abstract) and the medical subject heading (from the MeSH Thesaurus) used to index each article. The accuracy of these filters in retrieving clinical prediction rules was then assessed using articles in the January through June issues (validation set). The sensitivity, specificity, positive predictive value, and positive likelihood ratio of several different search filters were measured. The filter "predict$ OR clinical$ OR outcome$ OR risk$" retrieved 98 percent of clinical prediction rules. Four filters, such as "predict$ OR validat$ OR rule$ OR predictive value of tests," had both sensitivity and specificity above 90 percent. The top-performing filter for positive predictive value and positive likelihood ratio in the validation set was "predict$.ti. AND rule$." Several filters with high retrieval value were found. Depending on the goals and time constraints of the searcher, one of these filters could be used.

  12. Prediction of earthquake response spectra

    USGS Publications Warehouse

    Joyner, W.B.; Boore, David M.

    1982-01-01

    We have developed empirical equations for predicting earthquake response spectra in terms of magnitude, distance, and site conditions, using a two-stage regression method similar to the one we used previously for peak horizontal acceleration and velocity. We analyzed horizontal pseudo-velocity response at 5 percent damping for 64 records of 12 shallow earthquakes in Western North America, including the recent Coyote Lake and Imperial Valley, California, earthquakes. We developed predictive equations for 12 different periods between 0.1 and 4.0 s, both for the larger of two horizontal components and for the random horizontal component. The resulting spectra show amplification at soil sites compared to rock sites for periods greater than or equal to 0.3 s, with maximum amplification exceeding a factor of 2 at 2.0 s. For periods less than 0.3 s there is slight deamplification at the soil sites. These results are generally consistent with those of several earlier studies. A particularly significant aspect of the predicted spectra is the change of shape with magnitude (confirming earlier results by McGuire and by Irifunac and Anderson). This result indicates that the conventional practice of scaling a constant spectral shape by peak acceleration will not give accurate answers. The Newmark and Hall method of spectral scaling, using both peak acceleration and peak velocity, largely avoids this error. Comparison of our spectra with the Nuclear Regulatory Commission's Regulatory Guide 1.60 spectrum anchored at the same value at 0.1 s shows that the Regulatory Guide 1.60 spectrum is exceeded at soil sites for a magnitude of 7.5 at all distances for periods greater than about 0.5 s. Comparison of our spectra for soil sites with the corresponding ATC-3 curve of lateral design force coefficient for the highest seismic zone indicates that the ATC-3 curve is exceeded within about 7 km of a magnitude 6.5 earthquake and within about 15 km of a magnitude 7.5 event. The amount by

  13. American Society of Clinical Oncology provisional clinical opinion: testing for KRAS gene mutations in patients with metastatic colorectal carcinoma to predict response to anti-epidermal growth factor receptor monoclonal antibody therapy.

    PubMed

    Allegra, Carmen J; Jessup, J Milburn; Somerfield, Mark R; Hamilton, Stanley R; Hammond, Elizabeth H; Hayes, Daniel F; McAllister, Pamela K; Morton, Roscoe F; Schilsky, Richard L

    2009-04-20

    An American Society of Clinical Oncology (ASCO) provisional clinical opinion (PCO), offers timely clinical direction to ASCO's oncologists following publication or presentation of potentially practice-changing data from major studies. This PCO addresses the utility of KRAS gene mutation testing in patients with metastatic colorectal carcinoma to predict response to anti-epidermal growth factor receptor (anti-EGFR) monoclonal antibody (MoAb) therapy with cetuximab or panitumumab (see Note). Recent results from phase II and III clinical trials demonstrate that patients with metastatic colorectal cancer benefit from therapy with monoclonal antibodies directed against the EGFR, when used either as monotherapy or combined with chemotherapy. Retrospective subset analyses of the data from these trials strongly suggest that patients who have KRAS mutations detected in codon 12 or 13 do not benefit from this therapy. Five randomized controlled trials of cetuximab or panitumumab have evaluated outcomes for patients with metastatic colorectal carcinoma in relation to KRAS mutational status as no mutation detected (wild type) or abnormal (mutated). Another five single-arm studies have retrospectively evaluated tumor response according to KRAS status. Based on systematic reviews of the relevant literature, all patients with metastatic colorectal carcinoma who are candidates for anti-EGFR antibody therapy should have their tumor tested for KRAS mutations in a CLIA-accredited laboratory. If KRAS mutation in codon 12 or 13 is detected, then patients with metastatic colorectal carcinoma should not receive anti-EGFR antibody therapy as part of their treatment. ASCO's provisional clinical opinions (PCOs) reflect expert consensus based on clinical evidence and literature available at the time they are written, and are intended to assist physicians in clinical decision-making and identify questions and settings for further research. Due to the rapid flow of scientific information in

  14. Early prediction of histopathological response of rectal tumors after one week of preoperative radiochemotherapy using 18 F-FDG PET-CT imaging. A prospective clinical study

    PubMed Central

    2012-01-01

    Background Preoperative radiochemotherapy (RCT) is standard in locally advanced rectal cancer (LARC). Initial data suggest that the tumor’s metabolic response, i.e. reduction of its 18 F-FDG uptake compared with the baseline, observed after two weeks of RCT, may correlate with histopathological response. This prospective study evaluated the ability of a very early metabolic response, seen after only one week of RCT, to predict the histopathological response to treatment. Methods Twenty patients with LARC who received standard RCT regimen followed by radical surgery participated in this study. Maximum standardized uptake value (SUV-MAX), measured by PET-CT imaging at baseline and on day 8 of RCT, and the changes in FDG uptake (ΔSUV-MAX), were compared with the histopathological response at surgery. Response was classified by tumor regression grade (TRG) and by achievement of pathological complete response (pCR). Results Absolute SUV-MAX values at both time points did not correlate with histopathological response. However, patients with pCR had a larger drop in SUV-MAX after one week of RCT (median: -35.31% vs −18.42%, p = 0.046). In contrast, TRG did not correlate with ΔSUV-MAX. The changes in FGD-uptake predicted accurately the achievement of pCR: only patients with a decrease of more than 32% in SUV-MAX had pCR while none of those whose tumors did not show any decrease in SUV-MAX had pCR. Conclusions A decrease in ΔSUV-MAX after only one week of RCT for LARC may be able to predict the achievement of pCR in the post-RCT surgical specimen. Validation in a larger independent cohort is planned. PMID:22853868

  15. Clinical Usefulness of Urinary Fatty Acid Binding Proteins in Assessing the Severity and Predicting Treatment Response of Pneumonia in Critically Ill Patients: A Cross-Sectional Study.

    PubMed

    Tsao, Tsung-Cheng; Tsai, Han-Chen; Chang, Shi-Chuan

    2016-05-01

    pneumonia severity and in predicting treatment response, respectively. Further studies with larger populations are needed to verify these issues.

  16. Clinical significance of pretherapeutic Ki67 as a predictive parameter for response to neoadjuvant chemotherapy in breast cancer: is it equally useful across tumor subtypes?

    PubMed

    Sueta, Aiko; Yamamoto, Yutaka; Hayashi, Mitsuhiro; Yamamoto, Satoko; Inao, Toko; Ibusuki, Mutsuko; Murakami, Keiichi; Iwase, Hirotaka

    2014-05-01

    Ki67 has been identified as a prognostic and predictive marker for breast cancer and it was suggested that it may contribute to pathologic complete response (pCR) after neoadjuvant chemotherapy. It is unclear whether expression of Ki67 is particularly helpful for prediction of pCR across tumor subtypes. Pretherapeutic Ki67 was evaluated in a series of 121 breast cancer core biopsies. After neoadjuvant chemotherapy, we used postoperative specimens to evaluate the pCR status. Several parameters predictive of pCR were identified using logistic regression analysis. We investigated subgroups defined by estrogen receptor (ER), progesterone receptor, and human epidermal growth factor receptor 2, in which predicting pCR with Ki67 might be feasible. Ki67 was found to be an independent predictor of pCR in multivariate analysis (odds ratio [OR], 3.62; 95% CI, 1.21-10.8). When stratified by ER, the above significance was exclusive to ER-positive tumors (OR, 6.24; 95% CI, 1.40-27.7). Using an receiver-operating characteristic curve, we obtained moderate discriminative accuracy with an area under the curve of 0.7752 for Ki67 prediction of pCR in ER-positive tumors. In subgroup analysis, patients with high Ki67 showed significantly improved pCR rate in luminal-type disease, with a median Ki67 value of 43% in the patients who achieved pCR, versus 29% for those without pCR (P = .018), whereas no associations were observed in other subtypes. Our results suggest that stratification according to Ki67 levels might improve predictive significance of the response in hormone-responsive breast cancer. Even in these subtypes assumed to be less chemosensitive, some patients with highly proliferative tumors derive a significant benefit from chemotherapy, and consequently it is important to identify them. Copyright © 2014 Mosby, Inc. All rights reserved.

  17. Outcome Prediction in Clinical Treatment Processes.

    PubMed

    Huang, Zhengxing; Dong, Wei; Ji, Lei; Duan, Huilong

    2016-01-01

    Clinical outcome prediction, as strong implications for health service delivery of clinical treatment processes (CTPs), is important for both patients and healthcare providers. Prior studies typically use a priori knowledge, such as demographics or patient physical factors, to estimate clinical outcomes at early stages of CTPs (e.g., admission). They lack the ability to deal with temporal evolution of CTPs. In addition, most of the existing studies employ data mining or machine learning methods to generate a prediction model for a specific type of clinical outcome, however, a mathematical model that predicts multiple clinical outcomes simultaneously, has not yet been established. In this study, a hybrid approach is proposed to provide a continuous predictive monitoring service on multiple clinical outcomes. More specifically, a probabilistic topic model is applied to discover underlying treatment patterns of CTPs from electronic medical records. Then, the learned treatment patterns, as low-dimensional features of CTPs, are exploited for clinical outcome prediction across various stages of CTPs based on multi-label classification. The proposal is evaluated to predict three typical classes of clinical outcomes, i.e., length of stay, readmission time, and the type of discharge, using 3492 pieces of patients' medical records of the unstable angina CTP, extracted from a Chinese hospital. The stable model was characterized by 84.9% accuracy and 6.4% hamming-loss with 3 latent treatment patterns discovered from data, which outperforms the benchmark multi-label classification algorithms for clinical outcome prediction. Our study indicates the proposed approach can potentially improve the quality of clinical outcome prediction, and assist physicians to understand the patient conditions, treatment inventions, and clinical outcomes in an integrated view.

  18. Predicting disease onset in clinically healthy people

    PubMed Central

    2016-01-01

    Virtually all human disease is induced by oxidative stress. Oxidative stress, which is caused by toxic environmental exposure, the presence of disease, lifestyle choices, stress, chronic inflammation or combinations of these, is responsible for most disease. Oxidative stress from all sources is additive and it is the total oxidative stress from all sources that induces the onset of most disease. Oxidative stress leads to lipid peroxidation, which in turn produces Malondialdehyde. Serum malondialdehyde level is an additive parameter resulting from all sources of oxidative stress and, therefore, is a reliable indicator of total oxidative stress which can be used to predict the onset of disease in clinically asymptomatic individuals and to suggest the need for treatment that can prevent much human disease. PMID:28652846

  19. IMPROVEMENT OF CLINICAL PREDICTION THROUGH SPECIAL TRAINING.

    ERIC Educational Resources Information Center

    KRAUSKOPF, C.J.; AND OTHERS

    A SERIES OF STUDIES WAS REPORTED ON INCREASING ACCURACY IN CLINICAL PREDICTION BY USING AN IMMEDIATE FEEDBACK PROCEDURE. THE GENERAL DESIGN IMPOSED EIGHT EXPERIMENTS AND THREE SETS OF ITEMS. SET ONE TESTED PREDICTIVE LEVEL BEFORE FEEDBACK. SET TWO WAS THE TRAINING SET. SET THREE TESTED THE EFFECT OF FEEDBACK TRAINING. THE PREDICTOR VARIABLE WAS…

  20. When Clinical Description Becomes Statistical Prediction

    ERIC Educational Resources Information Center

    Western, Drew; Weinberger, Joel

    2004-01-01

    This article reconsiders the issue of clinical versus statistical prediction. The term clinical is widely used to denote 1 pole of 2 independent axes: the observer whose data are being aggregated (clinician/expert vs. lay) and the method of aggregating those data (impressionistic vs. statistical). Fifty years of research suggests that when…

  1. Does psychological testing help to predict the response to acupuncture or massage/relaxation therapy in patients presenting to a general neurology clinic with headache?

    PubMed

    Wylie, K R; Jackson, C; Crawford, P M

    1997-06-01

    Patients with chronic headache were offered treatment by acupuncture or massage with relaxation instead of a change in their prescribed medication. They were randomly allocated to either treatment. There was a significant improvement in pain ratings with both treatment types. Specifically a greater effect was seen in migraine patients treated by massage with relaxation when compared to acupuncture. No psychological factors were found to predict response to either treatment. At the end of the study, 13% of patients were significantly more worried that there may be a more serious cause underlying their headache despite reassurance and an improvement in their headache scores.

  2. Predicting Diabetes: Clinical, Biological, and Genetic Approaches

    PubMed Central

    Balkau, Beverley; Lange, Céline; Fezeu, Leopold; Tichet, Jean; de Lauzon-Guillain, Blandine; Czernichow, Sebastien; Fumeron, Frederic; Froguel, Philippe; Vaxillaire, Martine; Cauchi, Stephane; Ducimetière, Pierre; Eschwège, Eveline

    2008-01-01

    OBJECTIVE—To provide a simple clinical diabetes risk score and to identify characteristics that predict later diabetes using variables available in the clinic setting as well as biological variables and polymorphisms. RESEARCH DESIGN AND METHODS—Incident diabetes was studied in 1,863 men and 1,954 women, 30–65 years of age at baseline, with diabetes defined by treatment or by fasting plasma glucose ≥7.0 mmol/l at 3-yearly examinations over 9 years. Sex-specific logistic regression equations were used to select variables for prediction. RESULTS—A total of 140 men and 63 women developed diabetes. The predictive clinical variables were waist circumference and hypertension in both sexes, smoking in men, and diabetes in the family in women. Discrimination, as measured by the area under the receiver operating curves (AROCs), were 0.713 for men and 0.827 for women, a little higher than for the Finish Diabetes Risk (FINDRISC) score, with fewer variables in the score. Combining clinical and biological variables, the predictive equation included fasting glucose, waist circumference, smoking, and γ-glutamyltransferase for men and fasting glucose, BMI, triglycerides, and diabetes in family for women. The number of TCF7L2 and IL6 deleterious alleles was predictive in both sexes, but after including the above clinical and biological variables, this variable was only predictive in women (P < 0.03) and the AROC statistics increased only marginally. CONCLUSIONS—The best clinical predictor of diabetes is adiposity, and baseline glucose is the best biological predictor. Clinical and biological predictors differed marginally between men and women. The genetic polymorphisms added little to the prediction of diabetes. PMID:18689695

  3. In vivo mesolimbic D2/3 receptor binding predicts posttherapeutic clinical responses in restless legs syndrome: a positron emission tomography study.

    PubMed

    Oboshi, Yumi; Ouchi, Yasuomi; Yagi, Shunsuke; Kono, Satoshi; Nakai, Noriyoshi; Yoshikawa, Etsuji; Futatsubashi, Masami; Terada, Tatsuhiro; Kim, Kang; Harada, Kiyoshi

    2012-04-01

    Although D2/3 agonists have been used as a first-line medication for idiopathic restless legs syndrome (iRLS), findings on D2/3 receptors have been inconsistent. Here, we aimed to clarify the contribution of D2/3 receptor function to the clinical symptoms of iRLS by comparing the binding potential (BP(ND)) of [(11)C]raclopride with clinical improvements after D2/3 stimulation by pramipexole. Eight drug-naïve, iRLS patients and eight age-matched healthy subjects were scanned with positron emission tomography (PET). After PET scans, all patients received pramipexole (0.125 mg) orally for 2 weeks. Patients were evaluated every day with several standardized clinical tests. The BP(ND) values were compared using regions of interest and voxel-based methods. Results showed that the mean magnitude of [(11)C]raclopride BP(ND) in the mesolimbic dopamine region (nucleus accumbens (NA) and caudate) was significantly lower in the iRLS group. No significant differences between groups were observed in the putamen. The NA [(11)C]raclopride BP(ND) levels correlated negatively with clinical severity scores and positively with the degree of posttreatment improvement in iRLS. The present results suggest that alterations in mesolimbic D2/3 receptor function reflect the pathophysiology of iRLS, and the baseline availability of D2/3 receptors may predict the clinical outcome after D2/3 agonist treatment.

  4. Improved tumour response prediction with equivalent uniform dose in pre-clinical study using direct intratumoural infusion of liposome-encapsulated 186Re radionuclides

    NASA Astrophysics Data System (ADS)

    Hrycushko, Brian A.; Ware, Steve; Li, Shihong; Bao, Ande

    2011-09-01

    Crucial to all cancer therapy modalities is a strong correlation between treatment and effect. Predictability of therapy success/failure allows for the optimization of treatment protocol and aids in the decision of whether additional treatment is necessary to prevent tumour progression. This work evaluated the relationship between cancer treatment and effect for intratumoural infusions of liposome-encapsulated 186Re to head and neck squamous cell carcinoma xenografts of nude rats. Absorbed dose calculations using a dose-point kernel convolution technique showed significant intratumoural dose heterogeneity due to the short range of the beta-particle emissions. The use of three separate tumour infusion locations improved dose homogeneity compared to a single infusion location as a result of a more uniform radioactivity distribution. An improved dose-response correlation was obtained when using effective uniform dose (EUD) calculations based on a generic set of radiobiological parameters (R2 = 0.84) than when using average tumour absorbed dose (R2 = 0.22). Varying radiobiological parameter values over ranges commonly used for all types of tumours showed little effect on EUD calculations, which suggests that individualized parameter use is of little significance as long as the intratumoural dose heterogeneity is taken into consideration in the dose-response relationship. The improved predictability achieved when using EUD calculations for this cancer therapy modality may be useful for treatment planning and evaluation.

  5. Healthcare provider perceptions of clinical prediction rules.

    PubMed

    Richardson, Safiya; Khan, Sundas; McCullagh, Lauren; Kline, Myriam; Mann, Devin; McGinn, Thomas

    2015-09-02

    To examine internal medicine and emergency medicine healthcare provider perceptions of usefulness of specific clinical prediction rules. The study took place in two academic medical centres. A web-based survey was distributed and completed by participants between 1 January and 31 May 2013. Medical doctors, doctors of osteopathy or nurse practitioners employed in the internal medicine or emergency medicine departments at either institution. The primary outcome was to identify the clinical prediction rules perceived as most useful by healthcare providers specialising in internal medicine and emergency medicine. Secondary outcomes included comparing usefulness scores of specific clinical prediction rules based on provider specialty, and evaluating associations between usefulness scores and perceived characteristics of these clinical prediction rules. Of the 401 healthcare providers asked to participate, a total of 263 (66%), completed the survey. The CHADS2 score was chosen by most internal medicine providers (72%), and Pulmonary Embolism Rule-Out Criteria (PERC) score by most emergency medicine providers (45%), as one of the top three most useful from a list of 24 clinical prediction rules. Emergency medicine providers rated their top three significantly more positively, compared with internal medicine providers, as having a better fit into their workflow (p=0.004), helping more with decision-making (p=0.037), better fitting into their thought process when diagnosing patients (p=0.001) and overall, on a 10-point scale, more useful (p=0.009). For all providers, the perceived qualities of useful at point of care, helps with decision making, saves time diagnosing, fits into thought process, and should be the standard of clinical care correlated highly (≥0.65) with overall 10-point usefulness scores. Healthcare providers describe clear preferences for certain clinical prediction rules, based on medical specialty. Published by the BMJ Publishing Group Limited. For

  6. Healthcare provider perceptions of clinical prediction rules

    PubMed Central

    Richardson, Safiya; Khan, Sundas; McCullagh, Lauren; Kline, Myriam; Mann, Devin; McGinn, Thomas

    2015-01-01

    Objectives To examine internal medicine and emergency medicine healthcare provider perceptions of usefulness of specific clinical prediction rules. Setting The study took place in two academic medical centres. A web-based survey was distributed and completed by participants between 1 January and 31 May 2013. Participants Medical doctors, doctors of osteopathy or nurse practitioners employed in the internal medicine or emergency medicine departments at either institution. Primary and secondary outcome measures The primary outcome was to identify the clinical prediction rules perceived as most useful by healthcare providers specialising in internal medicine and emergency medicine. Secondary outcomes included comparing usefulness scores of specific clinical prediction rules based on provider specialty, and evaluating associations between usefulness scores and perceived characteristics of these clinical prediction rules. Results Of the 401 healthcare providers asked to participate, a total of 263 (66%), completed the survey. The CHADS2 score was chosen by most internal medicine providers (72%), and Pulmonary Embolism Rule-Out Criteria (PERC) score by most emergency medicine providers (45%), as one of the top three most useful from a list of 24 clinical prediction rules. Emergency medicine providers rated their top three significantly more positively, compared with internal medicine providers, as having a better fit into their workflow (p=0.004), helping more with decision-making (p=0.037), better fitting into their thought process when diagnosing patients (p=0.001) and overall, on a 10-point scale, more useful (p=0.009). For all providers, the perceived qualities of useful at point of care, helps with decision making, saves time diagnosing, fits into thought process, and should be the standard of clinical care correlated highly (≥0.65) with overall 10-point usefulness scores. Conclusions Healthcare providers describe clear preferences for certain clinical prediction

  7. SU-F-R-48: Early Prediction of Pathological Response of Locally Advanced Rectal Cancer Using Perfusion CT:A Prospective Clinical Study

    SciTech Connect

    Nie, K; Yue, N; Jabbour, S; Kim, S; Shi, L; Mao, T; Qian, L; Hu, X; Sun, X; Niu, T

    2016-06-15

    Purpose: To prospectively evaluate the tumor vascularity assessed by perfusion CT for prediction of chemo-radiation treatment (CRT) response in locally advanced rectal cancer (LARC). Methods: Eighteen consecutive patients (61.9±8.8 years, from March–June 2015) diagnosed with LARC who underwent 6–8 weeks CRT followed by surgery were included. The pre-treatment perfusion CT was acquired after a 5s delay of contrast agent injection for 45s with 1s interval. A total of 7-cm craniocaudal range covered the tumor region with 3-mm slice thickness. The effective radiation dose is around 15mSv, which is about 1.5 the conventional abdomen/pelvis CT dose. The parametric map of blood flow (BF), blood volume (BV), mean transit time (MTT), permeability (PMB), and maximum intensity map (MIP) were obtained from commercial software (Syngo-CT 2011A, Siemens). An experienced radiation oncologist outlined the tumor based on the pre-operative MR and pathologic residual region, but was blinded with regards to pathological tumor stage. The perfusion parameters were compared to histopathological response quantified by tumor regression grade as good-responder (GR, TRG 0-1) vs. non-good responder (non-GR). Furthermore, the predictive value for pathological complete response (pCR) was also investigated. Results: Both BV (p=0.02) and MTT (P=0.02) was significantly higher and permeambility was lower (p=0.004) in the good responders. The BF was higher in GR group but not statistically significant. Regarding the discrimination of pCR vs non-pCR, the BF was higher in the pCR group (p=0.08) but none of those parameters showed statistically significant differences. Conclusion: BV and MTT can discriminate patients with a favorable response from those that fail to respond well, potentially selecting high-risk patients with resistant tumors that may benefit from an aggressive preoperative treatment approach. However, future studies with more patient data are needed to verify the prognostic value

  8. Participants' responsibilities in clinical research.

    PubMed

    Resnik, David B; Ness, Elizabeth

    2012-12-01

    Discussions on the ethics and regulation of clinical research have a great deal to say about the responsibilities of investigators, sponsors, research institutions and institutional review boards, but very little about the responsibilities of research participants. In this article, we discuss the responsibilities of participants in clinical research. We argue that competent adult participants are responsible for complying with study requirements and fulfilling other obligations they undertake when they make an informed choice to enroll in a study. These responsibilities are based on duties related to promise-keeping, avoiding harm to one's self or others, beneficence and reciprocity. Investigators and research staff should inform participants about their responsibilities during the consent process, and should stress the importance of fulfilling study requirements. They should address any impediments to compliance, and they may provide participants with financial incentives for meeting study requirements. In very rare cases, coercive measures may be justified to prevent immanent harm to others resulting from non-compliance with study requirements.

  9. Participants’ responsibilities in clinical research

    PubMed Central

    Resnik, David B; Ness, Elizabeth

    2014-01-01

    Discussions on the ethics and regulation of clinical research have a great deal to say about the responsibilities of investigators, sponsors, research institutions and institutional review boards, but very little about the responsibilities of research participants. In this article, we discuss the responsibilities of participants in clinical research. We argue that competent adult participants are responsible for complying with study requirements and fulfilling other obligations they undertake when they make an informed choice to enrol in a study. These responsibilities are based on duties related to promise-keeping, avoiding harm to one’s self or others, beneficence and reciprocity. Investigators and research staff should inform participants about their responsibilities during the consent process, and should stress the importance of fulfilling study requirements. They should address any impediments to compliance, and they may provide participants with financial incentives for meeting study requirements. In very rare cases, coercive measures may be justified to prevent immanent harm to others resulting from non-compliance with study requirements. PMID:22822200

  10. Early sorafenib-related adverse events predict therapy response of TACE plus sorafenib: A multicenter clinical study of 606 HCC patients.

    PubMed

    Zhao, Yan; Li, Hailiang; Bai, Wei; Liu, Jueshi; Lv, Weifu; Sahu, Sonia; Guan, Sheng; Qin, Xiao; Wang, Wenhui; Ren, Weixin; Mu, Wei; Guo, Weidong; Gu, Shanzhi; Ma, Yilong; Yin, Zhanxin; Guo, Wengang; Wang, Wenjun; Wang, Yongji; Duran, Rafael; Fan, Daiming; Zhang, Zhuoli; Han, Guohong

    2016-08-15

    The purpose of our study was to test the hypothesis that sorafenib-related dermatologic adverse events (AEs) as an early biomarker can predict the long-term outcomes following the combination therapy of transarterial chemoembolization (TACE) plus sorafenib (TACE-S). The intermediate-stage hepatocellular carcinoma patients who received either TACE-S or TACE-alone treatment were consecutively included into analysis. In the TACE-S group, patients with ≥ grade 2 dermatologic AEs within the first month of sorafenib initiation were defined as responders; whereas those with < grade 2 were defined as nonresponders. In the TACE-S group, the median overall survival (OS) of the responders was significantly longer than that of nonresponders (28.9 months vs. 16.8 months, respectively; p = 0.004). Multivariate analysis demonstrated that nonresponders were significantly associated with an increased risk of death compared with responders (HR = 1.9; 95% confidence Interval-CI: 1.3-2.7; p = 0.001). The survival analysis showed that the median OS was 27.9 months (95% CI: 25.0-30.8) among responders treated with TACE-S vs.18.3 months (95% CI: 14.5-22.1) among those who received TACE-alone (p = 0.046). The median time to progression was 13.1 months (95% CI: 4.4-21.8) in the TACE-S group, a duration that was significantly longer than that in the TACE-alone group [5 months (95% CI: 6.4-13.3), p = 0.014]. This study demonstrated that sorafenib-related dermatologic AEs are clinical biomarkers to identify responders from all of the patients for TACE-S therapy. Sorafenib-related dermatologic AEs, clinical biomarkers, can predict the efficacy of TACE-S in future randomized controlled trials. © 2016 UICC.

  11. What predicts performance during clinical psychology training?

    PubMed

    Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

    2014-06-01

    While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Longitudinal cross-sectional study using prospective and retrospective data. Characteristics at application were analysed in relation to a range of in-course assessments for 274 trainee clinical psychologists who had completed or were in the final stage of their training. Trainees were diverse in age, pre-training experience, and academic performance at A-level (advanced level certificate required for university admission), but not in gender or ethnicity. Failure rates across the three performance domains (academic, clinical, research) were very low, suggesting that selection was successful in screening out less suitable candidates. Key predictors of good performance on the course were better A-levels and better degree class. Non-white students performed less well on two outcomes. Type and extent of pre-training clinical experience on outcomes had varied effects on outcome. Research supervisor ratings emerged as global indicators and predicted nearly all outcomes, but may have been biased as they were retrospective. Referee ratings predicted only one of the seven outcomes examined, and interview ratings predicted none of the outcomes. Predicting who will do well or poorly in clinical psychology training is complex. Interview and referee ratings may well be successful in screening out unsuitable candidates, but appear to be a poor guide to performance on the course. © 2013 The Authors. British Journal of Clinical Psychology published by John Wiley & Sons Ltd on behalf of the British Psychological Society.

  12. [18F]FLT-PET to predict pharmacodynamic and clinical response to cetuximab therapy in Ménétrier’s disease

    PubMed Central

    McKinley, Eliot T.; Smith, R. Adam; Tanksley, Jarred P.; Washington, Mary Kay; Walker, Ronald; Coffey, Robert J.; Manning, H. Charles

    2013-01-01

    Molecular imaging biomarkers of proliferation hold great promise for quantifying response to personalized medicine. One such approach utilizes the positron emission tomography (PET) tracer 3′-deoxy-3′ [18F]-fluorothymidine ([18F]FLT), an investigational agent whose uptake reflects thymidine salvage-dependent DNA synthesis. The goal of this study was to evaluate [18F]FLT-PET in the setting of Ménétrier’s disease (MD), a rare, premalignant hyperproliferative disorder of the stomach treatable with cetuximab therapy. Over 15 months, a patient with confirmed MD underwent cetuximab therapy and was followed with sequential [18F]FLT-PET. For comparison to MD, an [18F]FLT-PET study was conducted in another patient to quantify uptake in a normal stomach.Prior to cetuximab therapy, stomach tissue in MD was easily visualized with [18F]FLT-PET, with pre-treatment uptake levels exceeding normal stomach uptake by approximately 4-fold. Diminished [18F]FLT-PET in MD was observed following the initial and subsequent doses of cetuximab and correlated with clinical resolution of the disease. To our knowledge, this study reports the first clinical use of [18F]FLT-PET to assess proliferation in a premalignant disorder. We illustrate that the extent of MD involvement throughout the stomach could be easily visualized using [18F]FLT-PET, and that response to cetuximab could be followed quantitatively and non-invasively in sequential [18F]FLT-PET studies. Thus, [18F]FLT-PET appears to have potential to monitor response to treatment in this and potentially other hyperproliferative disorders. PMID:22821337

  13. Predicting responses from Rasch measures.

    PubMed

    Linacre, John M

    2010-01-01

    There is a growing family of Rasch models for polytomous observations. Selecting a suitable model for an existing dataset, estimating its parameters and evaluating its fit is now routine. Problems arise when the model parameters are to be estimated from the current data, but used to predict future data. In particular, ambiguities in the nature of the current data, or overfit of the model to the current dataset, may mean that better fit to the current data may lead to worse fit to future data. The predictive power of several Rasch and Rasch-related models are discussed in the context of the Netflix Prize. Rasch-related models are proposed based on Singular Value Decomposition (SVD) and Boltzmann Machines.

  14. Drug Response Prediction as a Link Prediction Problem

    PubMed Central

    Stanfield, Zachary; Coşkun, Mustafa; Koyutürk, Mehmet

    2017-01-01

    Drug response prediction is a well-studied problem in which the molecular profile of a given sample is used to predict the effect of a given drug on that sample. Effective solutions to this problem hold the key for precision medicine. In cancer research, genomic data from cell lines are often utilized as features to develop machine learning models predictive of drug response. Molecular networks provide a functional context for the integration of genomic features, thereby resulting in robust and reproducible predictive models. However, inclusion of network data increases dimensionality and poses additional challenges for common machine learning tasks. To overcome these challenges, we here formulate drug response prediction as a link prediction problem. For this purpose, we represent drug response data for a large cohort of cell lines as a heterogeneous network. Using this network, we compute “network profiles” for cell lines and drugs. We then use the associations between these profiles to predict links between drugs and cell lines. Through leave-one-out cross validation and cross-classification on independent datasets, we show that this approach leads to accurate and reproducible classification of sensitive and resistant cell line-drug pairs, with 85% accuracy. We also examine the biological relevance of the network profiles. PMID:28067293

  15. Caregiver responsiveness to the family bereavement program: what predicts responsiveness? What does responsiveness predict?

    PubMed

    Schoenfelder, Erin N; Sandler, Irwin N; Millsap, Roger E; Wolchik, Sharlene A; Berkel, Cady; Ayers, Timothy S

    2013-12-01

    The study developed a multidimensional measure to assess participant responsiveness to a preventive intervention and applied this measure to study how participant baseline characteristics predict responsiveness and how responsiveness predicts program outcomes. The study was conducted with caregivers who participated in the parenting-focused component of the Family Bereavement Program (FBP), a prevention program for families that have experienced parental death. The sample consisted of 89 caregivers assigned to the intervention condition in the efficacy trial of the FBP. Positive parenting, caregiver depression, and child externalizing problems at baseline were found to predict caregivers' use of program skills outside the group, and more child internalizing problems predicted more positive perceptions of the group environment. Higher levels of skill use during the program predicted increased positive parenting at the 11-month follow-up, whereas positive perceptions of the group environment predicted decreased caregiver depressive symptoms at follow-up. Caregiver skill use mediated the relation between baseline positive parenting and improvements in positive parenting at 11-month follow-up, and skill use and perceived group environment mediated changes in caregiver depression from baseline to 11-month follow-up.

  16. Caregiver Responsiveness to the Family Bereavement Program: What predicts responsiveness? What does responsiveness predict?

    PubMed Central

    Schoenfelder, Erin N.; Sandler, Irwin N.; Millsap, Roger E.; Wolchik, Sharlene A.; Berkel, Cady; Ayers, Timothy S.

    2013-01-01

    The study developed a multi-dimensional measure to assess participant responsiveness to a preventive intervention, and applied this measure to study how participant baseline characteristics predict responsiveness and how responsiveness predicts program outcomes. The study was conducted with caregivers who participated in the parenting-focused component of the Family Bereavement Program (FBP), a prevention program for families that have experienced parental death. The sample consisted of 89 caregivers assigned to the intervention condition in the efficacy trial of the FBP. Positive parenting, caregiver depression, and child externalizing problems at baseline were found to predict caregivers’ use of program skills outside the group, and more child internalizing problems predicted more positive perceptions of the group environment. Higher levels of skill use during the program predicted increased positive parenting at the 11-month follow-up, whereas positive perceptions of the group environment predicted decreased caregiver depressive symptoms at follow-up. Caregiver skill use mediated the relation between baseline positive parenting and improvements in positive parenting at 11-month follow-up, and skill use and perceived group environment mediated changes in caregiver depression from baseline to 11-month follow-up. PMID:23404661

  17. Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

    PubMed

    Iniesta, Raquel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana; Souery, Daniel; Stahl, Daniel; Dobson, Richard; Aitchison, Katherine J; Farmer, Anne; Lewis, Cathryn M; McGuffin, Peter; Uher, Rudolf

    2016-07-01

    The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  18. ¹⁸F-FDG PET/CT in the early prediction of pathological response in aggressive subtypes of breast cancer: review of the literature and recommendations for use in clinical trials.

    PubMed

    Groheux, David; Mankoff, David; Espié, Marc; Hindié, Elif

    2016-05-01

    Early assessment of response to neoadjuvant chemotherapy (NAC) might be helpful in avoiding the toxicity of ineffective chemotherapy and allowing refinement of treatment. We conducted a review of the literature regarding the applicability of (18)F-FDG PET/CT to the prediction of an early pathological response in different subgroups of breast cancer. Clinical research in this field has intensified in the last few years. Early studies by various groups have shown the potential of (18)F-FDG PET/CT in the early assessment of response to NAC. However, interim PET/CT in breast cancer has not yet gained wide acceptance compared to its use in other settings such as lymphomas. This is in part due to a lack of consensus that early evaluation of response can be used to direct change in therapy in the neoadjuvant breast cancer setting, and only limited data showing that response-adaptive therapy leads to improved outcomes. However, one major element that has hampered the use of (18)F-FDG PET/CT in directing neoadjuvant therapy is its evaluation in populations with mixed subtypes of breast cancer. However, major improvements have occurred in recent years. Pilot studies have highlighted the need for considering breast cancer subtype and the type of treatment, and have offered criteria for the use of PET/CT for the early prediction of response in specific settings. (18)F-FDG PET/CT has considerable potential for the early prediction of pathological complete response to NAC in aggressive subtypes such as triple-negative or HER2-positive breast cancers. The results of a multicentre trial that used early metabolic response on (18)F-FDG PET/CT as a means to select poor responders to adapt neoadjuvant treatment have recently been published. Other trials are ongoing or being planned.

  19. SCCA-IC serum levels are predictive of clinical response in HCV chronic hepatitis to antiviral therapy: a multicentric prospective study.

    PubMed

    Fransvea, E; Trerotoli, P; Sacco, R; Bernabucci, V; Milella, M; Napoli, N; Mazzocca, A; Renna, E; Quaranta, M; Angarano, G; Villa, E; Antonaci, S; Giannelli, G

    2012-10-01

    The combination of pegylated interferon (Peg-IFN) and ribavirin is currently the gold standard therapy in patients with HCV chronic infection. The duration of therapy, as well as the therapeutic dosage, depend on the genotype. Identification of the genotype and rapid virological response (RVR) are widely accepted as the most important predictors of clinical outcome during antiviral therapy but to optimize cost-benefits and to reduce possible side effects, further prognostic factors are needed. Squamous cell carcinoma antigens immunocomplex (SCCA-IC) has been reported to be increased in the serum of patients with liver cancer. In this multicentric prospective study, we investigated the serum levels of SCCA-IC in 103 patients with HCV chronic infection. Serum HCV-RNA was detected before the beginning of treatment, after 4, 12, 24 or 48 weeks, and at week 24 during follow-up. RVR, early virological response and sustained virological response (SVR) were assessed following the international guidelines. SCCA-IC levels were higher in responders (238 AU, interquartile difference 130-556 AU) and decreased significantly to 125 AU (70-290 AU). The mean baseline value in nonresponders was 149 AU (86.5-306.5 AU), but after 4 weeks of treatment the serum levels decreased to 115 AU (80-280 AU): the profile of reduction was different between patients with or without a positive SVR. Logistic regression with SVR as dependent variable identified as significant independent variables: the reduction in SCCA-IC after 1 month (OR = 4.82; 95% CI 1.39-16.67; P = 0.131) and a genotype other than 1 (OR = 0.094; 95% CI 0.21-0.42; P = 0.002); sex and age were also significant factors influencing SVR. SCCA-IC seems to be a reliable independent prognostic marker of therapeutic effectiveness in anti-HCV positive patients undergoing antiviral therapy.

  20. What predicts performance during clinical psychology training?

    PubMed Central

    Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

    2014-01-01

    Objectives While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Design Longitudinal cross-sectional study using prospective and retrospective data. Method Characteristics at application were analysed in relation to a range of in-course assessments for 274 trainee clinical psychologists who had completed or were in the final stage of their training. Results Trainees were diverse in age, pre-training experience, and academic performance at A-level (advanced level certificate required for university admission), but not in gender or ethnicity. Failure rates across the three performance domains (academic, clinical, research) were very low, suggesting that selection was successful in screening out less suitable candidates. Key predictors of good performance on the course were better A-levels and better degree class. Non-white students performed less well on two outcomes. Type and extent of pre-training clinical experience on outcomes had varied effects on outcome. Research supervisor ratings emerged as global indicators and predicted nearly all outcomes, but may have been biased as they were retrospective. Referee ratings predicted only one of the seven outcomes examined, and interview ratings predicted none of the outcomes. Conclusions Predicting who will do well or poorly in clinical psychology training is complex. Interview and referee ratings may well be successful in screening out unsuitable candidates, but appear to be a poor guide to performance on the course. Practitioner points While referee and selection interview ratings did not predict performance during training, they may be useful in screening out unsuitable candidates at the application stage High school final academic performance

  1. No predictive effect of body mass index on clinical response in patients with rheumatoid arthritis after 24 weeks of biological disease-modifying antirheumatic drugs: a single-center study.

    PubMed

    Kim, Seong-Kyu; Choe, Jung-Yoon; Park, Sung-Hoon; Lee, Hwajeong

    2016-05-01

    The aim of this study was to determine whether body mass index (BMI) is associated with clinical response to biologics in patients with rheumatoid arthritis (RA). We enrolled 68 patients with RA who were treated with biological disease-modifying antirheumatic drugs (bDMARDs). Biologics included abatacept, tocilizumab, and tumor necrosis factor-α (TNF-α) blockers (etanercept and adalimumab). Baseline BMI (kg/m(2)) was classified as normal (BMI < 23.0), overweight (23.0 ≤ BMI < 25.0), or obese (BMI ≥ 25.0). Improvement of disease activity score 28 (DAS28) and achievement of the European League Against Rheumatism (EULAR) remission and responses between baseline and 24 weeks were our measures of clinical improvement. Mean baseline BMI before treatment with bDMARDs in patients with RA was 22.2 (SD 3.6). DAS28-ESR and DAS28-CRP were significantly reduced from baseline after 24 weeks of treatment with bDMARDs (p < 0.001 of both). ∆DAS28-ESR and ∆DAS28-CRP were not found among patients with normal, overweight, or obese BMI (p = 0.133 and p = 0.255, respectively) nor were EULAR responses or EULAR remission (p = 0.540 and p = 0.957, respectively). Logistic regression analysis showed no relationship of BMI with EULAR clinical responses (p = 0.093 for good response and p = 0.878 for EULAR remission). This study reveals that BMI is not a predictive factor of clinical response to bDMARDs in patients with RA.

  2. Resting state functional connectivity predicts neurofeedback response

    PubMed Central

    Scheinost, Dustin; Stoica, Teodora; Wasylink, Suzanne; Gruner, Patricia; Saksa, John; Pittenger, Christopher; Hampson, Michelle

    2014-01-01

    Tailoring treatments to the specific needs and biology of individual patients—personalized medicine—requires delineation of reliable predictors of response. Unfortunately, these have been slow to emerge, especially in neuropsychiatric disorders. We have recently described a real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback protocol that can reduce contamination-related anxiety, a prominent symptom of many cases of obsessive-compulsive disorder (OCD). Individual response to this intervention is variable. Here we used patterns of brain functional connectivity, as measured by baseline resting-state fMRI (rs-fMRI), to predict improvements in contamination anxiety after neurofeedback training. Activity of a region of the orbitofrontal cortex (OFC) and anterior prefrontal cortex, Brodmann area (BA) 10, associated with contamination anxiety in each subject was measured in real time and presented as a neurofeedback signal, permitting subjects to learn to modulate this target brain region. We have previously reported both enhanced OFC/BA 10 control and improved anxiety in a group of subclinically anxious subjects after neurofeedback. Five individuals with contamination-related OCD who underwent the same protocol also showed improved clinical symptomatology. In both groups, these behavioral improvements were strongly correlated with baseline whole-brain connectivity in the OFC/BA 10, computed from rs-fMRI collected several days prior to neurofeedback training. These pilot data suggest that rs-fMRI can be used to identify individuals likely to benefit from rt-fMRI neurofeedback training to control contamination anxiety. PMID:25309375

  3. Radiogenomics predicting tumor responses to radiotherapy in lung cancer.

    PubMed

    Das, Amit K; Bell, Marcus H; Nirodi, Chaitanya S; Story, Michael D; Minna, John D

    2010-07-01

    The recently developed ability to interrogate genome-wide data arrays has provided invaluable insights into the molecular pathogenesis of lung cancer. These data have also provided information for developing targeted therapy in lung cancer patients based on the identification of cancer-specific vulnerabilities and set the stage for molecular biomarkers that provide information on clinical outcome and response to treatment. In addition, there are now large panels of lung cancer cell lines, both non-small-cell lung cancer and small-cell lung cancer, that have distinct chemotherapy and radiation response phenotypes. We anticipate that the integration of molecular data with therapy response data will allow for the generation of biomarker signatures that predict response to therapy. These signatures will need to be validated in clinical studies, at first retrospective analyses and then prospective clinical trials, to show that the use of these biomarkers can aid in predicting patient outcomes (eg, in the case of radiation therapy for local control and survival). This review highlights recent advances in molecular profiling of tumor responses to radiotherapy and identifies challenges and opportunities in developing molecular biomarker signatures for predicting radiation response for individual patients with lung cancer. Copyright 2010 Elsevier Inc. All rights reserved.

  4. Radiogenomics- predicting tumor responses to radiotherapy in lung cancer

    PubMed Central

    Das, Amit K.; Bell, Marcus H.; Nirodi, Chaitanya S.; Story, Michael D.; Minna, John D.

    2010-01-01

    The recently developed ability to interrogate genome wide data arrays has provided invaluable insights into the molecular pathogenesis of lung cancer. These data have also provided information for developing targeted therapy in lung cancer patients based upon identification of cancer specific vulnerabilities and set the stage for molecular biomarkers that provide information on clinical outcome and response to treatment. In addition, there are now large panels of lung cancer cell lines, both non small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), which have distinct chemotherapy and radiation response phenotypes. We anticipate that the integration of molecular data with therapy response data will allow for the generation of biomarker signatures that predict response to therapy. These signatures will need to be validated in clinical studies, at first retrospective analyses and then prospective clinical trials to show that the use of these biomarkers can aid in predicting patient outcomes (e.g. in the case of radiation therapy for local control and survival). This review highlights recent advances in molecular profiling of tumor responses to radiotherapy and identifies challenges and opportunities in developing molecular biomarker signatures for predicting radiation response for individual patients with lung cancer. PMID:20685577

  5. Is the Ultimate Treatment Response Predictable with Early Response in Major Depressive Episode?

    PubMed Central

    ÇİFTÇİ, Aslı; ULAŞ, Halis; TOPUZOĞLU, Ahmet; TUNCA, Zeliha

    2016-01-01

    Introduction New evidence suggests that the efficacy of antidepressants occurs within the first weeks of treatment and this early response predicts the later response. The purpose of the present study was to investigate if the partial response in the first week predicts the response at the end of treatment in patients with major depressive disorder who are treated with either antidepressant medication or electroconvulsive therapy. Methods Inpatients from Dokuz Eylül University Hospital with a major depressive episode, treated with antidepressant medication (n=52) or electroconvulsive therapy (ECT) (n=48), were recruited for the study. The data were retrospectively collected to decide whether a 25% decrease in the Hamilton Depression Rating Scale (HDRS) score at the first week of treatment predicts a 50% decrease at the third week using validity analysis. In addition, the effects of socio-demographic and clinical variables on the treatment response were assessed. Results A 25% decrease in the HDRS score in the first week of treatment predicted a 50% decrease in the HDRS score in the third week with a 78.3% positive predictive value, 62.1% negative predictive value, 62.1% sensitivity, and 78.3% specificity for antidepressant medications and an 88% positive predictive value, 52.2% negative predictive value, 66.7% sensitivity, and 80% specificity for ECT. The number of previous hospitalizations, comorbid medical illnesses, number of depressive episodes, duration of illness, and duration of the current episode were related to the treatment response. Conclusion Treatment response in the first week predicted the response in the third week with a high specificity and a high positive predictive value. Close monitoring of the response from the first week of treatment may thus help the clinician to predict the subsequent response. PMID:28373802

  6. Predictability of clinical assessments for driving performance.

    PubMed

    Stav, Wendy B; Justiss, Michael D; McCarthy, Dennis P; Mann, William C; Lanford, Desiree N

    2008-01-01

    As the number of older drivers grows, it is increasingly important to accurately identify at-risk drivers. This study tested clinical assessments predictive of real-time driving performance. Selected assessment tools considered important in the identification of at-risk older drivers represented the domains of vision, cognition, motor performance, and driving knowledge. Participants were administered the battery of assessments followed by an on-road test. A univariate analysis was conducted to identify significant factors (<.05) to be included in a multivariate regression model. Assessments identified as independently associated with driving performance in the regression model included: FACTTM Contrast sensitivity slide-B, Rapid Pace Walk, UFOV rating, and MMSE total score. The domains of vision, cognitive, and motor performance were represented in the predictive model. Due to the dynamic nature of the driving task, it is not likely that a single assessment tool will identify at risk drivers. By standardizing the selection of clinical assessments used in driving evaluations, practitioners should be able to provide services more efficiently, more objectively, and more accurately to identify at-risk drivers.

  7. On understanding and predicting groundwater response time.

    PubMed

    Sophocleous, Marios

    2012-01-01

    An aquifer system, when perturbed, has a tendency to evolve to a new equilibrium, a process that can take from just a few seconds to possibly millions of years. The time scale on which a system adjusts to a new equilibrium is often referred to as "response time" or "lag time." Because groundwater response time affects the physical and economic viability of various management options in a basin, natural resource managers are increasingly interested in incorporating it into policy. However, the processes of how groundwater responds to land-use change are not well understood, making it difficult to predict the timing of groundwater response to such change. The difficulty in estimating groundwater response time is further compounded because the data needed to quantify this process are not usually readily available. This article synthesizes disparate pieces of information on aquifer response times into a relatively brief but hopefully comprehensive review that the community of water professionals can use to better assess the impact of aquifer response time in future groundwater management investigations. A brief exposition on dimensional/scaling analysis is presented first, followed by an overview of aquifer response time for simplified aquifer systems. The aquifer response time is considered first from a water-quantity viewpoint and later expanded to incorporate groundwater age and water-quality aspects. Monitoring programs today, as well as water policies and regulations, should address this issue of aquifer response time so that more realistic management expectations can be reached.

  8. Predicting Responses to Contemporary Environmental Change Using Evolutionary Response Architectures.

    PubMed

    Bay, Rachael A; Rose, Noah; Barrett, Rowan; Bernatchez, Louis; Ghalambor, Cameron K; Lasky, Jesse R; Brem, Rachel B; Palumbi, Stephen R; Ralph, Peter

    2017-05-01

    Rapid environmental change currently presents a major threat to global biodiversity and ecosystem functions, and understanding impacts on individual populations is critical to creating reliable predictions and mitigation plans. One emerging tool for this goal is high-throughput sequencing technology, which can now be used to scan the genome for signs of environmental selection in any species and any system. This explosion of data provides a powerful new window into the molecular mechanisms of adaptation, and although there has been some success in using genomic data to predict responses to selection in fields such as agriculture, thus far genomic data are rarely integrated into predictive frameworks of future adaptation in natural populations. Here, we review both theoretical and empirical studies of adaptation to rapid environmental change, focusing on areas where genomic data are poised to contribute to our ability to estimate species and population persistence and adaptation. We advocate for the need to study and model evolutionary response architectures, which integrate spatial information, fitness estimates, and plasticity with genetic architecture. Understanding how these factors contribute to adaptive responses is essential in efforts to predict the responses of species and ecosystems to future environmental change.

  9. Early prediction of blonanserin response in Japanese patients with schizophrenia

    PubMed Central

    Kishi, Taro; Matsuda, Yuki; Fujita, Kiyoshi; Iwata, Nakao

    2014-01-01

    Background Blonanserin is a second-generation antipsychotic used for the treatment of schizophrenia in Japan and Korea. The present study aimed to examine early prediction of blonanserin in patients with schizophrenia. Methods An 8-week, prospective, single-arm, flexible-dose clinical trial of blonanserin in patients with schizophrenia was conducted under real-world conditions. The inclusion criteria were antipsychotic naïve, and first-episode schizophrenia patients or schizophrenia patients with no consumption of any antipsychotic medication for more than 4 weeks before enrollment in this study. The positive predictive value, negative predictive value, sensitivity, specificity, and predictive power were calculated for the response status at week 4 to predict the subsequent response at week 8. Results Thirty-seven patients were recruited (56.8% of them had first-episode schizophrenia), and 28 (75.7%) completed the trial. At week 8, blonanserin was associated with a significant improvement in the Positive and Negative Syndrome Scale (PANSS) total score (P<0.0001) and in positive (P<0.0001), negative (P<0.0001), and general subscale scores (P<0.0001). In terms of percentage improvement of PANSS total scores from baseline to week 8, 64.9% of patients showed a ≥20% reduction in the PANSS total score and 48.6% showed a ≥30% reduction. However, 8.1% of patients experienced at least one adverse event. Using the 20% reduction in the PANSS total score at week 4 as a definition of an early response, the negative predictive values for later responses (ie, reductions of ≥30 and ≥40 in the PANSS total scores) were 88.9% and 94.1%, respectively. The specificities were 80.0% and 51.6%, respectively. Conclusion Our results suggest that the blonanserin response at week 4 could predict the later response at week 8. PMID:25285009

  10. Early prediction of blonanserin response in Japanese patients with schizophrenia.

    PubMed

    Kishi, Taro; Matsuda, Yuki; Fujita, Kiyoshi; Iwata, Nakao

    2014-01-01

    Blonanserin is a second-generation antipsychotic used for the treatment of schizophrenia in Japan and Korea. The present study aimed to examine early prediction of blonanserin in patients with schizophrenia. An 8-week, prospective, single-arm, flexible-dose clinical trial of blonanserin in patients with schizophrenia was conducted under real-world conditions. The inclusion criteria were antipsychotic naïve, and first-episode schizophrenia patients or schizophrenia patients with no consumption of any antipsychotic medication for more than 4 weeks before enrollment in this study. The positive predictive value, negative predictive value, sensitivity, specificity, and predictive power were calculated for the response status at week 4 to predict the subsequent response at week 8. Thirty-seven patients were recruited (56.8% of them had first-episode schizophrenia), and 28 (75.7%) completed the trial. At week 8, blonanserin was associated with a significant improvement in the Positive and Negative Syndrome Scale (PANSS) total score (P<0.0001) and in positive (P<0.0001), negative (P<0.0001), and general subscale scores (P<0.0001). In terms of percentage improvement of PANSS total scores from baseline to week 8, 64.9% of patients showed a ≥20% reduction in the PANSS total score and 48.6% showed a ≥30% reduction. However, 8.1% of patients experienced at least one adverse event. Using the 20% reduction in the PANSS total score at week 4 as a definition of an early response, the negative predictive values for later responses (ie, reductions of ≥30 and ≥40 in the PANSS total scores) were 88.9% and 94.1%, respectively. The specificities were 80.0% and 51.6%, respectively. Our results suggest that the blonanserin response at week 4 could predict the later response at week 8.

  11. Physiological threat responses predict number processing.

    PubMed

    Scholl, Annika; Moeller, Korbinian; Scheepers, Daan; Nuerk, Hans-Christoph; Sassenberg, Kai

    2017-01-01

    Being able to adequately process numbers is a key competency in everyday life. Yet, self-reported negative affective responses towards numbers are known to deteriorate numerical performance. Here, we investigated how physiological threat responses predict numerical performance. Physiological responses reflect whether individuals evaluate a task as exceeding or matching their resources and in turn experience either threat or challenge, which influences subsequent performance. We hypothesized that, the more individuals respond to a numerical task with physiological threat, the worse they would perform. Results of an experiment with cardiovascular indicators of threat/challenge corroborated this expectation. The findings thereby contribute to our understanding of the physiological mechanism underlying the influence of negative affective responses towards numbers on numerical performance.

  12. Is (18)F-FDG-PET suitable to predict clinical response to the treatment of geriatric depression? A systematic review of PET studies.

    PubMed

    De Crescenzo, Franco; Ciliberto, Mario; Menghini, Deny; Treglia, Giorgio; Ebmeier, Klaus P; Janiri, Luigi

    2017-09-01

    Geriatric depression is one of the most common psychiatric disorders in later life. It differs from earlier depression in its presentation, etiology, risk factors, protective factors and outcome. Positron emission tomography (PET) can be used to detect changes in neural circuitry in neuropsychiatric disorders, and several authors have assessed its role in the diagnosis and follow-up of patients with geriatric depression. We reviewed the current evidence on the use of fluorine-18-fluorodeoxyglucose positron emission tomography ((18)F-FDG-PET) in geriatric depressed patients to find predictors of treatment response. We searched PubMed/MEDLINE, Scopus, Embase, Cochrane Library, CINAHL and the PsycINFO databases to find relevant peer-reviewed articles on PET in geriatric depression using the search terms ('PET' or 'positron emission tomography') and ('mood' or 'affective disorder' or 'affective disorders' or 'depression' or 'dysthymia' or 'seasonal affective disorder'). Eleven articles comprising 128 patients were included. We extracted data on glucose uptake of depressed patients and controls at baseline and after different types of intervention (total sleep deprivation followed by a recovery sleep and treatment with selective serotonin reuptake inhibitors). (18)F-FDG-PET showed significant alterations of glucose uptake in several brain areas, in particular the anterior cingulate cortex, which showed reduced metabolism after treatment, and was a predictor of treatment response.

  13. Simple clinical variables predict liver histology in hepatitis C: prospective validation of a clinical prediction model.

    PubMed

    Romagnuolo, Joseph; Andrews, Christopher N; Bain, Vincent G; Bonacini, Maurizio; Cotler, Scott J; Ma, Mang; Sherman, Morris

    2005-11-01

    A recent single-center multivariate analysis of hepatitis C (HCV) patients showed that having any two criteria: 1) ferritin > or =200 microg/l and 2) spider nevi and/or albumin < or = 35 g/l predicted grade 2 or greater histological inflammation; the presence of any two of the following criteria: spider nevi, platelets < or =150 x 109/l, palpable splenomegaly and/or albumin < or =35 g/l predicted stage 2 or greater histological fibrosis. Absence of predictors also predicted a lack of inflammation and fibrosis. Our aim was prospectively to validate this clinical prediction model using an independent multicenter sample. Eighty-one patients with previously untreated active chronic HCV underwent physical examination, laboratory investigation, and liver biopsy. Biopsies were read, in blinded fashion, by a single pathologist, using a modified Hytiroglou (1995) scale. The clinical scoring system was correlated with histology; likelihood ratios (LRs), Fisher's exact p-values, and receiver operating characteristics (ROCs) were calculated. Data recording was complete in 77 and 38 patients regarding fibrotic stage and inflammatory grade, respectively. For fibrosis, 3/3 patients with any three criteria (LR 17, positive predictive value (PPV) 100%), 4/5 patients with any two criteria (LR 5.1), and 15/47 with no criteria (LR 0.6, negative predictive value (NPV) 68%) had stage 2 or greater fibrosis on biopsy (p=0.01). For inflammation, 5/5 patients with both criteria (LR 15, PPV 100%), and 8/19 patients with no criteria (LR 0.5, NPV 58%) had moderate-severe inflammation on liver biopsy (p=0.036). When missing variables were assumed to be normal, recalculated LRs were almost identical. An alanine aminotransferase (ALAT) level <60 U/l may increase the NPVs. This independent multicenter data set has validated our published model which uses simple clinical variables accurately and significantly to predict hepatic fibrosis and inflammation in HCV patients.

  14. Physiotherapy students' perceptions and experiences of clinical prediction rules.

    PubMed

    Knox, Grahame M; Snodgrass, Suzanne J; Stanton, Tasha R; Kelly, David H; Vicenzino, Bill; Wand, Benedict M; Rivett, Darren A

    2017-09-01

    Clinical reasoning can be difficult to teach to pre-professional physiotherapy students due to their lack of clinical experience. It may be that tools such as clinical prediction rules (CPRs) could aid the process, but there has been little investigation into their use in physiotherapy clinical education. This study aimed to determine the perceptions and experiences of physiotherapy students regarding CPRs, and whether they are learning about CPRs on clinical placement. Cross-sectional survey using a paper-based questionnaire. Final year pre-professional physiotherapy students (n=371, response rate 77%) from five universities across five states of Australia. Sixty percent of respondents had not heard of CPRs, and a further 19% had not clinically used CPRs. Only 21% reported using CPRs, and of these nearly three-quarters were rarely, if ever, learning about CPRs in the clinical setting. However most of those who used CPRs (78%) believed CPRs assisted in the development of clinical reasoning skills and none (0%) was opposed to the teaching of CPRs to students. The CPRs most commonly recognised and used by students were those for determining the need for an X-ray following injuries to the ankle and foot (67%), and for identifying deep venous thrombosis (63%). The large majority of students in this sample knew little, if anything, about CPRs and few had learned about, experienced or practiced them on clinical placement. However, students who were aware of CPRs found them helpful for their clinical reasoning and were in favour of learning more about them. Copyright © 2016 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

  15. Prediction of response to tapentadol in chronic low back pain.

    PubMed

    Reimer, M; Hüllemann, P; Hukauf, M; Keller, T; Binder, A; Gierthmühlen, J; Baron, R

    2017-02-01

    Many chronic low back pain (cLBP) patients do not satisfactorily respond to treatment. The knowledge of responders and non-responders before initiating treatment would improve decision making and reduce health care costs. The aims of this exploratory prediction study in cLBP patients treated with tapentadol were to identify predictors of treatment outcome based on baseline characteristics, to evaluate quality-of-life and functionality as alternative outcome parameters and to develop nomograms to calculate the individual probability of response. In a retrospective analysis of an open-label phase 3b trial, 46 baseline characteristics were included into statistical prediction modelling. One hundred and twenty-one patients were followed up during the titration and treatment period and 67 patients were analysed who discontinued the trial. Demographic data were not relevant for response prediction. Nine baseline co-variables were robust: painDETECT score, intensity of burning and painful attacks, SF36 Health Survey score (MCS, PCS), EuroQol-5, Hospital Anxiety/Depression Scale. Gender had a minor influence. Alternative outcomes (quality-of-life, functionality) were more important for response prediction than conventional pain intensity measures. Neuropathic symptoms (high painDETECT score) had a positive predictive validity. Painful attacks and classical yellow flags (depression, anxiety) negatively influenced the treatment response. High depression scores, female gender and low burning predicted discontinuation during titration. In this exploratory study, predictive baseline characteristics have been identified that can be used to calculate the individual probability of tapentadol response in cLBP. The small sample size in relation to the number of initial variables is a limitation of this approach. Predictors for treatment response of tapentadol were identified in patients with chronic low back pain based on clinical pre-treatment characteristics that can guide

  16. Prediction of psilocybin response in healthy volunteers.

    PubMed

    Studerus, Erich; Gamma, Alex; Kometer, Michael; Vollenweider, Franz X

    2012-01-01

    Responses to hallucinogenic drugs, such as psilocybin, are believed to be critically dependent on the user's personality, current mood state, drug pre-experiences, expectancies, and social and environmental variables. However, little is known about the order of importance of these variables and their effect sizes in comparison to drug dose. Hence, this study investigated the effects of 24 predictor variables, including age, sex, education, personality traits, drug pre-experience, mental state before drug intake, experimental setting, and drug dose on the acute response to psilocybin. The analysis was based on the pooled data of 23 controlled experimental studies involving 409 psilocybin administrations to 261 healthy volunteers. Multiple linear mixed effects models were fitted for each of 15 response variables. Although drug dose was clearly the most important predictor for all measured response variables, several non-pharmacological variables significantly contributed to the effects of psilocybin. Specifically, having a high score in the personality trait of Absorption, being in an emotionally excitable and active state immediately before drug intake, and having experienced few psychological problems in past weeks were most strongly associated with pleasant and mystical-type experiences, whereas high Emotional Excitability, low age, and an experimental setting involving positron emission tomography most strongly predicted unpleasant and/or anxious reactions to psilocybin. The results confirm that non-pharmacological variables play an important role in the effects of psilocybin.

  17. Prediction of Psilocybin Response in Healthy Volunteers

    PubMed Central

    Studerus, Erich; Gamma, Alex; Kometer, Michael; Vollenweider, Franz X.

    2012-01-01

    Responses to hallucinogenic drugs, such as psilocybin, are believed to be critically dependent on the user's personality, current mood state, drug pre-experiences, expectancies, and social and environmental variables. However, little is known about the order of importance of these variables and their effect sizes in comparison to drug dose. Hence, this study investigated the effects of 24 predictor variables, including age, sex, education, personality traits, drug pre-experience, mental state before drug intake, experimental setting, and drug dose on the acute response to psilocybin. The analysis was based on the pooled data of 23 controlled experimental studies involving 409 psilocybin administrations to 261 healthy volunteers. Multiple linear mixed effects models were fitted for each of 15 response variables. Although drug dose was clearly the most important predictor for all measured response variables, several non-pharmacological variables significantly contributed to the effects of psilocybin. Specifically, having a high score in the personality trait of Absorption, being in an emotionally excitable and active state immediately before drug intake, and having experienced few psychological problems in past weeks were most strongly associated with pleasant and mystical-type experiences, whereas high Emotional Excitability, low age, and an experimental setting involving positron emission tomography most strongly predicted unpleasant and/or anxious reactions to psilocybin. The results confirm that non-pharmacological variables play an important role in the effects of psilocybin. PMID:22363492

  18. Predicting allopurinol response in patients with gout

    PubMed Central

    Duffull, Stephen B.; Merriman, Tony R.; Dalbeth, Nicola; Barclay, Murray L.; Stamp, Lisa K.

    2015-01-01

    Aims The primary aim of this research was to predict the allopurinol maintenance doses required to achieve the target plasma urate of ≤0.36 mmol l−1. Methods A population analysis was conducted in nonmem using oxypurinol and urate plasma concentrations from 133 gout patients. Maintenance dose predictions to achieve the recommended plasma urate target were generated. Results The urate response was best described by a direct effects model. Renal function, diuretic use and body size were found to be significant covariates. Dose requirements increased approximately 2‐fold over a 3‐fold range of total body weight and were 1.25–2 fold higher in those taking diuretics. Renal function had only a modest impact on dose requirements. Conclusions Contrary to current guidelines, the model predicted that allopurinol dose requirements were determined primarily by differences in body size and diuretic use. A revised guide to the likely allopurinol doses to achieve the target plasma urate concentration is proposed. PMID:26451524

  19. Predicting Flutter and Forced Response in Turbomachinery

    NASA Technical Reports Server (NTRS)

    VanZante, Dale E.; Adamczyk, John J.; Srivastava, Rakesh; Bakhle, Milind A.; Shabbir, Aamir; Chen, Jen-Ping; Janus, J. Mark; To, Wai-Ming; Barter, John

    2005-01-01

    TURBO-AE is a computer code that enables detailed, high-fidelity modeling of aeroelastic and unsteady aerodynamic characteristics for prediction of flutter, forced response, and blade-row interaction effects in turbomachinery. Flow regimes that can be modeled include subsonic, transonic, and supersonic, with attached and/or separated flow fields. The three-dimensional Reynolds-averaged Navier-Stokes equations are solved numerically to obtain extremely accurate descriptions of unsteady flow fields in multistage turbomachinery configurations. Blade vibration is simulated by use of a dynamic-grid-deformation technique to calculate the energy exchange for determining the aerodynamic damping of vibrations of blades. The aerodynamic damping can be used to assess the stability of a blade row. TURBO-AE also calculates the unsteady blade loading attributable to such external sources of excitation as incoming gusts and blade-row interactions. These blade loadings, along with aerodynamic damping, are used to calculate the forced responses of blades to predict their fatigue lives. Phase-lagged boundary conditions based on the direct-store method are used to calculate nonzero interblade phase-angle oscillations; this practice eliminates the need to model multiple blade passages, and, hence, enables large savings in computational resources.

  20. Mouse models of human AML accurately predict chemotherapy response

    PubMed Central

    Zuber, Johannes; Radtke, Ina; Pardee, Timothy S.; Zhao, Zhen; Rappaport, Amy R.; Luo, Weijun; McCurrach, Mila E.; Yang, Miao-Miao; Dolan, M. Eileen; Kogan, Scott C.; Downing, James R.; Lowe, Scott W.

    2009-01-01

    The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients. PMID:19339691

  1. Mouse models of human AML accurately predict chemotherapy response.

    PubMed

    Zuber, Johannes; Radtke, Ina; Pardee, Timothy S; Zhao, Zhen; Rappaport, Amy R; Luo, Weijun; McCurrach, Mila E; Yang, Miao-Miao; Dolan, M Eileen; Kogan, Scott C; Downing, James R; Lowe, Scott W

    2009-04-01

    The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients.

  2. Coping styles predict responsiveness to cognitive behaviour therapy in psychosis.

    PubMed

    Premkumar, Preethi; Peters, Emmanuelle R; Fannon, Dominic; Anilkumar, Anantha P; Kuipers, Elizabeth; Kumari, Veena

    2011-05-30

    The study aimed to determine the clinical and neuropsychological predictors of responsiveness to cognitive behavioural therapy for psychosis (CBTp). Sixty patients with schizophrenia or schizoaffective disorder and 25 healthy individuals took part in the study. Thirty patients (25 protocol completers) received CBTp in addition to standard care (SC); 30 patients (18 protocol completers) received SC only. All patients were assessed on symptoms using the Positive and Negative Syndrome Scale (PANSS) and clinical and neuropsychological function before and after CBTp. Symptoms and self-esteem improved to a greater extent in the CBTp+SC than SC control group. Greater pre-therapy coping ability and the self-reflectiveness dimension of cognitive insight at baseline predicted improvement in symptoms in the CBTp+SC group, but not the SC control group, explaining up to 21% of the variance in symptom improvement. Pre-therapy neuropsychological function, duration of illness, clinical insight and gender did not predict CBTp responsiveness. Being able to have a range of coping strategies and reflect on one's experiences while refraining from overconfidence in one's interpretations before therapy is conducive to better CBTp responsiveness. Copyright © 2010 Elsevier Ltd. All rights reserved.

  3. Predicting and Monitoring Cancer Treatment Response with DW-MRI

    PubMed Central

    Thoeny, Harriet C.; Ross, Brian D.

    2010-01-01

    An imaging biomarker that would provide for an early quantitative metric of clinical treatment response in cancer patients would provide for a paradigm shift in cancer care. Currently, non-image based clinical outcome metrics include morphology, clinical and laboratory parameters however, these are obtained relatively late following treatment. Diffusion-weighted MRI (DW-MRI) holds promise for use as a cancer treatment response biomarker as it is sensitive to macromolecular and microstructural changes which can occur at the cellular level earlier than anatomical changes during therapy. Studies have shown that successful treatment of a many tumor types can be detected using DW-MRI as an early increase in the apparent diffusion coefficient (ADC) values. Additionally, low pre-treatment ADC values of various tumors are often predictive of better outcome. These capabilities, once validated, could provide for an important opportunity to individualize therapy thereby minimizing unnecessary systemic toxicity associated with ineffective therapies with the additional advantage of improving overall patient health care and associated costs. In this report, we provide a brief technical overview of DW-MRI acquisition protocols, quantitative image analysis approaches and review studies which have implemented DW-MRI for the purpose of early prediction of cancer treatment response. PMID:20575076

  4. Coping styles predict responsiveness to cognitive behaviour therapy in psychosis

    PubMed Central

    Premkumar, Preethi; Peters, Emmanuelle R.; Fannon, Dominic; Anilkumar, Anantha P.; Kuipers, Elizabeth; Kumari, Veena

    2011-01-01

    The study aimed to determine the clinical and neuropsychological predictors of responsiveness to cognitive behavioural therapy for psychosis (CBTp). Sixty patients with schizophrenia or schizoaffective disorder and 25 healthy individuals took part in the study. Thirty patients (25 protocol completers) received CBTp in addition to standard care (SC); 30 patients (18 protocol completers) received SC only. All patients were assessed on symptoms using the Positive and Negative Syndrome Scale (PANSS) and clinical and neuropsychological function before and after CBTp. Symptoms and self-esteem improved to a greater extent in the CBTp + SC than SC control group. Greater pre-therapy coping ability and the self-reflectiveness dimension of cognitive insight at baseline predicted improvement in symptoms in the CBTp + SC group, but not the SC control group, explaining up to 21% of the variance in symptom improvement. Pre-therapy neuropsychological function, duration of illness, clinical insight and gender did not predict CBTp responsiveness. Being able to have a range of coping strategies and reflect on one's experiences while refraining from overconfidence in one's interpretations before therapy is conducive to better CBTp responsiveness. PMID:21262541

  5. Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data.

    PubMed

    Meng, Xing; Jiang, Rongtao; Lin, Dongdong; Bustillo, Juan; Jones, Thomas; Chen, Jiayu; Yu, Qingbao; Du, Yuhui; Zhang, Yu; Jiang, Tianzi; Sui, Jing; Calhoun, Vince D

    2017-01-15

    Neuroimaging techniques have greatly enhanced the understanding of neurodiversity (human brain variation across individuals) in both health and disease. The ultimate goal of using brain imaging biomarkers is to perform individualized predictions. Here we proposed a generalized framework that can predict explicit values of the targeted measures by taking advantage of joint information from multiple modalities. This framework also enables whole brain voxel-wise searching by combining multivariate techniques such as ReliefF, clustering, correlation-based feature selection and multiple regression models, which is more flexible and can achieve better prediction performance than alternative atlas-based methods. For 50 healthy controls and 47 schizophrenia patients, three kinds of features derived from resting-state fMRI (fALFF), sMRI (gray matter) and DTI (fractional anisotropy) were extracted and fed into a regression model, achieving high prediction for both cognitive scores (MCCB composite r=0.7033, MCCB social cognition r=0.7084) and symptomatic scores (positive and negative syndrome scale [PANSS] positive r=0.7785, PANSS negative r=0.7804). Moreover, the brain areas likely responsible for cognitive deficits of schizophrenia, including middle temporal gyrus, dorsolateral prefrontal cortex, striatum, cuneus and cerebellum, were located with different weights, as well as regions predicting PANSS symptoms, including thalamus, striatum and inferior parietal lobule, pinpointing the potential neuromarkers. Finally, compared to a single modality, multimodal combination achieves higher prediction accuracy and enables individualized prediction on multiple clinical measures. There is more work to be done, but the current results highlight the potential utility of multimodal brain imaging biomarkers to eventually inform clinical decision-making. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. Electronic clinical predictive thermometer using logarithm for temperature prediction

    NASA Technical Reports Server (NTRS)

    Cambridge, Vivien J. (Inventor); Koger, Thomas L. (Inventor); Nail, William L. (Inventor); Diaz, Patrick (Inventor)

    1998-01-01

    A thermometer that rapidly predicts body temperature based on the temperature signals received from a temperature sensing probe when it comes into contact with the body. The logarithms of the differences between the temperature signals in a selected time frame are determined. A line is fit through the logarithms and the slope of the line is used as a system time constant in predicting the final temperature of the body. The time constant in conjunction with predetermined additional constants are used to compute the predicted temperature. Data quality in the time frame is monitored and if unacceptable, a different time frame of temperature signals is selected for use in prediction. The processor switches to a monitor mode if data quality over a limited number of time frames is unacceptable. Determining the start time on which the measurement time frame for prediction is based is performed by summing the second derivatives of temperature signals over time frames. When the sum of second derivatives in a particular time frame exceeds a threshold, the start time is established.

  7. Host genetics predict clinical deterioration in HCV-related cirrhosis.

    PubMed

    King, Lindsay Y; Johnson, Kara B; Zheng, Hui; Wei, Lan; Gudewicz, Thomas; Hoshida, Yujin; Corey, Kathleen E; Ajayi, Tokunbo; Ufere, Nneka; Baumert, Thomas F; Chan, Andrew T; Tanabe, Kenneth K; Fuchs, Bryan C; Chung, Raymond T

    2014-01-01

    Single nucleotide polymorphisms (SNPs) in the epidermal growth factor (EGF, rs4444903), patatin-like phospholipase domain-containing protein 3 (PNPLA3, rs738409) genes, and near the interleukin-28B (IL28B, rs12979860) gene are linked to treatment response, fibrosis, and hepatocellular carcinoma (HCC) in chronic hepatitis C. Whether these SNPs independently or in combination predict clinical deterioration in hepatitis C virus (HCV)-related cirrhosis is unknown. We genotyped SNPs in EGF, PNPLA3, and IL28B from liver tissue from 169 patients with biopsy-proven HCV cirrhosis. We estimated risk of clinical deterioration, defined as development of ascites, encephalopathy, variceal hemorrhage, HCC, or liver-related death using Cox proportional hazards modeling. During a median follow-up of 6.6 years, 66 of 169 patients experienced clinical deterioration. EGF non-AA, PNPLA3 non-CC, and IL28B non-CC genotypes were each associated with increased risk of clinical deterioration in age, sex, and race-adjusted analysis. Only EGF non-AA genotype was independently associated with increased risk of clinical deterioration (hazard ratio [HR] 2.87; 95% confidence interval [CI] 1.31-6.25) after additionally adjusting for bilirubin, albumin, and platelets. Compared to subjects who had 0-1 unfavorable genotypes, the HR for clinical deterioration was 1.79 (95%CI 0.96-3.35) for 2 unfavorable genotypes and 4.03 (95%CI 2.13-7.62) for unfavorable genotypes for all three loci (Ptrend<0.0001). In conclusion, among HCV cirrhotics, EGF non-AA genotype is independently associated with increased risk for clinical deterioration. Specific PNPLA3 and IL28B genotypes also appear to be associated with clinical deterioration. These SNPs have potential to identify patients with HCV-related cirrhosis who require more intensive monitoring for decompensation or future therapies preventing disease progression.

  8. Host Genetics Predict Clinical Deterioration in HCV-Related Cirrhosis

    PubMed Central

    King, Lindsay Y.; Johnson, Kara B.; Zheng, Hui; Wei, Lan; Gudewicz, Thomas; Hoshida, Yujin; Corey, Kathleen E.; Ajayi, Tokunbo; Ufere, Nneka; Baumert, Thomas F.; Chan, Andrew T.; Tanabe, Kenneth K.; Fuchs, Bryan C.; Chung, Raymond T.

    2014-01-01

    Single nucleotide polymorphisms (SNPs) in the epidermal growth factor (EGF, rs4444903), patatin-like phospholipase domain-containing protein 3 (PNPLA3, rs738409) genes, and near the interleukin-28B (IL28B, rs12979860) gene are linked to treatment response, fibrosis, and hepatocellular carcinoma (HCC) in chronic hepatitis C. Whether these SNPs independently or in combination predict clinical deterioration in hepatitis C virus (HCV)-related cirrhosis is unknown. We genotyped SNPs in EGF, PNPLA3, and IL28B from liver tissue from 169 patients with biopsy-proven HCV cirrhosis. We estimated risk of clinical deterioration, defined as development of ascites, encephalopathy, variceal hemorrhage, HCC, or liver-related death using Cox proportional hazards modeling. During a median follow-up of 6.6 years, 66 of 169 patients experienced clinical deterioration. EGF non-AA, PNPLA3 non-CC, and IL28B non-CC genotypes were each associated with increased risk of clinical deterioration in age, sex, and race-adjusted analysis. Only EGF non-AA genotype was independently associated with increased risk of clinical deterioration (hazard ratio [HR] 2.87; 95% confidence interval [CI] 1.31–6.25) after additionally adjusting for bilirubin, albumin, and platelets. Compared to subjects who had 0–1 unfavorable genotypes, the HR for clinical deterioration was 1.79 (95%CI 0.96–3.35) for 2 unfavorable genotypes and 4.03 (95%CI 2.13–7.62) for unfavorable genotypes for all three loci (Ptrend<0.0001). In conclusion, among HCV cirrhotics, EGF non-AA genotype is independently associated with increased risk for clinical deterioration. Specific PNPLA3 and IL28B genotypes also appear to be associated with clinical deterioration. These SNPs have potential to identify patients with HCV-related cirrhosis who require more intensive monitoring for decompensation or future therapies preventing disease progression. PMID:25504078

  9. A review of statistical updating methods for clinical prediction models.

    PubMed

    Su, Ting-Li; Jaki, Thomas; Hickey, Graeme L; Buchan, Iain; Sperrin, Matthew

    2016-07-26

    A clinical prediction model is a tool for predicting healthcare outcomes, usually within a specific population and context. A common approach is to develop a new clinical prediction model for each population and context; however, this wastes potentially useful historical information. A better approach is to update or incorporate the existing clinical prediction models already developed for use in similar contexts or populations. In addition, clinical prediction models commonly become miscalibrated over time, and need replacing or updating. In this article, we review a range of approaches for re-using and updating clinical prediction models; these fall in into three main categories: simple coefficient updating, combining multiple previous clinical prediction models in a meta-model and dynamic updating of models. We evaluated the performance (discrimination and calibration) of the different strategies using data on mortality following cardiac surgery in the United Kingdom: We found that no single strategy performed sufficiently well to be used to the exclusion of the others. In conclusion, useful tools exist for updating existing clinical prediction models to a new population or context, and these should be implemented rather than developing a new clinical prediction model from scratch, using a breadth of complementary statistical methods. © The Author(s) 2016.

  10. Predictability of Biogeochemical Responses in Engineered Watersheds

    NASA Astrophysics Data System (ADS)

    Yaeger, M. A.; Voepel, H. E.; Basu, N. B.; Rao, P. C.; Donner, S. D.; Packman, A. I.

    2009-12-01

    Examining the impacts of large-scale human modifications of watersheds (e.g., land-use intensification for food production; hydrologic modification through extensive tile-drainage, etc.) on the hydrologic and biogeochemical responses, and ecological impacts at various scales has been the focus of monitoring and modeling studies over the past two decades. Complex interactions between hydrology and biogeochemistry and the need to predict responses across scales has led to the development of detailed process-based models that are computationally intensive and calibration-dependent. Our overall hypothesis is that human modifications and intensive management of these watersheds have led to more predictable responses, which are typical of engineered, less-complex systems rather than natural, complex systems. We examined monitoring data for nitrogen, phosphorous, silica and chloride in 25 large watersheds (10,000 km2 to 500,000 km2) in the Mississippi River Basin. This sparse dataset was complemented with nitrogen cycling and hydrology output from a whole-basin terrestrial and aquatic modeling system (IBIS-THMB). These sub-basins have diverse land uses, although agriculture still dominates (from ~30% to ~80%). Despite diversity in soils, geology, rainfall patterns, and land use, a linear relationship was observed between the annual cumulative discharge (Q; m3/yr) and the measured nitrate load (L; kg/yr). The slopes of these linear L-Q plots represent the flow-weighted annual average concentrations (Cf), and a linear L-Q relationship indicates an apparent “chemostatic” response of these large watersheds. Analysis of Mississippi River monitoring data for nitrate and IBIS-THMB simulations revealed that Cf is a strong function of land-use (eg, percent corn) that defines the chemical input function. The scatter around the L-Q plots was small for “endogenous” (generated from internal sources) solutes (eg, silica), intermediate for “hybrid” (contributions from both

  11. Prediction of higher cost of antiretroviral therapy (ART) according to clinical complexity. A validated clinical index.

    PubMed

    Velasco, Cesar; Pérez, Inaki; Podzamczer, Daniel; Llibre, Josep Maria; Domingo, Pere; González-García, Juan; Puig, Inma; Ayala, Pilar; Martín, Mayte; Trilla, Antoni; Lázaro, Pablo; Gatell, Josep Maria

    2016-03-01

    The financing of antiretroviral therapy (ART) is generally determined by the cost incurred in the previous year, the number of patients on treatment, and the evidence-based recommendations, but not the clinical characteristics of the population. To establish a score relating the cost of ART and patient clinical complexity in order to understand the costing differences between hospitals in the region that could be explained by the clinical complexity of their population. Retrospective analysis of patients receiving ART in a tertiary hospital between 2009 and 2011. Factors potentially associated with a higher cost of ART were assessed by bivariate and multivariate analysis. Two predictive models of "high-cost" were developed. The normalized estimated (adjusted for the complexity scores) costs were calculated and compared with the normalized real costs. In the Hospital Index, 631 (16.8%) of the 3758 patients receiving ART were responsible for a "high-cost" subgroup, defined as the highest 25% of spending on ART. Baseline variables that were significant predictors of high cost in the Clinic-B model in the multivariate analysis were: route of transmission of HIV, AIDS criteria, Spanish nationality, year of initiation of ART, CD4+ lymphocyte count nadir, and number of hospital admissions. The Clinic-B score ranged from 0 to 13, and the mean value (5.97) was lower than the overall mean value of the four hospitals (6.16). The clinical complexity of the HIV patient influences the cost of ART. The Clinic-B and Clinic-BF scores predicted patients with high cost of ART and could be used to compare and allocate costs corrected for the patient clinical complexity. Copyright © 2015 Elsevier España, S.L.U. y Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

  12. Clinical predictors of therapeutic response to antipsychotics in schizophrenia.

    PubMed

    Carbon, Maren; Correll, Christoph U

    2014-12-01

    The search for clinical outcome predictors for schizophrenia is as old as the field of psychiatry. However, despite a wealth of large, longitudinal studies into prognostic factors, only very few clinically useful outcome predictors have been identified. The goal of future treatment is to either affect modifiable risk factors, or use nonmodifiable factors to parse patients into therapeutically meaningful subgroups. Most clinical outcome predictors are nonspecific and/or nonmodifiable. Nonmodifiable predictors for poor odds of remission include male sex, younger age at disease onset, poor premorbid adjustment, and severe baseline psychopathology. Modifiable risk factors for poor therapeutic outcomes that clinicians can act upon include longer duration of untreated illness, nonadherence to antipsychotics, comorbidities (especially substance-use disorders), lack of early antipsychotic response, and lack of improvement with non-clozapine antipsychotics, predicting clozapine response. It is hoped that this limited capacity for prediction will improve as pathophysiological understanding increases and/or new treatments for specific aspects of schizophrenia become available.

  13. Extended RAS Gene Mutation Testing in Metastatic Colorectal Carcinoma to Predict Response to Anti-Epidermal Growth Factor Receptor Monoclonal Antibody Therapy: American Society of Clinical Oncology Provisional Clinical Opinion Update 2015.

    PubMed

    Allegra, Carmen J; Rumble, R Bryan; Hamilton, Stanley R; Mangu, Pamela B; Roach, Nancy; Hantel, Alexander; Schilsky, Richard L

    2016-01-10

    An American Society of Clinical Oncology Provisional Clinical Opinion (PCO) offers timely clinical direction after publication or presentation of potentially practice-changing data from major studies. This PCO update addresses the utility of extended RAS gene mutation testing in patients with metastatic colorectal cancer (mCRC) to detect resistance to anti-epidermal growth factor receptor (EGFR) monoclonal antibody (MoAb) therapy. Recent results from phase II and III clinical trials in mCRC demonstrate that patients whose tumors harbor RAS mutations in exons 2 (codons 12 and 13), 3 (codons 59 and 61), and 4 (codons 117 and 146) are unlikely to benefit from therapy with MoAbs directed against EGFR, when used as monotherapy or combined with chemotherapy. In addition to the evidence reviewed in the original PCO, 11 systematic reviews with meta-analyses, two retrospective analyses, and two health technology assessments based on a systematic review were obtained. These evaluated the outcomes for patients with mCRC with no mutation detected or presence of mutation in additional exons in KRAS and NRAS. PCO: All patients with mCRC who are candidates for anti-EGFR antibody therapy should have their tumor tested in a Clinical Laboratory Improvement Amendments-certified laboratory for mutations in both KRAS and NRAS exons 2 (codons 12 and 13), 3 (codons 59 and 61), and 4 (codons 117 and 146). The weight of current evidence indicates that anti-EGFR MoAb therapy should only be considered for treatment of patients whose tumor is determined to not have mutations detected after such extended RAS testing. © 2015 by American Society of Clinical Oncology.

  14. Serum immune responses predict rapid disease progression among children with Crohn's disease: immune responses predict disease progression.

    PubMed

    Dubinsky, Marla C; Lin, Ying-Chao; Dutridge, Debra; Picornell, Yoana; Landers, Carol J; Farrior, Sharmayne; Wrobel, Iwona; Quiros, Antonio; Vasiliauskas, Eric A; Grill, Bruce; Israel, David; Bahar, Ron; Christie, Dennis; Wahbeh, Ghassan; Silber, Gary; Dallazadeh, Saied; Shah, Praful; Thomas, Danny; Kelts, Drew; Hershberg, Robert M; Elson, Charles O; Targan, Stephan R; Taylor, Kent D; Rotter, Jerome I; Yang, Huiying

    2006-02-01

    Crohn's disease (CD) is a heterogeneous disorder characterized by diverse clinical phenotypes. Childhood-onset CD has been described as a more aggressive phenotype. Genetic and immune factors may influence disease phenotype and clinical course. We examined the association of immune responses to microbial antigens with disease behavior and prospectively determined the influence of immune reactivity on disease progression in pediatric CD patients. Sera were collected from 196 pediatric CD cases and tested for immune responses: anti-I2, anti-outer membrane protein C (anti-OmpC), anti-CBir1 flagellin (anti-CBir1), and anti-Saccharomyces-cerevisiae (ASCA) using ELISA. Associations between immune responses and clinical phenotype were evaluated. Fifty-eight patients (28%) developed internal penetrating and/or stricturing (IP/S) disease after a median follow-up of 18 months. Both anti-OmpC (p < 0.0006) and anti-I2 (p < 0.003) were associated with IP/S disease. The frequency of IP/S disease increased with increasing number of immune responses (p trend = 0.002). The odds of developing IP/S disease were highest in patients positive for all four immune responses (OR (95% CI): 11 (1.5-80.4); p = 0.03). Pediatric CD patients positive for > or =1 immune response progressed to IP/S disease sooner after diagnosis as compared to those negative for all immune responses (p < 0.03). The presence and magnitude of immune responses to microbial antigens are significantly associated with more aggressive disease phenotypes among children with CD. This is the first study to prospectively demonstrate that the time to develop a disease complication in children is significantly faster in the presence of immune reactivity, thereby predicting disease progression to more aggressive disease phenotypes among pediatric CD patients.

  15. Serum Immune Responses Predict Rapid Disease Progression among Children with Crohn’s Disease: Immune Responses Predict Disease Progression

    PubMed Central

    Dubinsky, Marla C.; Lin, Ying-Chao; Dutridge, Debra; Picornell, Yoana; Landers, Carol J.; Farrior, Sharmayne; Wrobel, Iwona; Quiros, Antonio; Vasiliauskas, Eric A.; Grill, Bruce; Israel, David; Bahar, Ron; Christie, Dennis; Wahbeh, Ghassan; Silber, Gary; Dallazadeh, Saied; Shah, Praful; Thomas, Danny; Kelts, Drew; Hershberg, Robert M.; Elson, Charles O.; Targan, Stephan R.; Taylor, Kent D.; Rotter, Jerome I.; Yang, Huiying

    2007-01-01

    BACKGROUND AND AIM Crohn’s disease (CD) is a heterogeneous disorder characterized by diverse clinical phenotypes. Childhood-onset CD has been described as a more aggressive phenotype. Genetic and immune factors may influence disease phenotype and clinical course. We examined the association of immune responses to microbial antigens with disease behavior and prospectively determined the influence of immune reactivity on disease progression in pediatric CD patients. METHODS Sera were collected from 196 pediatric CD cases and tested for immune responses: anti-I2, anti-outer membrane protein C (anti-OmpC), anti-CBir1 flagellin (anti-CBir1), and anti-Saccharomyces-cerevisiae (ASCA) using ELISA. Associations between immune responses and clinical phenotype were evaluated. RESULTS Fifty-eight patients (28%) developed internal penetrating and/or stricturing (IP/S) disease after a median follow-up of 18 months. Both anti-OmpC (p < 0.0006) and anti-I2 (p < 0.003) were associated with IP/S disease. The frequency of IP/S disease increased with increasing number of immune responses (p trend = 0.002). The odds of developing IP/S disease were highest in patients positive for all four immune responses (OR (95% CI): 11 (1.5–80.4); p = 0.03). Pediatric CD patients positive for ≥1 immune response progressed to IP/S disease sooner after diagnosis as compared to those negative for all immune responses (p < 0.03). CONCLUSIONS The presence and magnitude of immune responses to microbial antigens are significantly associated with more aggressive disease phenotypes among children with CD. This is the first study to prospectively demonstrate that the time to develop a disease complication in children is significantly faster in the presence of immune reactivity, thereby predicting disease progression to more aggressive disease phenotypes among pediatric CD patients. PMID:16454844

  16. Predicting Methylphenidate Response in ADHD Using Machine Learning Approaches.

    PubMed

    Kim, Jae-Won; Sharma, Vinod; Ryan, Neal D

    2015-05-10

    There are no objective, biological markers that can robustly predict methylphenidate response in attention deficit hyperactivity disorder. This study aimed to examine whether applying machine learning approaches to pretreatment demographic, clinical questionnaire, environmental, neuropsychological, neuroimaging, and genetic information can predict therapeutic response following methylphenidate administration. The present study included 83 attention deficit hyperactivity disorder youth. At baseline, parents completed the ADHD Rating Scale-IV and Disruptive Behavior Disorder rating scale, and participants undertook the continuous performance test, Stroop color word test, and resting-state functional MRI scans. The dopamine transporter gene, dopamine D4 receptor gene, alpha-2A adrenergic receptor gene (ADRA2A) and norepinephrine transporter gene polymorphisms, and blood lead and urine cotinine levels were also measured. The participants were enrolled in an 8-week, open-label trial of methylphenidate. Four different machine learning algorithms were used for data analysis. Support vector machine classification accuracy was 84.6% (area under receiver operating characteristic curve 0.84) for predicting methylphenidate response. The age, weight, ADRA2A MspI and DraI polymorphisms, lead level, Stroop color word test performance, and oppositional symptoms of Disruptive Behavior Disorder rating scale were identified as the most differentiating subset of features. Our results provide preliminary support to the translational development of support vector machine as an informative method that can assist in predicting treatment response in attention deficit hyperactivity disorder, though further work is required to provide enhanced levels of classification performance. © The Author 2015. Published by Oxford University Press on behalf of CINP.

  17. Suction blister grafting for vitiligo: efficacy and clinical predictive factors.

    PubMed

    Gou, Darlene; Currimbhoy, Sharif; Pandya, Amit G

    2015-05-01

    Suction blister epidermal grafting (SBEG) is a well-established treatment modality for vitiligo, but predictive factors for outcomes are not well characterized. To determine the efficacy and predictive variables for response to SBEG in patients with vitiligo. A retrospective single-center review of all cases treated with SBEG was performed. Repigmentation was assessed by 2 independent reviewers by assessing pigment spread of grafts during the postoperative period. Repigmentation rates were then compared with patient demographics and transplant location. A total of 28 patients were enrolled in this study. The total number of grafts was 129, of which 86.8% (112/129) survived. Highest rate of graft survival was seen in patients younger than 20 years (100%) and the lowest in patients older than 40 years (75%-78%). Repigmentation was seen in 68% of patients. The highest degree of pigment spread was on the neck (283%) and face (231%), whereas the hands and feet had the least response (119%). Blister grafting is successful in most patients with vitiligo, with a high graft survival rate; however, the degree of pigment spread is variable and depends on clinical characteristics of the patient and graft site.

  18. Clinical and EEG response to anticonvulsants in neonatal seizures.

    PubMed Central

    Connell, J; Oozeer, R; de Vries, L; Dubowitz, L M; Dubowitz, V

    1989-01-01

    During a two year period prospective continuous electroencephalographic (EEG) monitoring of 275 infants identified seizure activity in 55 cases, 31 of whom were treated with anticonvulsant drugs on clinical grounds. EEG and clinical response was complete in only two and equivocal in another six. Clinical response with persistent EEG seizures occurred in 13 and neither clinical nor EEG response in 10. There was no significant improvement in the generally poor neurological outcome compared with that in 24 infants whose seizures were not treated because of limited or absent clinical manifestations. Background EEG abnormality (as an index of associated cerebral dysfunction) was a guide to potential lack of response to anticonvulsant drugs; it was also predictive of subsequent clinical outcome irrespective of treatment. This study shows that commonly used anticonvulsant drugs (phenobarbitone, paraldehyde, phenytoin, and diazepam) have little effect on seizure control or neurological outcome in neonatal seizures associated with haemorrhagic, hypoxic, or ischaemic cerebral lesions. In view of the variable clinical appearance of EEG seizure activity, continuous EEG monitoring should be an essential feature of further study of neonatal anticonvulsant treatment. PMID:2730114

  19. Risk and the physics of clinical prediction.

    PubMed

    McEvoy, John W; Diamond, George A; Detrano, Robert C; Kaul, Sanjay; Blaha, Michael J; Blumenthal, Roger S; Jones, Steven R

    2014-04-15

    The current paradigm of primary prevention in cardiology uses traditional risk factors to estimate future cardiovascular risk. These risk estimates are based on prediction models derived from prospective cohort studies and are incorporated into guideline-based initiation algorithms for commonly used preventive pharmacologic treatments, such as aspirin and statins. However, risk estimates are more accurate for populations of similar patients than they are for any individual patient. It may be hazardous to presume that the point estimate of risk derived from a population model represents the most accurate estimate for a given patient. In this review, we exploit principles derived from physics as a metaphor for the distinction between predictions regarding populations versus patients. We identify the following: (1) predictions of risk are accurate at the level of populations but do not translate directly to patients, (2) perfect accuracy of individual risk estimation is unobtainable even with the addition of multiple novel risk factors, and (3) direct measurement of subclinical disease (screening) affords far greater certainty regarding the personalized treatment of patients, whereas risk estimates often remain uncertain for patients. In conclusion, shifting our focus from prediction of events to detection of disease could improve personalized decision-making and outcomes. We also discuss innovative future strategies for risk estimation and treatment allocation in preventive cardiology. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. Fluid bolus therapy: monitoring and predicting fluid responsiveness.

    PubMed

    Carsetti, Andrea; Cecconi, Maurizio; Rhodes, Andrew

    2015-10-01

    When a condition of hypoperfusion has been identified, clinicians must decide whether fluids may increase blood flow or whether other therapeutic approaches are needed. For this purpose, several tests and parameters have been introduced in clinical practice to predict fluid responsiveness and guide therapy. Fluid challenge is the gold standard test to assess the preload dependence of the patients. Moreover, several parameters and tests avoiding fluid administration are now available. Pulse pressure variation and stroke volume variation are based on heart-lung interaction and can be used to assess fluid responsiveness. These parameters have several limitations and can really be used in a limited number of critically ill patients. End-expiratory occlusion test and passive leg raising have been proposed to overcome these limitations. The aim of resuscitation is to increase blood flow and perfusion pressure. Dynamic arterial elastance has been recently proposed to predict the pressure response after fluid challenge in preload-dependent patients. Finally, the effects of volume expansion of hemodynamic parameters do not necessarily reach the microcirculation, which should also be assessed. Nowadays, several parameters are available to assess fluid responsiveness. Clinicians need to know all of them, with their limitations, without forgetting that the final aim of all therapies is to improve the microcirculation.

  1. Response Predicting LTCC Firing Shrinkage: A Response Surface Analysis Study

    SciTech Connect

    Girardi, Michael; Barner, Gregg; Lopez, Cristie; Duncan, Brent; Zawicki, Larry

    2009-02-25

    The Low Temperature Cofired Ceramic (LTCC) technology is used in a variety of applications including military/space electronics, wireless communication, MEMS, medical and automotive electronics. The use of LTCC is growing due to the low cost of investment, short development time, good electrical and mechanical properties, high reliability, and flexibility in design integration (3 dimensional (3D) microstructures with cavities are possible)). The dimensional accuracy of the resulting x/y shrinkage of LTCC substrates is responsible for component assembly problems with the tolerance effect that increases in relation to the substrate size. Response Surface Analysis was used to predict product shrinkage based on specific process inputs (metal loading, layer count, lamination pressure, and tape thickness) with the ultimate goal to optimize manufacturing outputs (NC files, stencils, and screens) in achieving the final product design the first time. Three (3) regression models were developed for the DuPont 951 tape system with DuPont 5734 gold metallization based on green tape thickness.

  2. Prediction of Achievement in Clinical Pharmacy Courses

    ERIC Educational Resources Information Center

    Simon, Lee S.

    1978-01-01

    A study sought to identify student characteristics which account for academic achievement in clinical pharmacy courses. Preclinical grade point average was the best predictor. Subscales of the California Personality Inventory and the Myers-Briggs Type Indicator, work experience, sex, and age were the other predictor variables. (SW)

  3. Predicting Response to EGFR Inhibitors in Metastatic Colorectal Cancer: Current Practice and Future Directions

    PubMed Central

    Shankaran, Veena; Obel, Jennifer

    2010-01-01

    The identification of KRAS mutational status as a predictive marker of response to antibodies against the epidermal growth factor receptor (EGFR) has been one of the most significant and practice-changing recent advances in colorectal cancer research. Recently, data suggesting a potential role for other markers (including BRAF mutations, loss of phosphatase and tensin homologue deleted on chromosome ten expression, and phosphatidylinositol-3-kinase–AKT pathway mutations) in predicting response to anti-EGFR therapy have emerged. Ongoing clinical trials and correlative analyses are essential to definitively identify predictive markers and develop therapeutic strategies for patients who may not derive benefit from anti-EGFR therapy. This article reviews recent clinical trials supporting the predictive role of KRAS, recent changes to clinical guidelines and pharmaceutical labeling, investigational predictive molecular markers, and newer clinical trials targeting patients with mutated KRAS. PMID:20133499

  4. DIAGNOSTICS ALGORITHM OF DIABETIC POLYNEUROPATHY IN PREDICTION OF CLINICAL COURSE.

    PubMed

    Popova, T E; Tappahov, A A; Shnaider, N A; Petrova, M M; Nikolaeva, T Y; Konnikova, E E; Kozhevnikov, A A; Ammosov, V G; Vinokurova, N E

    2015-01-01

    To estimate the importance of new algorithm introducing of PDP diagnostics in practice of NEFU medical institute Clinic in detection of severity level and predicting of clinical course. 50 people with sensory-motor PDP form among patients with 2 type diabetes were examined on the basis of Clinic of NEFU medical institute. Patients have been divided into 2 groups by disease duration: the first groups were patients with duration of disease till 10 years, the second group--more than 10 years. Diagnostics methods: clinical neurologic, neurophysiological. Patients underwent polymodal sensitivity analysis, computer pallesteziometry, stabilometry, electroneuromyography. The dependence of clinical neurophysiological PDP parametres from severity of the duration of type 2 diabetes has been revealed. Thus, dependence of clinical-neurophysiological parametres of PDP severity from the duration of 2 type diabetes has been revealed. The new algorithm raised efficacy of clinical-neurophysiological PDP diagnostics and helped the predicting of the clinical course.

  5. Statistical and practical considerations for clinical evaluation of predictive biomarkers.

    PubMed

    Polley, Mei-Yin C; Freidlin, Boris; Korn, Edward L; Conley, Barbara A; Abrams, Jeffrey S; McShane, Lisa M

    2013-11-20

    Predictive biomarkers to guide therapy for cancer patients are a cornerstone of precision medicine. Discussed herein are considerations regarding the design and interpretation of such predictive biomarker studies. These considerations are important for both planning and interpreting prospective studies and for using specimens collected from completed randomized clinical trials. Specific issues addressed are differentiation between qualitative and quantitative predictive effects, challenges due to sample size requirements for predictive biomarker assessment, and consideration of additional factors relevant to clinical utility assessment, such as toxicity and cost of new therapies as well as costs and potential morbidities associated with routine use of biomarker-based tests.

  6. Accurate assessment and prediction of noise in clinical CT images.

    PubMed

    Tian, Xiaoyu; Samei, Ehsan

    2016-01-01

    The objectives of this study were (a) to devise a technique for measuring quantum noise in clinical body computed tomography (CT) images and (b) to develop a model for predicting that noise with high accuracy. The study included 83 clinical image sets at two dose levels (clinical and 50% reduced dose levels). The quantum noise in clinical images was measured by subtracting sequential slices and filtering out edges. Noise was then measured in the resultant uniform area. The noise measurement technique was validated using 17 clinical image cases and a turkey phantom. With a validated method to measure noise in clinical images, this noise was predicted by establishing the correlation between water-equivalent diameter (Dw) and noise in a variable-sized phantom and ascribing a noise level to the patient based on Dw estimated from CT image. The accuracy of this prediction model was validated using 66 clinical image sets. The error in noise measurement was within 1.5 HU across two reconstruction algorithms. In terms of noise prediction, across the 83 clinical image sets, the average discrepancies between predicted and measured noise were 6.9% and 6.6% for adaptive statistical iterative reconstruction and filtered back projection reconstruction, respectively. This study proposed a practically applicable method to assess quantum noise in clinical images. The image-based measurement technique enables automatic quality control monitoring of image noise in clinical practice. Further, a phantom-based model can accurately predict quantum noise level in patient images. The prediction model can be used to quantitatively optimize individual protocol to achieve targeted noise level in clinical images.

  7. Predicting response to antimicrobial therapy in children with acute sinusitis

    PubMed Central

    Shaikh, Nader; Wald, Ellen R.; Jeong, Jong H.; Kurs-Lasky, Marcia; Bowen, A’Delbert; Flom, Lynda L.; Hoberman, Alejandro

    2014-01-01

    Objective To determine prognostic factors that independently predict response to antimicrobial therapy in children with acute sinusitis. Study design 206 children meeting a priori clinical criteria for acute sinusitis who were given antimicrobial therapy by their primary care provider were included. The severity of symptoms in the 8 to 12 days after treatment was initiated was followed using a validated scale. We examined the univariate and multivariate association between factors present at the time of diagnosis (symptoms, signs, nasopharyngeal culture result, radiograph results) and time to resolution of symptoms. This study was conducted 8 to 10 years after 7-valent pneumococcal conjugate vaccination was introduced, but before introduction of the 13-valent pneumococcal conjugate vaccination. Results Children with proven nasopharyngeal colonization with Streptococcus pneumoniae improved more rapidly (6.5 vs. 8.5 median days to symptom resolution) than those who were not colonized with S. pneumoniae. Age and radiograph findings did not predict time to symptom resolution. Conclusions In children with acute sinusitis, proven nasopharyngeal colonization with S. pneumoniae at presentation independently predicted time to symptom resolution. Future randomized, placebo-controlled trials could investigate the usefulness of testing for the presence of nasopharyngeal pathogens as a predictor of response to treatment. PMID:24367985

  8. Predicting success of pharmacy students in basic science and clinical clerkship courses.

    PubMed

    Kimberlin, C L; Hadsall, R S; Gourley, D R; Benedict, L K

    1983-04-01

    A number of studies on the ability of admissions variables to predict success in pharmacy schools have examined only success in the first professional year, which typically consists primarily of basic science courses. This study examined not only grades in basic science courses but also performance on clinical clerkships, for two classes of students. It also examined the ability of various personality variables to predict performance in clinical and basic science coursework. Previous grade point average (GPA) was the best single predictor of performance. In one class, the personality variable of Responsibility best predicted clinical clerkship performance. However, it only accounted for 13 percent of the variance in clerkship grades. Pharmacy College Admission Test (PCAT) Biology and PCAT Verbal Ability scores added to the predictive ability of previous GPA in one class, but none of the PCAT scales entered a prediction equation for the other class. The limitations on our ability to predict, with any consistency, academic performance in pharmacy school is discussed.

  9. Can colchicine response be predicted in familial Mediterranean fever patients?

    PubMed

    Özçakar, Zeynep Birsin; Elhan, Atilla H; Yalçınkaya, Fatoş

    2014-10-01

    The aims of this study were to explore whether the demographic and clinical features of paediatric familial Mediterranean fever (FMF) patients with different colchicine response vary or not and to determine whether colchicine response can be predicted in FMF patients. Files of patients who have been on colchicine therapy for at least 6 months were retrospectively evaluated. Patients were divided into two groups: group I included patients with no attacks after colchicine and group II comprised patients with ongoing attacks. Thereafter group II was further divided into two groups according to the reduction rate of attack frequency: group IIA (>50%) and group IIB (≤50%). The study group comprised 221 FMF patients (116 females, 105 males). There were 131 patients in group I and 90 patients in group II (54 in group IIA and 36 in group IIB). Leg pain and M694V homozygosity were more frequent in group II (P < 0.05). Final colchicine doses, disease severity scores and number of patients with elevated acute phase reactant levels (attack-free period) were significantly higher and colchicine compliance was lower in group II when compared with group I (P < 0.05). Erysipelas-like erythema (ELE), leg pain and protracted arthritis/protracted febrile myalgia/vasculitis were more frequently detected in group IIB (P < 0.05). Colchicine response is excellent in the majority of FMF patients, however, colchicine unresponsiveness cannot be predicted easily at onset. More rarely encountered clinical findings such as ELE, leg pain and protracted complaints and M694V homozygosity may be a clue for less colchicine response. © The Author 2014. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  10. Clinical prediction models for aneurysmal subarachnoid hemorrhage: a systematic review.

    PubMed

    Jaja, Blessing N R; Cusimano, Michael D; Etminan, Nima; Hanggi, Daniel; Hasan, David; Ilodigwe, Don; Lantigua, Hector; Le Roux, Peter; Lo, Benjamin; Louffat-Olivares, Ada; Mayer, Stephan; Molyneux, Andrew; Quinn, Audrey; Schweizer, Tom A; Schenk, Thomas; Spears, Julian; Todd, Michael; Torner, James; Vergouwen, Mervyn D I; Wong, George K C; Singh, Jeff; Macdonald, R Loch

    2013-02-01

    Clinical prediction models can enhance clinical decision-making and research. However, available prediction models in aneurysmal subarachnoid hemorrhage (aSAH) are rarely used. We evaluated the methodological validity of SAH prediction models and the relevance of the main predictors to identify potentially reliable models and to guide future attempts at model development. We searched the EMBASE, MEDLINE, and Web of Science databases from January 1995 to June 2012 to identify studies that reported clinical prediction models for mortality and functional outcome in aSAH. Validated methods were used to minimize bias. Eleven studies were identified; 3 developed models from datasets of phase 3 clinical trials, the others from single hospital records. The median patient sample size was 340 (interquartile range 149-733). The main predictors used were age (n = 8), Fisher grade (n = 6), World Federation of Neurological Surgeons grade (n = 5), aneurysm size (n = 5), and Hunt and Hess grade (n = 3). Age was consistently dichotomized. Potential predictors were prescreened by univariate analysis in 36 % of studies. Only one study was penalized for model optimism. Details about model development were often insufficiently described and no published studies provided external validation. While clinical prediction models for aSAH use a few simple predictors, there are substantial methodological problems with the models and none have had external validation. This precludes the use of existing models for clinical or research purposes. We recommend further studies to develop and validate reliable clinical prediction models for aSAH.

  11. Validating a Clinical Prediction Rule for Ventricular Shunt Malfunction.

    PubMed

    Boyle, Tehnaz P; Kimia, Amir A; Nigrovic, Lise E

    2017-01-17

    This study aims to validate a published ventricular shunt clinical prediction rule for the identification of children at low risk for ventricular shunt malfunction based on the absence of 3 high-risk clinical predictors (irritability, nausea or vomiting, and headache). We identified children aged 21 years and younger with a ventricular shunt who presented between 2010 and 2013 to a single pediatric emergency department (ED) for evaluation of potential shunt malfunction. We defined a ventricular shunt malfunction as obstruction to cerebrospinal fluid flow requiring operative neurosurgical intervention within 72 hours of initial ED evaluation. We applied this ventricular shunt clinical prediction rule to the study population and report the test characteristics. We identified 755 ED visits for 294 children with potential ventricular shunt malfunction. Of these encounters, 146 (19%; 95% confidence interval [CI], 17%-22%) had a ventricular shunt malfunction. The ventricular shunt clinical prediction rule had a sensitivity of 99% (95% CI, 94%-100%), specificity of 7% (95% CI, 5%-9%), and negative predictive value of 95% (95% CI, 82%-99%). Two children with a ventricular shunt malfunction were misclassified as low risk by this clinical prediction rule. Ventricular shunt malfunctions were common. Although children classified as low risk by the ventricular shunt clinical prediction rule were less likely to have a shunt malfunction, routine neuroimaging may still be required because exclusion of ventricular shunt malfunction may be difficult on clinical grounds alone.

  12. Personality predicts brain responses to cognitive demands.

    PubMed

    Kumari, Veena; ffytche, Dominic H; Williams, Steven C R; Gray, Jeffrey A

    2004-11-24

    Eysenck (1981) proposed that the personality dimension of introversion- extraversion (E) reflects individual differences in a cortical arousal system modulated by reticulothalamic- cortical pathways: it is chronically more active in introverts relative to extraverts and influences cognitive performance in interaction with task parameters. A circuit with connections to this system, including the dorsolateral prefrontal cortex (DLPFC) and anterior cingulate (AC) cortex, has been identified in studies applying functional magnetic resonance imaging (fMRI) to a broad range of cognitive tasks. We examined the influence of E, assessed with the Eysenck Personality Questionnaire-Revised (Eysenck and Eysenck, 1991), in fMRI activity during an "n-back" task involving four memory loads (0-, 1-, 2-, and 3-back) and a rest condition in healthy men. To confirm the specificity of E effects, we also examined the effects of neuroticism and psychoticism (P) scores. We observed that, as predicted by Eysenck's model, the higher the E score, the greater the change in fMRI signal from rest to the 3-back condition in the DLPFC and AC. In addition, E scores were negatively associated with resting fMRI signals in the thalamus and Broca's area extending to Wernicke's area, supporting the hypothesized (negative) relationship between E and resting arousal. P scores negatively correlated with resting fMRI signal in the globus pallidus-putamen, extending previous findings of a negative relationship of schizotypy to striatal activity seen with older neuroimaging modalities to fMRI. These observations suggest that individual differences affect brain responses during cognitive activity and at rest and provide evidence for the hypothesized neurobiological basis of personality.

  13. Predicting response to treatment in chronic inflammatory demyelinating polyradiculoneuropathy.

    PubMed

    Chan, Y-C; Allen, D C; Fialho, D; Mills, K R; Hughes, R A C

    2006-01-01

    To discover whether Inflammatory Neuropathy Cause and Treatment Group (INCAT) electrophysiological criteria for demyelinating neuropathy predict response to immunotherapy in chronic inflammatory demyelinating polyradiculoneuropathy (CIDP). This was a retrospective case note study of patients who had attended Guy's Hospital Peripheral Nerve Clinic between January 2001 and March 2004, been diagnosed as having CIDP, and given treatment with corticosteroids, intravenous immunoglobulin (IVIg), or plasma exchange (PE). Patients' nerve conduction studies (NCS) were reviewed for evidence of demyelination and whether the abnormalities fulfilled modified INCAT electrophysiological criteria. Patients whose NCS fulfilled the criteria were assigned to the neurophysiologically definite CIDP group, while those that did not were labelled as neurophysiologically probable CIDP. Responses to any of the three immunotherapy agents were compared between the two groups. Out of 50 patients, 27 (54%) were classified as neurophysiologically definite and 23 (46%) as neurophysiologically probable CIDP patients. Twenty (74%) neurophysiologically definite and 17 (73.9%) neurophysiologically probable CIDP patients responded to treatment. INCAT electrophysiological criteria did not predict a higher rate of response to immunotherapy. Neurophysiologically probable CIDP patients should be given a trial of immunotherapy.

  14. Predicting response to treatment in chronic inflammatory demyelinating polyradiculoneuropathy

    PubMed Central

    Chan, Y‐C; Allen, D C; Fialho, D; Mills, K R; Hughes, R A C

    2006-01-01

    Objective To discover whether Inflammatory Neuropathy Cause and Treatment Group (INCAT) electrophysiological criteria for demyelinating neuropathy predict response to immunotherapy in chronic inflammatory demyelinating polyradiculoneuropathy (CIDP). Methods This was a retrospective case note study of patients who had attended Guy's Hospital Peripheral Nerve Clinic between January 2001 and March 2004, been diagnosed as having CIDP, and given treatment with corticosteroids, intravenous immunoglobulin (IVIg), or plasma exchange (PE). Patients' nerve conduction studies (NCS) were reviewed for evidence of demyelination and whether the abnormalities fulfilled modified INCAT electrophysiological criteria. Patients whose NCS fulfilled the criteria were assigned to the neurophysiologically definite CIDP group, while those that did not were labelled as neurophysiologically probable CIDP. Responses to any of the three immunotherapy agents were compared between the two groups. Results Out of 50 patients, 27 (54%) were classified as neurophysiologically definite and 23 (46%) as neurophysiologically probable CIDP patients. Twenty (74%) neurophysiologically definite and 17 (73.9%) neurophysiologically probable CIDP patients responded to treatment. Conclusions INCAT electrophysiological criteria did not predict a higher rate of response to immunotherapy. Neurophysiologically probable CIDP patients should be given a trial of immunotherapy. PMID:16361609

  15. Roles and Responsibilities of Clinical Nurse Researchers.

    ERIC Educational Resources Information Center

    Kirchhoff, Karin T.; Mateo, Magdelena A.

    1996-01-01

    A follow-up survey of 142 nurse researchers employed in clinical settings (75% response) found that fewer than half have a budget, 52% have secretarial support, 82% have a research committee, and 71% report to the chief nurse executive. Although their positions were primarily research, the average time spent on research was 50%. (JOW)

  16. [Clinical Responses To Infants and Families.

    ERIC Educational Resources Information Center

    Fenichel, Emily, Ed.

    1995-01-01

    This journal issue focuses on family service clinical responses to infants and families. In "The Therapeutic Relationship as Human Connectedness," Jeree H. Pawl stresses the importance of caregivers creating in children the sense and experience of human connectedness that arises from the feeling of existing in the mind of someone…

  17. Responsive Assessment: Assessing Student Nurses' Clinical Competence.

    ERIC Educational Resources Information Center

    Neary, Mary

    2001-01-01

    A study involving 300 nursing students, 155 nurse practitioners, and 80 assessors tested a model of responsive assessment that includes identification of learning needs and potential, assignment to suitable placements, continuous assessment of clinical practice and patient care, and alignment of teaching and assessment with patient needs and…

  18. Predictive data mining in clinical medicine: current issues and guidelines.

    PubMed

    Bellazzi, Riccardo; Zupan, Blaz

    2008-02-01

    The widespread availability of new computational methods and tools for data analysis and predictive modeling requires medical informatics researchers and practitioners to systematically select the most appropriate strategy to cope with clinical prediction problems. In particular, the collection of methods known as 'data mining' offers methodological and technical solutions to deal with the analysis of medical data and construction of prediction models. A large variety of these methods requires general and simple guidelines that may help practitioners in the appropriate selection of data mining tools, construction and validation of predictive models, along with the dissemination of predictive models within clinical environments. The goal of this review is to discuss the extent and role of the research area of predictive data mining and to propose a framework to cope with the problems of constructing, assessing and exploiting data mining models in clinical medicine. We review the recent relevant work published in the area of predictive data mining in clinical medicine, highlighting critical issues and summarizing the approaches in a set of learned lessons. The paper provides a comprehensive review of the state of the art of predictive data mining in clinical medicine and gives guidelines to carry out data mining studies in this field. Predictive data mining is becoming an essential instrument for researchers and clinical practitioners in medicine. Understanding the main issues underlying these methods and the application of agreed and standardized procedures is mandatory for their deployment and the dissemination of results. Thanks to the integration of molecular and clinical data taking place within genomic medicine, the area has recently not only gained a fresh impulse but also a new set of complex problems it needs to address.

  19. Genetic Markers Predict Primary Non-Response and Durable Response To Anti-TNF Biologic Therapies in Crohn's Disease.

    PubMed

    Barber, Grant E; Yajnik, Vijay; Khalili, Hamed; Giallourakis, Cosmas; Garber, John; Xavier, Ramnik; Ananthakrishnan, Ashwin N

    2016-12-01

    One-fifth of patients with Crohn's disease (CD) are primary non-responders to anti-tumor necrosis factor (anti-TNF) therapy, and an estimated 10-15% will fail therapy annually. Little is known about the genetics of response to anti-TNF therapy. The aim of our study was to identify genetic factors associated with primary non-response (PNR) and loss of response to anti-TNFs in CD. From a prospective registry, we characterized the response of 427 CD patients to their first anti-TNF therapy. Patients were designated as achieving primary response, durable response, and non-durable response based on clinical, endoscopic, and radiologic criteria. Genotyping was performed on the Illumina Immunochip. Separate genetic scores based on presence of predictive genetic alleles were calculated for PNR and durable response and performance of clinical and genetics models were compared. From 359 patients, 36 were adjudged to have PNR (10%), 200 had durable response, and 74 had non-durable response. PNRs had longer disease duration and were more likely to be smokers. Fifteen risk alleles were associated with PNR. Patients with PNR had a significantly higher genetic risk score (GRS) (P =8 × 10(-12)). A combined clinical-genetic model more accurately predicted PNR when compared with a clinical only model (0.93 vs. 0.70, P <0.001). Sixteen distinct single nucleotide polymorphisms predicted durable response with a higher GRS (P =7 × 10(-13)). The GRSs for PNR and durable response were not mutually correlated, suggesting distinct mechanisms. Genetic risk alleles can predict primary non-response and durable response to anti-TNF therapy in CD.

  20. Which ante mortem clinical features predict progressive supranuclear palsy pathology?

    PubMed

    Respondek, Gesine; Kurz, Carolin; Arzberger, Thomas; Compta, Yaroslau; Englund, Elisabet; Ferguson, Leslie W; Gelpi, Ellen; Giese, Armin; Irwin, David J; Meissner, Wassilios G; Nilsson, Christer; Pantelyat, Alexander; Rajput, Alex; van Swieten, John C; Troakes, Claire; Josephs, Keith A; Lang, Anthony E; Mollenhauer, Brit; Müller, Ulrich; Whitwell, Jennifer L; Antonini, Angelo; Bhatia, Kailash P; Bordelon, Yvette; Corvol, Jean-Christophe; Colosimo, Carlo; Dodel, Richard; Grossman, Murray; Kassubek, Jan; Krismer, Florian; Levin, Johannes; Lorenzl, Stefan; Morris, Huw; Nestor, Peter; Oertel, Wolfgang H; Rabinovici, Gil D; Rowe, James B; van Eimeren, Thilo; Wenning, Gregor K; Boxer, Adam; Golbe, Lawrence I; Litvan, Irene; Stamelou, Maria; Höglinger, Günter U

    2017-07-01

    Progressive supranuclear palsy (PSP) is a neuropathologically defined disease presenting with a broad spectrum of clinical phenotypes. To identify clinical features and investigations that predict or exclude PSP pathology during life, aiming at an optimization of the clinical diagnostic criteria for PSP. We performed a systematic review of the literature published since 1996 to identify clinical features and investigations that may predict or exclude PSP pathology. We then extracted standardized data from clinical charts of patients with pathologically diagnosed PSP and relevant disease controls and calculated the sensitivity, specificity, and positive predictive value of key clinical features for PSP in this cohort. Of 4166 articles identified by the database inquiry, 269 met predefined standards. The literature review identified clinical features predictive of PSP, including features of the following 4 functional domains: ocular motor dysfunction, postural instability, akinesia, and cognitive dysfunction. No biomarker or genetic feature was found reliably validated to predict definite PSP. High-quality original natural history data were available from 206 patients with pathologically diagnosed PSP and from 231 pathologically diagnosed disease controls (54 corticobasal degeneration, 51 multiple system atrophy with predominant parkinsonism, 53 Parkinson's disease, 73 behavioral variant frontotemporal dementia). We identified clinical features that predicted PSP pathology, including phenotypes other than Richardson's syndrome, with varying sensitivity and specificity. Our results highlight the clinical variability of PSP and the high prevalence of phenotypes other than Richardson's syndrome. The features of variant phenotypes with high specificity and sensitivity should serve to optimize clinical diagnosis of PSP. © 2017 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

  1. Target Predictability, Sustained Attention, and Response Inhibition

    ERIC Educational Resources Information Center

    Carter, Leonie; Russell, Paul N.; Helton, William S.

    2013-01-01

    We examined whether the sustained attention to response task is a better measure of response inhibition or sustained attention. Participants performed a number detection task for 37.3 min using either a Sustained Attention to Response Task (SART; high Go low No-Go) or a more traditionally formatted vigilance task (TFT; high No-Go low Go) response…

  2. Target Predictability, Sustained Attention, and Response Inhibition

    ERIC Educational Resources Information Center

    Carter, Leonie; Russell, Paul N.; Helton, William S.

    2013-01-01

    We examined whether the sustained attention to response task is a better measure of response inhibition or sustained attention. Participants performed a number detection task for 37.3 min using either a Sustained Attention to Response Task (SART; high Go low No-Go) or a more traditionally formatted vigilance task (TFT; high No-Go low Go) response…

  3. Evaluating virulence of waterborne and clinical Aeromonas isolates using gene expression and mortality in neonatal mice followed by assessing cell culture's ability to predict virulence based on transcriptional response.

    PubMed

    Hayes, S L; Rodgers, M R; Lye, D J; Stelma, G N; McKinstry, C A; Malard, J M; Vesper, S J

    2007-10-01

    To assess the virulence of Aeromonas spp. using two models, a neonatal mouse assay and a mouse intestinal cell culture. After artificial infection with a variety of Aeromonas spp., mRNA extracts from the two models were processed and hydridized to murine microarrays to determine host gene response. Definition of virulence was determined based on host mRNA production in murine neonatal intestinal tissue and mortality of infected animals. Infections of mouse intestinal cell cultures were then performed to determine whether this simpler model system's mRNA responses correlated to neonatal results and therefore be predictive of virulence of Aeromonas spp. Virulent aeromonads up-regulated transcripts in both models including multiple host defense gene products (chemokines, regulation of transcription and apoptosis and cell signalling). Avirulent species exhibited little or no host response in neonates. Mortality results correlated well with both bacterial dose and average fold change of up-regulated transcripts in the neonatal mice. Cell culture results were less discriminating but showed promise as potentially being able to be predictive of virulence. Jun oncogene up-regulation in murine cell culture is potentially predictive of Aeromonas virulence. Having the ability to determine virulence of waterborne pathogens quickly would potentially assist public health officials to rapidly assess exposure risks.

  4. Clinical and Statistical Issues Related to Predicting Therapeutic Outcome.

    ERIC Educational Resources Information Center

    Ghiselli, William B.

    1983-01-01

    Studied predictability of therapeutic outcome of an alcoholism treatment program. Data analyzed by a mathematically oriented linear regression approach and by a clinically oriented retrospective parametric approach showed different predictors. Suggested that the parametric clinical approach be used to explain why therapy succeeded or failed.…

  5. Predicting oxygenator clinical performance from laboratory in-vitro testing.

    PubMed

    Griffith, K E; Vasquez, M R; Beckley, P D; LaLone, B J

    1994-09-01

    Knowledge and predictability of oxygenator performance is vital to safe and effective conduct of cardiopulmonary bypass. The determination of oxygenator performance in the laboratory, however, is carried out under a strict set of conditions established by the Association for the Advancement of Medical Instrumentation (AAMI). This performance data is of limited value in the clinical setting where the perfusionist generally operates outside this set of parameters. This study (1) reports the laboratory performance characteristics of a hollow fiber membrane oxygenator (Sorin Monolyth), (2) uses this data to develop a model to predict performance under a wide range of clinical conditions, (3) compares predicted performance with clinical data collected at two open heart centers, and (4) reviews the complexities of comparing laboratory and clinical performance. An in-vitro "oxygenator-deoxygenator" circuit was utilized to determine O2 and CO2 gas exchange, blood path pressure drop, and heat exchanger efficiency at a variety of blood and gas flows, under standard (AAMI) blood inlet conditions: [table: see text] This laboratory performance data was compared to hospital and computer modeling data. Simple numerical comparison and analysis of variance of regression coefficients over groups indicated that some clinical parameters of performance (oxygen transfer and coefficient of heat exchange) were not predicted with the laboratory data. It is concluded that the laboratory performance data determined under strict controlled conditions may be of limited value in predicting clinical performance unless modeled to allow for variances in operating conditions.

  6. Auditory brainstem responses to stop consonants predict literacy.

    PubMed

    Neef, Nicole E; Schaadt, Gesa; Friederici, Angela D

    2017-03-01

    Precise temporal coding of speech plays a pivotal role in sound processing throughout the central auditory system, which, in turn, influences literacy acquisition. The current study tests whether an electrophysiological measure of this precision predicts literacy skills. Complex auditory brainstem responses were analysed from 62 native German-speaking children aged 11-13years. We employed the cross-phaseogram approach to compute the quality of the electrophysiological stimulus contrast [da] and [ba]. Phase shifts were expected to vary with literacy. Receiver operating curves demonstrated a feasible sensitivity and specificity of the electrophysiological measure. A multiple regression analysis resulted in a significant prediction of literacy by delta cross-phase as well as phonological awareness. A further commonality analysis separated a unique variance that was explained by the physiological measure, from a unique variance that was explained by the behavioral measure, and common effects of both. Despite multicollinearities between literacy, phonological awareness, and subcortical differentiation of stop consonants, a combined assessment of behavior and physiology strongly increases the ability to predict literacy skills. The strong link between the neurophysiological signature of sound encoding and literacy outcome suggests that the delta cross-phase could indicate the risk of dyslexia and thereby complement subjective psychometric measures for early diagnoses. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  7. Human models of pain for the prediction of clinical analgesia.

    PubMed

    Lötsch, Jörn; Oertel, Bruno G; Ultsch, Alfred

    2014-10-01

    Human experimental pain models are widely used to study drug effects under controlled conditions. However, efforts to improve both animal and human experimental model selection, on the basis of increased understanding of the underlying pathophysiological pain mechanisms, have been disappointing, with poor translation of results to clinical analgesia. We have developed an alternative approach to the selection of suitable pain models that can correctly predict drug efficacy in particular clinical settings. This is based on the analysis of successful or unsuccessful empirical prediction of clinical analgesia using experimental pain models. We analyzed statistically the distribution of published mutual agreements or disagreements between drug efficacy in experimental and clinical pain settings. Significance limits were derived by random permutations of agreements. We found that a limited subset of pain models predicts a large number of clinically relevant pain settings, including efficacy against neuropathic pain for which novel analgesics are particularly needed. Thus, based on empirical evidence of agreement between drugs for their efficacy in experimental and clinical pain settings, it is possible to identify pain models that reliably predict clinical analgesic drug efficacy in cost-effective experimental settings.

  8. Imbalanced target prediction with pattern discovery on clinical data repositories.

    PubMed

    Chan, Tak-Ming; Li, Yuxi; Chiau, Choo-Chiap; Zhu, Jane; Jiang, Jie; Huo, Yong

    2017-04-20

    Clinical data repositories (CDR) have great potential to improve outcome prediction and risk modeling. However, most clinical studies require careful study design, dedicated data collection efforts, and sophisticated modeling techniques before a hypothesis can be tested. We aim to bridge this gap, so that clinical domain users can perform first-hand prediction on existing repository data without complicated handling, and obtain insightful patterns of imbalanced targets for a formal study before it is conducted. We specifically target for interpretability for domain users where the model can be conveniently explained and applied in clinical practice. We propose an interpretable pattern model which is noise (missing) tolerant for practice data. To address the challenge of imbalanced targets of interest in clinical research, e.g., deaths less than a few percent, the geometric mean of sensitivity and specificity (G-mean) optimization criterion is employed, with which a simple but effective heuristic algorithm is developed. We compared pattern discovery to clinically interpretable methods on two retrospective clinical datasets. They contain 14.9% deaths in 1 year in the thoracic dataset and 9.1% deaths in the cardiac dataset, respectively. In spite of the imbalance challenge shown on other methods, pattern discovery consistently shows competitive cross-validated prediction performance. Compared to logistic regression, Naïve Bayes, and decision tree, pattern discovery achieves statistically significant (p-values < 0.01, Wilcoxon signed rank test) favorable averaged testing G-means and F1-scores (harmonic mean of precision and sensitivity). Without requiring sophisticated technical processing of data and tweaking, the prediction performance of pattern discovery is consistently comparable to the best achievable performance. Pattern discovery has demonstrated to be robust and valuable for target prediction on existing clinical data repositories with imbalance and

  9. Statistical energy analysis response prediction methods for structural systems

    NASA Technical Reports Server (NTRS)

    Davis, R. F.

    1979-01-01

    The results of an effort to document methods for accomplishing response predictions for commonly encountered aerospace structural configurations is presented. Application of these methods to specified aerospace structure to provide sample analyses is included. An applications manual, with the structural analyses appended as example problems is given. Comparisons of the response predictions with measured data are provided for three of the example problems.

  10. Predictive markers of response to isotretinoin in female acne.

    PubMed

    Preneau, Sophie; Dessinioti, Clio; Nguyen, Jean-Michel; Katsambas, Andreas; Dreno, Brigitte

    2013-01-01

    Acne vulgaris is a common and chronic disorder of the pilosebaceous unit. Female acne may be a subtype differing from teenager acne. Isotretinoin is the only therapy impacting on all the major acne-related aetiological factors. All clinical studies demonstrating isotretinoin efficacy in acne patients have been performed either in teenagers or in a mixed population of teenagers and adults. To evaluate isotretinoin efficiency and tolerance in a cohort of females with acne, aged 20+ years. Study of 32 women prescribed isotretinoin according to the European recommendations (0.5 mg/kg) in two dermatology departments (France and Greece). The ECLA scale and a global evaluation using the GEA grading were used to evaluate isotretinoin efficacy. The correlation between the clinical response and the different epidemiological factors was determined. Complete response reached 59% on the face, 78% on the trunk and 43% on both the face and trunk. A significant correlation was observed between the facial response and body mass index (p = 0.02), the high-glycemic-load diet (p = 0.0009), tobacco (p = 0.05) and age at acne onset (p = 0.05). Isotretinoin at 0.5mg/kg is effective and well tolerated in mild-to-moderate acne in females over 20 years old and results were similar to those of teenagers and men. We can propose positive predictive markers of response to isotretinoin in female acne, including a low body mass index, low glycemic-load diet, no tobacco, absence of early acne onset and of lesions on the neck.

  11. DYNAMICALLY EVOLVING CLINICAL PRACTICES AND IMPLICATIONS FOR PREDICTING MEDICAL DECISIONS

    PubMed Central

    CHEN, JONATHAN H; GOLDSTEIN, MARY K; ASCH, STEVEN M; ALTMAN, RUSS B

    2015-01-01

    Automatically data-mining clinical practice patterns from electronic health records (EHR) can enable prediction of future practices as a form of clinical decision support (CDS). Our objective is to determine the stability of learned clinical practice patterns over time and what implication this has when using varying longitudinal historical data sources towards predicting future decisions. We trained an association rule engine for clinical orders (e.g., labs, imaging, medications) using structured inpatient data from a tertiary academic hospital. Comparing top order associations per admission diagnosis from training data in 2009 vs. 2012, we find practice variability from unstable diagnoses with rank biased overlap (RBO)<0.35 (e.g., pneumonia) to stable admissions for planned procedures (e.g., chemotherapy, surgery) with comparatively high RBO>0.6. Predicting admission orders for future (2013) patients with associations trained on recent (2012) vs. older (2009) data improved accuracy evaluated by area under the receiver operating characteristic curve (ROC-AUC) 0.89 to 0.92, precision at ten (positive predictive value of the top ten predictions against actual orders) 30% to 37%, and weighted recall (sensitivity) at ten 2.4% to 13%, (P<10−10). Training with more longitudinal data (2009-2012) was no better than only using recent (2012) data. Secular trends in practice patterns likely explain why smaller but more recent training data is more accurate at predicting future practices. PMID:26776186

  12. Adaptation of Clinical Prediction Models for Application in Local Settings

    PubMed Central

    Kappen, Teus H.; Vergouwe, Yvonne; van Klei, Wilton A.; van Wolfswinkel, Leo; Kalkman, Cor J.

    2012-01-01

    Background. When planning to use a validated prediction model in new patients, adequate performance is not guaranteed. For example, changes in clinical practice over time or a different case mix than the original validation population may result in inaccurate risk predictions. Objective. To demonstrate how clinical information can direct updating a prediction model and development of a strategy for handling missing predictor values in clinical practice. Methods. A previously derived and validated prediction model for postoperative nausea and vomiting was updated using a data set of 1847 patients. The update consisted of 1) changing the definition of an existing predictor, 2) reestimating the regression coefficient of a predictor, and 3) adding a new predictor to the model. The updated model was then validated in a new series of 3822 patients. Furthermore, several imputation models were considered to handle real-time missing values, so that possible missing predictor values could be anticipated during actual model use. Results. Differences in clinical practice between our local population and the original derivation population guided the update strategy of the prediction model. The predictive accuracy of the updated model was better (c statistic, 0.68; calibration slope, 1.0) than the original model (c statistic, 0.62; calibration slope, 0.57). Inclusion of logistical variables in the imputation models, besides observed patient characteristics, contributed to a strategy to deal with missing predictor values at the time of risk calculation. Conclusions. Extensive knowledge of local, clinical processes provides crucial information to guide the process of adapting a prediction model to new clinical practices. PMID:22427369

  13. Adaptation of clinical prediction models for application in local settings.

    PubMed

    Kappen, Teus H; Vergouwe, Yvonne; van Klei, Wilton A; van Wolfswinkel, Leo; Kalkman, Cor J; Moons, Karel G M

    2012-01-01

    When planning to use a validated prediction model in new patients, adequate performance is not guaranteed. For example, changes in clinical practice over time or a different case mix than the original validation population may result in inaccurate risk predictions. To demonstrate how clinical information can direct updating a prediction model and development of a strategy for handling missing predictor values in clinical practice. A previously derived and validated prediction model for postoperative nausea and vomiting was updated using a data set of 1847 patients. The update consisted of 1) changing the definition of an existing predictor, 2) reestimating the regression coefficient of a predictor, and 3) adding a new predictor to the model. The updated model was then validated in a new series of 3822 patients. Furthermore, several imputation models were considered to handle real-time missing values, so that possible missing predictor values could be anticipated during actual model use. Differences in clinical practice between our local population and the original derivation population guided the update strategy of the prediction model. The predictive accuracy of the updated model was better (c statistic, 0.68; calibration slope, 1.0) than the original model (c statistic, 0.62; calibration slope, 0.57). Inclusion of logistical variables in the imputation models, besides observed patient characteristics, contributed to a strategy to deal with missing predictor values at the time of risk calculation. Extensive knowledge of local, clinical processes provides crucial information to guide the process of adapting a prediction model to new clinical practices.

  14. Response to intravenous fentanyl infusion predicts subsequent response to transdermal fentanyl.

    PubMed

    Hayashi, Norihito; Kanai, Akifumi; Suzuki, Asaha; Nagahara, Yuki; Okamoto, Hirotsugu

    2016-04-01

    Prediction of the response to transdermal fentanyl (FENtd) before its use for chronic pain is desirable. We tested the hypothesis that the response to intravenous fentanyl infusion (FENiv) can predict the response to FENtd, including the analgesic and adverse effects. The study subjects were 70 consecutive patients with chronic pain. The response to fentanyl at 0.1 mg diluted in 50 ml of physiological saline and infused over 30 min was tested. This was followed by treatment with FENtd (Durotep MT patch 2.1 mg) at a dose of 12.5 µg/h for 2 weeks. Pain intensity before and after FENiv and 2 weeks after FENtd, and the response to treatment, were assessed by the numerical rating scale (NRS), clinical global impression-improvement scale (CGI-I), satisfaction scale (SS), and adverse effects. The NRS score decreased significantly from 7 (4-9) [median (range)] at baseline to 3 (0-8) after FENiv (p < 0.001), and to 4 (1-8) after FENtd (p < 0.001). The effects of FENiv, as evaluated by ΔNRS, CGI-I, and SS, were significantly greater than those of FENtd (p < 0.001, each), but not by the frequency and the severity of adverse effects, with the exception of dizziness. ΔNRS, and severity of adverse effects (drowsiness, dizziness, nausea, dry mouth, and pruritus) of FENiv correlated significantly with those of FENtd (rs > 0.04, each). The analgesic and side effects after intravenous fentanyl infusion can be used to predict the response to short-term transdermal treatment with fentanyl.

  15. Endosonographic radial tumor thickness after neoadjuvant chemoradiation therapy to predict response and survival in patients with locally advanced esophageal cancer: a prospective multicenter phase ll study by the Swiss Group for Clinical Cancer Research (SAKK 75/02).

    PubMed

    Jost, Christian; Binek, Janek; Schuller, Jan C; Bauerfeind, Peter; Metzger, Urs; Werth, Baseli; Knuchel, Juerg; Frossard, Jean-Louis; Bertschinger, Philipp; Brauchli, Peter; Meyenberger, Christa; Ruhstaller, Thomas

    2010-06-01

    EUS response assessment in patients with locally advanced esophageal cancer undergoing neoadjuvant chemoradiation therapy (CRT) is limited by disintegration of the involved anatomic structures. Predictive and prognostic values of a prospectively defined maximum tumor thickness (MTT). Prospective open-label phase ll study (SAKK 75/02). Multicenter, nationwide. Of 66 patients with primary CRT, 56 underwent en bloc esophagectomy. EUS-measured MTT before and 2-5 weeks after CRT (yMTT). Cutoffs: (1) absolute thickness (yMTT) after CRT < or = 6 mm; (2) relative reduction compared with baseline (ratio yMTT/MTT) < or = 50%. Correlation between EUS measurements and histopathologic tumor regression grade (TRG) and overall survival (OS). Sixteen of 56 patients were not included for EUS evaluation (10 severe stenosis, 5 MTT not measured, 1 intolerance to second EUS). Characteristics (n = 40) were as follow: median age, 60 years; squamous cell carcinoma, 42%; and adenocarcinoma (AC), 58%. Initial stage was: 10 T2N1, 3 T3N0, 26 T3N1, 1 T3Nx; 14 of 23 AC Siewert type 1. Wilcoxon rank sum test showed significant correlation of TRG1 with yMTT < or = 6 mm (P = .008) and yMTT/MTT < or = 50% (P = .003). The effect of yMTT on TRG1 was significant (P = .0193; odds ratio, 0.687 [95% CI, 0.502-0.941]). The predefined cutoff of < or = 6 mm for yMTT was predictive for TRG1 (P = .0037; Fisher exact test). After a median follow-up of 28.6 months, there was a clear trend for benefit in OS with yMTT < or = 6 mm and yMTT/MTT < or = 50%. Small sample size. In a multicenter setting, MTT measured by EUS after CRT was highly predictive for response and showed a clear trend for predicting survival. Copyright 2010 American Society for Gastrointestinal Endoscopy. Published by Mosby, Inc. All rights reserved.

  16. Clinical time series prediction: Toward a hierarchical dynamical system framework.

    PubMed

    Liu, Zitao; Hauskrecht, Milos

    2015-09-01

    Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. Clinical time series prediction: towards a hierarchical dynamical system framework

    PubMed Central

    Liu, Zitao; Hauskrecht, Milos

    2014-01-01

    Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive

  18. Tumor Endothelial Inflammation Predicts Clinical Outcome in Diverse Human Cancers

    PubMed Central

    Filippo, Matthew; Labay, Edwardine; Beckett, Michael A.; Mauceri, Helena J.; Liang, Hua; Darga, Thomas E.; Perakis, Samantha; Khan, Sajid A.; Sutton, Harold G.; Zhang, Wei; Khodarev, Nikolai N.; Garcia, Joe G. N.; Weichselbaum, Ralph R.

    2012-01-01

    Background Vascular endothelial cells contribute to the pathogenesis of numerous human diseases by actively regulating the stromal inflammatory response; however, little is known regarding the role of endothelial inflammation in the growth of human tumors and its influence on the prognosis of human cancers. Methods Using an experimental model of tumor necrosis factor-alpha (TNF-α)-mediated inflammation, we characterized inflammatory gene expression in immunopurified tumor-associated endothelial cells. These genes formed the basis of a multivariate molecular predictor of overall survival that was trained and validated in four types of human cancer. Results We report that expression of experimentally derived tumor endothelial genes distinguished pathologic tissue specimens from normal controls in several human diseases associated with chronic inflammation. We trained these genes in human cancer datasets and defined a six-gene inflammatory signature that predicted significantly reduced overall survival in breast cancer, colon cancer, lung cancer, and glioma. This endothelial-derived signature predicted outcome independently of, but cooperatively with, standard clinical and pathological prognostic factors. Consistent with these findings, conditioned culture media from human endothelial cells stimulated by pro-inflammatory cytokines accelerated the growth of human colon and breast tumors in immunodeficient mice as compared with conditioned media from untreated endothelial cells. Conclusions This study provides the first prognostic cancer gene signature derived from an experimental model of tumor-associated endothelial inflammation. These findings support the notion that activation of inflammatory pathways in non-malignant tumor-infiltrating endothelial cells contributes to tumor growth and progression in multiple human cancers. Importantly, these results identify endothelial-derived factors that could serve as potential targets for therapy in diverse human cancers

  19. Integrative neuroscience approach to predict ADHD stimulant response.

    PubMed

    Hermens, Daniel F; Rowe, Donald L; Gordon, Evian; Williams, Leanne M

    2006-05-01

    Despite high rates of prescription, little is known about the long-term consequences of stimulant medication therapy for attention-deficit hyperactivity disorder (ADHD) sufferers. Historically, the clinical use of stimulants for ADHD has been based on trial and error before optimal therapy is reached. Concurrently, scientific research on the mechanism of action of stimulants has influenced neurobiological models of ADHD, but has not always informed their prescription. Whilst the two main stimulant types (methylphenidate and dexamphetamine) have numerous similarities, they also differ (slightly) in mechanism and possibly individual response. A further issue relates to differences in cost and availability compounded by the expectation for stimulants to be effective in ameliorating a broad spectrum of ADHD-related symptoms. Thus, there is an increasing need for treating clinicians to prescribe not only the most effective drug, but also the most appropriate dose with the associated release mechanism and schedule for each ADHD patient presented. In this regard, the field is witnessing an emergence of the personalized medicine approach to ADHD, in which treatment decisions are tailored to each individual. This shift requires a new approach to research into treatment response prediction. Given the heterogeneity of ADHD, a profile of information may be required to capture the most sensitive predictors of treatment response in individuals. These profiles will also benefit from the integration of data from clinical rating scales with more direct measures of cognition and brain function. In conclusion, there is a need to establish a more robust normative framework as the baseline for treatment, as well as diagnostic decisions, and as discussed, the growth of integrated neuroscience databases will be important in this regard.

  20. Atypical clinical response patterns to ipilimumab.

    PubMed

    Ledezma, Blanca; Binder, Sandra; Hamid, Omid

    2011-08-01

    Patients with advanced melanoma have few treatment options, and survival is poor. However, improved understanding of how the immune system interacts with cancer has led to the development of novel therapies. Ipilimumab is a monoclonal antibody that inhibits cytotoxic T-lymphocyte antigen-4 (CTLA-4), a key negative regulator of host T-cell responses. This article presents cases of patients receiving ipilimumab in clinical trials along with a discussion of their significance and relevance to nursing practice. The patients showed different response patterns to ipilimumab and also had various typical immune-related adverse events (irAEs), which were managed successfully. The atypical response patterns produced by ipilimumab likely reflect its mechanism of action, which requires time for the immune system to mount an effective antitumor response. Meanwhile, lesions may appear to enlarge as a consequence of enhanced T-cell infiltration, although this may not necessarily be true disease progression. Patients receiving ipilimumab may respond very differently compared to how they might react to chemotherapy. Responses can take weeks or months to develop; therefore, clinicians should not terminate treatment prematurely, providing the patient's condition allows for continuation. Early recognition of irAEs combined with prompt management will ensure that events are more likely to resolve without serious consequences.

  1. Predicting analysis times in randomized clinical trials with cancer immunotherapy.

    PubMed

    Chen, Tai-Tsang

    2016-02-01

    A new class of immuno-oncology agents has recently been shown to induce long-term survival in a proportion of treated patients. This phenomenon poses unique challenges for the prediction of analysis time in event-driven studies. If the phenomenon of long-term survival is not accounted for properly, the accuracy of the prediction based on the existing methods may be substantially compromised. Parametric mixture cure rate models with the best fit to empirical clinical trial data were proposed to predict analysis times in immuno-oncology studies during the course of the study. The proposed prediction procedure also accounts for the mechanism of action introduced by cancer immunotherapies, such as delayed and long-term survival effects. The proposed methodology was retrospectively applied to a randomized phase III immuno-oncology clinical trial. Among various parametric mixture cure rate models, the Weibull cure rate model was found to be the best-fitting model for this study. The unique survival kinetics of cancer immunotherapy was captured in the longitudinal predictions of the final analysis times. Parametric mixture cure rate models, along with estimated long-term survival rates, probabilities of study incompletion, and expected statistical powers over time, provide immuno-oncology clinical trial researchers with a useful tool for continuous event monitoring and prediction of analysis times, such that informed decisions with quantifiable risks can be made for better resource and logistic planning.

  2. Neuropsychological impairments predict the clinical course in schizophrenia.

    PubMed

    Wölwer, Wolfgang; Brinkmeyer, Jürgen; Riesbeck, Mathias; Freimüller, Lena; Klimke, Ansgar; Wagner, Michael; Möller, Hans-Jürgen; Klingberg, Stefan; Gaebel, Wolfgang

    2008-11-01

    To add to the open question whether cognitive impairments predict clinical outcome in schizophrenia, a sample of 125 first episode patients was assessed at the onset and over one year of controlled long-term treatment within a study of the German Research Network on Schizophrenia. No relapse according to predefined criteria occurred within the first year, but a total of 29 patients fulfilled post-hoc criteria of "clinical deterioration". Impairments in cognitive functioning assessed by the Trail-Making Test B at the onset of long-term treatment differentiated between patients with vs. without later clinical deterioration and proved to be a significant predictor of the clinical course in a regression analysis outperforming initial clinical status as predictor. However, low sensitivity (72%) and specificity (51%) limit possibilities of a transfer to individual predictions. As a linear combination of neuropsychological and psychopathological variables obtained highest predictive validity, such a combination may improve the prediction of the course of schizophrenic disorders and may ultimately lead to a more efficient and comprehensive treatment planning.

  3. Predicting clinical judgment for a primary grade apperception battery.

    PubMed

    Peterson, R A; Kroeker, L; Torshen, K

    1976-08-01

    A six-card Primary Grade Apperception Battery (three cards from the CAT and three from the SAM) was administered to one group of first grade children on a 4 month test-retest schedule and to a new group of first graders 1 year later. Two clinical psychologists read the protocols and made clinical judgments regarding home and school adjustment on a four-point scale. An initial regression formula to predict clinical judgment from objective apperception score data was derived. The formula was validated on the retest data and the new sample. The results indicate the derived apperception score reliably predicted clinical judgment. In general, the results also suggest the six card apperception battery may be a useful screening test for school and home adjustment for first and second grade children.

  4. On-time clinical phenotype prediction based on narrative reports

    PubMed Central

    Bejan, Cosmin A.; Vanderwende, Lucy; Evans, Heather L.; Wurfel, Mark M.; Yetisgen-Yildiz, Meliha

    2013-01-01

    In this paper we describe a natural language processing system which is able to predict whether or not a patient exhibits a specific phenotype using the information extracted from the narrative reports associated with the patient. Furthermore, the phenotypic annotations from our report dataset were performed at the report level which allows us to perform the prediction of the clinical phenotype at any point in time during the patient hospitalization period. Our experiments indicate that an important factor in achieving better results for this problem is to determine how much information to extract from the patient reports in the time interval between the patient admission time and the current prediction time. PMID:24551325

  5. Clinical and Immunological Responses in Ocular Demodecosis

    PubMed Central

    Kim, Jae Hoon; Chun, Yeoun Sook

    2011-01-01

    The purpose of this study was to investigate clinical and immunological responses to Demodex on the ocular surface. Thirteen eyes in 10 patients with Demodex blepharitis and chronic ocular surface disorders were included in this study and treated by lid scrubbing with tea tree oil for the eradication of Demodex. We evaluated ocular surface manifestations and Demodex counts, and analyzed IL-1β, IL-5, IL-7, IL-12, IL-13, IL-17, granulocyte colony-stimulating factor, and macrophage inflammatory protein-1β in tear samples before and after the treatment. All patients exhibited ocular surface manifestations including corneal nodular opacity, peripheral corneal vascularization, refractory corneal erosion and infiltration, or chronic conjunctival inflammatory signs before treatment. After treatment, Demodex was nearly eradicated, tear concentrations of IL-1β and IL-17 were significantly reduced and substantial clinical improvement was observed in all patients. In conclusion, we believe that Demodex plays an aggravating role in inflammatory ocular surface disorders. PMID:21935281

  6. Clinical and immunological responses in ocular demodecosis.

    PubMed

    Kim, Jae Hoon; Chun, Yeoun Sook; Kim, Jae Chan

    2011-09-01

    The purpose of this study was to investigate clinical and immunological responses to Demodex on the ocular surface. Thirteen eyes in 10 patients with Demodex blepharitis and chronic ocular surface disorders were included in this study and treated by lid scrubbing with tea tree oil for the eradication of Demodex. We evaluated ocular surface manifestations and Demodex counts, and analyzed IL-1β, IL-5, IL-7, IL-12, IL-13, IL-17, granulocyte colony-stimulating factor, and macrophage inflammatory protein-1β in tear samples before and after the treatment. All patients exhibited ocular surface manifestations including corneal nodular opacity, peripheral corneal vascularization, refractory corneal erosion and infiltration, or chronic conjunctival inflammatory signs before treatment. After treatment, Demodex was nearly eradicated, tear concentrations of IL-1β and IL-17 were significantly reduced and substantial clinical improvement was observed in all patients. In conclusion, we believe that Demodex plays an aggravating role in inflammatory ocular surface disorders.

  7. Mass Law Predicts Hyperbolic Hypoxic Ventilatory Response

    NASA Astrophysics Data System (ADS)

    Severinghaus, John W.

    The hyperbolic hypoxic ventilatory response vs PaO2, HVRp, is interpreted as relecting a mass hyperbolic relationship of cytochrome PcO2 to cytochrome potential Ec, offset 32 torr by the constant diffusion gradient between arterial blood and cytochrome in CB at its constant metabolic rate dot VO_2 . Ec is taken to be a linear function of redox reduction and CB ventilatory drive. As Ec rises in hypoxia, the absolute potentials of each step in the citric acid cycle rises equally while the potential drop across each step remains constant because flux rate remains constant. A hypothetic HVRs ( dot VE vs SaO2) response curve computed from these assumptions is strikingly non linear. A hypothetic HVRp calculated from an assumed linear HVRs cannot be fit to the observed hyperbolic increase of ventilation in response to isocapnic hypoxia at PO2 less than 40 torr. The incompatibility of these results suggest that in future studies HVRs will not be found to be linear, especially below 80% SaO2 and HVRp will fail to be accurately hyperbolic.

  8. Enhanced clinical pharmacy service targeting tools: risk-predictive algorithms.

    PubMed

    El Hajji, Feras W D; Scullin, Claire; Scott, Michael G; McElnay, James C

    2015-04-01

    This study aimed to determine the value of using a mix of clinical pharmacy data and routine hospital admission spell data in the development of predictive algorithms. Exploration of risk factors in hospitalized patients, together with the targeting strategies devised, will enable the prioritization of clinical pharmacy services to optimize patient outcomes. Predictive algorithms were developed using a number of detailed steps using a 75% sample of integrated medicines management (IMM) patients, and validated using the remaining 25%. IMM patients receive targeted clinical pharmacy input throughout their hospital stay. The algorithms were applied to the validation sample, and predicted risk probability was generated for each patient from the coefficients. Risk threshold for the algorithms were determined by identifying the cut-off points of risk scores at which the algorithm would have the highest discriminative performance. Clinical pharmacy staffing levels were obtained from the pharmacy department staffing database. Numbers of previous emergency admissions and admission medicines together with age-adjusted co-morbidity and diuretic receipt formed a 12-month post-discharge and/or readmission risk algorithm. Age-adjusted co-morbidity proved to be the best index to predict mortality. Increased numbers of clinical pharmacy staff at ward level was correlated with a reduction in risk-adjusted mortality index (RAMI). Algorithms created were valid in predicting risk of in-hospital and post-discharge mortality and risk of hospital readmission 3, 6 and 12 months post-discharge. The provision of ward-based clinical pharmacy services is a key component to reducing RAMI and enabling the full benefits of pharmacy input to patient care to be realized. © 2014 John Wiley & Sons, Ltd.

  9. A model for predicting lung cancer response to therapy

    SciTech Connect

    Seibert, Rebecca M. . E-mail: rseiber1@utk.edu; Ramsey, Chester R.; Hines, J. Wesley; Kupelian, Patrick A.; Langen, Katja M.; Meeks, Sanford L.; Scaperoth, Daniel D.

    2007-02-01

    Purpose: Volumetric computed tomography (CT) images acquired by image-guided radiation therapy (IGRT) systems can be used to measure tumor response over the course of treatment. Predictive adaptive therapy is a novel treatment technique that uses volumetric IGRT data to actively predict the future tumor response to therapy during the first few weeks of IGRT treatment. The goal of this study was to develop and test a model for predicting lung tumor response during IGRT treatment using serial megavoltage CT (MVCT). Methods and Materials: Tumor responses were measured for 20 lung cancer lesions in 17 patients that were imaged and treated with helical tomotherapy with doses ranging from 2.0 to 2.5 Gy per fraction. Five patients were treated with concurrent chemotherapy, and 1 patient was treated with neoadjuvant chemotherapy. Tumor response to treatment was retrospectively measured by contouring 480 serial MVCT images acquired before treatment. A nonparametric, memory-based locally weight regression (LWR) model was developed for predicting tumor response using the retrospective tumor response data. This model predicts future tumor volumes and the associated confidence intervals based on limited observations during the first 2 weeks of treatment. The predictive accuracy of the model was tested using a leave-one-out cross-validation technique with the measured tumor responses. Results: The predictive algorithm was used to compare predicted verse-measured tumor volume response for all 20 lesions. The average error for the predictions of the final tumor volume was 12%, with the true volumes always bounded by the 95% confidence interval. The greatest model uncertainty occurred near the middle of the course of treatment, in which the tumor response relationships were more complex, the model has less information, and the predictors were more varied. The optimal days for measuring the tumor response on the MVCT images were on elapsed Days 1, 2, 5, 9, 11, 12, 17, and 18 during

  10. Clinical predictors of therapeutic response to antipsychotics in schizophrenia

    PubMed Central

    Carbon, Maren; Correll, Christoph U.

    2014-01-01

    The search for clinical outcome predictors for schizophrenia is as old as the field of psychiatry. However, despite a wealth of large, longitudinal studies into prognostic factors, only very few clinically useful outcome predictors have been identified. The goal of future treatment is to either affect modifiable risk factors, or use nonmodifiable factors to parse patients into therapeutically meaningful subgroups. Most clinical outcome predictors are nonspecific and/or nonmodifiable. Nonmodifiable predictors for poor odds of remission include male sex, younger age at disease onset, poor premorbid adjustment, and severe baseline psychopathology. Modifiable risk factors for poor therapeutic outcomes that clinicians can act upon include longer duration of untreated illness, nonadherence to antipsychotics, comorbidities (especially substance-use disorders), lack of early antipsychotic response, and lack of improvement with non-clozapine antipsychotics, predicting clozapine response. It is hoped that this limited capacity for prediction will improve as pathophysiological understanding increases and/or new treatments for specific aspects of schizophrenia become available. PMID:25733955

  11. Shunting normal pressure hydrocephalus: the predictive value of combined clinical and CT data.

    PubMed Central

    Vanneste, J; Augustijn, P; Tan, W F; Dirven, C

    1993-01-01

    The value of an ordinal global scale derived from combined clinical and CT data (clin/CT scale) to predict the clinical outcome in 112 patients shunted for presumed normal pressure hydrocephalus (NPH) was analysed. The clinical data were retrospectively collected, all CT scans were re-evaluated, and the clin/CT scale was determined blind to the results of further ancillary tests and to the post-surgical outcome. The scale ranked three classes of prediction: on the basis of clinical and CT characteristics, improvement after shunting was probable, possible, or improbable. The predictive value of the clin/CT scale for the subgroup of communicating NPH was established for two different strategies, depending on the strictness of selection criteria for shunting. In the subgroup of patients with presumed communicating NPH, the prevalence of shunt responsiveness was 29%; the best strategy was to shunt only patients with probable shunt-responsive NPH: the sensitivity was 0.54, the specificity 0.84, and the predictive accuracy 0.75, with a limited number of ineffective shunts (11%) and missed improvements (13%). The study illustrates its need to assess the pre-test probability of NPH based on combined clinical and CT data, before establishing the clinical usefulness of an ancillary test. PMID:8459240

  12. Serum metabolites predict response to angiotensin II receptor blockers in patients with diabetes mellitus.

    PubMed

    Pena, Michelle J; Heinzel, Andreas; Rossing, Peter; Parving, Hans-Henrik; Dallmann, Guido; Rossing, Kasper; Andersen, Steen; Mayer, Bernd; Heerspink, Hiddo J L

    2016-07-05

    Individual patients show a large variability in albuminuria response to angiotensin receptor blockers (ARB). Identifying novel biomarkers that predict ARB response may help tailor therapy. We aimed to discover and validate a serum metabolite classifier that predicts albuminuria response to ARBs in patients with diabetes mellitus and micro- or macroalbuminuria. Liquid chromatography-tandem mass spectrometry metabolomics was performed on serum samples. Data from patients with type 2 diabetes and microalbuminuria (n = 49) treated with irbesartan 300 mg/day were used for discovery. LASSO and ridge regression were performed to develop the classifier. Improvement in albuminuria response prediction was assessed by calculating differences in R(2) between a reference model of clinical parameters and a model with clinical parameters and the classifier. The classifier was externally validated in patients with type 1 diabetes and macroalbuminuria (n = 50) treated with losartan 100 mg/day. Molecular process analysis was performed to link metabolites to molecular mechanisms contributing to ARB response. In discovery, median change in urinary albumin excretion (UAE) was -42 % [Q1-Q3: -69 to -8]. The classifier, consisting of 21 metabolites, was significantly associated with UAE response to irbesartan (p < 0.001) and improved prediction of UAE response on top of the clinical reference model (R(2) increase from 0.10 to 0.70; p < 0.001). In external validation, median change in UAE was -43 % [Q1-Q35: -63 to -23]. The classifier improved prediction of UAE response to losartan (R(2) increase from 0.20 to 0.59; p < 0.001). Specifically ADMA impacting eNOS activity appears to be a relevant factor in ARB response. A serum metabolite classifier was discovered and externally validated to significantly improve prediction of albuminuria response to ARBs in diabetes mellitus.

  13. The Autonomic System Functional State Predicts Responsiveness in Disorder of Consciousness.

    PubMed

    Riganello, Francesco; Cortese, Maria D; Dolce, Giuliano; Lucca, Lucia F; Sannita, Walter G

    2015-07-15

    Diagnosis and early prognosis of the vegetative state/unresponsive wakefulness syndrome (VS/UWS) and its differentiation from the minimally-conscious state still rest on the clinical observation of responsiveness. The incidence of established clinical indicators of responsiveness also has proven variable in the single subject and is correlated to measures of heart rate variability (HRV) describing the sympathetic/parasympathetic balance. We tested responsiveness when the HRV descriptors nuLF and peakLF were or were not in the ranges with highest incidence of response based on findings from previous studies (10.0-70.0 and 0.05-0.11 Hz, respectively). Testing was blind by The Coma Recovery Scale-revised in the two conditions and in two experimental sessions with a one-week interval. The incidence of responses was not randomly distributed in the "response" and "no-response" conditions (McNemar test; p < 0.0001). The observed incidence in the "response" condition (visual: 55.1%; auditory: 51.5%) was higher than predicted statistically (32.1%) or described in previous clinical studies; responses were only occasional in the "no-response" condition (visual, 15.9%; auditory, 13.4%). Models validated the predictability with high accuracy. The current clinical criteria for diagnosis and prognosis based on neurological signs should be reconsidered, including variability over time and the autonomic system functional state, which could also qualify per se as an independent indicator for diagnosis and prognosis.

  14. Motor cortex activity predicts response alternation during sensorimotor decisions

    PubMed Central

    Pape, Anna-Antonia; Siegel, Markus

    2016-01-01

    Our actions are constantly guided by decisions based on sensory information. The motor cortex is traditionally viewed as the final output stage in this process, merely executing motor responses based on these decisions. However, it is not clear if, beyond this role, the motor cortex itself impacts response selection. Here, we report activity fluctuations over motor cortex measured using MEG, which are unrelated to choice content and predict responses to a visuomotor task seconds before decisions are made. These fluctuations are strongly influenced by the previous trial's response and predict a tendency to switch between response alternatives for consecutive decisions. This alternation behaviour depends on the size of neural signals still present from the previous response. Our results uncover a response-alternation bias in sensorimotor decision making. Furthermore, they suggest that motor cortex is more than an output stage and instead shapes response selection during sensorimotor decision making. PMID:27713396

  15. Zebrafish Locomotor Responses Predict Irritant Potential of ...

    EPA Pesticide Factsheets

    Over the past few decades, the drying and warming trends of global climate change have increased wildland fire (WF) season length, as well as geographic area impacted. Consequently, exposures to WF fine particulate matter (PM2.5; aerodynamic diameter <2.5 µm) are likely to increase in frequency and duration, contributing to a growing public health burden. Given the influence of fuel type and combustion conditions on WFPM2.5 composition, there is pressing need to identify the biomass fuel sources and emission constituents that drive toxicity. Previously, we reported the utility of 6-day post-fertilization (dpf) zebrafish larvae in evaluating diesel exhaust PM-induced irritation, demonstrating responses analogous to those in mammals. In the present study, combustions, separated by smoldering or flaming conditions, of pine needles, red oak, pine, eucalyptus, and peat were achieved using an automated tube furnace paired with a cryo-trapping apparatus to collect condensates of emissions. The condensates were extracted and prepared for use in zebrafish assays. We hypothesized that 1) the extractable organic fractions of biomass smoke PM will elicit dose-dependent irritant responses in 6-dpf zebrafish larvae, and 2) the relative potencies will vary across biomass emissions, potentially driven by varying chemical composition of fuel sources. Six-dpf zebrafish (n= 28-32/group) were exposed acutely to PM extracts (5 concentrations; 0.3-30 µg/ml; half-log intervals) and

  16. [Application of three compartment model and response surface model to clinical anesthesia using Microsoft Excel].

    PubMed

    Abe, Eiji; Abe, Mari

    2011-08-01

    With the spread of total intravenous anesthesia, clinical pharmacology has become more important. We report Microsoft Excel file applying three compartment model and response surface model to clinical anesthesia. On the Microsoft Excel sheet, propofol, remifentanil and fentanyl effect-site concentrations are predicted (three compartment model), and probabilities of no response to prodding, shaking, surrogates of painful stimuli and laryngoscopy are calculated using predicted effect-site drug concentration. Time-dependent changes in these calculated values are shown graphically. Recent development in anesthetic drug interaction studies are remarkable, and its application to clinical anesthesia with this Excel file is simple and helpful for clinical anesthesia.

  17. Modeling of Cancer Stem Cell State Transitions Predicts Therapeutic Response

    PubMed Central

    Sehl, Mary E.; Shimada, Miki; Landeros, Alfonso; Lange, Kenneth; Wicha, Max S.

    2015-01-01

    Cancer stem cells (CSCs) possess capacity to both self-renew and generate all cells within a tumor, and are thought to drive tumor recurrence. Targeting the stem cell niche to eradicate CSCs represents an important area of therapeutic development. The complex nature of many interacting elements of the stem cell niche, including both intracellular signals and microenvironmental growth factors and cytokines, creates a challenge in choosing which elements to target, alone or in combination. Stochastic stimulation techniques allow for the careful study of complex systems in biology and medicine and are ideal for the investigation of strategies aimed at CSC eradication. We present a mathematical model of the breast cancer stem cell (BCSC) niche to predict population dynamics during carcinogenesis and in response to treatment. Using data from cell line and mouse xenograft experiments, we estimate rates of interconversion between mesenchymal and epithelial states in BCSCs and find that EMT/MET transitions occur frequently. We examine bulk tumor growth dynamics in response to alterations in the rate of symmetric self-renewal of BCSCs and find that small changes in BCSC behavior can give rise to the Gompertzian growth pattern observed in breast tumors. Finally, we examine stochastic reaction kinetic simulations in which elements of the breast cancer stem cell niche are inhibited individually and in combination. We find that slowing self-renewal and disrupting the positive feedback loop between IL-6, Stat3 activation, and NF-κB signaling by simultaneous inhibition of IL-6 and HER2 is the most effective combination to eliminate both mesenchymal and epithelial populations of BCSCs. Predictions from our model and simulations show excellent agreement with experimental data showing the efficacy of combined HER2 and Il-6 blockade in reducing BCSC populations. Our findings will be directly examined in a planned clinical trial of combined HER2 and IL-6 targeted therapy in HER2

  18. Factors Predicting the Ocular Surface Response to Desiccating Environmental Stress

    PubMed Central

    Alex, Anastasia; Edwards, Austin; Hays, J. Daniel; Kerkstra, Michelle; Shih, Amanda; de Paiva, Cintia S.; Pflugfelder, Stephen C.

    2013-01-01

    Purpose. To identify factors predicting the ocular surface response to experimental desiccating stress. Methods. The ocular surfaces of both eyes of 15 normal and 10 dry eye subjects wearing goggles were exposed to a controlled desiccating environment (15%–25% relative humidity and 2–5 L/min airflow) for 90 minutes. Eye irritation symptoms, blink rate, tear meniscus dimensions, noninvasive (RBUT) and invasive tear break-up time, and corneal fluorescein and conjunctival lissamine green-dye staining were recorded before and after desiccating stress. Pre- and postexposure measurements were compared, and Pearson correlations between clinical parameters before and after desiccating stress were calculated. Results. Corneal and conjunctival dye staining significantly increased in all subjects following 90-minute exposure to desiccating environment, and the magnitude of change was similar in normal and dry eye subjects; except superior cornea staining was greater in dry eye. Irritation severity in the desiccating environment was associated with baseline dye staining, baseline tear meniscus height, and blink rate after 45 minutes. Desiccation-induced change in corneal fluorescein staining was inversely correlated to baseline tear meniscus width, whereas change in total ocular surface dye staining was inversely correlated to baseline dye staining, RBUT, and tear meniscus height and width. Blink rate from 30 to 90 minutes in desiccating environment was higher in the dry eye than normal group. Blink rate significantly correlated to baseline corneal fluorescein staining and environmental-induced change in corneal fluorescein staining. Conclusions. Ocular surface dye staining increases in response to desiccating stress. Baseline ocular surface dye staining, tear meniscus height, and blink rate predict severity of ocular surface dye staining following exposure to a desiccating environment. PMID:23572103

  19. Dopamine neurons share common response function for reward prediction error

    PubMed Central

    Eshel, Neir; Tian, Ju; Bukwich, Michael; Uchida, Naoshige

    2016-01-01

    Dopamine neurons are thought to signal reward prediction error, or the difference between actual and predicted reward. How dopamine neurons jointly encode this information, however, remains unclear. One possibility is that different neurons specialize in different aspects of prediction error; another is that each neuron calculates prediction error in the same way. We recorded from optogenetically-identified dopamine neurons in the lateral ventral tegmental area (VTA) while mice performed classical conditioning tasks. Our tasks allowed us to determine the full prediction error functions of dopamine neurons and compare them to each other. We found striking homogeneity among individual dopamine neurons: their responses to both unexpected and expected rewards followed the same function, just scaled up or down. As a result, we could describe both individual and population responses using just two parameters. Such uniformity ensures robust information coding, allowing each dopamine neuron to contribute fully to the prediction error signal. PMID:26854803

  20. Clinical Prediction Rule of Drug Resistant Epilepsy in Children.

    PubMed

    Boonluksiri, Pairoj; Visuthibhan, Anannit; Katanyuwong, Kamornwan

    2015-12-01

    Clinical prediction rules (CPR) are clinical decision-making tools containing variables such as history, physical examination, diagnostic tests by developing scoring model from potential risk factors. This study is to establish clinical prediction scoring of drug-resistant epilepsy (DRE) in children using clinical manifestationa and only basic electroencephalography (EEG). Retrospective cohort study was conducted. A total of 308 children with diagnosed epilepsy were recruited. Primary outcome was the incidence of DRE. Independent determinants were patient characteristics, clinical manifestations and electroencephalography. CPR was performed based on multiple logistic regression. The incidence of DRE was 42%. Risk factors were age onset, prior neurological deficits, and abnormal EEG. CPR can be established and stratified the prediction using scores into 3 levels such as low risk (score<6), moderate risk (score 6-12) and high risk (score>12) with positive likelihood ratio of 0.5, 1.8 and 12.5 respectively. CPR with scoring risks were stratified into 3 levels. The strongest risk is prior global neurological deficits.

  1. Connecting clinical and actuarial prediction with rule-based methods.

    PubMed

    Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H

    2015-06-01

    Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods. (c) 2015 APA, all rights reserved).

  2. Predictive Response Value of Pre- and Postchemoradiotherapy Variables in Rectal Cancer: An Analysis of Histological Data.

    PubMed

    Santos, Marisa D; Silva, Cristina; Rocha, Anabela; Nogueira, Carlos; Matos, Eduarda; Lopes, Carlos

    2016-01-01

    Background. Neoadjuvant chemoradiotherapy (nCRT) followed by curative surgery in locally advanced rectal cancer (LARC) improves pelvic disease control. Survival improvement is achieved only if pathological response occurs. Mandard tumor regression grade (TRG) proved to be a valid system to measure nCRT response. Potential predictive factors for Mandard response are analyzed. Materials and Methods. 167 patients with LARC were treated with nCRT and curative surgery. Tumor biopsies and surgical specimens were reviewed and analyzed regarding mitotic count, necrosis, desmoplastic reaction, and inflammatory infiltration grade. Surgical specimens were classified according to Mandard TRG. The patients were divided as "good responders" (Mandard TRG1-2) and "bad responders" (Mandard TRG3-5). According to results from our previous data, good responders have better prognosis than bad responders. We examined predictive factors for Mandard response and performed statistical analysis. Results. In univariate analysis, distance from anal verge and ten other postoperative variables related with nCRT tumor response had predictive value for Mandard response. In multivariable analysis only mitotic count, necrosis, and differentiation grade in surgical specimen had predictive value. Conclusions. There is a lack of clinical and pathological preoperative variables able to predict Mandard response. Only postoperative pathological parameters related with nCRT response have predictive value.

  3. Predictability of steel containment response near failure

    SciTech Connect

    Costello, J.F.; Ludwigsen, J.S.; Luk, V.K.; Hessheimer, M.F.

    2000-01-06

    The Nuclear Power Engineering Corporation of Japan and the US Nuclear Regulatory Commission Office of Nuclear Regulatory Research, are co-sponsoring and jointly funding a Cooperative Containment Research Program at Sandia National Laboratories, Albuquerque, New Mexico, USA. As a part of this program, a steel containment vessel model and contact structure assembly was tested to failure with over pressurization at Sandia on December 11--12, 1996. The steel containment vessel model was a mixed-scale model (1:10 in geometry and 1:4 in shell thickness) of a steel containment for an improved Mark-II Boiling Water Reactor plant in Japan. The contact structure, which is a thick, bell-shaped steel shell separated at a nominally uniform distance from the model, provides a simplified representation of features of the concrete reactor shield building in the actual plant. The objective of the internal pressurization test was to provide measurement data of the structural response of the model up to its failure in order to validate analytical modeling, to find its pressure capacity, and to observe the failure model and mechanisms.

  4. Prediction and diagnosis of clinical outcomes affecting restoration margins.

    PubMed

    Dennison, J B; Sarrett, D C

    2012-04-01

    The longevity of dental restorations is largely dependent on the continuity at the interface between the restorative material and adjacent tooth structure (the restoration margin). Clinical decisions on restoration repair or replacement are usually based upon the weakest point along that margin interface. Physical properties of a restorative material, such as polymerisation shrinkage, water sorption, solubility, elastic modulus and shear strength, all have an effect on stress distribution and can significantly affect margin integrity. This review will focus on two aspects of margin deterioration in the oral environment: the in vitro testing of margin seal using emersion techniques to simulate the oral environment and to predict clinical margin failure and the relationship between clinically observable microleakage and secondary caries. The many variables associated with in vitro testing of marginal leakage and the interpretation of the data are presented in detail. The most recent studies of marginal leakage mirror earlier methodology and lack validity and reliability. The lack of standardised testing procedures makes it impossible to compare studies or to predict the clinical performance of adhesive materials. Continual repeated in vitro studies contribute little to the science in this area. Clinical evidence is cited to refute earlier conclusions that clinical microleakage (penetrating margin discoloration) leads to caries development and is an indication for restoration replacement. Margin defects, without visible evidence of soft dentin on the wall or base of the defect, should be monitored, repaired or resealed, in lieu of total restoration replacement. © 2011 Blackwell Publishing Ltd.

  5. Prediction of Psychosis in Youth at High Clinical Risk

    PubMed Central

    Cannon, Tyrone D.; Cadenhead, Kristin; Cornblatt, Barbara; Woods, Scott W.; Addington, Jean; Walker, Elaine; Seidman, Larry J.; Perkins, Diana; Tsuang, Ming; McGlashan, Thomas; Heinssen, Robert

    2011-01-01

    Context Early detection and prospective evaluation of individuals who will develop schizophrenia or other psychotic disorders are critical to efforts to isolate mechanisms underlying psychosis onset and to the testing of preventive interventions, but existing risk prediction approaches have achieved only modest predictive accuracy. Objectives To determine the risk of conversion to psychosis and to evaluate a set of prediction algorithms maximizing positive predictive power in a clinical high-risk sample. Design, Setting, and Participants Longitudinal study with a 2½-year follow-up of 291 prospectively identified treatment-seeking patients meeting Structured Interview for Prodromal Syndromes criteria. The patients were recruited and underwent evaluation across 8 clinical research centers as part of the North American Prodrome Longitudinal Study. Main Outcome Measure Time to conversion to a fully psychotic form of mental illness. Results The risk of conversion to psychosis was 35%, with a decelerating rate of transition during the 2½-year follow-up. Five features assessed at baseline contributed uniquely to the prediction of psychosis: a genetic risk for schizophrenia with recent deterioration in functioning, higher levels of unusual thought content, higher levels of suspicion/paranoia, greater social impairment, and a history of substance abuse. Prediction algorithms combining 2 or 3 of these variables resulted in dramatic increases in positive predictive power (ie, 68%–80%) compared with the prodromal criteria alone. Conclusions These findings demonstrate that prospective ascertainment of individuals at risk for psychosis is feasible, with a level of predictive accuracy comparable to that in other areas of preventive medicine. They provide a benchmark for the rate and shape of the psychosis risk function against which standardized preventive intervention programs can be compared. PMID:18180426

  6. Prediction of clinical risks by analysis of preclinical and clinical adverse events.

    PubMed

    Clark, Matthew

    2015-04-01

    This study examines the ability of nonclinical adverse event observations to predict human clinical adverse events observed in drug development programs. In addition it examines the relationship between nonclinical and clinical adverse event observations to drug withdrawal and proposes a model to predict drug withdrawal based on these observations. These analyses provide risk assessments useful for both planning patient safety programs, as well as a statistical framework for assessing the future success of drug programs based on nonclinical and clinical observations. Bayesian analyses were undertaken to investigate the connection between nonclinical adverse event observations and observations of that same event in clinical trial for a large set of approved drugs. We employed the same statistical methods used to evaluate the efficacy of diagnostic tests to evaluate the ability of nonclinical studies to predict adverse events in clinical studies, and adverse events in both to predict drug withdrawal. We find that some nonclinical observations suggest higher risk for observing the same adverse event in clinical studies, particularly arrhythmias, QT prolongation, and abnormal hepatic function. However the lack of these events in nonclinical studies is found to not be a good predictor of safety in humans. Some nonclinical and clinical observations appear to be associated with high risk of drug withdrawal from market, especially arrhythmia and hepatic necrosis. We use the method to estimate the overall risk of drug withdrawal from market using the product of the risks from each nonclinical and clinical observation to create a risk profile. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. [Clinical probability of PE: should we use a clinical prediction rule?].

    PubMed

    Le Gal, G; Righini, M; Perrier, A

    2008-12-01

    The determination of the clinical pretest probability using clinical prediction models is an important step in the assessment of patients with suspected pulmonary embolism (PE). It helps establish which test or sequence of tests can effectively corroborate or safely rule out PE. For example, it has been demonstrated that it is safe to withhold anticoagulant therapy in patients with negative d-dimer results and low pretest probability at initial presentation. Clinical probability will also increase the diagnostic yield of ventilation perfusion lung scan. Compared with clinical gestalt, clinical prediction rules provide a standardized and more reproducible estimate of a patient's probability of having a PE. Clinical prediction models combine aspects of the history and physical examination to categorize a patient's probability of having a disease. The models classify patients as having a low, moderate, or high likelihood of having PE. Clinical prediction models have been validated and are well established for the diagnosis of PE in symptomatic patients. They allow all physicians, whatever their expertise, to reliably determine the clinical pretest probability of PE, and thus safely manage their patients using diagnostic and therapeutic algorithms.

  8. [Predictive ability of clinical parameters of bacteremia in hemodialysed patients].

    PubMed

    Egea, Ana L; Vilaró, Mario; De la Fuente, Jorge; Cuestas, Eduardo; Bongiovanni, María E

    2012-01-01

    No clinical events to differentiate bacteteremia from other pathologies in hemodialysis patients therefore the physicians makes diagnosis and treatment decisions based on clinical evidence an local epidemiology. the aim of this work was to study the frequency of microorganism isolated from blood culture of hemodialysis patients with suspected bacteraemia and evaluate Sensitivity (S) and Specificity (E) of medical diagnostic orientation in this cases of suspected Materials and methods: we performed an observational and prospective study for one year in hemodialysis patient with suspected bacteremia. We evaluated blood pressure, temperature (Tº), altered conscious state (AEC), respiratory frequency (FR), chills (ESC),diarrhea (DIARR), blood culture results and microbiological identification. We work with the mean ± standar desviation for continuous variables and frequencies for categorical variables We analyzed S, E, negative predictive value (VPN), positive predictive value (VPP) RESULTADOS: a total of 87 events with suspected bacteremia 34 (39%) were confirmed with positive blood culture the most common microorganisms were cocci Gram positive (CGP) 65%, Most relevant clinical variables were PCP ≥ 2 (VPN 81%), Tº ≥ 38 (VPN 76%) and AEC (E 98% y VPP 80%). CGP were the most prevalent microorganisms None of the clinical variables shows high S and E indicating low usefulness as a predictive tool of bacteremia Excepting AEC with E98% and VPP 80% but it would be necessary to evaluate this variable with a more number patient. Results justify to routine HC use like diagnostic tool.

  9. Can simple clinical tests predict walking ability after prosthetic rehabilitation?

    PubMed

    Sansam, Kate; O'Connor, Rory J; Neumann, Vera; Bhakta, Bipin

    2012-11-01

    To investigate whether simple clinical measures can predict walking ability after lower limb prosthetic rehabilitation. Prospective observational study. Ninety five adults who were assessed as suitable for lower limb prosthetic rehabilitation by the multidisciplinary team. Information regarding baseline clinical factors (amputation details, comorbidities, physical ability, mood and cognitive ability) was collected prior to provision of the prosthesis. Backward step linear regression was used to identify factors predictive of performance on the Timed Up and Go test following rehabilitation. Seventy one participants were able to complete this walking test and were included in the final analysis. The backward step regression model had an adjusted R2 of 0.588 and comprised 6 factors: age (p = 0.002), gender (p = 0.027), level of amputation (p = 0.000), presence of contracture (p = 0.088), ability to stand on one leg (p = 0.062) and Trail Making Tests A + B (p = 0.047), a test of cognitive flexibility. Cause of amputation (dysvascular or non-dysvascular) was not an independent predictor of walking outcome. These results indicate that simple clinical assessments completed prior to prosthetic provision can be used to predict mobility outcome. These findings need to be validated in a larger population across other amputee rehabilitation services and if confirmed could easily be incorporated into routine clinical practice.

  10. Probabilistic prediction of barrier-island response to hurricanes

    USGS Publications Warehouse

    Plant, Nathaniel G.; Stockdon, Hilary F.

    2012-01-01

    Prediction of barrier-island response to hurricane attack is important for assessing the vulnerability of communities, infrastructure, habitat, and recreational assets to the impacts of storm surge, waves, and erosion. We have demonstrated that a conceptual model intended to make qualitative predictions of the type of beach response to storms (e.g., beach erosion, dune erosion, dune overwash, inundation) can be reformulated in a Bayesian network to make quantitative predictions of the morphologic response. In an application of this approach at Santa Rosa Island, FL, predicted dune-crest elevation changes in response to Hurricane Ivan explained about 20% to 30% of the observed variance. An extended Bayesian network based on the original conceptual model, which included dune elevations, storm surge, and swash, but with the addition of beach and dune widths as input variables, showed improved skill compared to the original model, explaining 70% of dune elevation change variance and about 60% of dune and shoreline position change variance. This probabilistic approach accurately represented prediction uncertainty (measured with the log likelihood ratio), and it outperformed the baseline prediction (i.e., the prior distribution based on the observations). Finally, sensitivity studies demonstrated that degrading the resolution of the Bayesian network or removing data from the calibration process reduced the skill of the predictions by 30% to 40%. The reduction in skill did not change conclusions regarding the relative importance of the input variables, and the extended model's skill always outperformed the original model.

  11. Early prediction of clinical benefit of treating ovarian cancer using quantitative CT image feature analysis.

    PubMed

    Qiu, Yuchen; Tan, Maxine; McMeekin, Scott; Thai, Theresa; Ding, Kai; Moore, Kathleen; Liu, Hong; Zheng, Bin

    2016-09-01

    In current clinical trials of treating ovarian cancer patients, how to accurately predict patients' response to the chemotherapy at an early stage remains an important and unsolved challenge. To investigate feasibility of applying a new quantitative image analysis method for predicting early response of ovarian cancer patients to chemotherapy in clinical trials. A dataset of 30 patients was retrospectively selected in this study, among which 12 were responders with 6-month progression-free survival (PFS) and 18 were non-responders. A computer-aided detection scheme was developed to segment tumors depicted on two sets of CT images acquired pre-treatment and 4-6 weeks post treatment. The scheme computed changes of three image features related to the tumor volume, density, and density variance. We analyzed performance of using each image feature and applying a decision tree to predict patients' 6-month PFS. The prediction accuracy of using quantitative image features was also compared with the clinical record based on the Response Evaluation Criteria in Solid Tumors (RECIST) guideline. The areas under receiver operating characteristic curve (AUC) were 0.773 ± 0.086, 0.680 ± 0.109, and 0.668 ± 0.101, when using each of three features, respectively. AUC value increased to 0.831 ± 0.078 when combining these features together. The decision-tree classifier achieved a higher predicting accuracy (76.7%) than using RECIST guideline (60.0%). This study demonstrated the potential of using a quantitative image feature analysis method to improve accuracy of predicting early response of ovarian cancer patients to the chemotherapy in clinical trials. © The Foundation Acta Radiologica 2015.

  12. Can Synovial Pathobiology Integrate with Current Clinical and Imaging Prediction Models to Achieve Personalized Health Care in Rheumatoid Arthritis?

    PubMed Central

    Humby, Frances Claire; Al Balushi, Farida; Lliso, Gloria; Cauli, Alberto; Pitzalis, Costantino

    2017-01-01

    Although great progress has been made in the past decade toward understanding the pathogenesis of rheumatoid arthritis (RA), clinicians remain some distance from a goal of personalized health care. The capacity to diagnose RA early, predict prognosis, and moreover predict response to biologic therapies has been a research focus for many years. How currently available clinical prediction models can facilitate such goals is reviewed in this article. In addition, the role of current imaging techniques in this regard is also discussed. Finally, the authors review the current literature regarding synovial biomarkers and consider whether integration of synovial pathobiology into clinical prediction algorithms may enhance their predictive value. PMID:28516086

  13. Clinical Gestalt and the Prediction of Massive Transfusion after Trauma

    PubMed Central

    Pommerening, Matthew J.; Goodman, Michael D.; Holcomb, John B.; Wade, Charles E.; Fox, Erin E.; del Junco, Deborah J.; Brasel, Karen J.; Bulger, Eileen M.; Cohen, Mitch J.; Alarcon, Louis H.; Schreiber, Martin A.; Myers, John G.; Phelan, Herb A.; Muskat, Peter; Rahbar, Mohammad; Cotton, Bryan A.

    2016-01-01

    Introduction Early recognition and treatment of trauma patients requiring massive transfusion (MT) has been shown to reduce mortality. While many risk factors predicting MT have been demonstrated, there is no universally accepted method or algorithm to identify these patients. We hypothesized that even among experienced trauma surgeons, the clinical gestalt of identifying patients who will require MT is unreliable. Methods Transfusion and mortality outcomes after trauma were observed at 10 U.S. Level-1 trauma centers in patients who survived ≥30 minutes after admission and received ≥1 unit of RBC within 6 hours of arrival. Subjects who received ≥ 10 units within 24 hours of admission were classified as MT patients. Trauma surgeons were asked the clinical gestalt question “Is the patient likely to be massively transfused?” ten minutes after the patients arrival. The performance of clinical gestalt to predict MT was assessed using chi-square tests and ROC analysis to compare gestalt to previously described scoring systems. Results Of the 1,245 patients enrolled, 966 met inclusion criteria and 221 (23%) patients received MT. 415 (43%) were predicted to have a MT and 551(57%) were predicted to not have MT. Patients predicted to have MT were younger, more often sustained penetrating trauma, had higher ISS scores, higher heart rates, and lower systolic blood pressures (all p < 0.05). Gestalt sensitivity was 65.6% and specificity was 63.8%. PPV and NPV were 34.9% and 86.2% respectively. Conclusion Data from this large multicenter trial demonstrates that predicting the need for MT continues to be a challenge. Because of the increased mortality associated with delayed therapy, a more reliable algorithm is needed to identify and treat these severely injured patients earlier. Level of Evidence II; Diagnostic study - Development of diagnostic criteria on basis of consecutive patients (with universally applied reference standard) PMID:25682314

  14. Clinical gestalt and the prediction of massive transfusion after trauma.

    PubMed

    Pommerening, Matthew J; Goodman, Michael D; Holcomb, John B; Wade, Charles E; Fox, Erin E; Del Junco, Deborah J; Brasel, Karen J; Bulger, Eileen M; Cohen, Mitch J; Alarcon, Louis H; Schreiber, Martin A; Myers, John G; Phelan, Herb A; Muskat, Peter; Rahbar, Mohammad; Cotton, Bryan A

    2015-05-01

    Early recognition and treatment of trauma patients requiring massive transfusion (MT) has been shown to reduce mortality. While many risk factors predicting MT have been demonstrated, there is no universally accepted method or algorithm to identify these patients. We hypothesised that even among experienced trauma surgeons, the clinical gestalt of identifying patients who will require MT is unreliable. Transfusion and mortality outcomes after trauma were observed at 10 U.S. Level-1 trauma centres in patients who survived ≥ 30 min after admission and received ≥ 1 unit of RBC within 6h of arrival. Subjects who received ≥ 10 units within 24h of admission were classified as MT patients. Trauma surgeons were asked the clinical gestalt question "Is the patient likely to be massively transfused?" 10 min after the patients arrival. The performance of clinical gestalt to predict MT was assessed using chi-square tests and ROC analysis to compare gestalt to previously described scoring systems. Of the 1245 patients enrolled, 966 met inclusion criteria and 221 (23%) patients received MT. 415 (43%) were predicted to have a MT and 551(57%) were predicted to not have MT. Patients predicted to have MT were younger, more often sustained penetrating trauma, had higher ISS scores, higher heart rates, and lower systolic blood pressures (all p<0.05). Gestalt sensitivity was 65.6% and specificity was 63.8%. PPV and NPV were 34.9% and 86.2% respectively. Data from this large multicenter trial demonstrates that predicting the need for MT continues to be a challenge. Because of the increased mortality associated with delayed therapy, a more reliable algorithm is needed to identify and treat these severely injured patients earlier. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Long‐Term Post‐CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions

    PubMed Central

    Carr, Brendan M.; Romeiser, Jamie; Ruan, Joyce; Gupta, Sandeep; Seifert, Frank C.; Zhu, Wei

    2015-01-01

    Abstract Background/aim Clinical risk models are commonly used to predict short‐term coronary artery bypass grafting (CABG) mortality but are less commonly used to predict long‐term mortality. The added value of long‐term mortality clinical risk models over traditional actuarial models has not been evaluated. To address this, the predictive performance of a long‐term clinical risk model was compared with that of an actuarial model to identify the clinical variable(s) most responsible for any differences observed. Methods Long‐term mortality for 1028 CABG patients was estimated using the Hannan New York State clinical risk model and an actuarial model (based on age, gender, and race/ethnicity). Vital status was assessed using the Social Security Death Index. Observed/expected (O/E) ratios were calculated, and the models' predictive performances were compared using a nested c‐index approach. Linear regression analyses identified the subgroup of risk factors driving the differences observed. Results Mortality rates were 3%, 9%, and 17% at one‐, three‐, and five years, respectively (median follow‐up: five years). The clinical risk model provided more accurate predictions. Greater divergence between model estimates occurred with increasing long‐term mortality risk, with baseline renal dysfunction identified as a particularly important driver of these differences. Conclusions Long‐term mortality clinical risk models provide enhanced predictive power compared to actuarial models. Using the Hannan risk model, a patient's long‐term mortality risk can be accurately assessed and subgroups of higher‐risk patients can be identified for enhanced follow‐up care. More research appears warranted to refine long‐term CABG clinical risk models. doi: 10.1111/jocs.12665 (J Card Surg 2016;31:23–30) PMID:26543019

  16. Neoadjuvant treatment for advanced esophageal cancer: response assessment before surgery and how to predict response to chemoradiation before starting treatment

    PubMed Central

    Hölscher, Arnulf H.; Schmidt, Matthias; Warnecke-Eberz, Ute

    2015-01-01

    Patients with advanced esophageal cancer (T3-4, N) have a poor prognosis. Chemoradiation or chemotherapy before esophagectomy with adequate lymphadenectomy is the standard treatment for patients with resectable advanced esophageal carcinoma. However, only patients with major histopathologic response (regression to less than 10% of the primary tumor) after preoperative treatment will have a prognostic benefit of preoperative chemoradiation. Using current therapy regimens about 40% to 50% of the patients show major histopathological response. The remaining cohort does not benefit from this neoadjuvant approach but might benefit from earlier surgical resection. Therefore, it is an aim to develop tools for response prediction before starting the treatment and for early response assessment identifying responders. The current review discusses the different imaging techniques and the most recent studies about molecular markers for early response prediction. The results show that [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET) has a good sensitivity but the specificity is not robust enough for routine clinical use. Newer positron emission tomography detector technology, the combination of FDG-PET with computed tomography, additional evaluation criteria and standardization of evaluation may improve the predictive value. There exist a great number of retrospective studies using molecular markers for prediction of response. Until now the clinical use is missing. But the results of first prospective studies are promising. A future perspective may be the combination of imaging technics and special molecular markers for individualized therapy. Another aspect is the response assessment after finishing neoadjuvant treatment protocol. The different clinical methods are discussed. The results show that until now no non-invasive method is valid enough to assess complete histopathological response. PMID:26157318

  17. Fracture prediction from repeat BMD measurements in clinical practice.

    PubMed

    Leslie, W D; Brennan-Olsen, S L; Morin, S N; Lix, L M

    2016-01-01

    We investigated whether repeat BMD measurements in clinical populations are useful for fracture risk assessment. We report that repeat BMD measurements are a robust predictor of fracture in clinical populations; this is not affected by preceding BMD change or recent osteoporosis therapy. In clinical practice, many patients selectively undergo repeat bone mineral density (BMD) measurements. We investigated whether repeat BMD measurements in clinical populations are useful for fracture risk assessment and whether this is affected by preceding change in BMD or recent osteoporosis therapy. We identified women and men aged ≥ 50 years who had a BMD measurement during 1990-2009 from a large clinical BMD database for Manitoba, Canada (n = 50,215). Patient subgroups aged ≥ 50 years at baseline with repeat BMD measures were identified. Data were linked to an administrative data repository, from which osteoporosis therapy, fracture outcomes, and covariates were extracted. Using Cox proportional hazards models, we assessed covariate-adjusted risk for major osteoporotic fracture (MOF) and hip fracture according to BMD (total hip, lumbar spine, femoral neck) at different time points. Prevalence of osteoporosis therapy increased from 18 % at baseline to 55 % by the fourth measurement. Total hip BMD was predictive of MOF at each time point. In the patient subgroup with two repeat BMD measurements (n = 13,481), MOF prediction with the first and second measurements was similar: adjusted-hazard ratio (HR) per SD 1.45 (95 % CI 1.34-1.56) vs. 1.64 (95 % CI 1.48-1.81), respectively. No differences were seen when the second measurement results were stratified by preceding change in BMD or osteoporosis therapy (both p-interactions >0.2). Similar results were seen for hip fracture prediction and when spine and femoral neck BMD were analyzed. Repeat BMD measurements are a robust predictor of fracture in clinical populations; this is not affected by preceding BMD change or recent

  18. Variability in pathogenicity prediction programs: impact on clinical diagnostics

    PubMed Central

    Walters-Sen, Lauren C; Hashimoto, Sayaka; Thrush, Devon Lamb; Reshmi, Shalini; Gastier-Foster, Julie M; Astbury, Caroline; Pyatt, Robert E

    2015-01-01

    Current practice by clinical diagnostic laboratories is to utilize online prediction programs to help determine the significance of novel variants in a given gene sequence. However, these programs vary widely in their methods and ability to correctly predict the pathogenicity of a given sequence change. The performance of 17 publicly available pathogenicity prediction programs was assayed using a dataset consisting of 122 credibly pathogenic and benign variants in genes associated with the RASopathy family of disorders and limb-girdle muscular dystrophy. Performance metrics were compared between the programs to determine the most accurate program for loss-of-function and gain-of-function mechanisms. No one program correctly predicted the pathogenicity of all variants analyzed. A major hindrance to the analysis was the lack of output from a significant portion of the programs. The best performer was MutPred, which had a weighted accuracy of 82.6% in the full dataset. Surprisingly, combining the results of the top three programs did not increase the ability to predict pathogenicity over the top performer alone. As the increasing number of sequence changes in larger datasets will require interpretation, the current study demonstrates that extreme caution must be taken when reporting pathogenicity based on statistical online protein prediction programs in the absence of functional studies. PMID:25802880

  19. Predicting Treatment Response in Social Anxiety Disorder From Functional Magnetic Resonance Imaging

    PubMed Central

    Doehrmann, Oliver; Ghosh, Satrajit S.; Polli, Frida E.; Reynolds, Gretchen O.; Horn, Franziska; Keshavan, Anisha; Triantafyllou, Christina; Saygin, Zeynep M.; Whitfield-Gabrieli, Susan; Hofmann, Stefan G.; Pollack, Mark; Gabrieli, John D.

    2013-01-01

    Context Current behavioral measures poorly predict treatment outcome in social anxiety disorder (SAD). To our knowledge, this is the first study to examine neuroimaging-based treatment prediction in SAD. Objective To measure brain activation in patients with SAD as a biomarker to predict subsequent response to cognitive behavioral therapy (CBT). Design Functional magnetic resonance imaging (fMRI) data were collected prior to CBT intervention. Changes in clinical status were regressed on brain responses and tested for selectivity for social stimuli. Setting Patients were treated with protocol-based CBT at anxiety disorder programs at Boston University or Massachusetts General Hospital and underwent neuroimaging data collection at Massachusetts Institute of Technology. Patients Thirty-nine medication-free patients meeting DSM-IV criteria for the generalized subtype of SAD. Interventions Brain responses to angry vs neutral faces or emotional vs neutral scenes were examined with fMRI prior to initiation of CBT. Main Outcome Measures Whole-brain regression analyses with differential fMRI responses for angry vs neutral faces and changes in Liebowitz Social Anxiety Scale score as the treatment outcome measure. Results Pretreatment responses significantly predicted subsequent treatment outcome of patients selectively for social stimuli and particularly in regions of higher-order visual cortex. Combining the brain measures with information on clinical severity accounted for more than 40% of the variance in treatment response and substantially exceeded predictions based on clinical measures at baseline. Prediction success was unaffected by testing for potential confounding factors such as depression severity at baseline. Conclusions The results suggest that brain imaging can provide biomarkers that substantially improve predictions for the success of cognitive behavioral interventions and more generally suggest that such biomarkers may offer evidence-based, personalized

  20. Predicting treatment response in social anxiety disorder from functional magnetic resonance imaging.

    PubMed

    Doehrmann, Oliver; Ghosh, Satrajit S; Polli, Frida E; Reynolds, Gretchen O; Horn, Franziska; Keshavan, Anisha; Triantafyllou, Christina; Saygin, Zeynep M; Whitfield-Gabrieli, Susan; Hofmann, Stefan G; Pollack, Mark; Gabrieli, John D

    2013-01-01

    Current behavioral measures poorly predict treatment outcome in social anxiety disorder (SAD). To our knowledge, this is the first study to examine neuroimaging-based treatment prediction in SAD. To measure brain activation in patients with SAD as a biomarker to predict subsequent response to cognitive behavioral therapy (CBT). Functional magnetic resonance imaging (fMRI) data were collected prior to CBT intervention. Changes in clinical status were regressed on brain responses and tested for selectivity for social stimuli. Patients were treated with protocol-based CBT at anxiety disorder programs at Boston University or Massachusetts General Hospital and underwent neuroimaging data collection at Massachusetts Institute of Technology. Thirty-nine medication-free patients meeting DSM-IV criteria for the generalized subtype of SAD. Brain responses to angry vs neutral faces or emotional vs neutral scenes were examined with fMRI prior to initiation of CBT. Whole-brain regression analyses with differential fMRI responses for angry vs neutral faces and changes in Liebowitz Social Anxiety Scale score as the treatment outcome measure. Pretreatment responses significantly predicted subsequent treatment outcome of patients selectively for social stimuli and particularly in regions of higher-order visual cortex. Combining the brain measures with information on clinical severity accounted for more than 40% of the variance in treatment response and substantially exceeded predictions based on clinical measures at baseline. Prediction success was unaffected by testing for potential confounding factors such as depression severity at baseline. The results suggest that brain imaging can provide biomarkers that substantially improve predictions for the success of cognitive behavioral interventions and more generally suggest that such biomarkers may offer evidence-based, personalized medicine approaches for optimally selecting among treatment options for a patient.

  1. Drug-induced death signaling strategy rapidly predicts cancer response to chemotherapy

    PubMed Central

    Montero, Joan; Sarosiek, Kristopher A.; DeAngelo, Joseph D.; Maertens, Ophélia; Ryan, Jeremy; Ercan, Dalia; Piao, Huiying; Horowitz, Neil S.; Berkowitz, Ross S.; Matulonis, Ursula; Jänne, Pasi A.; Amrein, Philip C.; Cichowski, Karen; Drapkin, Ronny; Letai, Anthony

    2015-01-01

    SUMMARY There is a lack of effective predictive biomarkers to precisely assign optimal therapy to cancer patients. While most efforts are directed at inferring drug response phenotype based on genotype, there is very focused and useful phenotypic information to be gained from directly perturbing the patient’s living cancer cell with the drug(s) in question. To satisfy this unmet need we developed the Dynamic BH3 Profiling technique to measure early changes in net pro-apoptotic signaling at the mitochondrion (‘priming’) induced by chemotherapeutic agents in cancer cells, not requiring prolonged ex vivo culture. We find in cell line and clinical experiments that early drug-induced death signaling measured by Dynamic BH3 Profiling predicts chemotherapy response across many cancer types and many agents, including combinations of chemotherapies. We propose that Dynamic BH3 Profiling can be used as a broadly applicable predictive biomarker to predict cytotoxic response of cancers to chemotherapeutics in vivo. PMID:25723171

  2. Clinical prediction and the idea of a population.

    PubMed

    Armstrong, David

    2017-01-01

    Using an analysis of the British Medical Journal over the past 170 years, this article describes how changes in the idea of a population have informed new technologies of medical prediction. These approaches have largely replaced older ideas of clinical prognosis based on understanding the natural histories of the underlying pathologies. The 19(th)-century idea of a population, which provided a denominator for medical events such as births and deaths, was constrained in its predictive power by its method of enumerating individual bodies. During the 20(th) century, populations were increasingly constructed through inferential techniques based on patient groups and samples seen to possess variable characteristics. The emergence of these new virtual populations created the conditions for the emergence of predictive algorithms that are used to foretell our medical futures.

  3. Predicting response and survival in chemotherapy-treated triple-negative breast cancer

    PubMed Central

    Prat, A; Lluch, A; Albanell, J; Barry, W T; Fan, C; Chacón, J I; Parker, J S; Calvo, L; Plazaola, A; Arcusa, A; Seguí-Palmer, M A; Burgues, O; Ribelles, N; Rodriguez-Lescure, A; Guerrero, A; Ruiz-Borrego, M; Munarriz, B; López, J A; Adamo, B; Cheang, M C U; Li, Y; Hu, Z; Gulley, M L; Vidal, M J; Pitcher, B N; Liu, M C; Citron, M L; Ellis, M J; Mardis, E; Vickery, T; Hudis, C A; Winer, E P; Carey, L A; Caballero, R; Carrasco, E; Martín, M; Perou, C M; Alba, E

    2014-01-01

    Background: In this study, we evaluated the ability of gene expression profiles to predict chemotherapy response and survival in triple-negative breast cancer (TNBC). Methods: Gene expression and clinical–pathological data were evaluated in five independent cohorts, including three randomised clinical trials for a total of 1055 patients with TNBC, basal-like disease (BLBC) or both. Previously defined intrinsic molecular subtype and a proliferation signature were determined and tested. Each signature was tested using multivariable logistic regression models (for pCR (pathological complete response)) and Cox models (for survival). Within TNBC, interactions between each signature and the basal-like subtype (vs other subtypes) for predicting either pCR or survival were investigated. Results: Within TNBC, all intrinsic subtypes were identified but BLBC predominated (55–81%). Significant associations between genomic signatures and response and survival after chemotherapy were only identified within BLBC and not within TNBC as a whole. In particular, high expression of a previously identified proliferation signature, or low expression of the luminal A signature, was found independently associated with pCR and improved survival following chemotherapy across different cohorts. Significant interaction tests were only obtained between each signature and the BLBC subtype for prediction of chemotherapy response or survival. Conclusions: The proliferation signature predicts response and improved survival after chemotherapy, but only within BLBC. This highlights the clinical implications of TNBC heterogeneity, and suggests that future clinical trials focused on this phenotypic subtype should consider stratifying patients as having BLBC or not. PMID:25101563

  4. Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

    DOE PAGES

    Thomas, Edward V.; Lewis, John. R.; Anderson-Cook, Christine Michaela; ...

    2017-07-01

    The inverse prediction is important in a variety of scientific and engineering applications, such as to predict properties/characteristics of an object by using multiple measurements obtained from it. Inverse prediction can be accomplished by inverting parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are computational/science based; but often, forward models are empirically based response surface models, obtained by using the results of controlled experimentation. For empirical models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). And while nature dictatesmore » the causal relationships between factors and responses, experimenters can control the complexity, accuracy, and precision of forward models constructed via selection of factors, factor levels, and the set of trials that are performed. Recognition of the uncertainty in the estimated forward models leads to an errors-in-variables approach for inverse prediction. The forward models (estimated by experiments or science based) can also be used to analyze how well candidate responses complement one another for inverse prediction over the range of the factor space of interest. Furthermore, one may find that some responses are complementary, redundant, or noninformative. Simple analysis and examples illustrate how an informative and discriminating subset of responses could be selected among candidates in cases where the number of responses that can be acquired during inverse prediction is limited by difficulty, expense, and/or availability of material.« less

  5. Identifying a predictive model for response to atypical antipsychotic monotherapy treatment in south Indian schizophrenia patients.

    PubMed

    Gupta, Meenal; Moily, Nagaraj S; Kaur, Harpreet; Jajodia, Ajay; Jain, Sanjeev; Kukreti, Ritushree

    2013-08-01

    Atypical antipsychotic (AAP) drugs are the preferred choice of treatment for schizophrenia patients. Patients who do not show favorable response to AAP monotherapy are subjected to random prolonged therapeutic treatment with AAP multitherapy, typical antipsychotics or a combination of both. Therefore, prior identification of patients' response to drugs can be an important step in providing efficacious and safe therapeutic treatment. We thus attempted to elucidate a genetic signature which could predict patients' response to AAP monotherapy. Our logistic regression analyses indicated the probability that 76% patients carrying combination of four SNPs will not show favorable response to AAP therapy. The robustness of this prediction model was assessed using repeated 10-fold cross validation method, and the results across n-fold cross-validations (mean accuracy=71.91%; 95%CI=71.47-72.35) suggest high accuracy and reliability of the prediction model. Further validations of these results in large sample sets are likely to establish their clinical applicability.

  6. Both Financial and Cognitive Decline Predict Clinical Progression in MCI

    PubMed Central

    Gerstenecker, Adam; Triebel, Kristen L.; Martin, Roy; Snyder, Scott; Marson, Daniel C.

    2015-01-01

    We investigated the roles of financial/functional and cognitive abilities in predicting clinical progression in patients with mild cognitive impairment (MCI). In a longitudinal sample of 51 patients with consensus-conference diagnosed MCI likely due to Alzheimer’s disease (AD). Two-year change scores were calculated for a performance measure of functional ability, cognitive variables, and three outcome measures used to track progression in neurologic disorders. We examined patterns of financial and cognitive decline across the two-year study period, and used this data and the three outcome variables to construct discrete predictor models of clinical progression in MCI. We found that both financial skills and cognitive abilities declined over the two-year study period, were significantly associated with clinical progression, and contributed unique variance all three predictor models. The resulting models accounted for 40–75% of variance in clinical progression across outcome variables. Taken together, our results indicate that changes in both cognitive abilities and higher-order functional skills appear integral to understanding clinical progression in MCI likely due to AD. Specifically, declines in financial skills contribute unique variance to measures commonly used to track progression in neurological disorders associated with aging and thus represent an important functional marker of clinical progression in prodromal AD. PMID:26900988

  7. Both Financial and Cognitive Decline Predict Clinical Progression in MCI.

    PubMed

    Gerstenecker, Adam; Triebel, Kristen L; Martin, Roy; Snyder, Scott; Marson, Daniel C

    2016-01-01

    We investigated the roles of financial/functional and cognitive abilities in predicting clinical progression in patients with mild cognitive impairment (MCI). In a longitudinal sample of 51 patients with consensus conference diagnosed MCI likely due to Alzheimer disease (AD), two-year change scores were calculated for a performance measure of functional ability, cognitive variables, and 3 outcome measures used to track progression in neurological disorders. We examined patterns of financial and cognitive decline across the 2-year study period, and used these data and the 3 outcome variables to construct discrete predictor models of clinical progression in MCI. We found that both financial skills and cognitive abilities declined over the 2-year study period, were significantly associated with clinical progression, and contributed unique variance to all 3 predictor models. The resulting models accounted for 40% to 75% of variance in clinical progression across outcome variables. Taken together, our results indicate that changes in both cognitive abilities and higher order functional skills appear integral to understanding clinical progression in MCI likely due to AD. Specifically, declines in financial skills contribute unique variance to measures commonly used to track progression in neurological disorders associated with aging, and thus represent an important functional marker of clinical progression in prodromal AD.

  8. How to predict clinical relapse in inflammatory bowel disease patients

    PubMed Central

    Liverani, Elisa; Scaioli, Eleonora; Digby, Richard John; Bellanova, Matteo; Belluzzi, Andrea

    2016-01-01

    Inflammatory bowel diseases have a natural course characterized by alternating periods of remission and relapse. Disease flares occur in a random way and are currently unpredictable for the most part. Predictors of benign or unfavourable clinical course are required to facilitate treatment decisions and to avoid overtreatment. The present article provides a literature review of the current evidence on the main clinical, genetic, endoscopic, histologic, serologic and fecal markers to predict aggressiveness of inflammatory bowel disease and discuss their prognostic role, both in Crohn’s disease and ulcerative colitis. No single marker seems to be reliable alone as a flare predictor, even in light of promising evidence regarding the role of fecal markers, in particular fecal calprotectin, which has reported good results recently. In order to improve our daily clinical practice, validated prognostic scores should be elaborated, integrating clinical and biological markers of prognosis. Finally, we propose an algorithm considering clinical history and biological markers to intercept patients with high risk of clinical relapse. PMID:26811644

  9. Predicted ball grid array thermal response during reflow soldering

    SciTech Connect

    Voth, T.E.; Bergman, T.L.

    1995-12-31

    A numerical model is developed to predict the detailed thermomechanical response of a BGA assembly during reflow soldering. The governing coupled solid mechanics and heat diffusion equations are solved using a commercially available finite element package. Reported predictions illustrate the system`s sensitivity to both thermal and mechanical processing conditions, as well as component thermal properties. Specifically, assemblies with components of high thermal conductivity show the greatest sensitivity to mechanical loading conditions.

  10. Accuracy of physical examination, ultrasonography, and magnetic resonance imaging in predicting response to neo-adjuvant chemotherapy for breast cancer.

    PubMed

    Chen, Man; Zhan, Wei-Wei; Han, Bao-San; Fei, Xiao-Chun; Jin, Xiao-Long; Chai, Wei-Min; Wang, Deng-Bing; Shen, Kun-Wei; Wang, Wen-Ping

    2012-06-01

    Accurate evaluation of response following chemotherapy treatment is essential for surgical decision making in patients with breast cancer. Modalities that have been used to monitor response to neo-adjuvant chemotherapy (NAC) include physical examination (PE), ultrasound (US), and magnetic resonance imaging (MRI). The purpose of this study was to evaluate the accuracy of PE, US, and MRI in predicting the response to NAC in patients with breast cancer. According to the response evaluation criteria in solid tumors guidelines, the largest unidimensional measurement of the tumor diameter evaluated by PE, US, and MRI before and after NAC was classified into four grades, including clinical complete response, clinical partial response, clinical progressive disease, clinical stable disease, and compared with the final histopathological examination. Of the 64 patients who received NAC, the pathologic complete response (pCR) was shown in 13 of 64 patients (20%). The sensitivity of PE, US, and MRI in predicting the major pathologic response was 73%, 75%, and 80%, respectively, and the specificity was 45%, 50%, and 50% respectively. For predicting a pCR, the sensitivity of PE, US, and MRI was 46%, 46%, and 39%, respectively, and the specificity was 65%, 98%, and 92% respectively. Compared with final pathologic findings, all these three clinical and imaging modalities tended to obviously underestimate the pCR rate. A more appropriate, universal, and practical standard by clinical and imaging modalities in predicting the response to neo-adjuvant chemotherapy in vivo is essential.

  11. Biological and clinical evidence for somatic mutations in BRCA1 and BRCA2 as predictive markers for olaparib response in high-grade serous ovarian cancers in the maintenance setting.

    PubMed

    Dougherty, Brian A; Lai, Zhongwu; Hodgson, Darren R; Orr, Maria C M; Hawryluk, Matthew; Sun, James; Yelensky, Roman; Spencer, Stuart K; Robertson, Jane D; Ho, Tony W; Fielding, Anitra; Ledermann, Jonathan A; Barrett, J Carl

    2017-07-04

    To gain a better understanding of the role of somatic mutations in olaparib response, next-generation sequencing (NGS) of BRCA1 and BRCA2 was performed as part of a planned retrospective analysis of tumors from a randomized, double-blind, Phase II trial (Study 19; D0810C00019; NCT00753545) in 265 patients with platinum-sensitive high-grade serous ovarian cancer. BRCA1/2 loss-of-function mutations were found in 55% (114/209) of tumors, were mutually exclusive, and demonstrated high concordance with Sanger-sequenced germline mutations in matched blood samples, confirming the accuracy (97%) of tumor BRCA1/2 NGS testing. Additionally, NGS identified somatic mutations absent from germline testing in 10% (20/209) of the patients. Somatic mutations had >80% biallelic inactivation frequency and were predominantly clonal, suggesting that BRCA1/2 loss occurs early in the development of these cancers. Clinical outcomes between placebo- and olaparib-treated patients with somatic BRCA1/2 mutations were similar to those with germline BRCA1/2 mutations, indicating that patients with somatic BRCA1/2 mutations benefit from treatment with olaparib.

  12. Clinical prediction rules for failed nonoperative reduction of intussusception.

    PubMed

    Khorana, Jiraporn; Patumanond, Jayanton; Ukarapol, Nuthapong; Laohapensang, Mongkol; Visrutaratna, Pannee; Singhavejsakul, Jesda

    2016-01-01

    The nonoperative reduction of intussusception in children can be performed safely if there are no contraindications. Many risk factors associated with failed reduction were defined. The aim of this study was to develop a scoring system for predicting the failure of nonoperative reduction using various determinants. The data were collected from Chiang Mai University Hospital and Siriraj Hospital from January 2006 to December 2012. Inclusion criteria consisted of patients with intussusception aged 0-15 years with no contraindications for nonoperative reduction. The clinical prediction rules were developed using significant risk factors from the multivariable analysis. A total of 170 patients with intussusception were included in the study. In the final analysis model, 154 patients were used for identifying the significant risk factors of failure of reduction. Ten factors clustering by the age of 3 years were identified and used for developing the clinical prediction rules, and the factors were as follows: body weight <12 kg (relative risk [RR] =1.48, P=0.004), duration of symptoms >48 hours (RR =1.26, P<0.001), vomiting (RR =1.63, P<0.001), rectal bleeding (RR =1.50, P<0.001), abdominal distension (RR =1.60, P=0.003), temperature >37.8°C (RR =1.51, P<0.001), palpable mass (RR =1.26, P<0.001), location of mass (left over right side RR =1.48, P<0.001), ultrasound showed poor prognostic signs (RR =1.35, P<0.001), and the method of reduction (hydrostatic over pneumatic, RR =1.34, P=0.023). Prediction scores ranged from 0 to 16. A high-risk group (scores 12-16) predicted a greater chance of reduction failure (likelihood ratio of positive [LR+] =18.22, P<0.001). A low-risk group (score 0-11) predicted a lower chance of reduction failure (LR+ =0.79, P<0.001). The performance of the scoring model was 80.68% (area under the receiver operating characteristic curve). This scoring guideline was used to predict the results of nonoperative reduction and forecast the prognosis of

  13. Clinical scales in progressive MS: predicting long-term disability.

    PubMed

    Bosma, Libertje V A E; Kragt, Jolijn J; Knol, Dirk L; Polman, Chris H; Uitdehaag, Bernard M J

    2012-03-01

    To determine which short-term changes on clinical scales including the Expanded Disability Status Scale (EDSS), Timed 25-Foot Walk (T25FW), 9-Hole Peg test (9HPT) and Guy's Neurological Disability Scale (GNDS) are most predictive of long-term outcome of disability as rated by the EDSS in progressive multiple sclerosis (MS). From a longitudinal database, all progressive patients, both primary (PP) and secondary (SP), were selected on the basis of at least two complete examinations being available within a time interval of 1-2 years (short-term change). All patients who fulfilled the selection criteria were invited for a third visit after an interval of at least 3 years (long-term outcome). We used ordinal logistic regression to see which early changes were most predictive of the long-term EDSS. 181 patients fulfilled the selection criteria. Early change on EDSS and T25FW were the best predictors of long-term EDSS; both were significant predictors in a 'single predictor' model. Early EDSS change was a slightly stronger single predictor (R(2) 0.38, Wald χ(2) 42.65, p < 0.001) compared with early T25FW change (R(2) 0.27, Wald χ(2) 12.35, p < 0.001). Adding early T25FW change to early EDSS change in a 'combined predictor' model improved prediction (p = 0.036). Both early change on EDSS and T25FW predict long-term EDSS with comparable strength. Early change on T25FW adds significant independent information and improves the prediction model with early EDSS change only. Therefore we support the use of early T25FW examinations in future clinical trials in progressive MS.

  14. Clinical chemistry in higher dimensions: Machine-learning and enhanced prediction from routine clinical chemistry data.

    PubMed

    Richardson, Alice; Signor, Ben M; Lidbury, Brett A; Badrick, Tony

    2016-11-01

    Big Data is having an impact on many areas of research, not the least of which is biomedical science. In this review paper, big data and machine learning are defined in terms accessible to the clinical chemistry community. Seven myths associated with machine learning and big data are then presented, with the aim of managing expectation of machine learning amongst clinical chemists. The myths are illustrated with four examples investigating the relationship between biomarkers in liver function tests, enhanced laboratory prediction of hepatitis virus infection, the relationship between bilirubin and white cell count, and the relationship between red cell distribution width and laboratory prediction of anaemia.

  15. Prediction and control of neural responses to pulsatile electrical stimulation

    NASA Astrophysics Data System (ADS)

    Campbell, Luke J.; Sly, David James; O'Leary, Stephen John

    2012-04-01

    This paper aims to predict and control the probability of firing of a neuron in response to pulsatile electrical stimulation of the type delivered by neural prostheses such as the cochlear implant, bionic eye or in deep brain stimulation. Using the cochlear implant as a model, we developed an efficient computational model that predicts the responses of auditory nerve fibers to electrical stimulation and evaluated the model's accuracy by comparing the model output with pooled responses from a group of guinea pig auditory nerve fibers. It was found that the model accurately predicted the changes in neural firing probability over time to constant and variable amplitude electrical pulse trains, including speech-derived signals, delivered at rates up to 889 pulses s-1. A simplified version of the model that did not incorporate adaptation was used to adaptively predict, within its limitations, the pulsatile electrical stimulus required to cause a desired response from neurons up to 250 pulses s-1. Future stimulation strategies for cochlear implants and other neural prostheses may be enhanced using similar models that account for the way that neural responses are altered by previous stimulation.

  16. Prediction and control of neural responses to pulsatile electrical stimulation.

    PubMed

    Campbell, Luke J; Sly, David James; O'Leary, Stephen John

    2012-04-01

    This paper aims to predict and control the probability of firing of a neuron in response to pulsatile electrical stimulation of the type delivered by neural prostheses such as the cochlear implant, bionic eye or in deep brain stimulation. Using the cochlear implant as a model, we developed an efficient computational model that predicts the responses of auditory nerve fibers to electrical stimulation and evaluated the model's accuracy by comparing the model output with pooled responses from a group of guinea pig auditory nerve fibers. It was found that the model accurately predicted the changes in neural firing probability over time to constant and variable amplitude electrical pulse trains, including speech-derived signals, delivered at rates up to 889 pulses s(-1). A simplified version of the model that did not incorporate adaptation was used to adaptively predict, within its limitations, the pulsatile electrical stimulus required to cause a desired response from neurons up to 250 pulses s(-1). Future stimulation strategies for cochlear implants and other neural prostheses may be enhanced using similar models that account for the way that neural responses are altered by previous stimulation.

  17. Thermo-mechanical response predictions for metal matrix composite laminates

    NASA Technical Reports Server (NTRS)

    Aboudi, J.; Hidde, J. S.; Herakovich, C. T.

    1991-01-01

    An analytical micromechanical model is employed for prediction of the stress-strain response of metal matrix composite laminates subjected to thermomechanical loading. The predicted behavior of laminates is based upon knowledge of the thermomechanical response of the transversely isotropic, elastic fibers and the elastic-viscoplastic, work-hardening matrix. The method is applied to study the behavior of silicon carbide/titanium metal matrix composite laminates. The response of laminates is compared with that of unidirectional lamina. The results demonstrate the effect of cooling from a stress-free temperature and the mismatch of thermal and mechanical properties of the constituent phases on the laminate's subsequent mechanical response. Typical results are presented for a variety of laminates subjected to monotonic tension, monotonic shear and cyclic tensile/compressive loadings.

  18. 42 CFR 493.1457 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 42 Public Health 5 2010-10-01 2010-10-01 false Standard; Clinical consultant responsibilities. 493... Testing Laboratories Performing High Complexity Testing § 493.1457 Standard; Clinical consultant responsibilities. The clinical consultant provides consultation regarding the appropriateness of the...

  19. 42 CFR 493.1419 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 42 Public Health 5 2010-10-01 2010-10-01 false Standard; Clinical consultant responsibilities. 493... Testing Laboratories Performing Moderate Complexity Testing § 493.1419 Standard; Clinical consultant responsibilities. The clinical consultant provides consultation regarding the appropriateness of the...

  20. 42 CFR 493.1419 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 42 Public Health 5 2012-10-01 2012-10-01 false Standard; Clinical consultant responsibilities. 493... Testing Laboratories Performing Moderate Complexity Testing § 493.1419 Standard; Clinical consultant responsibilities. The clinical consultant provides consultation regarding the appropriateness of the testing...

  1. 42 CFR 493.1457 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 42 Public Health 5 2013-10-01 2013-10-01 false Standard; Clinical consultant responsibilities. 493... Testing Laboratories Performing High Complexity Testing § 493.1457 Standard; Clinical consultant responsibilities. The clinical consultant provides consultation regarding the appropriateness of the testing...

  2. 42 CFR 493.1419 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 42 Public Health 5 2011-10-01 2011-10-01 false Standard; Clinical consultant responsibilities. 493... Testing Laboratories Performing Moderate Complexity Testing § 493.1419 Standard; Clinical consultant responsibilities. The clinical consultant provides consultation regarding the appropriateness of the testing...

  3. 42 CFR 493.1419 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 42 Public Health 5 2013-10-01 2013-10-01 false Standard; Clinical consultant responsibilities. 493... Testing Laboratories Performing Moderate Complexity Testing § 493.1419 Standard; Clinical consultant responsibilities. The clinical consultant provides consultation regarding the appropriateness of the testing...

  4. 42 CFR 493.1457 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 42 Public Health 5 2012-10-01 2012-10-01 false Standard; Clinical consultant responsibilities. 493... Testing Laboratories Performing High Complexity Testing § 493.1457 Standard; Clinical consultant responsibilities. The clinical consultant provides consultation regarding the appropriateness of the testing...

  5. 42 CFR 493.1419 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 42 Public Health 5 2014-10-01 2014-10-01 false Standard; Clinical consultant responsibilities. 493... Testing Laboratories Performing Moderate Complexity Testing § 493.1419 Standard; Clinical consultant responsibilities. The clinical consultant provides consultation regarding the appropriateness of the testing...

  6. 42 CFR 493.1457 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 42 Public Health 5 2011-10-01 2011-10-01 false Standard; Clinical consultant responsibilities. 493... Testing Laboratories Performing High Complexity Testing § 493.1457 Standard; Clinical consultant responsibilities. The clinical consultant provides consultation regarding the appropriateness of the testing...

  7. 42 CFR 493.1457 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 42 Public Health 5 2014-10-01 2014-10-01 false Standard; Clinical consultant responsibilities. 493... Testing Laboratories Performing High Complexity Testing § 493.1457 Standard; Clinical consultant responsibilities. The clinical consultant provides consultation regarding the appropriateness of the testing...

  8. Ventricular repolarization markers for predicting malignant arrhythmias in clinical practice

    PubMed Central

    Castro-Torres, Yaniel; Carmona-Puerta, Raimundo; Katholi, Richard E

    2015-01-01

    Malignant cardiac arrhythmias which result in sudden cardiac death may be present in individuals apparently healthy or be associated with other medical conditions. The way to predict their appearance represents a challenge for the medical community due to the tragic outcomes in most cases. In the last two decades some ventricular repolarization (VR) markers have been found to be useful to predict malignant cardiac arrhythmias in several clinical conditions. The corrected QT, QT dispersion, Tpeak-Tend, Tpeak-Tend dispersion and Tp-e/QT have been studied and implemented in clinical practice for this purpose. These markers are obtained from 12 lead surface electrocardiogram. In this review we discuss how these markers have demonstrated to be effective to predict malignant arrhythmias in medical conditions such as long and short QT syndromes, Brugada syndrome, early repolarization syndrome, acute myocardial ischemia, heart failure, hypertension, diabetes mellitus, obesity and highly trained athletes. Also the main pathophysiological mechanisms that explain the arrhythmogenic predisposition in these diseases and the basis for the VR markers are discussed. However, the same results have not been found in all conditions. Further studies are needed to reach a global consensus in order to incorporate these VR parameters in risk stratification of these patients. PMID:26301231

  9. Response to Lithium in Bipolar Disorder: Clinical and Genetic Findings

    PubMed Central

    2014-01-01

    The use of lithium is a cornerstone for preventing recurrences in bipolar disorder (BD). The response of patients with bipolar disorder to lithium has different levels of magnitude. About one-third of lithium-treated patients are excellent lithium responders (ELR), showing total prevention of the episodes. A number of clinical characteristics were delineated in patients with favorable response to lithium as regards to clinical course, family history of mood disorders, and psychiatric comorbidity. We have also demonstrated that temperamental features of hypomania (a hyperthymic temperament) and a lack of cognitive disorganization predict the best results of lithium prophylaxis. A degree of prevention against manic and depressive episodes has been regarded as an endophenotype for pharmacogenetic studies. The majority of data have been gathered from so-called “candidate” gene studies. The candidates were selected on the basis of neurobiology of bipolar disorder and mechanisms of lithium action including, among others, neurotransmission, intracellular signaling, neuroprotection or circadian rhythms. We demonstrated that response to lithium has been connected with the genotype of BDNF gene and serum BDNF levels and have shown that ELR have normal cognitive functions and serum BDNF levels, even after long-term duration of the illness. A number of genome-wide association studies (GWAS) of BD have been also performed in recent years, some of which also focused on lithium response. The Consortium on Lithium Genetics (ConLiGen) has established the large sample for performing the genome-wide association study (GWAS) of lithium response in BD, and the first results have already been published. PMID:24625017

  10. Response to lithium in bipolar disorder: clinical and genetic findings.

    PubMed

    Rybakowski, Janusz K

    2014-06-18

    The use of lithium is a cornerstone for preventing recurrences in bipolar disorder (BD). The response of patients with bipolar disorder to lithium has different levels of magnitude. About one-third of lithium-treated patients are excellent lithium responders (ELR), showing total prevention of the episodes. A number of clinical characteristics were delineated in patients with favorable response to lithium as regards to clinical course, family history of mood disorders, and psychiatric comorbidity. We have also demonstrated that temperamental features of hypomania (a hyperthymic temperament) and a lack of cognitive disorganization predict the best results of lithium prophylaxis. A degree of prevention against manic and depressive episodes has been regarded as an endophenotype for pharmacogenetic studies. The majority of data have been gathered from so-called "candidate" gene studies. The candidates were selected on the basis of neurobiology of bipolar disorder and mechanisms of lithium action including, among others, neurotransmission, intracellular signaling, neuroprotection or circadian rhythms. We demonstrated that response to lithium has been connected with the genotype of BDNF gene and serum BDNF levels and have shown that ELR have normal cognitive functions and serum BDNF levels, even after long-term duration of the illness. A number of genome-wide association studies (GWAS) of BD have been also performed in recent years, some of which also focused on lithium response. The Consortium on Lithium Genetics (ConLiGen) has established the large sample for performing the genome-wide association study (GWAS) of lithium response in BD, and the first results have already been published.

  11. Modeling and predicting community responses to events using cultural demographics

    NASA Astrophysics Data System (ADS)

    Jaenisch, Holger M.; Handley, James W.; Hicklen, Michael L.

    2007-04-01

    This paper describes a novel capability for modeling and predicting community responses to events (specifically military operations) related to demographics. Demographics in the form of words and/or numbers are used. As an example, State of Alabama annual demographic data for retail sales, auto registration, wholesale trade, shopping goods, and population were used; from which we determined a ranked estimate of the sensitivity of the demographic parameters on the cultural group response. Our algorithm and results are summarized in this paper.

  12. Implicit Learning Abilities Predict Treatment Response in Autism Spectrum Disorders

    DTIC Science & Technology

    2015-09-01

    2 AWARD NUMBER: W81XWH-14-1-0261 TITLE: Implicit Learning Abilities Predict Treatment Response in Autism Spectrum Disorders PRINCIPAL...Treatment Response in Autism Spectrum Disorders 5b. GRANT NUMBER W81XWH-14-1-0261 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER...for Autism Spectrum Disorder (ASD), but almost half of the children do not make significant gains. Implicit learning skills are integral to

  13. Labour induction at term: clinical, biophysical and molecular predictive factors.

    PubMed

    Riboni, Francesca; Garofalo, Greta; Pascoli, Irene; Vitulo, Anna; Dell'avanzo, Marinella; Battagliarin, Giuseppe; Paternoster, Delia

    2012-11-01

    The aim of this multicentric study is to compare clinical, biophysical and molecular parameters in the prediction of the success of labour induction with prostaglandins. We included 115 women, who underwent to labour induction at term with vaginal prostaglandin gel. We evaluated the diagnostic efficiency of endocervical phosphorylated insulin-like growth factor-binding protein (phIGFBP-1), cervicovaginal interleukins 6 (IL-6) and 8 (IL-8). We analyzed the transvaginal sonographic measurement of cervical length. A receiver-operating characteristics (ROC) curve was used to determine the most useful cut-off point. A multivariate logistic regression model was used to analyze the combination of significant predictive variables following univariate analysis. We analyzed all the data searching for the parameters that best predict the beginning of the active phase of labour within 12 h. 36.5 % of the patients delivered within 12 h. The Bishop score was >4 in the 43 % of patients with an active phase. The best cut-off values at ROC curves for cervical length, IL-6 and IL-8 were respectively 22 mm, 5 mg/dl and 20,237 mg/dl. At univariate analysis, all predictors of success, with the exception of IL-6, were significantly associated with the beginning of the active phase. Multivariate analysis of the Bishop score (OR 2.3), phIGFBP-1 test (OR 11.2) and IL-8 (OR 6.6) showed that the variables were independent and therefore useful in combination to predict the success of labour induction. The phIGFBP-1 test is a fast and easy test that can be used with Bishop score and IL-8 to reach an high positive predictive value in the prediction of the success of labour induction with prostaglandins.

  14. Predicting postoperative mortality after colorectal surgery: a novel clinical model.

    PubMed

    van der Sluis, F J; Espin, E; Vallribera, F; de Bock, G H; Hoekstra, H J; van Leeuwen, B L; Engel, A F

    2014-08-01

    The aim of this study was to develop and externally validate a clinically, practical and discriminative prediction model designed to estimate in-hospital mortality of patients undergoing colorectal surgery. All consecutive patients who underwent elective or emergency colorectal surgery from 1990 to 2005, at the Zaandam Medical Centre, The Netherlands, were included in this study. Multivariate logistic regression analysis was performed to estimate odds ratios (ORs) and 95% confidence intervals (CIs) linking the explanatory variables to the outcome variable in-hospital mortality, and a simplified Identification of Risk in Colorectal Surgery (IRCS) score was constructed. The model was validated in a population of patients who underwent colorectal surgery from 2005 to 2011 in Barcelona, Spain. Predictive performance was estimated by calculating the area under the receiver operating characteristic curve. The strongest predictors of in-hospital mortality were emergency surgery (OR = 6.7, 95% CI 4.7-9.5), tumour stage (OR = 3.2, 95% CI 2.8-4.6), age (OR = 13.1, 95% CI 6.6-26.0), pulmonary failure (OR = 4.9, 95% CI 3.3-7.1) and cardiac failure (OR = 3.7, 95% CI 2.6-5.3). These parameters were included in the prediction model and simplified scoring system. The IRCS model predicted in-hospital mortality and demonstrated a predictive performance of 0.83 (95% CI 0.79-0.87) in the validation population. In this population the predictive performance of the CR-POSSUM score was 0.76 (95% CI 0.71-0.81). The results of this study have shown that the IRCS score is a good predictor of in-hospital mortality after colorectal surgery despite the relatively low number of model parameters. Colorectal Disease © 2014 The Association of Coloproctology of Great Britain and Ireland.

  15. Predicting Response to Histone Deacetylase Inhibitors Using High-Throughput Genomics

    PubMed Central

    Geeleher, Paul; Loboda, Andrey; Lenkala, Divya; Wang, Fan; LaCroix, Bonnie; Karovic, Sanja; Wang, Jacqueline; Nebozhyn, Michael; Chisamore, Michael; Hardwick, James; Maitland, Michael L.

    2015-01-01

    Background: Many disparate biomarkers have been proposed as predictors of response to histone deacetylase inhibitors (HDI); however, all have failed when applied clinically. Rather than this being entirely an issue of reproducibility, response to the HDI vorinostat may be determined by the additive effect of multiple molecular factors, many of which have previously been demonstrated. Methods: We conducted a large-scale gene expression analysis using the Cancer Genome Project for discovery and generated another large independent cancer cell line dataset across different cancers for validation. We compared different approaches in terms of how accurately vorinostat response can be predicted on an independent out-of-batch set of samples and applied the polygenic marker prediction principles in a clinical trial. Results: Using machine learning, the small effects that aggregate, resulting in sensitivity or resistance, can be recovered from gene expression data in a large panel of cancer cell lines. This approach can predict vorinostat response accurately, whereas single gene or pathway markers cannot. Our analyses recapitulated and contextualized many previous findings and suggest an important role for processes such as chromatin remodeling, autophagy, and apoptosis. As a proof of concept, we also discovered a novel causative role for CHD4, a helicase involved in the histone deacetylase complex that is associated with poor clinical outcome. As a clinical validation, we demonstrated that a common dose-limiting toxicity of vorinostat, thrombocytopenia, can be predicted (r = 0.55, P = .004) several days before it is detected clinically. Conclusion: Our work suggests a paradigm shift from single-gene/pathway evaluation to simultaneously evaluating multiple independent high-throughput gene expression datasets, which can be easily extended to other investigational compounds where similar issues are hampering clinical adoption. PMID:26296641

  16. Clinical Experiences Are Not Predictive of Outcomes on the NATABOC Examination

    PubMed Central

    Turocy, Paula Sammarone; Comfort, Ronald E.; Perrin, David H.; Gieck, Joe H.

    2000-01-01

    Objective: To determine the efficacy of the National Athletic Trainers' Association Board of Certification (NATABOC) clinical experience requirements and individual student characteristics to predict candidate outcomes on the NATABOC certification examination. Design and Setting: For all subjects, we gathered survey information and examination scores. The survey information included age, sex, route to certification, previous athletic training and allied health experience, and clinical education experiences. Subjects: A total of 269 subjects, 22.25% of all first-time candidates for the June and November 1993 NATABOC examinations, were included in this study. Measurements: Data were analyzed for standard descriptive statistics and parametric linear regression and correlational relationships. Results: Total clinical hours, high-risk sport experiences, and previous athletic training experience were not predictive of examination outcomes. Although our results indicated a relationship between previous allied health experience and both outcome on the written section of the examination and age and outcome on the oral/practical section, these characteristics also were not predictive of examination outcomes. Conclusions: Gaining clinical experience hours in excess of 400 hours beyond the 800-or 1500-hour requirement may yield no greater benefit for an entry-level professional than less time. The quality, rather than the quantity, of clinical experiences should be evaluated. More emphasis should be placed on the achievement of an entry level of clinical competency, rather than on total hour collection. Also, because high-risk sport experiences did not predict outcomes on the NATABOC examination, the emphasis of clinical education should be on students' receiving a more structured clinical experience, in which they are progressively required to assume greater responsibilities integrating both cognitive and psychomotor skills, while working under the supervision of a certified

  17. Posterior Predictive Assessment of Item Response Theory Models

    ERIC Educational Resources Information Center

    Sinharay, Sandip; Johnson, Matthew S.; Stern, Hal S.

    2006-01-01

    Model checking in item response theory (IRT) is an underdeveloped area. There is no universally accepted tool for checking IRT models. The posterior predictive model-checking method is a popular Bayesian model-checking tool because it has intuitive appeal, is simple to apply, has a strong theoretical basis, and can provide graphical or numerical…

  18. Posterior Predictive Model Checking for Multidimensionality in Item Response Theory

    ERIC Educational Resources Information Center

    Levy, Roy; Mislevy, Robert J.; Sinharay, Sandip

    2009-01-01

    If data exhibit multidimensionality, key conditional independence assumptions of unidimensional models do not hold. The current work pursues posterior predictive model checking, a flexible family of model-checking procedures, as a tool for criticizing models due to unaccounted for dimensions in the context of item response theory. Factors…

  19. Characteristics Predicting Children's Responses to Sexual Encounters with Other Children.

    ERIC Educational Resources Information Center

    Haugaard, Jeffrey J.; Tilly, Christina

    1988-01-01

    Undergraduates (N=1000) were surveyed concerning childhood sexual encounters. Forty-two percent of subjects reported a childhood sexual encounter with another child. High levels of coercion from the other child, homosexual encounters, and encounters with those other than friends predicted a more negative response by the child. (Author/DB)

  20. Predicting the response of populations to environmental change

    SciTech Connect

    Ives, A.R.

    1995-04-01

    When subject to long-term directional environmental perturbations, changes in population densities depend on the positive and negative feedbacks operating through interactions within and among species in a community. This paper develops techniques to predict the long-term responses of population densities to environmental changes using data on short-term population fluctuations driven by short-term environmental variability. In addition to giving quantitative predictions, the techniques also reveal how different qualitative patterns of species interactions either buffer or accentuate population responses to environmental trends. All of the predictions are based on regression coefficients extracted from time series data, and they can therefore be applied with a minimum of mathematical and statistical gymnastics. 48 refs., 10 figs., 4 tabs.

  1. Advanced Computational Modeling Approaches for Shock Response Prediction

    NASA Technical Reports Server (NTRS)

    Derkevorkian, Armen; Kolaini, Ali R.; Peterson, Lee

    2015-01-01

    Motivation: (1) The activation of pyroshock devices such as explosives, separation nuts, pin-pullers, etc. produces high frequency transient structural response, typically from few tens of Hz to several hundreds of kHz. (2) Lack of reliable analytical tools makes the prediction of appropriate design and qualification test levels a challenge. (3) In the past few decades, several attempts have been made to develop methodologies that predict the structural responses to shock environments. (4) Currently, there is no validated approach that is viable to predict shock environments overt the full frequency range (i.e., 100 Hz to 10 kHz). Scope: (1) Model, analyze, and interpret space structural systems with complex interfaces and discontinuities, subjected to shock loads. (2) Assess the viability of a suite of numerical tools to simulate transient, non-linear solid mechanics and structural dynamics problems, such as shock wave propagation.

  2. Parent Prediction of Child Mood and Emotional Resilience: The Role of Parental Responsiveness and Psychological Control

    PubMed Central

    Boughton, Kristy L.; Lumley, Margaret N.

    2011-01-01

    Research consistently shows low to moderate agreement between parent and child reports of child mood, suggesting that parents are not always the best predictors of child emotional functioning. This study examines parental responsiveness and psychological control for improving prediction of early adolescent mood and emotional resilience beyond parent report of child emotional functioning. Participants were 268 early adolescents administered measures of depression symptoms, emotional resilience, and perceptions of parenting. Parents of participating youth completed measures of youth emotional functioning. Parental responsiveness and psychological control each emerged as family variables that may be of value for predicting child emotional functioning beyond parent reports. Specifically, responsiveness explained significant variance in child depression and resilience after accounting for parent reports, while parental psychological control increased prediction of child mood alone. Results generally suggest that parenting behaviours may be an important consideration when children and parents provide discrepant reports of child emotional well-being. Conceptual and clinical implications of these results are discussed. PMID:22110912

  3. Personalized in vitro Cancer Models to Predict Therapeutic Response: Challenges and a Framework for Improvement

    PubMed Central

    Morgan, Molly M.; Johnson, Brian P.; Livingston, Megan K.; Schuler, Linda A.; Alarid, Elaine T.; Sung, Kyung E.; Beebe, David J.

    2017-01-01

    Personalized cancer therapy focuses on characterizing the relevant phenotypes of the patient, as well as the patient’s tumor, to predict the most effective cancer therapy. Historically, these methods have not proven predictive in regards to predicting therapeutic response. Emerging culture platforms are designed to better recapitulate the in vivo environment, thus, there is renewed interest in integrating patient samples into in vitro cancer models to assess therapeutic response. Successful examples of translating in vitro response to clinical relevance are limited due to issues with patient sample acquisition, variability and culture. We will review traditional and emerging in vitro models for personalized medicine, focusing on the technologies, microenvironmental components, and readouts utilized. We will then offer our perspective on how to apply a framework derived from toxicology and ecology towards designing improved personalized in vitro models of cancer. The framework serves as a tool for identifying optimal readouts and culture conditions, thus maximizing the information gained from each patient sample. PMID:27218886

  4. Parent prediction of child mood and emotional resilience: the role of parental responsiveness and psychological control.

    PubMed

    Boughton, Kristy L; Lumley, Margaret N

    2011-01-01

    Research consistently shows low to moderate agreement between parent and child reports of child mood, suggesting that parents are not always the best predictors of child emotional functioning. This study examines parental responsiveness and psychological control for improving prediction of early adolescent mood and emotional resilience beyond parent report of child emotional functioning. Participants were 268 early adolescents administered measures of depression symptoms, emotional resilience, and perceptions of parenting. Parents of participating youth completed measures of youth emotional functioning. Parental responsiveness and psychological control each emerged as family variables that may be of value for predicting child emotional functioning beyond parent reports. Specifically, responsiveness explained significant variance in child depression and resilience after accounting for parent reports, while parental psychological control increased prediction of child mood alone. Results generally suggest that parenting behaviours may be an important consideration when children and parents provide discrepant reports of child emotional well-being. Conceptual and clinical implications of these results are discussed.

  5. Prediction of the mortality dose-response relationship in man

    SciTech Connect

    Morris, M.D.; Jones, T.D.

    1987-01-01

    Based upon an extensive data base including 100 separate animal studies, an estimate of the mortality dose-response relationship due to continuous photon radiation is predicted for 70 kg man. The model used in this prediction exercise includes fixed terms accounting for effects of body weight and dose rate, and random terms accounting for inter- and intra-species variation and experimental error. Point predictions and 95% prediction intervals are given for the LD/sub 05/, LD/sub 10/, LD/sub 25/, LD/sub 50/, LD/sub 75/, LD/sub 90/, and LD/sub 95/, for dose rates ranging from 1 to 50 R/min. 6 refs., 5 tabs.

  6. Microtubule-Associated Protein Expression and Predicting Taxane Response

    DTIC Science & Technology

    2009-10-01

    taxanes. Our results indicate that MAP- tau functions as a prognostic factor in both the Yale cohort and the TAX 307 cohort with high MAP- tau ...expression associated with longer overall survival and TTP. Tau does NOT behave as a predictor of response to taxane-based chemotherapy since differences...between low and high MAP- tau groups by treatment arm and response rate were not observed in the TAX 307 clinical trial cohort. Our data supports the

  7. Tips for Teachers of Evidence-based Medicine: Clinical Prediction Rules (CPRs) and Estimating Pretest Probability

    PubMed Central

    McGinn, Thomas; Jervis, Ramiro; Wisnivesky, Juan; Keitz, Sheri

    2008-01-01

    Background Clinical prediction rules (CPR) are tools that clinicians can use to predict the most likely diagnosis, prognosis, or response to treatment in a patient based on individual characteristics. CPRs attempt to standardize, simplify, and increase the accuracy of clinicians’ diagnostic and prognostic assessments. The teaching tips series is designed to give teachers advice and materials they can use to attain specific educational objectives. Educational Objectives In this article, we present 3 teaching tips aimed at helping clinical learners use clinical prediction rules and to more accurately assess pretest probability in every day practice. The first tip is designed to demonstrate variability in physician estimation of pretest probability. The second tip demonstrates how the estimate of pretest probability influences the interpretation of diagnostic tests and patient management. The third tip exposes learners to various examples and different types of Clinical Prediction Rules (CPR) and how to apply them in practice. Pilot Testing We field tested all 3 tips with 16 learners, a mix of interns and senior residents. Teacher preparatory time was approximately 2 hours. The field test utilized a board and a data projector; 3 handouts were prepared. The tips were felt to be clear and the educational objectives reached. Potential teaching pitfalls were identified. Conclusion Teaching with these tips will help physicians appreciate the importance of applying evidence to their every day decisions. In 2 or 3 short teaching sessions, clinicians can also become familiar with the use of CPRs in applying evidence consistently in everyday practice. PMID:18491194

  8. Simplified Analysis Model for Predicting Pyroshock Responses on Composite Panel

    NASA Astrophysics Data System (ADS)

    Iwasa, Takashi; Shi, Qinzhong

    A simplified analysis model based on the frequency response analysis and the wave propagation analysis was established for predicting Shock Response Spectrum (SRS) on the composite panel subjected to pyroshock loadings. The complex composite panel was modeled as an isotropic single layer panel defined in NASA Lewis Method. Through the conductance of an impact excitation test on a composite panel with no equipment mounted on, it was presented that the simplified analysis model could estimate the SRS as well as the acceleration peak values in both near and far field in an accurate way. In addition, through the simulation for actual pyroshock tests on an actual satellite system, the simplified analysis model was proved to be applicable in predicting the actual pyroshock responses, while bringing forth several technical issues to estimate the pyroshock test specifications in early design stages.

  9. Prenatal cortisol exposure predicts infant cortisol response to acute stress.

    PubMed

    O'Connor, Thomas G; Bergman, Kristin; Sarkar, Pampa; Glover, Vivette

    2013-03-01

    Experimental animal findings suggest that early stress and glucocorticoid exposure may program the function of the hypothalamic-pituitary-adrenal (HPA) axis in the offspring. The extension of these findings to human development is not yet clear. A prospective longitudinal study was conducted on 125 mothers and their normally developing children. Amniotic fluid was obtained at, on average, 17.2 weeks gestation; infant behavior and cortisol response to a separation-reunion stress was assessed at 17 months. Amniotic fluid cortisol predicted infant cortisol response to separation-reunion stress: infants who were exposed to higher levels of cortisol in utero showed higher pre-stress cortisol values and blunted response to stress exposure. The association was independent of prenatal, obstetric, and socioeconomic factors and child-parent attachment. The findings provide some of the strongest data in humans that HPA axis functioning in the child may be predicted from prenatal cortisol exposure.

  10. Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

    PubMed

    Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

    2015-02-01

    Tumor genome sequencing leads to documenting thousands of DNA mutations and other genomic alterations. At present, these data cannot be analyzed adequately to aid in the understanding of tumorigenesis and its evolution. Moreover, we have little insight into how to use these data to predict clinical phenotypes and tumor progression to better design patient treatment. To meet these challenges, we discuss a cancer hallmark network framework for modeling genome sequencing data to predict cancer clonal evolution and associated clinical phenotypes. The framework includes: (1) cancer hallmarks that can be represented by a few molecular/signaling networks. 'Network operational signatures' which represent gene regulatory logics/strengths enable to quantify state transitions and measures of hallmark traits. Thus, sets of genomic alterations which are associated with network operational signatures could be linked to the state/measure of hallmark traits. The network operational signature transforms genotypic data (i.e., genomic alterations) to regulatory phenotypic profiles (i.e., regulatory logics/strengths), to cellular phenotypic profiles (i.e., hallmark traits) which lead to clinical phenotypic profiles (i.e., a collection of hallmark traits). Furthermore, the framework considers regulatory logics of the hallmark networks under tumor evolutionary dynamics and therefore also includes: (2) a self-promoting positive feedback loop that is dominated by a genomic instability network and a cell survival/proliferation network is the main driver of tumor clonal evolution. Surrounding tumor stroma and its host immune systems shape the evolutionary paths; (3) cell motility initiating metastasis is a byproduct of the above self-promoting loop activity during tumorigenesis; (4) an emerging hallmark network which triggers genome duplication dominates a feed-forward loop which in turn could act as a rate-limiting step for tumor formation; (5) mutations and other genomic alterations have

  11. Apoptosis and other immune biomarkers predict influenza vaccine responsiveness

    PubMed Central

    Furman, David; Jojic, Vladimir; Kidd, Brian; Shen-Orr, Shai; Price, Jordan; Jarrell, Justin; Tse, Tiffany; Huang, Huang; Lund, Peder; Maecker, Holden T; Utz, Paul J; Dekker, Cornelia L; Koller, Daphne; Davis, Mark M

    2013-01-01

    Despite the importance of the immune system in many diseases, there are currently no objective benchmarks of immunological health. In an effort to identifying such markers, we used influenza vaccination in 30 young (20–30 years) and 59 older subjects (60 to >89 years) as models for strong and weak immune responses, respectively, and assayed their serological responses to influenza strains as well as a wide variety of other parameters, including gene expression, antibodies to hemagglutinin peptides, serum cytokines, cell subset phenotypes and in vitro cytokine stimulation. Using machine learning, we identified nine variables that predict the antibody response with 84% accuracy. Two of these variables are involved in apoptosis, which positively associated with the response to vaccination and was confirmed to be a contributor to vaccine responsiveness in mice. The identification of these biomarkers provides new insights into what immune features may be most important for immune health. PMID:23591775

  12. Does Level of Response to SI Joint Block Predict Response to SI Joint Fusion?

    PubMed Central

    Cher, Daniel; Whang, Peter G.; Frank, Clay; Sembrano, Jonathan

    2016-01-01

    Background The degree of pain relief required to diagnose sacroiliac joint (SIJ) dysfunction following a diagnostic SIJ block (SIJB) is not known. No gold standard exists. Response to definitive (i.e., accepted as effective) treatment might be a reference standard. Methods Subgroup analysis of 320 subjects enrolled in two prospective multicenter trials evaluating SIJ fusion (SIJF) in patients with SIJ dysfunction diagnosed by history, physical exam and standardized diagnostic SIJB. A 50% reduction in pain at 30 or 60 minutes following SIJB was considered confirmatory. The absolute and percentage improvements in Visual Analog Scale (VAS) SIJ pain and Oswestry Disability Index (ODI) scores at 6 and 12 months after SIJF were correlated with the average acute improvement in SIJ pain with SIJB. Results The average pain reduction during the first hour after SIJB was 79.3%. Six months after SIJF, the overall mean VAS SIJ pain reduction was 50.9 points (0-100 scale) and the mean ODI reduction was 24.6 points. Reductions at 12 months after SIJF were similar. Examined in multiple ways, improvements in SIJ pain and ODI at 6 and 12 months did not correlate with SIJB findings. Conclusions The degree of pain improvement during SIJB did not predict improvements in pain or ODI scores after SIJF. A 50% SIJB threshold resulted in excellent post-SIJF responses. Using overly stringent selection criteria (i.e. 75%) to qualify patients for SIJF has no basis in evidence and would withhold a beneficial procedure from a substantial number of patients with SIJ dysfunction. Level of Evidence Level 1. Clinical Relevance The degree of pain improvement during an SIJ block does not predict the degree of pain improvement after SIJ fusion. PMID:26913224

  13. Dynamic Variables Fail to Predict Fluid Responsiveness in an Animal Model With Pericardial Effusion.

    PubMed

    Broch, Ole; Renner, Jochen; Meybohm, Patrick; Albrecht, Martin; Höcker, Jan; Haneya, Assad; Steinfath, Markus; Bein, Berthold; Gruenewald, Matthias

    2016-10-01

    The reliability of dynamic and volumetric variables of fluid responsiveness in the presence of pericardial effusion is still elusive. The aim of the present study was to investigate their predictive power in a porcine model with hemodynamic relevant pericardial effusion. A single-center animal investigation. Twelve German domestic pigs. Pigs were studied before and during pericardial effusion. Instrumentation included a pulmonary artery catheter and a transpulmonary thermodilution catheter in the femoral artery. Hemodynamic variables like cardiac output (COPAC) and stroke volume (SVPAC) derived from pulmonary artery catheter, global end-diastolic volume (GEDV), stroke volume variation (SVV), and pulse-pressure variation (PPV) were obtained. At baseline, SVV, PPV, GEDV, COPAC, and SVPAC reliably predicted fluid responsiveness (area under the curve 0.81 [p = 0.02], 0.82 [p = 0.02], 0.74 [p = 0.07], 0.74 [p = 0.07], 0.82 [p = 0.02]). After establishment of pericardial effusion the predictive power of dynamic variables was impaired and only COPAC and SVPAC and GEDV allowed significant prediction of fluid responsiveness (area under the curve 0.77 [p = 0.04], 0.76 [p = 0.05], 0.83 [p = 0.01]) with clinically relevant changes in threshold values. In this porcine model, hemodynamic relevant pericardial effusion abolished the ability of dynamic variables to predict fluid responsiveness. COPAC, SVPAC, and GEDV enabled prediction, but their threshold values were significantly changed. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. A clinical tool for predicting survival in ALS

    PubMed Central

    Knibb, Jonathan A; Keren, Noa; Kulka, Anna; Leigh, P Nigel; Martin, Sarah; Shaw, Christopher E; Tsuda, Miho; Al-Chalabi, Ammar

    2016-01-01

    Background Amyotrophic lateral sclerosis (ALS) is a progressive and usually fatal neurodegenerative disease. Survival from diagnosis varies considerably. Several prognostic factors are known, including site of onset (bulbar or limb), age at symptom onset, delay from onset to diagnosis and the use of riluzole and non-invasive ventilation (NIV). Clinicians and patients would benefit from a practical way of using these factors to provide an individualised prognosis. Methods 575 consecutive patients with incident ALS from a population-based registry in South-East England register for ALS (SEALS) were studied. Their survival was modelled as a two-step process: the time from diagnosis to respiratory muscle involvement, followed by the time from respiratory involvement to death. The effects of predictor variables were assessed separately for each time interval. Findings Younger age at symptom onset, longer delay from onset to diagnosis and riluzole use were associated with slower progression to respiratory involvement, and NIV use was associated with lower mortality after respiratory involvement, each with a clinically significant effect size. Riluzole may have a greater effect in younger patients and those with longer delay to diagnosis. A patient's survival time has a roughly 50% chance of falling between half and twice the predicted median. Interpretation A simple and clinically applicable graphical method of predicting an individual patient's survival from diagnosis is presented. The model should be validated in an independent cohort, and extended to include other important prognostic factors. PMID:27378085

  15. Clinical parameters predictive of enlargement of melanocytic choroidal lesions.

    PubMed Central

    Augsburger, J J; Schroeder, R P; Territo, C; Gamel, J W; Shields, J A

    1989-01-01

    The authors followed up 197 melanotic choroidal lesions (62 categorised as benign naevi, 76 classified as suspicious naevi, 41 diagnosed as dormant melanomas, and 18 categorised as active melanomas) left untreated after their initial clinical documentation. Thirty-nine of these lesions enlarged during a five-year follow-up interval (cumulative proportion of lesions that enlarged = 26.2% by Kaplan-Meier method). Individual clinical parameters predictive of lesion enlargement (p less than 0.01) included larger size of the lesion, especially lesion thickness, presence of retinal detachment, location of the lesion's posterior margin within 2 disc diameters of the optic disc, presence of symptoms, and presence of orange pigment clumps on the lesion's surface. The best combination of these parameters for prediction of lesion enlargement, as identified by multivariate Cox regression analysis, consisted of thickness of the lesion, retinal detachment, and symptoms. The five-year incidence of lesion enlargement for patients with none of these prognostic parameters was 5.8%, while that for patients with all three unfavourable parameters simultaneously was 90.6%. Images PMID:2605146

  16. Stochastic modeling and prediction for accrual in clinical trials.

    PubMed

    Zhang, Xiaoxi; Long, Qi

    2010-03-15

    Patient accrual in clinical trials is a topic of interest for important practical reasons. It has implications in both the initial planning and ongoing monitoring of trials. Slow accrual is of particular concern when it leads to reduced sample size. Although accrual in clinical trials has been studied and its estimation has been proposed and implemented, the existing methods are usually over-simplified by assuming a constant or piecewise constant accrual rate, and more flexible and realistic methods are needed. In this paper, we discuss a principled framework to monitor and predict trial accrual. We model trial accrual using a non-homogeneous Poisson process and model the underlying time-dependent accrual rate using cubic B-splines. The statistical inference and prediction procedure for the model are studied in a Bayesian paradigm. We conduct simulation studies to investigate the performance of the proposed approach and compare with a constant accrual rate model discussed by Gajewski et al. (Statist. Med. 2008; 27: 2328-2340). With satisfactory results, we illustrate the proposed method using accrual data from a real oncology trial. Our results show that the proposed model is more robust and achieves substantially better performance compared with the existing methods. Copyright (c) 2010 John Wiley & Sons, Ltd.

  17. Are we ready to predict late effects? A systematic review of clinically useful prediction models

    PubMed Central

    Salz, Talya; Baxi, Shrujal S.; Raghunathan, Nirupa; Onstad, Erin E.; Freedman, Andrew N.; Moskowitz, Chaya S.; Dalton, Susanne O.; Goodman, Karyn A.; Johansen, Christoffer; Matasar, Matthew J.; Brown, Peter de Nully; Oeffinger, Kevin C.; Vickers, Andrew J.

    2015-01-01

    Background After completing treatment for cancer, survivors may experience late effects: consequences of treatment that persist or arise after a latent period. Purpose To identify and describe all models that predict the risk of late effects and could be used in clinical practice. Data sources We searched Medline through April 2014. Study selection Studies describing models that 1) predicted the absolute risk of a late effect present at least one year post-treatment, and 2) could be used in a clinical setting. Data extraction Three authors independently extracted data pertaining to patient characteristics, late effects, the prediction model, and model evaluation. Data synthesis Across fourteen studies identified for review, nine late effects were predicted: erectile dysfunction and urinary incontinence after prostate cancer; arm lymphedema, psychological morbidity, cardiomyopathy or heart failure, and cardiac event after breast cancer; swallowing dysfunction after head and neck cancer; breast cancer after Hodgkin lymphoma; and thyroid cancer after childhood cancer. Of these, four late effects are persistent effects of treatment and five appear after a latent period. Two studies were externally validated. Six studies were designed to inform decisions about treatment rather than survivorship care. Nomograms were the most common clinical output. Conclusion Despite the call among survivorship experts for risk stratification, few published models are useful for risk-stratifying prevention, early detection, or management of late effects. Few models address serious, modifiable late effects, limiting their utility. Cancer survivors would benefit from models focused on long-term, modifiable, serious late effects to inform the management of survivorship care. PMID:25736818

  18. Histomorphological Factors Predicting the Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

    PubMed Central

    Jung, Yoon Yang; Hyun, Chang Lim; Jin, Min-Sun; Park, In Ae; Chung, Yul Ri; Shim, Bobae; Lee, Kyu Ho

    2016-01-01

    Purpose There is no standard targeted therapy for the treatment of triple-negative breast cancer (TNBC). Therefore, its management heavily depends on adjuvant chemotherapy. Using core needle biopsy, this study evaluated the histological factors of TNBC predicting the response to chemotherapy. Methods One hundred forty-three TNBC patients who received single-regimen neoadjuvant chemotherapy (NAC) with the combination of doxorubicin, cyclophosphamide, and docetaxel were enrolled. The core needle biopsy specimens acquired before NAC were used to analyze the clinicopathologic variables and overall performance of the predictive model for therapeutic response. Results Independent predictors of pathologic complete response after NAC were found to be higher number of tumor infiltrating lymphocytes (p=0.007), absence of clear cytoplasm (p=0.008), low necrosis (p=0.018), and high histologic grade (p=0.039). In the receiver operating characteristics curve analysis, the area under curve for the combination of these four variables was 0.777. Conclusion The present study demonstrated that a predictive model using the above four variables can predict therapeutic response to single-regimen NAC with the combination of doxorubicin, cyclophosphamide, and docetaxel in TNBC. Therefore, adding these morphologic variables to clinical and genomic signatures might enhance the ability to predict the therapeutic response to NAC in TNBC. PMID:27721875

  19. Physicochemical vs. Vibrational Descriptors for Prediction of Odor Receptor Responses.

    PubMed

    Gabler, Stephan; Soelter, Jan; Hussain, Taufia; Sachse, Silke; Schmuker, Michael

    2013-10-01

    Responses of olfactory receptors (ORs) can be predicted by applying machine learning methods on a multivariate encoding of an odorant's chemical structure. Physicochemical descriptors that encode features of the molecular graph are a popular choice for such an encoding. Here, we explore the EVA descriptor set, which encodes features derived from the vibrational spectrum of a molecule. We assessed the performance of Support Vector Regression (SVR) and Random Forest Regression (RFR) to predict the gradual response of Drosophila ORs. We compared a 27-dimensional variant of the EVA descriptor against a set of 1467 descriptors provided by the eDragon software package, and against a 32-dimensional subset thereof that has been proposed as the basis for an odor metric consisting of 32 descriptors (HADDAD). The best prediction performance was reproducibly achieved using SVR on the highest-dimensional feature set. The low-dimensional EVA and HADDAD feature sets predicted odor-OR interactions with similar accuracy. Adding charge and polarizability information to the EVA descriptor did not improve the results but rather decreased predictive power. Post-hoc in vivo measurements confirmed these results. Our findings indicate that EVA provides a meaningful low-dimensional representation of odor space, although EVA hardly outperformed "classical" descriptor sets.

  20. Idiopathic normal pressure hydrocephalus: diagnostic and predictive value of clinical testing, lumbar drainage, and CSF dynamics.

    PubMed

    Mahr, Cynthia V; Dengl, Markus; Nestler, Ulf; Reiss-Zimmermann, Martin; Eichner, Gerrit; Preuß, Matthias; Meixensberger, Jürgen

    2016-09-01

    OBJECTIVE The aim of the study was to analyze the diagnostic and predictive values of clinical tests, CSF dynamics, and intracranial pulsatility tests, compared with external lumbar drainage (ELD), for shunt response in patients with idiopathic normal pressure hydrocephalus (iNPH). METHODS Sixty-eight consecutive patients with suspected iNPH were prospectively evaluated. Preoperative assessment included clinical tests, overnight intracranial pressure (ICP) monitoring, lumbar infusion test (LIFT), and ELD for 24-72 hours. Simple and multiple linear regression analyses were conducted to identify predictive parameters concerning the outcome after shunt therapy. RESULTS Positive response to ELD correctly predicted improvement after CSF diversion in 87.9% of the patients. A Mini-Mental State Examination (MMSE) value below 21 was associated with nonresponse after shunt insertion (specificity 93%, sensitivity 67%). Resistance to outflow of CSF (ROut) > 12 mm Hg/ml/min was false negative in 21% of patients. Intracranial pulsatility parameters yielded different results in various parameters (correlation coefficient between pulse amplitude and ICP, slow wave amplitude, and mean ICP) but did not correlate to outcome. In multiple linear regression analysis, a calculation of presurgical MMSE versus the value after ELD, ROut, and ICP amplitude quotient during LIFT was significantly associated with outcome (p = 0.04). CONCLUSIONS Despite a multitude of invasive tests, presurgical clinical testing and response to ELD yielded the best prediction for improvement of symptoms following surgery. The complication rate of invasive testing was 5.4%. Multiple and simple linear regression analyses indicated that outcome can only be predicted by a combination of parameters, in accordance with a multifactorial pathogenesis of iNPH.

  1. Predicting methylphenidate response in attention deficit hyperactivity disorder: a preliminary study.

    PubMed

    Johnston, Blair A; Coghill, David; Matthews, Keith; Steele, J Douglas

    2015-01-01

    Methylphenidate (MPH) is established as the main pharmacological treatment for patients with attention deficit hyperactivity disorder (ADHD). Whilst MPH is generally a highly effective treatment, not all patients respond, and some experience adverse reactions. Currently, there is no reliable method to predict how patients will respond, other than by exposure to a trial of medication. In this preliminary study, we sought to investigate whether an accurate predictor of clinical response to methylphenidate could be developed for individual patients, using sociodemographic, clinical and neuropsychological measures. Of the 43 boys with ADHD included in this proof-of-concept study, 30 were classed as responders and 13 as non-responders to MPH, with no significant differences in age nor verbal intelligence quotient (IQ) between the groups. Here we report the application of a multivariate analysis approach to the prediction of clinical response to MPH, which achieved an accuracy of 77% (p = 0.005). The most important variables to the classifier were performance on a 'go/no go' task and comorbid conduct disorder. This preliminary study suggested that further investigation is merited. Achieving a highly significant accuracy of 77% for the prediction of MPH response is an encouraging step towards finding a reliable and clinically useful method that could minimise the number of children needlessly being exposed to MPH. © The Author(s) 2014.

  2. Baseline Brain Activity Predicts Response to Neuromodulatory Pain Treatment

    PubMed Central

    Jensen, Mark P.; Sherlin, Leslie H.; Fregni, Felipe; Gianas, Ann; Howe, Jon D.; Hakimian, Shahin

    2015-01-01

    Objectives The objective of this study was to examine the associations between baseline electroencephalogram (EEG)-assessed brain oscillations and subsequent response to four neuromodulatory treatments. Based on available research, we hypothesized that baseline theta oscillations would prospectively predict response to hypnotic analgesia. Analyses involving other oscillations and the other treatments (meditation, neurofeedback, and both active and sham transcranial direct current stimulation) were viewed as exploratory, given the lack of previous research examining brain oscillations as predictors of response to these other treatments. Design Randomized controlled study of single sessions of four neuromodulatory pain treatments and a control procedure. Methods Thirty individuals with spinal cord injury and chronic pain had their EEG recorded before each session of four active treatments (hypnosis, meditation, EEG biofeedback, transcranial direct current stimulation) and a control procedure (sham transcranial direct stimulation). Results As hypothesized, more presession theta power was associated with greater response to hypnotic analgesia. In exploratory analyses, we found that less baseline alpha power predicted pain reduction with meditation. Conclusions The findings support the idea that different patients respond to different pain treatments and that between-person treatment response differences are related to brain states as measured by EEG. The results have implications for the possibility of enhancing pain treatment response by either 1) better patient/treatment matching or 2) influencing brain activity before treatment is initiated in order to prepare patients to respond. Research is needed to replicate and confirm the findings in additional samples of individuals with chronic pain. PMID:25287554

  3. Baseline brain activity predicts response to neuromodulatory pain treatment.

    PubMed

    Jensen, Mark P; Sherlin, Leslie H; Fregni, Felipe; Gianas, Ann; Howe, Jon D; Hakimian, Shahin

    2014-12-01

    The objective of this study was to examine the associations between baseline electroencephalogram (EEG)-assessed brain oscillations and subsequent response to four neuromodulatory treatments. Based on available research, we hypothesized that baseline theta oscillations would prospectively predict response to hypnotic analgesia. Analyses involving other oscillations and the other treatments (meditation, neurofeedback, and both active and sham transcranial direct current stimulation) were viewed as exploratory, given the lack of previous research examining brain oscillations as predictors of response to these other treatments. Randomized controlled study of single sessions of four neuromodulatory pain treatments and a control procedure. Thirty individuals with spinal cord injury and chronic pain had their EEG recorded before each session of four active treatments (hypnosis, meditation, EEG biofeedback, transcranial direct current stimulation) and a control procedure (sham transcranial direct stimulation). As hypothesized, more presession theta power was associated with greater response to hypnotic analgesia. In exploratory analyses, we found that less baseline alpha power predicted pain reduction with meditation. The findings support the idea that different patients respond to different pain treatments and that between-person treatment response differences are related to brain states as measured by EEG. The results have implications for the possibility of enhancing pain treatment response by either 1) better patient/treatment matching or 2) influencing brain activity before treatment is initiated in order to prepare patients to respond. Research is needed to replicate and confirm the findings in additional samples of individuals with chronic pain. Wiley Periodicals, Inc.

  4. An empirical propellant response function for combustion stability predictions

    NASA Technical Reports Server (NTRS)

    Hessler, R. O.

    1980-01-01

    An empirical response function model was developed for ammonium perchlorate propellants to supplant T-burner testing at the preliminary design stage. The model was developed by fitting a limited T-burner data base, in terms of oxidizer size and concentration, to an analytical two parameter response function expression. Multiple peaks are predicted, but the primary effect is of a single peak for most formulations, with notable bulges for the various AP size fractions. The model was extended to velocity coupling with the assumption that dynamic response was controlled primarily by the solid phase described by the two parameter model. The magnitude of velocity coupling was then scaled using an erosive burning law. Routine use of the model for stability predictions on a number of propulsion units indicates that the model tends to overpredict propellant response. It is concluded that the model represents a generally conservative prediction tool, suited especially for the preliminary design stage when T-burner data may not be readily available. The model work included development of a rigorous summation technique for pseudopropellant properties and of a concept for modeling ordered packing of particulates.

  5. Specific molecular signatures predict decitabine response in chronic myelomonocytic leukemia.

    PubMed

    Meldi, Kristen; Qin, Tingting; Buchi, Francesca; Droin, Nathalie; Sotzen, Jason; Micol, Jean-Baptiste; Selimoglu-Buet, Dorothée; Masala, Erico; Allione, Bernardino; Gioia, Daniela; Poloni, Antonella; Lunghi, Monia; Solary, Eric; Abdel-Wahab, Omar; Santini, Valeria; Figueroa, Maria E

    2015-05-01

    Myelodysplastic syndromes and chronic myelomonocytic leukemia (CMML) are characterized by mutations in genes encoding epigenetic modifiers and aberrant DNA methylation. DNA methyltransferase inhibitors (DMTis) are used to treat these disorders, but response is highly variable, with few means to predict which patients will benefit. Here, we examined baseline differences in mutations, DNA methylation, and gene expression in 40 CMML patients who were responsive or resistant to decitabine (DAC) in order to develop a molecular means of predicting response at diagnosis. While somatic mutations did not differentiate responders from nonresponders, we identified 167 differentially methylated regions (DMRs) of DNA at baseline that distinguished responders from nonresponders using next-generation sequencing. These DMRs were primarily localized to nonpromoter regions and overlapped with distal regulatory enhancers. Using the methylation profiles, we developed an epigenetic classifier that accurately predicted DAC response at the time of diagnosis. Transcriptional analysis revealed differences in gene expression at diagnosis between responders and nonresponders. In responders, the upregulated genes included those that are associated with the cell cycle, potentially contributing to effective DAC incorporation. Treatment with CXCL4 and CXCL7, which were overexpressed in nonresponders, blocked DAC effects in isolated normal CD34+ and primary CMML cells, suggesting that their upregulation contributes to primary DAC resistance.

  6. Predicting Readmission at Early Hospitalization Using Electronic Clinical Data

    PubMed Central

    Sun, Xiaowu; Nunez, Carlos M.; Gupta, Vikas; Johannes, Richard S.

    2017-01-01

    Background: Identifying patients at high risk for readmission early during hospitalization may aid efforts in reducing readmissions. We sought to develop an early readmission risk predictive model using automated clinical data available at hospital admission. Methods: We developed an early readmission risk model using a derivation cohort and validated the model with a validation cohort. We used a published Acute Laboratory Risk of Mortality Score as an aggregated measure of clinical severity at admission and the number of hospital discharges in the previous 90 days as a measure of disease progression. We then evaluated the administrative data–enhanced model by adding principal and secondary diagnoses and other variables. We examined the c-statistic change when additional variables were added to the model. Results: There were 1,195,640 adult discharges from 70 hospitals with 39.8% male and the median age of 63 years (first and third quartile: 43, 78). The 30-day readmission rate was 11.9% (n=142,211). The early readmission model yielded a graded relationship of readmission and the Acute Laboratory Risk of Mortality Score and the number of previous discharges within 90 days. The model c-statistic was 0.697 with good calibration. When administrative variables were added to the model, the c-statistic increased to 0.722. Conclusions: Automated clinical data can generate a readmission risk score early at hospitalization with fair discrimination. It may have applied value to aid early care transition. Adding administrative data increases predictive accuracy. The administrative data–enhanced model may be used for hospital comparison and outcome research. PMID:27755391

  7. Multidimensional prediction of treatment response to antidepressants with cognitive control and functional MRI.

    PubMed

    Crane, Natania A; Jenkins, Lisanne M; Bhaumik, Runa; Dion, Catherine; Gowins, Jennifer R; Mickey, Brian J; Zubieta, Jon-Kar; Langenecker, Scott A

    2017-02-01

    Predicting treatment response for major depressive disorder can provide a tremendous benefit for our overstretched health care system by reducing number of treatments and time to remission, thereby decreasing morbidity. The present study used neural and performance predictors during a cognitive control task to predict treatment response (% change in Hamilton Depression Rating Scale pre- to post-treatment). Forty-nine individuals diagnosed with major depressive disorder were enrolled with intent to treat in the open-label study; 36 completed treatment, had useable data, and were included in most data analyses. Participants included in the data analysis sample received treatment with escitalopram (n = 22) or duloxetine (n = 14) for 10 weeks. Functional MRI and performance during a Parametric Go/No-go test were used to predict per cent reduction in Hamilton Depression Rating Scale scores after treatment. Haemodynamic response function-based contrasts and task-related independent components analysis (subset of sample: n = 29) were predictors. Independent components analysis component beta weights and haemodynamic response function modelling activation during Commission errors in the rostral and dorsal anterior cingulate, mid-cingulate, dorsomedial prefrontal cortex, and lateral orbital frontal cortex predicted treatment response. In addition, more commission errors on the task predicted better treatment response. Together in a regression model, independent component analysis, haemodynamic response function-modelled, and performance measures predicted treatment response with 90% accuracy (compared to 74% accuracy with clinical features alone), with 84% accuracy in 5-fold, leave-one-out cross-validation. Convergence between performance markers and functional magnetic resonance imaging, including novel independent component analysis techniques, achieved high accuracy in prediction of treatment response for major depressive disorder. The strong link to a task paradigm

  8. Dopamine Reward Prediction Error Responses Reflect Marginal Utility

    PubMed Central

    Stauffer, William R.; Lak, Armin; Schultz, Wolfram

    2014-01-01

    Summary Background Optimal choices require an accurate neuronal representation of economic value. In economics, utility functions are mathematical representations of subjective value that can be constructed from choices under risk. Utility usually exhibits a nonlinear relationship to physical reward value that corresponds to risk attitudes and reflects the increasing or decreasing marginal utility obtained with each additional unit of reward. Accordingly, neuronal reward responses coding utility should robustly reflect this nonlinearity. Results In two monkeys, we measured utility as a function of physical reward value from meaningful choices under risk (that adhered to first- and second-order stochastic dominance). The resulting nonlinear utility functions predicted the certainty equivalents for new gambles, indicating that the functions’ shapes were meaningful. The monkeys were risk seeking (convex utility function) for low reward and risk avoiding (concave utility function) with higher amounts. Critically, the dopamine prediction error responses at the time of reward itself reflected the nonlinear utility functions measured at the time of choices. In particular, the reward response magnitude depended on the first derivative of the utility function and thus reflected the marginal utility. Furthermore, dopamine responses recorded outside of the task reflected the marginal utility of unpredicted reward. Accordingly, these responses were sufficient to train reinforcement learning models to predict the behaviorally defined expected utility of gambles. Conclusions These data suggest a neuronal manifestation of marginal utility in dopamine neurons and indicate a common neuronal basis for fundamental explanatory constructs in animal learning theory (prediction error) and economic decision theory (marginal utility). PMID:25283778

  9. Clinical utility and validity of minoxidil response testing in androgenetic alopecia.

    PubMed

    Goren, Andy; Shapiro, Jerry; Roberts, Janet; McCoy, John; Desai, Nisha; Zarrab, Zoulikha; Pietrzak, Aldona; Lotti, Torello

    2015-01-01

    Clinical response to 5% topical minoxidil for the treatment of androgenetic alopecia (AGA) is typically observed after 3-6 months. Approximately 40% of patients will regrow hair. Given the prolonged treatment time required to elicit a response, a diagnostic test for ruling out nonresponders would have significant clinical utility. Two studies have previously reported that sulfotransferase enzyme activity in plucked hair follicles predicts a patient's response to topical minoxidil therapy. The aim of this study was to assess the clinical utility and validity of minoxidil response testing. In this communication, the present authors conducted an analysis of completed and ongoing studies of minoxidil response testing. The analysis confirmed the clinical utility of a sulfotransferase enzyme test in successfully ruling out 95.9% of nonresponders to topical minoxidil for the treatment of AGA. © 2014 Wiley Periodicals, Inc.

  10. Prediction of Response to Preoperative Chemoradiotherapy in Rectal Cancer by Multiplex Kinase Activity Profiling

    SciTech Connect

    Folkvord, Sigurd; Flatmark, Kjersti; Dueland, Svein

    2010-10-01

    Purpose: Tumor response of rectal cancer to preoperative chemoradiotherapy (CRT) varies considerably. In experimental tumor models and clinical radiotherapy, activity of particular subsets of kinase signaling pathways seems to predict radiation response. This study aimed to determine whether tumor kinase activity profiles might predict tumor response to preoperative CRT in locally advanced rectal cancer (LARC). Methods and Materials: Sixty-seven LARC patients were treated with a CRT regimen consisting of radiotherapy, fluorouracil, and, where possible, oxaliplatin. Pretreatment tumor biopsy specimens were analyzed using microarrays with kinase substrates, and the resulting substrate phosphorylation patterns were correlated with tumor response to preoperative treatment as assessed by histomorphologic tumor regression grade (TRG). A predictive model for TRG scores from phosphosubstrate signatures was obtained by partial-least-squares discriminant analysis. Prediction performance was evaluated by leave-one-out cross-validation and use of an independent test set. Results: In the patient population, 73% and 15% were scored as good responders (TRG 1-2) or intermediate responders (TRG 3), whereas 12% were assessed as poor responders (TRG 4-5). In a subset of 7 poor responders and 12 good responders, treatment outcome was correctly predicted for 95%. Application of the prediction model on the remaining patient samples resulted in correct prediction for 85%. Phosphosubstrate signatures generated by poor-responding tumors indicated high kinase activity, which was inhibited by the kinase inhibitor sunitinib, and several discriminating phosphosubstrates represented proteins derived from signaling pathways implicated in radioresistance. Conclusions: Multiplex kinase activity profiling may identify functional biomarkers predictive of tumor response to preoperative CRT in LARC.

  11. Infants, mothers, and dyadic contributions to stability and prediction of social stress response at 6 months.

    PubMed

    Provenzi, Livio; Olson, Karen L; Montirosso, Rosario; Tronick, Ed

    2016-01-01

    The study of infants' interactive style and social stress response to repeated stress exposures is of great interest for developmental and clinical psychologists. Stable maternal and dyadic behavior is critical to sustain infants' development of an adaptive social stress response, but the association between infants' interactive style and social stress response has received scant attention in previous literature. In the present article, overtime stability of infant, maternal, and dyadic behaviors was measured across 2 social stress (i.e., Face-to-Face Still-Face, FFSF) exposures, separated by 15 days. Moreover, infant, maternal, and dyadic behaviors were simultaneously assessed as predictors of infants' social stress to both FFSF exposures. Eighty-one mother-infant dyads underwent the FFSF twice, at 6 months (Exposure 1: the first social stress) and at 6 months and 15 days (Exposure 2: repeated social stress). Infant and mother behavior and dyadic synchrony were microanalytically coded. Overall, individual behavioral stability emerged between FFSF exposures. Infants' response to the first stress was predicted by infant behavior during Exposure 1 Play. Infants' response to the repeated social stress was predicted by infants' response to the first exposure to the Still-Face and by infants' behavior and dyadic synchrony during Exposure 2 Play. Findings reveal stability for individual, but not for dyadic, behavior between 2 social stress exposures at 6 months. Infants' response to repeated social stress was predicted by infants' earlier stress response, infants' own behavior in play, and dyadic synchrony. No predictive effects of maternal behavior were found. Insights for research and clinical work are discussed. (c) 2015 APA, all rights reserved).

  12. Rapid and Highly Accurate Prediction of Poor Loop Diuretic Natriuretic Response in Patients With Heart Failure

    PubMed Central

    Testani, Jeffrey M.; Hanberg, Jennifer S.; Cheng, Susan; Rao, Veena; Onyebeke, Chukwuma; Laur, Olga; Kula, Alexander; Chen, Michael; Wilson, F. Perry; Darlington, Andrew; Bellumkonda, Lavanya; Jacoby, Daniel; Tang, W. H. Wilson; Parikh, Chirag R.

    2015-01-01

    Background Removal of excess sodium and fluid is a primary therapeutic objective in acute decompensated heart failure (ADHF) and commonly monitored with fluid balance and weight loss. However, these parameters are frequently inaccurate or not collected and require a delay of several hours after diuretic administration before they are available. Accessible tools for rapid and accurate prediction of diuretic response are needed. Methods and Results Based on well-established renal physiologic principles an equation was derived to predict net sodium output using a spot urine sample obtained one or two hours following loop diuretic administration. This equation was then prospectively validated in 50 ADHF patients using meticulously obtained timed 6-hour urine collections to quantitate loop diuretic induced cumulative sodium output. Poor natriuretic response was defined as a cumulative sodium output of <50 mmol, a threshold that would result in a positive sodium balance with twice-daily diuretic dosing. Following a median dose of 3 mg (2–4 mg) of intravenous bumetanide, 40% of the population had a poor natriuretic response. The correlation between measured and predicted sodium output was excellent (r=0.91, p<0.0001). Poor natriuretic response could be accurately predicted with the sodium prediction equation (AUC=0.95, 95% CI 0.89–1.0, p<0.0001). Clinically recorded net fluid output had a weaker correlation (r=0.66, p<0.001) and lesser ability to predict poor natriuretic response (AUC=0.76, 95% CI 0.63–0.89, p=0.002). Conclusions In patients being treated for ADHF, poor natriuretic response can be predicted soon after diuretic administration with excellent accuracy using a spot urine sample. PMID:26721915

  13. Clinical prediction rules in practice: review of clinical guidelines and survey of GPs

    PubMed Central

    Plüddemann, Annette; Wallace, Emma; Bankhead, Clare; Keogh, Claire; Van der Windt, Danielle; Lasserson, Daniel; Galvin, Rose; Moschetti, Ivan; Kearley, Karen; O’Brien, Kirsty; Sanders, Sharon; Mallett, Susan; Malanda, Uriell; Thompson, Matthew; Fahey, Tom; Stevens, Richard

    2014-01-01

    Background The publication of clinical prediction rules (CPRs) studies has risen significantly. It is unclear if this reflects increasing usage of these tools in clinical practice or how this may vary across clinical areas. Aim To review clinical guidelines in selected areas and survey GPs in order to explore CPR usefulness in the opinion of experts and use at the point of care. Design and setting A review of clinical guidelines and survey of UK GPs. Method Clinical guidelines in eight clinical domains with published CPRs were reviewed for recommendations to use CPRs including primary prevention of cardiovascular disease, transient ischaemic attack (TIA) and stroke, diabetes mellitus, fracture risk assessment in osteoporosis, lower limb fractures, breast cancer, depression, and acute infections in childhood. An online survey of 401 UK GPs was also conducted. Results Guideline review: Of 7637 records screened by title and/or abstract, 243 clinical guidelines met inclusion criteria. CPRs were most commonly recommended in guidelines regarding primary prevention of cardiovascular disease (67%) and depression (67%). There was little consensus across various clinical guidelines as to which CPR to use preferentially. Survey: Of 401 responders to the GP survey, most were aware of and applied named CPRs in the clinical areas of cardiovascular disease and depression. The commonest reasons for using CPRs were to guide management and conform to local policy requirements. Conclusion GPs use CPRs to guide management but also to comply with local policy requirements. Future research could focus on which clinical areas clinicians would most benefit from CPRs and promoting the use of robust, externally validated CPRs. PMID:24686888

  14. Perturbation Predictability Can Influence the Long-Latency Stretch Response

    PubMed Central

    Forgaard, Christopher J.; Franks, Ian M.; Maslovat, Dana; Chua, Romeo

    2016-01-01

    Perturbations applied to the upper limbs elicit short (M1: 25–50 ms) and long-latency (M2: 50–100 ms) responses in the stretched muscle. M1 is produced by a spinal reflex loop, and M2 receives contribution from multiple spinal and supra-spinal pathways. While M1 is relatively immutable to voluntary intention, the remarkable feature of M2 is that its size can change based on intention or goal of the participant (e.g., increasing when resisting the perturbation and decreasing when asked to let-go or relax following the perturbation). While many studies have examined modulation of M2 between passive and various active conditions, through the use of constant foreperiods (interval between warning signal and a perturbation), it has also been shown that the magnitude of the M2 response in a passive condition can change based on factors such as habituation and anticipation of perturbation delivery. To prevent anticipation of a perturbation, most studies have used variable foreperiods; however, the range of possible foreperiod duration differs between experiments. The present study examined the influence of different variable foreperiods on modulation of the M2 response. Fifteen participants performed active and passive responses to a perturbation that stretched wrist flexors. Each block of trials had either a short (2.5–3.5 seconds; high predictability) or long (2.5–10.5 seconds; low predictability) variable foreperiod. As expected, no differences were found between any conditions for M1, while M2 was larger in the active rather than passive conditions. Interestingly, within the two passive conditions, the long variable foreperiods resulted in greater activity at the end of the M2 response than the trials with short foreperiods. These results suggest that perturbation predictability, even when using a variable foreperiod, can influence circuitry contributing to the long-latency stretch response. PMID:27727293

  15. Perturbation Predictability Can Influence the Long-Latency Stretch Response.

    PubMed

    Forgaard, Christopher J; Franks, Ian M; Maslovat, Dana; Chua, Romeo

    2016-01-01

    Perturbations applied to the upper limbs elicit short (M1: 25-50 ms) and long-latency (M2: 50-100 ms) responses in the stretched muscle. M1 is produced by a spinal reflex loop, and M2 receives contribution from multiple spinal and supra-spinal pathways. While M1 is relatively immutable to voluntary intention, the remarkable feature of M2 is that its size can change based on intention or goal of the participant (e.g., increasing when resisting the perturbation and decreasing when asked to let-go or relax following the perturbation). While many studies have examined modulation of M2 between passive and various active conditions, through the use of constant foreperiods (interval between warning signal and a perturbation), it has also been shown that the magnitude of the M2 response in a passive condition can change based on factors such as habituation and anticipation of perturbation delivery. To prevent anticipation of a perturbation, most studies have used variable foreperiods; however, the range of possible foreperiod duration differs between experiments. The present study examined the influence of different variable foreperiods on modulation of the M2 response. Fifteen participants performed active and passive responses to a perturbation that stretched wrist flexors. Each block of trials had either a short (2.5-3.5 seconds; high predictability) or long (2.5-10.5 seconds; low predictability) variable foreperiod. As expected, no differences were found between any conditions for M1, while M2 was larger in the active rather than passive conditions. Interestingly, within the two passive conditions, the long variable foreperiods resulted in greater activity at the end of the M2 response than the trials with short foreperiods. These results suggest that perturbation predictability, even when using a variable foreperiod, can influence circuitry contributing to the long-latency stretch response.

  16. Pragmatic hydraulic theory predicts stomatal responses to climatic water deficits.

    PubMed

    Sperry, John S; Wang, Yujie; Wolfe, Brett T; Mackay, D Scott; Anderegg, William R L; McDowell, Nate G; Pockman, William T

    2016-11-01

    Ecosystem models have difficulty predicting plant drought responses, partially from uncertainty in the stomatal response to water deficits in soil and atmosphere. We evaluate a 'supply-demand' theory for water-limited stomatal behavior that avoids the typical scaffold of empirical response functions. The premise is that canopy water demand is regulated in proportion to threat to supply posed by xylem cavitation and soil drying. The theory was implemented in a trait-based soil-plant-atmosphere model. The model predicted canopy transpiration (E), canopy diffusive conductance (G), and canopy xylem pressure (Pcanopy ) from soil water potential (Psoil ) and vapor pressure deficit (D). Modeled responses to D and Psoil were consistent with empirical response functions, but controlling parameters were hydraulic traits rather than coefficients. Maximum hydraulic and diffusive conductances and vulnerability to loss in hydraulic conductance dictated stomatal sensitivity and hence the iso- to anisohydric spectrum of regulation. The model matched wide fluctuations in G and Pcanopy across nine data sets from seasonally dry tropical forest and piñon-juniper woodland with < 26% mean error. Promising initial performance suggests the theory could be useful in improving ecosystem models. Better understanding of the variation in hydraulic properties along the root-stem-leaf continuum will simplify parameterization.

  17. Predictions of F-111 TACT aircraft buffet response

    NASA Technical Reports Server (NTRS)

    Cunningham, Atlee M., Jr.; Coe, Charles F.

    1990-01-01

    A summary is presented for the prediction method development and correlations of predicted response with flight test measurements. The prediction method was based on refinements to the method described by Cunningham. One improvement made use of direct time integration of the correlated fluctuating pressure data to obtain buffet excitation for the various modes of interest. Another improvement incorporated a hybrid technique for scaling measured wind tunnel damping data to full-scale for the modes of interest. A third improvement made use of the diagonalized form of the fully coupled equations of motion. Finally, a mechanism was described for explaining an apparent coupling between the aircraft wing torsion modes and shock induced trailing edge separation that led to very high wing motion on the aircraft that was not observed on the wind tunnel model.

  18. Predictive coding of music--brain responses to rhythmic incongruity.

    PubMed

    Vuust, Peter; Ostergaard, Leif; Pallesen, Karen Johanne; Bailey, Christopher; Roepstorff, Andreas

    2009-01-01

    During the last decades, models of music processing in the brain have mainly discussed the specificity of brain modules involved in processing different musical components. We argue that predictive coding offers an explanatory framework for functional integration in musical processing. Further, we provide empirical evidence for such a network in the analysis of event-related MEG-components to rhythmic incongruence in the context of strong metric anticipation. This is seen in a mismatch negativity (MMNm) and a subsequent P3am component, which have the properties of an error term and a subsequent evaluation in a predictive coding framework. There were both quantitative and qualitative differences in the evoked responses in expert jazz musicians compared with rhythmically unskilled non-musicians. We propose that these differences trace a functional adaptation and/or a genetic pre-disposition in experts which allows for a more precise rhythmic prediction.

  19. Prediction of Selection Response for Threshold Dichotomous Traits

    PubMed Central

    Foulley, J. L.

    1992-01-01

    This paper presents a formula to predict expected response to one generation of truncation selection for a dichotomous trait under polygenic additive inheritance. The derivation relies on the threshold liability concept and on the normality assumption of the joint distribution of additive genetic values and their predictors used as selection criteria. This formula accounts for asymmetry of response when both the prevalence of the trait and the selection rate differ from 1/2 via a bivariate normal integral term. The relationship with the classical formula R = ipσ(G) is explained with a Taylor expansion about a zero value of the correlation factor. Properties are illustrated with an example of sire selection based on progeny test performance which shows a departure from usual predictions up to 15-20% at low (0.05) or high (0.95) selection rates. Univariate approximations and extensions to several paths of genetic change are also discussed. PMID:1459435

  20. Proteomic profiling predicts drug response to novel targeted anticancer therapeutics.

    PubMed

    Lin, Fan; Li, Zilin; Hua, Yunfen; Lim, Yoon Pin

    2016-01-01

    Most recently approved anti-cancer drugs by the US FDA are targeted therapeutic agents and this represents an important trend for future anticancer therapy. Unlike conventional chemotherapy that rarely considers individual differences, it is crucial for targeted therapies to identify the beneficial subgroup of patients for the treatment. Currently, genomics and transcriptomics are the major 'omic' analytics used in studies of drug response prediction. However, proteomic profiling excels both in its advantages of directly detecting an instantaneous dynamic of the whole proteome, which contains most current diagnostic markers and therapeutic targets. Moreover, proteomic profiling improves understanding of the mechanism for drug resistance and helps finding optimal combination therapy. This article reviews the recent success of applications of proteomic analytics in predicting the response to targeted anticancer therapeutics, and discusses the potential avenues and pitfalls of proteomic platforms and techniques used most in the field.

  1. Creating and evaluating genetic tests predictive of drug response

    PubMed Central

    Weiss, Scott T.; McLeod, Howard L.; Flockhart, David A.; Dolan, M. Eileen; Benowitz, Neal L.; Johnson, Julie A.; Ratain, Mark J.; Giacomini, Kathleen M.

    2009-01-01

    A key goal of pharmacogenetics — the use of genetic variation to elucidate inter-individual variation in drug treatment response — is to aid the development of predictive genetic tests that could maximize drug efficacy and minimize drug toxicity. The completion of the Human Genome Project and the associated HapMap Project, together with advances in technologies for investigating genetic variation, have greatly advanced the potential to develop such tests; however, many challenges remain. With the aim of helping to address some of these challenges, this article discusses the steps that are involved in the development of predictive tests for drug treatment response based on genetic variation, and factors that influence the development and performance of these tests. PMID:18587383

  2. Predicting Individual Differences in Response to Sleep Loss

    DTIC Science & Technology

    2011-09-15

    2011 4. TITLE Predicting Individual Differences in Response to Sleep Loss 5a. Contract Number: 5b. Grant Number: 5c. Program Element Number: 5d...ADDRESS(ES) Naval Medical Reserach Unit – Dayton 2624 Q St., Bldg. 851, Area B Wright-Patterson AFB, OH 45433 8. PERFORMING ORGANIZATION... Program Department of the Navy 2300 E Street, NW Washington, DC 20372-5300 10. SPONSOR/MONITOR’S ACRONYM(S) BUMED 11. SPONSOR/MONITOR’S REPORT

  3. Predicting the response of olfactory sensory neurons to odor mixtures from single odor response

    NASA Astrophysics Data System (ADS)

    Marasco, Addolorata; de Paris, Alessandro; Migliore, Michele

    2016-04-01

    The response of olfactory receptor neurons to odor mixtures is not well understood. Here, using experimental constraints, we investigate the mathematical structure of the odor response space and its consequences. The analysis suggests that the odor response space is 3-dimensional, and predicts that the dose-response curve of an odor receptor can be obtained, in most cases, from three primary components with specific properties. This opens the way to an objective procedure to obtain specific olfactory receptor responses by manipulating mixtures in a mathematically predictable manner. This result is general and applies, independently of the number of odor components, to any olfactory sensory neuron type with a response curve that can be represented as a sigmoidal function of the odor concentration.

  4. Predicting the response of olfactory sensory neurons to odor mixtures from single odor response

    PubMed Central

    Marasco, Addolorata; De Paris, Alessandro; Migliore, Michele

    2016-01-01

    The response of olfactory receptor neurons to odor mixtures is not well understood. Here, using experimental constraints, we investigate the mathematical structure of the odor response space and its consequences. The analysis suggests that the odor response space is 3-dimensional, and predicts that the dose-response curve of an odor receptor can be obtained, in most cases, from three primary components with specific properties. This opens the way to an objective procedure to obtain specific olfactory receptor responses by manipulating mixtures in a mathematically predictable manner. This result is general and applies, independently of the number of odor components, to any olfactory sensory neuron type with a response curve that can be represented as a sigmoidal function of the odor concentration. PMID:27053070

  5. A Genomic Approach to Improve Prognosis and Predict Therapeutic Response in Chronic Lymphocytic Leukemia

    PubMed Central

    Friedman, Daphne R.; Weinberg, J. Brice; Barry, William T.; Goodman, Barbara K.; Volkheimer, Alicia D.; Bond, Karen M.; Chen, Youwei; Jiang, Ning; Moore, Joseph O.; Gockerman, Jon P.; Diehl, Louis F.; Decastro, Carlos M.; Potti, Anil; Nevins, Joseph R.

    2009-01-01

    Purpose Chronic lymphocytic leukemia (CLL) is a B-cell malignancy characterized by a variable clinical course. Several parameters have prognostic capabilities but are associated with altered response to therapy in only a small subset of patients. Experimental Design We used gene expression profiling methods to generate predictors of therapy response and prognosis. Genomic signatures that reflect progressive disease and responses to chemotherapy or chemo-immunotherapy were created using cancer cell lines and patient leukemia cell samples. We validated and applied these three signatures to independent clinical data from four cohorts representing a total of 301 CLL patients. Results A genomic signature of prognosis created from patient leukemic cell gene expression data coupled with clinical parameters significantly differentiated patients with stable disease from those with progressive disease in the training dataset. The progression signature was validated in two independent datasets, demonstrating a capacity to accurately identify patients at risk for progressive disease. In addition, genomic signatures that predict response to chlorambucil or pentostatin, cyclophosphamide, and rituximab were generated and could accurately distinguish responding and non-responding CLL patients. Conclusions Thus, microarray analysis of CLL lymphocytes can be used to refine prognosis and predict response to different therapies. These results have implications for standard and investigational therapeutics in CLL patients. PMID:19861443

  6. Optimally discriminative subnetwork markers predict response to chemotherapy

    PubMed Central

    Dao, Phuong; Wang, Kendric; Collins, Colin; Ester, Martin; Lapuk, Anna; Sahinalp, S. Cenk

    2011-01-01

    Motivation: Molecular profiles of tumour samples have been widely and successfully used for classification problems. A number of algorithms have been proposed to predict classes of tumor samples based on expression profiles with relatively high performance. However, prediction of response to cancer treatment has proved to be more challenging and novel approaches with improved generalizability are still highly needed. Recent studies have clearly demonstrated the advantages of integrating protein–protein interaction (PPI) data with gene expression profiles for the development of subnetwork markers in classification problems. Results: We describe a novel network-based classification algorithm (OptDis) using color coding technique to identify optimally discriminative subnetwork markers. Focusing on PPI networks, we apply our algorithm to drug response studies: we evaluate our algorithm using published cohorts of breast cancer patients treated with combination chemotherapy. We show that our OptDis method improves over previously published subnetwork methods and provides better and more stable performance compared with other subnetwork and single gene methods. We also show that our subnetwork method produces predictive markers that are more reproducible across independent cohorts and offer valuable insight into biological processes underlying response to therapy. Availability: The implementation is available at: http://www.cs.sfu.ca/~pdao/personal/OptDis.html Contact: cenk@cs.sfu.ca; alapuk@prostatecentre.com; ccollins@prostatecentre.com PMID:21685072

  7. Optimally discriminative subnetwork markers predict response to chemotherapy.

    PubMed

    Dao, Phuong; Wang, Kendric; Collins, Colin; Ester, Martin; Lapuk, Anna; Sahinalp, S Cenk

    2011-07-01

    Molecular profiles of tumour samples have been widely and successfully used for classification problems. A number of algorithms have been proposed to predict classes of tumor samples based on expression profiles with relatively high performance. However, prediction of response to cancer treatment has proved to be more challenging and novel approaches with improved generalizability are still highly needed. Recent studies have clearly demonstrated the advantages of integrating protein-protein interaction (PPI) data with gene expression profiles for the development of subnetwork markers in classification problems. We describe a novel network-based classification algorithm (OptDis) using color coding technique to identify optimally discriminative subnetwork markers. Focusing on PPI networks, we apply our algorithm to drug response studies: we evaluate our algorithm using published cohorts of breast cancer patients treated with combination chemotherapy. We show that our OptDis method improves over previously published subnetwork methods and provides better and more stable performance compared with other subnetwork and single gene methods. We also show that our subnetwork method produces predictive markers that are more reproducible across independent cohorts and offer valuable insight into biological processes underlying response to therapy. The implementation is available at: http://www.cs.sfu.ca/~pdao/personal/OptDis.html cenk@cs.sfu.ca; alapuk@prostatecentre.com; ccollins@prostatecentre.com.

  8. Clinical and laboratory predictive markers for acute dengue infection

    PubMed Central

    2013-01-01

    Background Early diagnosis of dengue virus infection during the febrile stage is essential for adjusting appropriate management. This study is to identify the predictive markers of clinical and laboratory findings in the acute stage of dengue infection during a major outbreak of dengue virus type 1 that occurred in southern Taiwan during 2007. A retrospective, hospital-based study was conducted at a university hospital in southern Taiwan from January to December, 2007. Patient who was reported for clinically suspected dengue infection was enrolled. Laboratory-positive dengue cases are confirmed by enzyme-linked immunosorbent assay of specific dengue IgM, fourfold increase of dengue-specific IgG titers in convalescent serum, or by reverse transcription-polymerase chain reaction (RT-PCR) of dengue virus. Results The suspected dengue cases consist of 100 children (≤ 18 years) and 481 adults. Among the 581 patients, 67 (67%) children and 309 (64.2%) adults were laboratory-confirmed. Patients who had laboratory indeterminate were excluded. Most cases were uncomplicated and 3.8% of children and 2.9% of adults developed dengue hemorrhagic fever or dengue shock syndrome (DHF/DSS). The overall mortality rate in those with DHF/DSS was 7.1%, and the average duration of hospitalization was 20 days. The most common symptoms/signs at admission were myalgia (46.8%), petechiae (36.9%) and nausea/vomiting (33.5%). The most notable laboratory findings included leukopenia (2966 ± 1896/cmm), thrombocytopenia (102 ± 45 × 103/cmm), prolonged activated partial thromboplastin time (aPTT) (45 ± 10 s), and elevated serum levels of aminotransferase (AST, 166 ± 208 U/L; ALT, 82 ± 103 U/L) and low C - reactive protein (CRP) (6 ± 11 mg/L). Based on the clinical features for predicting laboratory-confirmed dengue infection, the sensitivities of typical rash, myalgia, and positive tourniquet test are 59.2%, 46.8%, and 34.2%, while the specificities for

  9. Graphics and statistics for cardiology: clinical prediction rules.

    PubMed

    Woodward, Mark; Tunstall-Pedoe, Hugh; Peters, Sanne Ae

    2017-04-01

    Graphs and tables are indispensable aids to quantitative research. When developing a clinical prediction rule that is based on a cardiovascular risk score, there are many visual displays that can assist in developing the underlying statistical model, testing the assumptions made in this model, evaluating and presenting the resultant score. All too often, researchers in this field follow formulaic recipes without exploring the issues of model selection and data presentation in a meaningful and thoughtful way. Some ideas on how to use visual displays to make wise decisions and present results that will both inform and attract the reader are given. Ideas are developed, and results tested, using subsets of the data that were used to develop the ASSIGN cardiovascular risk score, as used in Scotland.

  10. Predicting aquifer response time for application in catchment modeling.

    PubMed

    Walker, Glen R; Gilfedder, Mat; Dawes, Warrick R; Rassam, David W

    2015-01-01

    It is well established that changes in catchment land use can lead to significant impacts on water resources. Where land-use changes increase evapotranspiration there is a resultant decrease in groundwater recharge, which in turn decreases groundwater discharge to streams. The response time of changes in groundwater discharge to a change in recharge is a key aspect of predicting impacts of land-use change on catchment water yield. Predicting these impacts across the large catchments relevant to water resource planning can require the estimation of groundwater response times from hundreds of aquifers. At this scale, detailed site-specific measured data are often absent, and available spatial data are limited. While numerical models can be applied, there is little advantage if there are no detailed data to parameterize them. Simple analytical methods are useful in this situation, as they allow the variability in groundwater response to be incorporated into catchment hydrological models, with minimal modeling overhead. This paper describes an analytical model which has been developed to capture some of the features of real, sloping aquifer systems. The derived groundwater response timescale can be used to parameterize a groundwater discharge function, allowing groundwater response to be predicted in relation to different broad catchment characteristics at a level of complexity which matches the available data. The results from the analytical model are compared to published field data and numerical model results, and provide an approach with broad application to inform water resource planning in other large, data-scarce catchments. © 2014, CommonWealth of Australia. Groundwater © 2014, National Ground Water Association.

  11. Predictive factors associated with hepatitis C antiviral therapy response

    PubMed Central

    Cavalcante, Lourianne Nascimento; Lyra, André Castro

    2015-01-01

    Hepatitis C virus (HCV) infection may lead to significant liver injury, and viral, environmental, host, immunologic and genetic factors may contribute to the differences in the disease expression and treatment response. In the early 2000s, dual therapy using a combination of pegylated interferon plus ribavirin (PR) became the standard of care for HCV treatment. In this PR era, predictive factors of therapy response related to virus and host have been identified. In 2010/2011, therapeutic regimens for HCV genotype 1 patients were modified, and the addition of NS3/4a protease inhibitors (boceprevir or telaprevir) to dual therapy increased the effectiveness and chances of sustained virologic response (SVR). Nevertheless, the first-generation triple therapy is associated with many adverse events, some of which are serious and associated with death, particularly in cirrhotic patients. This led to the need to identify viral and host predictive factors that might influence the SVR rate to triple therapy and avoid unnecessary exposure to these drugs. Over the past four years, hepatitis C treatment has been rapidly changing with the development of new therapies and other developments. Currently, with the more recent generations of pangenotipic antiviral therapies, there have been higher sustained virologic rates, and prognostic factors may not have the same importance and strength as before. Nonetheless, some variables may still be consistent with the low rates of non-response with regimens that include sofosbuvir, daclatasvir and ledipasvir. In this manuscript, we review the predictive factors of therapy response across the different treatment regimens over the last decade including the new antiviral drugs. PMID:26140082

  12. Ensemble ecosystem modeling for predicting ecosystem response to predator reintroduction.

    PubMed

    Baker, Christopher M; Gordon, Ascelin; Bode, Michael

    2017-04-01

    Introducing a new or extirpated species to an ecosystem is risky, and managers need quantitative methods that can predict the consequences for the recipient ecosystem. Proponents of keystone predator reintroductions commonly argue that the presence of the predator will restore ecosystem function, but this has not always been the case, and mathematical modeling has an important role to play in predicting how reintroductions will likely play out. We devised an ensemble modeling method that integrates species interaction networks and dynamic community simulations and used it to describe the range of plausible consequences of 2 keystone-predator reintroductions: wolves (Canis lupus) to Yellowstone National Park and dingoes (Canis dingo) to a national park in Australia. Although previous methods for predicting ecosystem responses to such interventions focused on predicting changes around a given equilibrium, we used Lotka-Volterra equations to predict changing abundances through time. We applied our method to interaction networks for wolves in Yellowstone National Park and for dingoes in Australia. Our model replicated the observed dynamics in Yellowstone National Park and produced a larger range of potential outcomes for the dingo network. However, we also found that changes in small vertebrates or invertebrates gave a good indication about the potential future state of the system. Our method allowed us to predict when the systems were far from equilibrium. Our results showed that the method can also be used to predict which species may increase or decrease following a reintroduction and can identify species that are important to monitor (i.e., species whose changes in abundance give extra insight into broad changes in the system). Ensemble ecosystem modeling can also be applied to assess the ecosystem-wide implications of other types of interventions including assisted migration, biocontrol, and invasive species eradication.

  13. Clinical benefit response in pancreatic cancer trials revisited.

    PubMed

    Bernhard, Jürg; Dietrich, Daniel; Glimelius, Bengt; Bodoky, György; Scheithauer, Werner; Herrmann, Richard

    2014-01-01

    Clinical benefit response (CBR), based on changes in pain, Karnofsky performance status, and weight, is an established palliative endpoint in trials for advanced gastrointestinal cancer. We investigated whether CBR is associated with survival, and whether CBR reflects a wide-enough range of domains to adequately capture patients' perception. CBR was prospectively evaluated in an international phase III chemotherapy trial in patients with advanced pancreatic cancer (n = 311) in parallel with patient-reported outcomes (PROs). The median time to treatment failure was 3.4 months (range: 0-6). The majority of the CBRs (n = 39) were noted in patients who received chemotherapy for at least 5 months. Patients with CBR (n = 62) had longer survival than non-responders (n = 182) (hazard ratio = 0.69; 95% confidence interval: 0.51-0.94; p = 0.013). CBR was predicted with a sensitivity and specificity of 77-80% by various combinations of 3 mainly physical PROs. A comparison between the duration of CBR (n = 62, median = 8 months, range = 4-31) and clinically meaningful improvements in the PROs (n = 100-116; medians = 9-11 months, range = 4-24) showed similar intervals. CBR is associated with survival and mainly reflects physical domains. Within phase III chemotherapy trials for advanced gastrointestinal cancer, CBR can be replaced by a PRO evaluation, without losing substantial information but gaining complementary information. © 2014 S. Karger GmbH, Freiburg.

  14. Lipidomic analysis enables prediction of clinical outcomes in burn patients

    PubMed Central

    Qi, Peter; Abdullahi, Abdikarim; Stanojcic, Mile; Patsouris, David; Jeschke, Marc G.

    2016-01-01

    Recent discoveries have highlighted the novel metabolic functions of adipose tissue in enhancing hypermetabolism after trauma. As the exact function and expression profiles of serum lipids and free fatty acids (FFA) are essentially unknown, we determined the lipidomic expression profile after burn in correlation to clinical outcomes to identify important lipid mediators affecting post-burn outcomes. We conducted a prospective cohort study with 46 adult burn patients and 5 healthy controls at the Ross Tilley Burn Center in Toronto, Canada. Patients were stratified based on major demographic and clinical variables, including age, burn severity, mortality, and sepsis. Serum FFAs and inflammatory markers were measured during acute hospital stay. We found that FFAs were acutely elevated post-burn and returned to baseline over time. Greater burn severity and age were associated with an impaired acute response in unsaturated FFAs and pro-inflammatory cytokines. Elevations in saturated and mono-unsaturated FFAs correlated significantly to increased mortality. In summary, persistent elevation of unsaturated lipids was associated with a functionally altered inflammatory-immunological milieu and worse clinical outcomes. The present lipidomic analysis indicates profound alterations in the lipid profile after burn by characterizing key lipids as potential diagnostic and outcome indicators in critically injured patients. PMID:27982130

  15. Prediction of Pharmacological and Xenobiotic Responses to Drugs Based on Time Course Gene Expression Profiles

    PubMed Central

    Hu, LeLe; Feng, KaiYan; Li, Yi-Xue; Cai, Yu-Dong

    2009-01-01

    More and more people are concerned by the risk of unexpected side effects observed in the later steps of the development of new drugs, either in late clinical development or after marketing approval. In order to reduce the risk of the side effects, it is important to look out for the possible xenobiotic responses at an early stage. We attempt such an effort through a prediction by assuming that similarities in microarray profiles indicate shared mechanisms of action and/or toxicological responses among the chemicals being compared. A large time course microarray database derived from livers of compound-treated rats with thirty-four distinct pharmacological and toxicological responses were studied. The mRMR (Minimum-Redundancy-Maximum-Relevance) method and IFS (Incremental Feature Selection) were used to select a compact feature set (141 features) for the reduction of feature dimension and improvement of prediction performance. With these 141 features, the Leave-one-out cross-validation prediction accuracy of first order response using NNA (Nearest Neighbor Algorithm) was 63.9%. Our method can be used for pharmacological and xenobiotic responses prediction of new compounds and accelerate drug development. PMID:19956587

  16. Prediction of heart rate response to conclusion of the spontaneous breathing trial by fluctuation dissipation theory

    NASA Astrophysics Data System (ADS)

    Chen, Man; Niestemski, Liang Ren; Prevost, Robert; McRae, Michael; Cholleti, Sharath; Najarro, Gabriel; Buchman, Timothy G.; Deem, Michael W.

    2013-02-01

    The non-equilibrium fluctuation dissipation theorem is applied to predict how critically ill patients respond to treatment, based upon data currently collected by standard hospital monitoring devices. This framework is demonstrated on a common procedure in critical care: the spontaneous breathing trial. It is shown that the responses of groups of similar patients to the spontaneous breathing trial can be predicted by the non-equilibrium fluctuation dissipation approach. This mathematical framework, when fully formed and applied to other clinical interventions, may serve as part of the basis for personalized critical care.

  17. Predictive models of spatial transcriptional response to high salinity.

    PubMed

    Uygun, Sahra; Seddon, Alexander E; Azodi, Christina B; Shiu, Shin-Han

    2017-04-03

    Plants are exposed to a variety of environmental conditions, and their ability to respond to environment variation depends on the proper regulation of gene expression in an organ, tissue, and cell type specific manner. Although our knowledge is accumulating on how stress responses are regulated, a genome-wide model of how plant transcription factors (TFs) and cis-regulatory elements (CREs) control spatially specific stress response has yet to emerge. Using Arabidopsis thaliana as a model, we identified a set of 1,894 putative CREs (pCREs) that are associated with high salinity (salt) up-regulated genes in the root or the shoot. These pCREs led to computational models that can better predict salt up-regulated genes in root and shoot compared to models based on known TF binding motifs. In addition, we incorporated TF binding sites identified via large-scale in vitro assays, chromatin accessibility, evolutionary conservation and pCRE combinatorial relations in machine learning models, and found that only consideration of pCRE combinations led to better performance in salt up-regulation prediction in root and shoot. Our results suggest that the plant organ transcriptional response to high salinity is regulated by a core set of pCREs and provide a genome-wide view on the cis-regulatory code of plant spatial transcriptional responses to environmental stress.

  18. Prediction of individual response to antidepressants and antipsychotics: an integrated concept.

    PubMed

    Preskorn, Sheldon H

    2014-12-01

    In both clinical trials and daily practice, there can be substantial inter- and even intraindividual variability in response--whether beneficial or adverse--to antidepressants and antipsychotic medications. So far, no tools have become available to predict the outcome of these treatments in specific patients. This is because the causes of such variability are often not known, and when they are, there is no way of predicting the effects of their various potential combinations in an individual. Given this background, this paper presents a conceptual framework for understanding known factors and their combinations so that eventually clinicians can better predict what medication(s) to select and at what dose they can optimize the outcome for a given individual. This framework is flexible enough to be readily adaptable as new information becomes available. The causes of variation in patient response are grouped into four categories: (i) genetics; (ii) age; (iii) disease; and (iv) environment (internal). Four cases of increasing complexity are used to illustrate the applicability of this framework in a clinically relevant way In addition, this paper reviews tools that the clinician can use to assess for and quantify such inter- and intraindividual variability. With the information gained, treatment can be adjusted to compensate for such variability, in order to optimize outcome. Finally, the limitations of existing antidepressant and antipsychotic therapy and the way they reduce current ability to predict response is discussed.

  19. Early improvement with pregabalin predicts endpoint response in patients with generalized anxiety disorder: an integrated and predictive data analysis.

    PubMed

    Montgomery, Stuart A; Lyndon, Gavin; Almas, Mary; Whalen, Ed; Prieto, Rita

    2017-01-01

    Generalized anxiety disorder (GAD), a common mental disorder, has several treatment options including pregabalin. Not all patients respond to treatment; quickly determining which patients will respond is an important treatment goal. Patient-level data were pooled from nine phase II and III randomized, double-blind, short-term, placebo-controlled trials of pregabalin for the treatment of GAD. Efficacy outcomes included the change from baseline in the Hamilton Anxiety Scale (HAM-A) total score and psychic and somatic subscales. Predictive modelling assessed baseline characteristics and early clinical responses to determine those predictive of clinical improvement at endpoint. A total of 2155 patients were included in the analysis (1447 pregabalin, 708 placebo). Pregabalin significantly improved the HAM-A total score compared with the placebo at endpoint, treatment difference (95% confidence interval), -2.61 (-3.21 to -2.01), P<0.0001. Pregabalin significantly improved HAM-A psychic and somatic scores compared with placebo, -1.52 (-1.85 to -1.18), P<0.0001, and -1.10 (-1.41 to -0.80), P<0.0001, respectively. Response to pregabalin in the first 1-2 weeks (≥20 or ≥30% improvement in HAM-A total, psychic or somatic score) was predictive of an endpoint greater than or equal to 50% improvement in the HAM-A total score. Pregabalin is an effective treatment option for patients with GAD. Patients with early response to pregabalin are more likely to respond significantly at endpoint.

  20. Neutrophil biomarkers predict response to therapy with tumor necrosis factor inhibitors in rheumatoid arthritis.

    PubMed

    Wright, Helen L; Cox, Trevor; Moots, Robert J; Edwards, Steven W

    2017-03-01

    Neutrophils are implicated in the pathology of rheumatoid arthritis (RA), but the mechanisms regulating their activation are largely unknown. RA is a heterogeneous disease, and whereas many patients show clinical improvement during TNF inhibitor (TNFi) therapy, a significant proportion fails to respond. In vitro activation of neutrophils with agents, including TNF, results in rapid and selective changes in gene expression, but how neutrophils contribute to TNF signaling in RA and whether TNFi sensitivity involves differential neutrophil responses are unknown. With the use of RNA sequencing (RNA-Seq), we analyzed blood neutrophils from 20 RA patients, pre-TNFi therapy, to identify biomarkers of response, measured by a decrease in disease activity score based on 28 joint count (DAS28), 12 wk post-therapy. Biomarkers were validated by quantitative PCR (qPCR) of blood neutrophils from 2 further independent cohorts of RA patients: 16 pre-TNFi and 16 predisease-modifying anti-rheumatic drugs (DMARDs). Twenty-three neutrophil transcripts predicted a 12-wk response to TNFi: 10 (IFN-regulated) genes predicting a European League against Rheumatism (EULAR) good response and 13 different genes [neutrophil granule protein (NGP) genes] predicting a nonresponse. Statistical analysis indicated a predictive sensitivity and specificity of each gene in the panel of >80%, with some 100% specific. A combination of 3 genes [cytidine monophosphate kinase 2 (CMPK2), IFN-induced protein with tetratricopeptide repeats 1B (IFIT1B), and RNASE3] had the greatest predictive power [area under the curve (AUC) 0.94]. No correlation was found for a response to DMARDs. We conclude that this panel of genes is selective for predicting a response to TNFi and is not a surrogate marker for disease improvement. We also show that in RA, there is great plasticity in neutrophil phenotype, with circulating cells expressing genes normally only expressed in more immature cells.

  1. Validation of a Deterministic Vibroacoustic Response Prediction Model

    NASA Technical Reports Server (NTRS)

    Caimi, Raoul E.; Margasahayam, Ravi

    1997-01-01

    This report documents the recently completed effort involving validation of a deterministic theory for the random vibration problem of predicting the response of launch pad structures in the low-frequency range (0 to 50 hertz). Use of the Statistical Energy Analysis (SEA) methods is not suitable in this range. Measurements of launch-induced acoustic loads and subsequent structural response were made on a cantilever beam structure placed in close proximity (200 feet) to the launch pad. Innovative ways of characterizing random, nonstationary, non-Gaussian acoustics are used for the development of a structure's excitation model. Extremely good correlation was obtained between analytically computed responses and those measured on the cantilever beam. Additional tests are recommended to bound the problem to account for variations in launch trajectory and inclination.

  2. Nonlinear random response prediction using MSC/NASTRAN

    NASA Astrophysics Data System (ADS)

    Robinson, J. H.; Chiang, C. K.; Rizzi, S. A.

    1993-10-01

    An equivalent linearization technique was incorporated into MSC/NASTRAN to predict the nonlinear random response of structures by means of Direct Matrix Abstract Programming (DMAP) modifications and inclusion of the nonlinear differential stiffness module inside the iteration loop. An iterative process was used to determine the rms displacements. Numerical results obtained for validation on simple plates and beams are in good agreement with existing solutions in both the linear and linearized regions. The versatility of the implementation will enable the analyst to determine the nonlinear random responses for complex structures under combined loads. The thermo-acoustic response of a hexagonal thermal protection system panel is used to highlight some of the features of the program.

  3. Nonlinear random response prediction using MSC/NASTRAN

    NASA Technical Reports Server (NTRS)

    Robinson, J. H.; Chiang, C. K.; Rizzi, S. A.

    1993-01-01

    An equivalent linearization technique was incorporated into MSC/NASTRAN to predict the nonlinear random response of structures by means of Direct Matrix Abstract Programming (DMAP) modifications and inclusion of the nonlinear differential stiffness module inside the iteration loop. An iterative process was used to determine the rms displacements. Numerical results obtained for validation on simple plates and beams are in good agreement with existing solutions in both the linear and linearized regions. The versatility of the implementation will enable the analyst to determine the nonlinear random responses for complex structures under combined loads. The thermo-acoustic response of a hexagonal thermal protection system panel is used to highlight some of the features of the program.

  4. Continuous immunotypes describe human immune variation and predict diverse responses.

    PubMed

    Kaczorowski, Kevin J; Shekhar, Karthik; Nkulikiyimfura, Dieudonné; Dekker, Cornelia L; Maecker, Holden; Davis, Mark M; Chakraborty, Arup K; Brodin, Petter

    2017-07-25

    The immune system consists of many specialized cell populations that communicate with each other to achieve systemic immune responses. Our analyses of various measured immune cell population frequencies in healthy humans and their responses to diverse stimuli show that human immune variation is continuous in nature, rather than characterized by discrete groups of similar individuals. We show that the same three key combinations of immune cell population frequencies can define an individual's immunotype and predict a diverse set of functional responses to cytokine stimulation. We find that, even though interindividual variations in specific cell population frequencies can be large, unrelated individuals of younger age have more homogeneous immunotypes than older individuals. Across age groups, cytomegalovirus seropositive individuals displayed immunotypes characteristic of older individuals. The conceptual framework for defining immunotypes suggested by our results could guide the development of better therapies that appropriately modulate collective immunotypes, rather than individual immune components.

  5. Urate predicts rate of clinical decline in Parkinson disease

    PubMed Central

    Ascherio, Alberto; LeWitt, Peter A.; Xu, Kui; Eberly, Shirley; Watts, Arthur; Matson, Wayne R.; Marras, Connie; Kieburtz, Karl; Rudolph, Alice; Bogdanov, Mikhail B.; Schwid, Steven R.; Tennis, Marsha; Tanner, Caroline M.; Beal, M. Flint; Lang, Anthony E.; Oakes, David; Fahn, Stanley; Shoulson, Ira; Schwarzschild, Michael A.

    2009-01-01

    Context The risk of Parkinson disease (PD) and its rate of progression may decline with increasing blood urate, a major antioxidant. Objective To determine whether serum and cerebrospinal fluid (CSF) concentrations of urate predict clinical progression in patients with PD. Design, Setting, and Participants 800 subjects with early PD enrolled in the DATATOP trial. Pre-treatment urate was measured in serum for 774 subjects and in CSF for 713. Main Outcome Measures Treatment-, age- and sex-adjusted hazard ratios (HRs) for clinical disability requiring levodopa therapy, the pre-specified primary endpoint. Results The HR of progressing to endpoint decreased with increasing serum urate (HR for 1 standard deviation increase = 0.82; 95% CI = 0.73 to 0.93). In analyses stratified by α-tocopherol treatment (2,000 IU/day), a decrease in the HR for the primary endpoint was seen only among subjects not treated with α-tocopherol (HR = 0.75; 95% CI = 0.62 to 0.89, versus those treated HR = 0.90; 95% CI = 0.75 to 1.08). Results were similar for the rate of change in the United Parkinson Disease Rating Scale (UPDRS). CSF urate was also inversely related to both the primary endpoint (HR for highest versus lowest quintile = 0.65; 95% CI: 0.54 to 0.96) and to the rate of change in UPDRS. As with serum urate, these associations were present only among subjects not treated with α-tocopherol. Conclusion Higher serum and CSF urate at baseline were associated with slower rates of clinical decline. The findings strengthen the link between urate and PD and the rationale for considering CNS urate elevation as a potential strategy to slow PD progression. PMID:19822770

  6. Impairing loyalty: corporate responsibility for clinical misadventure.

    PubMed

    Kipnis, Kenneth

    2011-09-01

    A medical device manufacturer pays a surgeon to demonstrate a novel medical instrument in a live broadcast to an audience of specialists in another city. The surgical patient is unaware of the broadcast and unaware of the doctor's relationship with the manufacturer. It turns out that the patient required a different surgical approach to her condition-one that would not have allowed a demonstration of the instrument--and she later dies. The paper is an exploration of whether the manufacturer shares, along with the doctor, responsibility for the death of the patient. Three arguments for corporate responsibility are considered; two are criticized and the third is offered as sound.

  7. Impact of triplicate testing on HIV genotypic tropism prediction in routine clinical practice.

    PubMed

    Symons, J; Vandekerckhove, L; Paredes, R; Verhofstede, C; Bellido, R; Demecheleer, E; van Ham, P M; van Lelyveld, S F L; Stam, A J; van Versendaal, D; Nijhuis, M; Wensing, A M J

    2012-06-01

    Guidelines state that the CCR5-inhibitor Maraviroc should be prescribed to patients infected with R5-tropic HIV-1 only. Therefore, viral tropism needs to be assessed phenotypically or genotypically. Preliminary clinical trial data suggest that genotypic analysis in triplicate is associated with improved prediction of virological response by increasing the detection of X4-tropic variants. Our objective was to evaluate the impact of triplicate genotypic analysis on prediction of co-receptor usage in routine clinical practice. Samples from therapy-naive and therapy-experienced patients were collected for routine tropism testing at three European clinical centres. Viral RNA was isolated from plasma and proviral DNA from peripheral blood mononuclear cells. Gp120-V3 was amplified in a triplicate nested RT-PCR procedure and sequenced. Co-receptor usage was predicted using the Geno2Pheno([coreceptor]) algorithm and analysed with a false-positive rate (FPR) of 5.75%, 10%, or an FPR of 20% and according to the current European guidelines on the clinical management of HIV-1 tropism testing. A total of 266 sequences were obtained from 101 patient samples. Discordance in tropism prediction for the triplicates was observed in ten samples using an FPR of 10%. Triplicate testing resulted in a 16.7% increase in X4-predicted samples and to reclassification from R5 to X4 tropism for four cases rendering these patients ineligible for Maraviroc treatment. In conclusion, triplicate genotypic tropism testing increases X4 tropism detection in individual cases, which may prove to be pivotal when CCR5-inhibitor therapy is applied.

  8. St. Gallen endocrine response classes predict recurrence rates over time.

    PubMed

    Koornstra, R H T; Beelen, K J; Vincent, A D; van der Noort, V; van Diest, P J; Linn, S C

    2015-12-01

    In 2007 the St. Gallen consensus panel defined three endocrine response classes: highly endocrine responsive (ER-H), incomplete endocrine responsive (ER-I) and non-endocrine responsive tumours (ER-N). However, it is uncertain whether ER-I tumours are less responsive than ER-H tumours. We investigated whether recurrence rates vary over time between response classes. Additionally, we investigated the most predictive response class definition for tamoxifen benefit. We recollected tumours from 646 patients who participated in a randomized trial of adjuvant tamoxifen vs. Estrogen receptor (ER), progesterone receptor (PgR), HER2 status and tumour grade were revised centrally. St. Gallen classes were evaluated for recurrence free interval (RFI). Change in hazards over time was assessed. Subsequently, 6 alternative response class definitions were compared to optimize the cut-off for PgR and ER. Schoenfeld residuals indicate a failure of proportional hazards between the endocrine response groups (p = 0.0001). The HR for recurrence risk shifted over time with the ER-H group initially being at lower risk (HR ER-H vs. ER-I 0.5), but after six years the recurrence risk increased (HR 1.9). The cut-off values for ER and PgR that statistically best discriminated RFI in the first 4 years for lymph node positive patients were ER ≥ 50% and PgR ≥ 75%. We demonstrated a marked variability in endocrine therapy benefit. Patients with ER-H tumours have a larger benefit during adjuvant tamoxifen and in the first years after accomplishing of the therapy, but suffer from late recurrences. This might have implications for optimal treatment duration. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. RESPONSE EXPECTANCIES AND IRRATIONAL BELIEFS PREDICT EXAM-RELATED DISTRESS

    PubMed Central

    Montgomery, Guy H.; David, Daniel; DiLorenzo, Terry A.; Schnur, Julie B.

    2009-01-01

    Individual differences in cognitive factors such as response expectancies and irrational beliefs (IBs) have been shown to contribute to variability in distress associated with stressful situations. However, their independent influence on distress when examined within the same study has not been established, nor has the potential of mediational relationships. The purpose of this study was to investigate the contribution of response expectancies and IBs (both general and exam-specific) to exam-related distress in a prospective study. Results revealed that both response expectancies and general IBs separately predicted exam-related distress (p’s <.05; N = 105). Observed effects of general IBs were perfectly mediated by, and observed effects of exam-specific IBs were partially mediated by, response expectancies using the Baron and Kenny approach. These data support the view that cognitive factors contribute to psychological distress and are consistent with response expectancy and rational emotive behavior theories. The results suggest that interventions focused on response expectancies and IBs might be an effective means to reduce psychological distress associated with real life stressors such as exams. Future research is needed to determine whether this effect generalizes to other stressful situations. PMID:20011227

  10. Clinical prediction of weaning and extubation in Australian and New Zealand intensive care units.

    PubMed

    Rose, L; Presneill, J J

    2011-07-01

    Our objective was to describe, in Australian and New Zealand adult intensive care units, the relative frequency in which various clinical criteria were used to predict weaning and extubation, and the weaning methods employed. Participant intensivists at 55 intensive care units completed a self-administered questionnaire, using visual analogue scales (0 = not at all predictive, 10 = perfectly predictive, not used = null score) to record the perceived utility of 30 potential predictors. Survey response rate was 71% (164/230). Those variables thought most predictive of weaning readiness were respiratory rate (median score 8.0, interquartile range 7.0 to 8.6) effective cough (7.3, 5.9 to 8.2) and pressure support setting (7.2, 6.0 to 8.0). The most highly rated predictors of extubation success were effective cough (8.0, 7.0 to 9.0), respiratory rate (8.0, 7.0 to 8.5) and Glasgow Coma Score (7.9, 6.1 to 8.3). Variables perceived least predictive of weaning and extubation success were P0.1, Acute Physiological and Chronic Health Evaluation score II, mean arterial pressure, electrolytes and maximum inspiratory pressure (individual median scores < 5). Most popular clinical criteria were those perceived to have high predictive accuracy, both for weaning (respiratory rate 96%, pressure support setting 94% and Glasgow coma score 91%) and extubation readiness (respiratory rate 98%, effective cough 94% and Glasgow Coma Score 92%). Weaning mostly employed pressure support ventilation (55%), with less use of synchronised intermittent mandatory ventilation (32%) and spontaneous breathing trials (13%). Classic ventilatory performance predictors including respiratory rate and effective cough were reported to be of greater clinical utility than other more recently proposed measures.

  11. Use of reflectance spectrophotometry to predict the response of port wine stains to pulsed dye laser.

    PubMed

    Halachmi, Shlomit; Azaria, Ron; Inbar, Roy; Ad-El, Dean; Lapidoth, Moshe

    2014-01-01

    Reflectance spectroscopy can be used to quantitate subtle differences in color. We applied a portable reflectance spectrometer to determine its utility in the evaluation of pulsed dye laser treatment of port wine stains (PWS) and in prediction of clinical outcome, in a prospective study. Forty-eight patients with PWS underwent one to nine pulsed dye laser treatments. Patient age and skin color as well as PWS surface area, anatomic location, and color were recorded. Pretreatment spectrophotometric measurements were performed. The subjective clinical results of treatment and the quantitative spectrophotometry results were evaluated by two independent teams, and the findings were correlated. The impact of the clinical characteristics on the response to treatment was assessed as well. Patients with excellent to good clinical results of laser treatments had pretreatment spectrophotometric measurements which differed by more than 10%, whereas patients with fair to poor results had spectrophotometric measurements with a difference of of less than 10%. The correlation between the spectrophotometric results and the clinical outcome was 73% (p < 0.01). The impact of the other clinical variables on outcome agreed with the findings in the literature. Spectrophotometry has a higher correlation with clinical outcome and a better predictive value than other nonmeasurable, nonquantitative, dependent variables.

  12. Is electromyography a predictive test of patient response to biofeedback in the treatment of fecal incontinence?

    PubMed

    Lacima, Gloria; Pera, Miguel; González-Argenté, Xavier; Torrents, Abiguei; Valls-Solé, Josep; Espuña-Pons, Montserrat

    2016-03-01

    Biofeedback is effective in more than 70% of patients with fecal incontinence. However, reliable predictors of successful treatment have not been identified. The aim was to identify clinical variables and diagnostic tests, particularly electromyography, that could predict a successful outcome. We included 135 consecutive women with fecal incontinence treated with biofeedback. Clinical evaluation, manometry, ultrasonography, electromyography, and pudendal nerve terminal motor latency were performed before therapy. Treatment outcome was assessed using a symptoms diary, Wexner incontinence score and the patient's subjective perception. According to the symptoms diaries, 106 (78.5%) women had a good clinical result and 29 (21.5%) had a poor result. There were no differences in age, severity and type of fecal incontinence. Maximum resting pressure (39.3 ± 19.1 mmHg vs. 33.7 ± 20.2 mmHg; P = 0.156) and maximum squeeze pressure (91.8 ± 33.2 mmHg vs. 79.8 ± 31.2 mmHg; P = 0.127) were higher in patients having good clinical outcome although the difference was not significant. There were no differences in the presence of sphincter defects or abnormalities in electromyographic recordings. Logistic regression analysis found no independent predictive factor for good clinical outcome. Biofeedback is effective in more than 75% of patients with fecal incontinence. Clinical characteristics of patients and results of baseline tests have no predictive value of response to therapy. Specifically, we found no association between severity of electromyographic deficit and clinical response. © 2015 Wiley Periodicals, Inc.

  13. Optimized outcome prediction in breast cancer by combining the 70-gene signature with clinical risk prediction algorithms.

    PubMed

    Drukker, C A; Nijenhuis, M V; Bueno-de-Mesquita, J M; Retèl, V P; van Harten, W H; van Tinteren, H; Wesseling, J; Schmidt, M K; Van't Veer, L J; Sonke, G S; Rutgers, E J T; van de Vijver, M J; Linn, S C

    2014-06-01

    Clinical guidelines for breast cancer treatment differ in their selection of patients at a high risk of recurrence who are eligible to receive adjuvant systemic treatment (AST). The 70-gene signature is a molecular tool to better guide AST decisions. The aim of this study was to evaluate whether adding the 70-gene signature to clinical risk prediction algorithms can optimize outcome prediction and consequently treatment decisions in early stage, node-negative breast cancer patients. A 70-gene signature was available for 427 patients participating in the RASTER study (cT1-3N0M0). Median follow-up was 61.6 months. Based on 5-year distant-recurrence free interval (DRFI) probabilities survival areas under the curve (AUC) were calculated and compared for risk estimations based on the six clinical risk prediction algorithms: Adjuvant! Online (AOL), Nottingham Prognostic Index (NPI), St. Gallen (2003), the Dutch National guidelines (CBO 2004 and NABON 2012), and PREDICT plus. Also, survival AUC were calculated after adding the 70-gene signature to these clinical risk estimations. Systemically untreated patients with a high clinical risk estimation but a low risk 70-gene signature had an excellent 5-year DRFI varying between 97.1 and 100 %, depending on the clinical risk prediction algorithms used in the comparison. The best risk estimation was obtained in this cohort by adding the 70-gene signature to CBO 2012 (AUC: 0.644) and PREDICT (AUC: 0.662). Clinical risk estimations by all clinical algorithms improved by adding the 70-gene signature. Patients with a low risk 70-gene signature have an excellent survival, independent of their clinical risk estimation. Adding the 70-gene signature to clinical risk prediction algorithms improves risk estimations and therefore might improve the identification of early stage node-negative breast cancer patients for whom AST has limited value. In this cohort, the PREDICT plus tool in combination with the 70-gene signature provided the

  14. Response expectancy versus response hope in predicting birth-related emotional distress and pain.

    PubMed

    Anton, Raluca; David, Daniel

    2013-01-01

    Response expectancies and response hopes have been shown to be two distinct constructs with important implications for nonvolitional outcomes. More specifically, studies show that response expectancies: (1) are sufficient to cause nonvolitional outcomes, (2) are not mediated by other psychological variables, and (3) are self-confirming while seemingly automatic. A new programmatic research line has differentiated between people's response expectancies and their response hopes regarding nonvolitional outcomes and showed that even if response hope and response expectancy are separate constructs, they are not unrelated. These concepts have not yet been studied in pregnant women. Moreover, determining the causal factors that best explain the variance of emotional distress and pain in pregnancy is of great importance. Thus, the aim of this study was to investigate the interrelations between response expectancy and response hope in pregnant women with respect to (1) emotional distress prior to giving birth and (2) pain during giving birth. Additionally, self-reported labor hours were analyzed as a secondary outcome. Results show that response expectancy for pain directly predicts pain, and that the discrepancy between response hopes and response expectancies is a strong predictor of investigated outcomes. Thus, our results support the idea that preventive psychological interventions for pregnant women should emphasize adjusting response expectancies and response hopes regarding the pain and emotional distress associated with giving birth. We believe that the results have both theoretical and practical implications and the topic deserves further investigation.

  15. Predicting water table response to rainfall events, central Florida.

    PubMed

    van Gaalen, J F; Kruse, S; Lafrenz, W B; Burroughs, S M

    2013-01-01

    A rise in water table in response to a rainfall event is a complex function of permeability, specific yield, antecedent soil-water conditions, water table level, evapotranspiration, vegetation, lateral groundwater flow, and rainfall volume and intensity. Predictions of water table response, however, commonly assume a linear relationship between response and rainfall based on cumulative analysis of water level and rainfall logs. By identifying individual rainfall events and responses, we examine how the response/rainfall ratio varies as a function of antecedent water table level (stage) and rainfall event size. For wells in wetlands and uplands in central Florida, incorporating stage and event size improves forecasting of water table rise by more than 30%, based on 10 years of data. At the 11 sites studied, the water table is generally least responsive to rainfall at smallest and largest rainfall event sizes and at lower stages. At most sites the minimum amount of rainfall required to induce a rise in water table is fairly uniform when the water table is within 50 to 100 cm of land surface. Below this depth, the minimum typically gradually increases with depth. These observations can be qualitatively explained by unsaturated zone flow processes. Overall, response/rainfall ratios are higher in wetlands and lower in uplands, presumably reflecting lower specific yields and greater lateral influx in wetland sites. Pronounced depth variations in rainfall/response ratios appear to correlate with soil layer boundaries, where corroborating data are available. © 2012, The Author(s). Groundwater © 2012, National Ground Water Association.

  16. Germline genetic testing to predict drug response and toxicity in oncology--reality or fiction?

    PubMed

    Soh, Thomas I P; Yong, Wei Peng

    2011-08-01

    In addition to 6-mercaptopurine, 5-fluorouracil and irinotecan, the United States Food and Drug Administration (US FDA) has recently recommended label change for tamoxifen, to include pharmacogenetic information on treatment outcome. With the increasing availability of pharmacogenetic testing, on germline as well as somatic mutations, oncologists are now able to identify individuals at risk of severe treatment toxicity or poor treatment response. However, there are still knowledge gaps to fill before rationalised therapy based on pharmacogenetics can be fully integrated into clinical practice. This review provides an overview on the application of pharmacogenetic testing for germ line mutations in oncology to predict response and toxicity.

  17. Myopodin methylation is a prognostic biomarker and predicts antiangiogenic response in advanced kidney cancer.

    PubMed

    Pompas-Veganzones, N; Sandonis, V; Perez-Lanzac, Alberto; Beltran, M; Beardo, P; Juárez, A; Vazquez, F; Cozar, J M; Alvarez-Ossorio, J L; Sanchez-Carbayo, Marta

    2016-10-01

    Myopodin is a cytoskeleton protein that shuttles to the nucleus depending on the cellular differentiation and stress. It has shown tumor suppressor functions. Myopodin methylation status was useful for staging bladder and colon tumors and predicting clinical outcome. To our knowledge, myopodin has not been tested in kidney cancer to date. The purpose of this study was to evaluate whether myopodin methylation status could be clinically useful in renal cancer (1) as a prognostic biomarker and 2) as a predictive factor of response to antiangiogenic therapy in patients with metastatic disease. Methylation-specific polymerase chain reactions (MS-PCR) were used to evaluate myopodin methylation in 88 kidney tumors. These belonged to patients with localized disease and no evidence of disease during follow-up (n = 25) (group 1), and 63 patients under antiangiogenic therapy (sunitinib, sorafenib, pazopanib, and temsirolimus), from which group 2 had non-metastatic disease at diagnosis (n = 32), and group 3 showed metastatic disease at diagnosis (n = 31). Univariate and multivariate Cox analyses were utilized to assess outcome and response to antiangiogenic agents taking progression, disease-specific survival, and overall survival as clinical endpoints. Myopodin was methylated in 50 out of the 88 kidney tumors (56.8 %). Among the 88 cases analyzed, 10 of them recurred (11.4 %), 51 progressed (57.9 %), and 40 died of disease (45.4 %). Myopodin methylation status correlated to MSKCC Risk score (p = 0.050) and the presence of distant metastasis (p = 0.039). Taking all patients, an unmethylated myopodin identified patients with shorter progression-free survival, disease-specific survival, and overall survival. Using also in univariate and multivariate models, an unmethylated myopodin predicted response to antiangiogenic therapy (groups 2 and 3) using progression-free survival, disease-specific, and overall survival as clinical endpoints. Myopodin was revealed

  18. A novel neural-inspired learning algorithm with application to clinical risk prediction.

    PubMed

    Tay, Darwin; Poh, Chueh Loo; Kitney, Richard I

    2015-04-01

    Clinical risk prediction - the estimation of the likelihood an individual is at risk of a disease - is a coveted and exigent clinical task, and a cornerstone to the recommendation of life saving management strategies. This is especially important for individuals at risk of cardiovascular disease (CVD) given the fact that it is the leading causes of death in many developed counties. To this end, we introduce a novel learning algorithm - a key factor that influences the performance of machine learning-based prediction models - and utilities it to develop CVD risk prediction tool. This novel neural-inspired algorithm, called the Artificial Neural Cell System for classification (ANCSc), is inspired by mechanisms that develop the brain and empowering it with capabilities such as information processing/storage and recall, decision making and initiating actions on external environment. Specifically, we exploit on 3 natural neural mechanisms responsible for developing and enriching the brain - namely neurogenesis, neuroplasticity via nurturing and apoptosis - when implementing ANCSc algorithm. Benchmark testing was conducted using the Honolulu Heart Program (HHP) dataset and results are juxtaposed with 2 other algorithms - i.e. Support Vector Machine (SVM) and Evolutionary Data-Conscious Artificial Immune Recognition System (EDC-AIRS). Empirical experiments indicate that ANCSc algorithm (statistically) outperforms both SVM and EDC-AIRS algorithms. Key clinical markers identified by ANCSc algorithm include risk factors related to diet/lifestyle, pulmonary function, personal/family/medical history, blood data, blood pressure, and electrocardiography. These clinical markers, in general, are also found to be clinically significant - providing a promising avenue for identifying potential cardiovascular risk factors to be evaluated in clinical trials.

  19. Does stroke location predict walk speed response to gait rehabilitation?

    PubMed Central

    Jones, P. Simon; Pomeroy, Valerie M.; Wang, Jasmine; Schlaug, Gottfried; Tulasi Marrapu, S.; Geva, Sharon; Rowe, Philip J.; Chandler, Elizabeth; Kerr, Andrew

    2015-01-01

    Abstract Objectives Recovery of independent ambulation after stroke is a major goal. However, which rehabilitation regimen best benefits each individual is unknown and decisions are currently made on a subjective basis. Predictors of response to specific therapies would guide the type of therapy most appropriate for each patient. Although lesion topography is a strong predictor of upper limb response, walking involves more distributed functions. Earlier studies that assessed the cortico‐spinal tract (CST) were negative, suggesting other structures may be important. Experimental Design: The relationship between lesion topography and response of walking speed to standard rehabilitation was assessed in 50 adult‐onset patients using both volumetric measurement of CST lesion load and voxel‐based lesion–symptom mapping (VLSM) to assess non‐CST structures. Two functional mobility scales, the functional ambulation category (FAC) and the modified rivermead mobility index (MRMI) were also administered. Performance measures were obtained both at entry into the study (3–42 days post‐stroke) and at the end of a 6‐week course of therapy. Baseline score, age, time since stroke onset and white matter hyperintensities score were included as nuisance covariates in regression models. Principal Observations: CST damage independently predicted response to therapy for FAC and MRMI, but not for walk speed. However, using VLSM the latter was predicted by damage to the putamen, insula, external capsule and neighbouring white matter. Conclusions Walk speed response to rehabilitation was affected by damage involving the putamen and neighbouring structures but not the CST, while the latter had modest but significant impact on everyday functions of general mobility and gait. Hum Brain Mapp 37:689–703, 2016. © 2015 Wiley Periodicals, Inc. PMID:26621010

  20. MGMT expression predicts response to temozolomide in pancreatic neuroendocrine tumors.

    PubMed

    Cros, J; Hentic, O; Rebours, V; Zappa, M; Gille, N; Theou-Anton, N; Vernerey, D; Maire, F; Lévy, P; Bedossa, P; Paradis, V; Hammel, P; Ruszniewski, P; Couvelard, A

    2016-08-01

    Temozolomide (TEM) showed encouraging results in well-differentiated pancreatic neuroendocrine tumors (WDPNETs). Low O(6)-methylguanine-DNA methyltransferase (MGMT) expression and MGMT promoter methylation within tumors correlate with a better outcome under TEM-based chemotherapy in glioblastoma. We aimed to assess whether MGMT expression and MGMT promoter methylation could help predict the efficacy of TEM-based chemotherapy in patients with WDPNET. Consecutive patients with progressive WDPNET and/or liver involvement over 50% who received TEM between 2006 and 2012 were retrospectively studied. Tumor response was assessed according to Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 guidelines. Nuclear expression of MGMT was assessed by immunochemistry (H-score, 0-300) and MGMT promoter methylation by pyrosequencing. Forty-three patients (21 men, 58years (27-84)) with grade 1 WDPNET (n=6) or 2 (n=36) were analyzed. Objective response, stable disease, and progression rates were seen in 17 patients (39.5%), 18 patients (41.9%), and 8 patients (18.6%), respectively. Low MGMT expression (≤50) was associated with radiological objective response (P=0.04) and better progression-free survival (PFS) (HR=0.35 (0.15-0.81), P=0.01). Disease control rate at 18months of treatment remained satisfying with an MGMT score up to 100 (74%) but dropped with a higher expression. High MGMT promoter methylation was associated with a low MGMT expression and longer PFS (HR=0.37 (0.29-1.08), P=0.05). Low MGMT score (≤50) appears to predict an objective tumor response, whereas an intermediate MGMT score (50-100) seems to be associated with prolonged stable disease.

  1. Responsiveness and predictive value of EDSS and MSFC in primary progressive MS.

    PubMed

    Kragt, J J; Thompson, A J; Montalban, X; Tintoré, M; Río, J; Polman, C H; Uitdehaag, B M J

    2008-03-25

    We studied the responsiveness and predictive value of two widely used clinical outcome measures that document multiple sclerosis (MS) disease progression-the Expanded Disability Status Scale (EDSS) and the Multiple Sclerosis Functional Composite (MSFC)-in patients with primary progressive (PP) MS. Disease course in PPMS shows less fluctuation than in relapsing remitting (RR) MS. In a group of 161 patients with PPMS, EDSS and MSFC were performed at three timepoints. To assess responsiveness, mean change scores and variances were plotted against baseline scores and effect sizes were calculated. Predictive value was determined by calculating sensitivity, specificity, and likelihood ratios (LRs) of 1-year changes to predict changes over 2 years. Furthermore, multivariate logistic regression models were used to assess the predictive value of short-term worsening on EDSS and MSFC. Responsiveness of both EDSS and MSFC was shown to be limited and mean changes were highly dependent on the baseline scores. Effect sizes for EDSS and MSFC were small and inconclusive (0.239 and 0.161). The predictive value of a short-term worsening (baseline to year 1) to predict worsening in the long term (baseline to year 2) was expressed for EDSS by a sensitivity of 0.55 and a LR+ of 8.64. For MSFC, sensitivity was 0.68 and LR+ was 3.14. However, short-term worsening was a poor predictor of subsequent worsening (year 1 to year 2) for EDSS (LR+ 1.06) and this relationship was actually inverse for MSFC (LR+ 0.61). In this study over a period of 2 years in primary progressive multiple sclerosis, the Multiple Sclerosis Functional Composite (MSFC) was less responsive than the Expanded Disability Status Scale (EDSS). The predictive value of neither EDSS nor MSFC was very powerful.

  2. Prediction of HR/BP response to the spontaneous breathing trial by fluctuation dissipation theory

    NASA Astrophysics Data System (ADS)

    Chen, Man

    2014-03-01

    We applied the non-equilibrium fluctuation dissipation theorem to predict how critically-ill patients respond to treatment, based on both heart rate data and blood pressure data collected by standard hospital monitoring devices. The non-equilibrium fluctuation dissipation theorem relates the response of a system to a perturbation to the fluctuations in the stationary state of the system. It is shown that the response of patients to a standard procedure performed on patients, the spontaneous breathing trial (SBT), can be predicted by the non-equilibrium fluctuation dissipation approach. We classify patients into different groups according to the patients' characteristics. For each patient group, we extend the fluctuation dissipation theorem to predict interactions between blood pressure and beat-to-beat dynamics of heart rate in response to a perturbation (SBT), We also extract the form of the perturbation function directly from the physiological data, which may help to reduce the prediction error. We note this method is not limited to the analysis of the heart rate dynamics, but also can be applied to analyze the response of other physiological signals to other clinical interventions.

  3. An IL28B Genotype-Based Clinical Prediction Model for Treatment of Chronic Hepatitis C

    PubMed Central

    O'Brien, Thomas R.; Everhart, James E.; Morgan, Timothy R.; Lok, Anna S.; Chung, Raymond T.; Shao, Yongwu; Shiffman, Mitchell L.; Dotrang, Myhanh; Sninsky, John J.; Bonkovsky, Herbert L.; Pfeiffer, Ruth M.

    2011-01-01

    Background Genetic variation in IL28B and other factors are associated with sustained virological response (SVR) after pegylated-interferon/ribavirin treatment for chronic hepatitis C (CHC). Using data from the HALT-C Trial, we developed a model to predict a patient's probability of SVR based on IL28B genotype and clinical variables. Methods HALT-C enrolled patients with advanced CHC who had failed previous interferon-based treatment. Subjects were re-treated with pegylated-interferon/ribavirin during trial lead-in. We used step-wise logistic regression to calculate adjusted odds ratios (aOR) and create the predictive model. Leave-one-out cross-validation was used to predict a priori probabilities of SVR and determine area under the receiver operator characteristics curve (AUC). Results Among 646 HCV genotype 1-infected European American patients, 14.2% achieved SVR. IL28B rs12979860-CC genotype was the strongest predictor of SVR (aOR, 7.56; p<.0001); the model also included HCV RNA (log10 IU/ml), AST∶ALT ratio, Ishak fibrosis score and prior ribavirin treatment. For this model AUC was 78.5%, compared to 73.0% for a model restricted to the four clinical predictors and 60.0% for a model restricted to IL28B genotype (p<0.001). Subjects with a predicted probability of SVR <10% had an observed SVR rate of 3.8%; subjects with a predicted probability >10% (43.3% of subjects) had an SVR rate of 27.9% and accounted for 84.8% of subjects actually achieving SVR. To verify that consideration of both IL28B genotype and clinical variables is required for treatment decisions, we calculated AUC values from published data for the IDEAL Study. Conclusion A clinical prediction model based on IL28B genotype and clinical variables can yield useful individualized predictions of the probability of treatment success that could increase SVR rates and decrease the frequency of futile treatment among patients with CHC. PMID:21760886

  4. Human arm posture prediction in response to isometric endpoint forces.

    PubMed

    Davoudabadi Farahani, Saeed; Andersen, Michael Skipper; de Zee, Mark; Rasmussen, John

    2015-11-26

    The ability to predict the musculoskeletal response to external loads has multiple applications for the design of machines with a human interface and for the prediction of outcomes of musculoskeletal interventions. In this study, we applied an inverse-inverse dynamics technique to investigate its ability to predict arm posture in response to isometric hand forces. For each subject, we made a three-dimensional musculoskeletal model using the AnyBody Modelling System (AMS). Then, we had each subject-specific model hold a weight anteriorly to the right shoulder joint at a distance of half of the arm length. We selected the glenohumeral abduction angle (GHAA) as the only free parameter. Subsequently, we used inverse-inverse dynamics to find the optimal GHAA that minimised a performance criterion with physiological constraints. In this study, we investigated the performance of two different objective functions: summation of squared muscle activity (SSMA) and summation of squared normalised joint torques (SSNJT). To validate the simulation results, arm posture responses to different isometric downward hand forces were measured for six healthy male subjects. Five trials were performed for each loading condition. The results showed that, with an increase in hand load, there was a reduced GHAA in all subjects. Another interesting finding was that self-selected postures for lighter tasks varied more than postures for heavier tasks for all subjects. To understand this, we investigated the curvature of the objective function as a function of the load and observed an increased curvature with increased load. This may explain the reduced intra-subject variations observed for increasing loads. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Microsatellite Instability Predicts Clinical Outcome in Radiation-Treated Endometrioid Endometrial Cancer

    SciTech Connect

    Bilbao, Cristina; Lara, Pedro Carlos; Ramirez, Raquel; Henriquez-Hernandez, Luis Alberto; Rodriguez, German; Falcon, Orlando; Leon, Laureano; Perucho, Manuel

    2010-01-15

    Purpose: To elucidate whether microsatellite instability (MSI) predicts clinical outcome in radiation-treated endometrioid endometrial cancer (EEC). Methods and Materials: A consecutive series of 93 patients with EEC treated with extrafascial hysterectomy and postoperative radiotherapy was studied. The median clinical follow-up of patients was 138 months, with a maximum of 232 months. Five quasimonomorphic mononucleotide markers (BAT-25, BAT-26, NR21, NR24, and NR27) were used for MSI classification. Results: Twenty-five patients (22%) were classified as MSI. Both in the whole series and in early stages (I and II), univariate analysis showed a significant association between MSI and poorer 10-year local disease-free survival, disease-free survival, and cancer-specific survival. In multivariate analysis, MSI was excluded from the final regression model in the whole series, but in early stages MSI provided additional significant predictive information independent of traditional prognostic and predictive factors (age, stage, grade, and vascular invasion) for disease-free survival (hazard ratio [HR] 3.25, 95% confidence interval [CI] 1.01-10.49; p = 0.048) and cancer-specific survival (HR 4.20, 95% CI 1.23-14.35; p = 0.022) and was marginally significant for local disease-free survival (HR 3.54, 95% CI 0.93-13.46; p = 0.064). Conclusions: These results suggest that MSI may predict radiotherapy response in early-stage EEC.

  6. Predicting MCI outcome with clinically available MRI and CSF biomarkers

    PubMed Central

    Heister, D.; Brewer, J.B.; Magda, S.; Blennow, K.

    2011-01-01

    Objective: To determine the ability of clinically available volumetric MRI (vMRI) and CSF biomarkers, alone or in combination with a quantitative learning measure, to predict conversion to Alzheimer disease (AD) in patients with mild cognitive impairment (MCI). Methods: We stratified 192 MCI participants into positive and negative risk groups on the basis of 1) degree of learning impairment on the Rey Auditory Verbal Learning Test; 2) medial temporal atrophy, quantified from Food and Drug Administration–approved software for automated vMRI analysis; and 3) CSF biomarker levels. We also stratified participants based on combinations of risk factors. We computed Cox proportional hazards models, controlling for age, to assess 3-year risk of converting to AD as a function of risk group and used Kaplan-Meier analyses to determine median survival times. Results: When risk factors were examined separately, individuals testing positive showed significantly higher risk of converting to AD than individuals testing negative (hazard ratios [HR] 1.8–4.1). The joint presence of any 2 risk factors substantially increased risk, with the combination of greater learning impairment and increased atrophy associated with highest risk (HR 29.0): 85% of patients with both risk factors converted to AD within 3 years, vs 5% of those with neither. The presence of medial temporal atrophy was associated with shortest median dementia-free survival (15 months). Conclusions: Incorporating quantitative assessment of learning ability along with vMRI or CSF biomarkers in the clinical workup of MCI can provide critical information on risk of imminent conversion to AD. PMID:21998317

  7. Clinical errors as a lack of context responsiveness.

    PubMed

    Bugatti, Matteo; Boswell, James F

    2016-09-01

    Although standardized treatments have the potential to decrease clinical errors, within-session responsiveness is complicated and complementary frameworks may be needed to foster enhanced responsiveness in the context of evidence-based treatments. Recent efforts have targeted the enhancement of flexibility and responsiveness in the delivery of manualized treatments, including the development of transdiagnostic treatments (i.e., protocols that are designed to be used across different diagnoses) intended to tailor intervention principles to the needs of individual patients. Context-Responsive Psychotherapy Integration (Constantino, Boswell, Bernecker, & Castonguay, 2013) offers an if-then framework that supports the utilization of evidence-based clinical strategies in response to the identification of specific process markers. Failure to identify or appropriately respond to such markers may result in negative therapeutic process as well as outcomes. This case study uses the context-response psychotherapy integration framework to understand critical moments of clinical decision-making through examining an individual treatment case that unilaterally terminated after seven sessions of transdiagnostic treatment. This illustrative empirical case analysis focuses on three potential clinical errors, as indicated by a lack of responsiveness to three candidate process markers: (a) low outcome expectations, (b) self-strivings, and (c) outcome monitoring. For each clinical error, alternative clinical strategies are discussed. PsycINFO Database Record (c) 2016 APA, all rights reserved

  8. The Meta-Analysis of Clinical Judgment Project: Fifty-Six Years of Accumulated Research on Clinical Versus Statistical Prediction

    ERIC Educational Resources Information Center

    Aegisdottir, Stefania; White, Michael J.; Spengler, Paul M.; Maugherman, Alan S.; Anderson, Linda A.; Cook, Robert S.; Nichols, Cassandra N.; Lampropoulos, Georgios K.; Walker, Blain S.; Cohen, Genna; Rush, Jeffrey D.

    2006-01-01

    Clinical predictions made by mental health practitioners are compared with those using statistical approaches. Sixty-seven studies were identified from a comprehensive search of 56 years of research; 92 effect sizes were derived from these studies. The overall effect of clinical versus statistical prediction showed a somewhat greater accuracy for…

  9. Predicting the Response to Intravenous Immunoglobulins in an Animal Model of Chronic Neuritis

    PubMed Central

    Pfaff, Johannes; Mathys, Christian; Mausberg, Anne K.; Bendszus, Martin; Pham, Mirko; Hartung, Hans-Peter; Kieseier, Bernd C.

    2016-01-01

    Chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is a disabling autoimmune disorder of the peripheral nervous system (PNS). Intravenous immunoglobulins (IVIg) are effective in CIDP, but the treatment response varies greatly between individual patients. Understanding this interindividual variability and predicting the response to IVIg constitute major clinical challenges in CIDP. We previously established intercellular adhesion molecule (ICAM)-1 deficient non-obese diabetic (NOD) mice as a novel animal model of CIDP. Here, we demonstrate that similar to human CIDP patients, ICAM-1 deficient NOD mice respond to IVIg treatment by clinical and histological measures. Nerve magnetic resonance imaging and histology demonstrated that IVIg ameliorates abnormalities preferentially in distal parts of the sciatic nerve branches. The IVIg treatment response also featured great heterogeneity allowing us to identify IVIg responders and non-responders. An increased production of interleukin (IL)-17 positively predicted IVIg treatment responses. In human sural nerve biopsy sections, high numbers of IL-17 producing cells were associated with younger age and shorter disease duration. Thus, our novel animal model can be utilized to identify prognostic markers of treatment responses in chronic inflammatory neuropathies and we identify IL-17 production as one potential such prognostic marker. PMID:27711247

  10. Brachial artery peak velocity variation to predict fluid responsiveness in mechanically ventilated patients

    PubMed Central

    2009-01-01

    Introduction Although several parameters have been proposed to predict the hemodynamic response to fluid expansion in critically ill patients, most of them are invasive or require the use of special monitoring devices. The aim of this study is to determine whether noninvasive evaluation of respiratory variation of brachial artery peak velocity flow measured using Doppler ultrasound could predict fluid responsiveness in mechanically ventilated patients. Methods We conducted a prospective clinical research in a 17-bed multidisciplinary ICU and included 38 mechanically ventilated patients for whom fluid administration was planned due to the presence of acute circulatory failure. Volume expansion (VE) was performed with 500 mL of a synthetic colloid. Patients were classified as responders if stroke volume index (SVi) increased ≥ 15% after VE. The respiratory variation in Vpeakbrach (ΔVpeakbrach) was calculated as the difference between maximum and minimum values of Vpeakbrach over a single respiratory cycle, divided by the mean of the two values and expressed as a percentage. Radial arterial pressure variation (ΔPPrad) and stroke volume variation measured using the FloTrac/Vigileo system (ΔSVVigileo), were also calculated. Results VE increased SVi by ≥ 15% in 19 patients (responders). At baseline, ΔVpeakbrach, ΔPPrad and ΔSVVigileo were significantly higher in responder than nonresponder patients [14 vs 8%; 18 vs. 5%; 13 vs 8%; P < 0.0001, respectively). A ΔVpeakbrach value >10% predicted fluid responsiveness with a sensitivity of 74% and a specificity of 95%. A ΔPPrad value >10% and a ΔSVVigileo >11% predicted volume responsiveness with a sensitivity of 95% and 79%, and a specificity of 95% and 89%, respectively. Conclusions Respiratory variations in brachial artery peak velocity could be a feasible tool for the noninvasive assessment of fluid responsiveness in patients with mechanical ventilatory support and acute circulatory failure. Trial Registration

  11. Challenges and progress in predicting biological responses to incorporated radioactivity.

    PubMed

    Howell, R W; Neti, P V S V; Pinto, M; Gerashchenko, B I; Narra, V R; Azzam, E I

    2006-01-01

    Prediction of risks and therapeutic outcome in nuclear medicine largely rely on calculation of the absorbed dose. Absorbed dose specification is complex due to the wide variety of radiations emitted, non-uniform activity distribution, biokinetics, etc. Conventional organ absorbed dose estimates assumed that radioactivity is distributed uniformly throughout the organ. However, there have been dramatic improvements in dosimetry models that reflect the substructure of organs as well as tissue elements within them. These models rely on improved nuclear medicine imaging capabilities that facilitate determination of activity within voxels that represent tissue elements of approximately 0.2-1 cm(3). However, even these improved approaches assume that all cells within the tissue element receive the same dose. The tissue element may be comprised of a variety of cells having different radiosensitivities and different incorporated radioactivity. Furthermore, the extent to which non-uniform distributions of radioactivity within a small tissue element impact the absorbed dose distribution is strongly dependent on the number, type, and energy of the radiations emitted by the radionuclide. It is also necessary to know whether the dose to a given cell arises from radioactive decays within itself (self-dose) or decays in surrounding cells (cross-dose). Cellular response to self-dose can be considerably different than its response to cross-dose from the same radiopharmaceutical. Bystander effects can also play a role in the response. Evidence shows that even under conditions of 'uniform' distribution of radioactivity, a combination of organ dosimetry, voxel dosimetry and dosimetry at the cellular and multicellular levels can be required to predict response.

  12. Prediction of individual response to antidepressants and antipsychotics: an integrated concept

    PubMed Central

    Preskorn, Sheldon H.

    2014-01-01

    In both clinical trials and daily practice, there can be substantial inter- and even intraindividual variability in response—whether beneficial or adverse—to antidepressants and antipsychotic medications. So far, no tools have become available to predict the outcome of these treatments in specific patients. This is because the causes of such variability are often not known, and when they are, there is no way of predicting the effects of their various potential combinations in an individual. Given this background, this paper presents a conceptual framework for understanding known factors and their combinations so that eventually clinicians can better predict what medication(s) to select and at what dose they can optimize the outcome for a given individual. This framework is flexible enough to be readily adaptable as new information becomes available. The causes of variation in patient response are grouped into four categories: (i) genetics; (ii) age; (iii) disease; and (iv) environment (internal). Four cases of increasing complexity are used to illustrate the applicability of this framework in a clinically relevant way In addition, this paper reviews tools that the clinician can use to assess for and quantify such inter- and intraindividual variability. With the information gained, treatment can be adjusted to compensate for such variability, in order to optimize outcome. Finally, the limitations of existing antidepressant and antipsychotic therapy and the way they reduce current ability to predict response is discussed. PMID:25733958

  13. Neural Reactivity to Angry Faces Predicts Treatment Response in Pediatric Anxiety.

    PubMed

    Bunford, Nora; Kujawa, Autumn; Fitzgerald, Kate D; Swain, James E; Hanna, Gregory L; Koschmann, Elizabeth; Simpson, David; Connolly, Sucheta; Monk, Christopher S; Phan, K Luan

    2017-02-01

    Although cognitive-behavioral psychotherapy (CBT) and pharmacotherapy are evidence-based treatments for pediatric anxiety, many youth with anxiety disorders fail to respond to these treatments. Given limitations of clinical measures in predicting treatment response, identifying neural predictors is timely. In this study, 35 anxious youth (ages 7-19 years) completed an emotional face-matching task during which the late positive potential (LPP), an event-related potential (ERP) component that indexes sustained attention towards emotional stimuli, was measured. Following the ERP measurement, youth received CBT or selective serotonin reuptake inhibitor (SSRI) treatment, and the LPP was examined as a predictor of treatment response. Findings indicated that, accounting for pre-treatment anxiety severity, neural reactivity to emotional faces predicted anxiety severity post- CBT and SSRI treatment such that enhanced electrocortical response to angry faces was associated with better treatment response. An enhanced LPP to angry faces may predict treatment response insofar as it may reflect greater emotion dysregulation or less avoidance and/or enhanced engagement with environmental stimuli in general, including with treatment.

  14. Prediction of Response to Medication and Cognitive Therapy in the Treatment of Moderate to Severe Depression

    PubMed Central

    Fournier, Jay C.; DeRubeis, Robert J.; Shelton, Richard C.; Hollon, Steven D.; Amsterdam, Jay D.; Gallop, Robert

    2009-01-01

    A recent randomized controlled trial found nearly equivalent response rates for antidepressant medications and cognitive therapy in a sample of moderate-to-severely depressed outpatients. In this article, we seek to identify the variables that were associated with response across both treatments as well as variables that predicted superior response in one treatment over the other. The sample consisted of 180 depressed outpatients: 60 of whom were randomly assigned to cognitive therapy; 120 were assigned to antidepressant medications. Treatment was provided for 16 weeks. Chronic depression, older age, and lower intelligence each predicted relatively poor response across both treatments. Three prescriptive variables were identified: marriage, unemployment, and having experienced a greater number of recent life events predicted superior response to cognitive therapy compared to antidepressant medications. Thus, six markers of treatment outcome were identified, each of which might be expected to carry considerable clinical utility. The three prognostic variables identify subgroups that might benefit from alternative treatment strategies; the three prescriptive variables identify groups who appear to respond particularly well to cognitive therapy. PMID:19634969

  15. Baseline Factors Predicting Placebo Response to Treatment in Children and Adolescents With Autism Spectrum Disorders

    PubMed Central

    King, Bryan H.; Dukes, Kimberly; Donnelly, Craig L.; Sikich, Linmarie; McCracken, James T.; Scahill, Lawrence; Hollander, Eric; Bregman, Joel D.; Anagnostou, Evdokia; Robinson, Fay; Sullivan, Lisa; Hirtz, Deborah

    2016-01-01

    IMPORTANCE The finding of factors that differentially predict the likelihood of response to placebo over that of an active drug could have a significant impact on study design in this population. OBJECTIVE To identify possible nonspecific, baseline predictors of response to intervention in a large randomized clinical trial of children and adolescents with autism spectrum disorders. DESIGN, SETTING, AND PARTICIPANTS Randomized clinical trial of citalopram hydrobromide for children and adolescents with autism spectrum disorders and prominent repetitive behavior. Baseline data at study entry were examined with respect to final outcome to determine if response predictors could be identified. A total of 149 children and adolescents 5 to 17 years of age (mean [SD] age, 9.4 [3.1] years) from 6 academic centers were randomly assigned to citalopram (n = 73) or placebo (n = 76). Participants had autistic disorder, Asperger syndrome, or pervasive developmental disorder, not otherwise specified; had illness severity ratings that were moderate or more than moderate on the Clinical Global Impression–Severity scale; and scored moderate or more than moderate on compulsive behaviors measured with the modified Children’s Yale-Brown Obsessive-Compulsive Scale. INTERVENTIONS Twelve weeks of treatment with citalopram (10 mg/5 mL) or placebo. The mean (SD) maximum dose of citalopram was 16.5 (6.5) mg by mouth daily (maximum dose, 20 mg/d). MAIN OUTCOMES AND MEASURES A positive response was defined as having a score of at least much improved on the Clinical Global Impression–Improvement scale at week 12. Baseline measures included demographic (sex, age, weight, and pubertal status), clinical, and family measures. Clinical variables included baseline illness severity ratings (the Aberrant Behavior Checklist, the Child and Adolescent Symptom Inventory, the Vineland Adaptive Behavior Scales, the Repetitive Behavior Scale–Revised, and the Children’s Yale-Brown Obsessive

  16. Can we predict disease course with clinical factors?

    PubMed

    Vegh, Zsuzsanna; Kurti, Zsuzsanna; Golovics, Petra Anna; Lakatos, Peter Laszlo

    2017-03-28

    The disease phenotype at diagnosis and the disease course of Crohn's disease (CD) and ulcerative colitis (UC) show remarkable heterogeneity across patients. In recent population-based epidemiological and referral cohort studies, the evolution of disease phenotype of CD and UC varied significantly. Most CD and severe UC patients still requires hospitalization or surgery/colectomy during follow-up. A change in the natural history of IBD with improved outcomes in parallel with tailored positioning of aggressive immunomodulator and biological therapy has been suspected according to the recently available literature. Therefore it is of major importance to refer IBD cases at risk for adverse disease outcomes as early during the disease course as possible. This review aims to summarize the currently available evidence on clinical and some environmental predictive factors, which clinicians should evaluate in the everyday practice together with other laboratory and imaging data to prevent disease progression, enable a more personalized therapy, and avoid negative disease outcomes. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  17. Using biomarkers to predict treatment response in major depressive disorder: evidence from past and present studies.

    PubMed

    Thase, Michael E

    2014-12-01

    Major depressive disorder (MDD) is a heterogeneous condition with a variable response to a wide range of treatments. Despite intensive efforts, no biomarker has been identified to date that can reliably predict response or non-response to any form of treatment, nor has one been identified that can be used to identify those at high risk of developing treatment-resistant depression (ie, non-response to a sequence of treatments delivered for adequate duration and intensity). This manuscript reviews some past areas of research that have proved informative, such as studies using indexes of hypercortisolism or sleep disturbance, and more recent research findings using measures of inflammation and different indicators of regional cortical activation to predict treatment response. It is concluded that, although no method has yet been demonstrated to be sufficiently accurate to be applied in clinical practice, progress has been made. It thus seems likely that--at some point in the not-too-distant future--it will be possible to prospectively identify, at least for some MDD patients, the likelihood of response or non-response to cognitive therapy or various antidepressant medications.

  18. Clinical factors associated with lithium response in bipolar disorders.

    PubMed

    Sportiche, Sarah; Geoffroy, Pierre Alexis; Brichant-Petitjean, Clara; Gard, Sebastien; Khan, Jean-Pierre; Azorin, Jean-Michel; Henry, Chantal; Leboyer, Marion; Etain, Bruno; Scott, Jan; Bellivier, Frank

    2017-05-01

    Bipolar disorder is a common chronic illness characterized by high levels of morbidity and all-cause mortality. Lithium is one of the gold standard mood stabilizer treatments, but the identification of good, partial and non-responders in clinical settings is inconsistent. We used an established rating scale (the Alda scale) to classify the degree of lithium response (good response, partial response, non-response) in a large, multicentre clinically representative sample of well-characterized cases of bipolar disorders I and II. Next, we examined previously reported clinical predictors of response to determine which factors significantly differentiated between the three response groups. Of 754 cases, 300 received lithium, for at least 6 months, as a treatment for bipolar disorder (40%). Of these cases, 17% were classified as good response, 52% as partial response and 31% as non-response. Lifetime history of mixed episodes ( p = 0.017) and alcohol use disorders ( p = 0.015) both occurred in >20% of partial response and non-response groups but <10% of good response cases. Family history of bipolar disorder I was of borderline statistical significance, being more frequent in the good response group (38%) compared with the non-response group (18%). There was a trend ( p = 0.06) for bipolar disorder II to be associated with non-response. Only three factors previously identified as predictors of lithium response significantly differentiated the response groups identified in our sample. Interestingly, these factors have all been found to co-occur more often than expected by chance, and it can be hypothesized that they may represent a shared underlying factor or dimension. Further prospective studies of predictors and the performance of the Alda scale are recommended.

  19. Clinical applications of the human brainstem responses to auditory stimuli

    NASA Technical Reports Server (NTRS)

    Galambos, R.; Hecox, K.

    1975-01-01

    A technique utilizing the frequency following response (FFR) (obtained by auditory stimulation, whereby the stimulus frequency and duration are mirror-imaged in the resulting brainwaves) as a clinical tool for hearing disorders in humans of all ages is presented. Various medical studies are discussed to support the clinical value of the technique. The discovery and origin of the FFR and another significant brainstem auditory response involved in studying the eighth nerve is also discussed.

  20. Predictive response biomarkers in rectal cancer neoadjuvant treatment.

    PubMed

    Agostini, Marco; Crotti, Sara; Bedin, Chiara; Cecchin, Erika; Maretto, Isacco; D'Angelo, Edoardo; Pucciarelli, Salvatore; Nitti, Donato

    2014-01-01

    Locally advanced rectal cancer (RC) treatment is a challenge, because RC has a high rate of local recurrence. To date preoperative chemoradiotherapy (pCRT) is widely accepted as standard protocol of care for middle-low RC, but complete tumour response rate ranges from 4 to 44% and 5-year local recurrence rate is 6%. Better understanding of molecular biology and carcinogenesis pathways could be used both for pre-neoplastic lesions and locally recurrence diagnosis, and for tumour response prediction to therapy. Circulating molecules, gene expression and protein signature are promising sources to biomarker discovery. Several studies have evaluated potential predictors of response and recently, cell-free Nucleic Acid levels have been associated to tumour response to neoadjuvant therapies. Alternative method is the serum or plasma proteome and peptidome analysis. It may be ideally suited for its minimal invasiveness and it can be repeated at multiple time points throughout the treatment in contrast to tissue-based methods which still remain the most reliable and specific approach. Many studies have analyzed preoperative rectal tissue prognostic factor, but data are controversial or not confirmed.

  1. Global genetic variations predict brain response to faces.

    PubMed

    Dickie, Erin W; Tahmasebi, Amir; French, Leon; Kovacevic, Natasa; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun; Büchel, Christian; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Gallinat, Juergen; Gowland, Penny; Heinz, Andreas; Ittermann, Bernd; Lawrence, Claire; Mann, Karl; Martinot, Jean-Luc; Nees, Frauke; Nichols, Thomas; Lathrop, Mark; Loth, Eva; Pausova, Zdenka; Rietschel, Marcela; Smolka, Michal N; Ströhle, Andreas; Toro, Roberto; Schumann, Gunter; Paus, Tomáš

    2014-08-01

    Face expressions are a rich source of social signals. Here we estimated the proportion of phenotypic variance in the brain response to facial expressions explained by common genetic variance captured by ∼ 500,000 single nucleotide polymorphisms. Using genomic-relationship-matrix restricted maximum likelihood (GREML), we related this global genetic variance to that in the brain response to facial expressions, as assessed with functional magnetic resonance imaging (fMRI) in a community-based sample of adolescents (n = 1,620). Brain response to facial expressions was measured in 25 regions constituting a face network, as defined previously. In 9 out of these 25 regions, common genetic variance explained a significant proportion of phenotypic variance (40-50%) in their response to ambiguous facial expressions; this was not the case for angry facial expressions. Across the network, the strength of the genotype-phenotype relationship varied as a function of the inter-individual variability in the number of functional connections possessed by a given region (R(2) = 0.38, p<0.001). Furthermore, this variability showed an inverted U relationship with both the number of observed connections (R2 = 0.48, p<0.001) and the magnitude of brain response (R(2) = 0.32, p<0.001). Thus, a significant proportion of the brain response to facial expressions is predicted by common genetic variance in a subset of regions constituting the face network. These regions show the highest inter-individual variability in the number of connections with other network nodes, suggesting that the genetic model captures variations across the adolescent brains in co-opting these regions into the face network.

  2. Global Genetic Variations Predict Brain Response to Faces

    PubMed Central

    Dickie, Erin W.; Tahmasebi, Amir; French, Leon; Kovacevic, Natasa; Banaschewski, Tobias; Barker, Gareth J.; Bokde, Arun; Büchel, Christian; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Gallinat, Juergen; Gowland, Penny; Heinz, Andreas; Ittermann, Bernd; Lawrence, Claire; Mann, Karl; Martinot, Jean-Luc; Nees, Frauke; Nichols, Thomas; Lathrop, Mark; Loth, Eva; Pausova, Zdenka; Rietschel, Marcela; Smolka, Michal N.; Ströhle, Andreas; Toro, Roberto; Schumann, Gunter; Paus, Tomáš

    2014-01-01

    Face expressions are a rich source of social signals. Here we estimated the proportion of phenotypic variance in the brain response to facial expressions explained by common genetic variance captured by ∼500,000 single nucleotide polymorphisms. Using genomic-relationship-matrix restricted maximum likelihood (GREML), we related this global genetic variance to that in the brain response to facial expressions, as assessed with functional magnetic resonance imaging (fMRI) in a community-based sample of adolescents (n = 1,620). Brain response to facial expressions was measured in 25 regions constituting a face network, as defined previously. In 9 out of these 25 regions, common genetic variance explained a significant proportion of phenotypic variance (40–50%) in their response to ambiguous facial expressions; this was not the case for angry facial expressions. Across the network, the strength of the genotype-phenotype relationship varied as a function of the inter-individual variability in the number of functional connections possessed by a given region (R2 = 0.38, p<0.001). Furthermore, this variability showed an inverted U relationship with both the number of observed connections (R2 = 0.48, p<0.001) and the magnitude of brain response (R2 = 0.32, p<0.001). Thus, a significant proportion of the brain response to facial expressions is predicted by common genetic variance in a subset of regions constituting the face network. These regions show the highest inter-individual variability in the number of connections with other network nodes, suggesting that the genetic model captures variations across the adolescent brains in co-opting these regions into the face network. PMID:25122193

  3. Clinical- and imaging-based prediction of stroke risk after transient ischemic attack: the CIP model.

    PubMed

    Ay, Hakan; Arsava, E Murat; Johnston, S Claiborne; Vangel, Mark; Schwamm, Lee H; Furie, Karen L; Koroshetz, Walter J; Sorensen, A Gregory

    2009-01-01

    Predictive instruments based on clinical features for early stroke risk after transient ischemic attack suffer from limited specificity. We sought to combine imaging and clinical features to improve predictions for 7-day stroke risk after transient ischemic attack. We studied 601 consecutive patients with transient ischemic attack who had MRI within 24 hours of symptom onset. A logistic regression model was developed using stroke within 7 days as the response criterion and diffusion-weighted imaging findings and dichotomized ABCD(2) score (ABCD(2) >/=4) as covariates. Subsequent stroke occurred in 25 patients (5.2%). Dichotomized ABCD(2) score and acute infarct on diffusion-weighted imaging were each independent predictors of stroke risk. The 7-day risk was 0.0% with no predictor, 2.0% with ABCD(2) score >/=4 alone, 4.9% with acute infarct on diffusion-weighted imaging alone, and 14.9% with both predictors (an automated calculator is available at http://cip.martinos.org). Adding imaging increased the area under the receiver operating characteristic curve from 0.66 (95% CI, 0.57 to 0.76) using the ABCD(2) score to 0.81 (95% CI, 0.74 to 0.88; P=0.003). The sensitivity of 80% on the receiver operating characteristic curve corresponded to a specificity of 73% for the CIP model and 47% for the ABCD(2) score. Combining acute imaging findings with clinical transient ischemic attack features causes a dramatic boost in the accuracy of predictions with clinical features alone for early risk of stroke after transient ischemic attack. If validated in relevant clinical settings, risk stratification by the CIP model may assist in early implementation of therapeutic measures and effective use of hospital resources.

  4. New Guideline for the Reporting of Studies Developing, Validating, or Updating a Multivariable Clinical Prediction Model: The TRIPOD Statement.

    PubMed

    Moons, Karel G M; Altman, Douglas G; Reitsma, Johannes B; Collins, Gary S

    2015-09-01

    Prediction models are developed to aid health care providers in estimating the probability that a specific outcome or disease is present (diagnostic prediction models) or will occur in the future (prognostic prediction models), to inform their decision making. Prognostic models here also include models to predict treatment outcomes or responses; in the cancer literature often referred to as predictive models. Clinical prediction models have become abundant. Pathology measurement or results are frequently included as predictors in such prediction models, certainly in the cancer domain. Only when full information on all aspects of a prediction modeling study are clearly reported, risk of bias and potential usefulness of the prediction model can be adequately assessed. Many reviews have illustrated that the quality of reports on the development, validation, and/or adjusting (updating) of prediction models, is very poor. Hence, the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) initiative has developed a comprehensive and user-friendly checklist for the reporting of studies on, both diagnostic and prognostic, prediction models. The TRIPOD Statement intends to improve the transparency and completeness of reporting of studies that report solely on development, both development and validation, and solely on the validation (with or without updating) of diagnostic or prognostic, including predictive, models.

  5. Aggression Questionnaire hostility scale predicts anger in response to mistreatment.

    PubMed

    Felsten, G; Hill, V

    1999-01-01

    We tested the hypotheses that the hostility and anger scales of the Buss and Perry (1992) [Buss, A. H. & Perry, M. (1992). The Aggression Questionnaire. Journal of Personality and Social Psychology, 63, 452-459.] Aggression Questionnaire would predict anger in college students in response to mistreatment. We found low and high hostility groups did not differ in anger at baseline or after completing a task without provocation, but the high hostility group reported greater anger than the low group after the onset of provocation, which required all students to redo completed tasks because some students (confederates) were observed cheating. Hostility also influenced anxiety and depression, but only anger was greater as a result of the provocation in the high than in the low hostility group. The anger scale did not predict anger in response to provocation, but anger was higher in the high than the low anger group before the provocation. These findings support the construct validity of the Aggression Questionnaire hostility scale as a measure of suspicion, resentment and sensitivity to mistreatment.

  6. Prediction of human thermophysiological responses during shower bathing.

    PubMed

    Munir, Abdul; Takada, Satoru; Matsushita, Takayuki; Kubo, Hiroko

    2010-03-01

    This study develops a model to predict the thermophysiological response of the human body during shower bathing. Despite the needs for the quantitative evaluation of human body response during bathing for thermal comfort and safety, the complicated mechanisms of heat transfer at the skin surface, especially during shower bathing, have disturbed the development of adequate models. In this study, an initial modeling approach is proposed by developing a simple heat transfer model at the skin surface during shower bathing applied to Stolwijk's human thermal model. The main feature of the model is the division of the skin surface into three parts: a dry part, a wet part without water flow, and a wet part with water flow. The area ratio of each part is decided by a simple formula developed from a geometrical approach based on the shape of the Stolwijk's human thermal model. At the same time, the convective heat transfer coefficient between the skin and the flowing water is determined experimentally. The proposed model is validated by a comparison with the results of human subject experiments under controlled and free shower conditions. The model predicts the mean skin temperature during shower fairly well both for controlled and free shower bathing styles.

  7. Prediction of human thermophysiological responses during shower bathing

    NASA Astrophysics Data System (ADS)

    Munir, Abdul; Takada, Satoru; Matsushita, Takayuki; Kubo, Hiroko

    2010-03-01

    This study develops a model to predict the thermophysiological response of the human body during shower bathing. Despite the needs for the quantitative evaluation of human body response during bathing for thermal comfort and safety, the complicated mechanisms of heat transfer at the skin surface, especially during shower bathing, have disturbed the development of adequate models. In this study, an initial modeling approach is proposed by developing a simple heat transfer model at the skin surface during shower bathing applied to Stolwijk’s human thermal model. The main feature of the model is the division of the skin surface into three parts: a dry part, a wet part without water flow, and a wet part with water flow. The area ratio of each part is decided by a simple formula developed from a geometrical approach based on the shape of the Stolwijk’s human thermal model. At the same time, the convective heat transfer coefficient between the skin and the flowing water is determined experimentally. The proposed model is validated by a comparison with the results of human subject experiments under controlled and free shower conditions. The model predicts the mean skin temperature during shower fairly well both for controlled and free shower bathing styles.

  8. Study protocol: multi-parametric magnetic resonance imaging for therapeutic response prediction in rectal cancer.

    PubMed

    Pham, Trang Thanh; Liney, Gary; Wong, Karen; Rai, Robba; Lee, Mark; Moses, Daniel; Henderson, Christopher; Lin, Michael; Shin, Joo-Shik; Barton, Michael Bernard

    2017-07-04

    Response to neoadjuvant chemoradiotherapy (CRT) of rectal cancer is variable. Accurate imaging for prediction and early assessment of response would enable appropriate stratification of management to reduce treatment morbidity and improve therapeutic outcomes. Use of either diffusion weighted imaging (DWI) or dynamic contrast enhanced (DCE) imaging alone currently lacks sufficient sensitivity and specificity for clinical use to guide individualized treatment in rectal cancer. Multi-parametric MRI and analysis combining DWI and DCE may have potential to improve the accuracy of therapeutic response prediction and assessment. This protocol describes a prospective non-interventional single-arm clinical study. Patients with locally advanced rectal cancer undergoing preoperative CRT will prospectively undergo multi-parametric MRI pre-CRT, week 3 CRT, and post-CRT. The protocol consists of DWI using a read-out segmented sequence (RESOLVE), and DCE with pre-contrast T1-weighted (VIBE) scans for T1 calculation, followed by 60 phases at high temporal resolution (TWIST) after gadoversetamide injection. A 3-dimensional voxel-by-voxel technique will be used to produce colour-coded ADC and K(trans) histograms, and data evaluated in combination using scatter plots. MRI parameters will be correlated with surgical histopathology. Histopathology analysis will be standardized, with chemoradiotherapy response defined according to AJCC 7th Edition Tumour Regression Grade (TRG) criteria. Good response will be defined as TRG 0-1, and poor response will be defined as TRG 2-3. The combination of DWI and DCE can provide information on physiological tumour factors such as cellularity and perfusion that may affect radiotherapy response. If validated, multi-parametric MRI combining DWI and DCE can be used to stratify management in rectal cancer patients. Accurate imaging prediction of patients with a complete response to CRT would enable a 'watch and wait' approach, avoiding surgical morbidity

  9. Dissociation predicts treatment response in eye-movement desensitization and reprocessing for posttraumatic stress disorder.

    PubMed

    Bae, Hwallip; Kim, Daeho; Park, Yong Chon

    2016-01-01

    Using clinical data from a specialized trauma clinic, this study investigated pretreatment clinical factors predicting response to eye-movement desensitization and reprocessing (EMDR) among adult patients diagnosed with posttraumatic stress disorder (PTSD). Participants were evaluated using the Clinician-Administered PTSD Scale (CAPS), the Symptom Checklist-90-Revised, the Beck Depression Inventory, and the Dissociative Experiences Scale before treatment and were reassessed using the CAPS after treatment and at 6-month follow-up. A total of 69 patients underwent an average of 4 sessions of EMDR, and 60 (87%) completed the posttreatment evaluation, including 8 participants who terminated treatment prematurely. Intent-to-treat analysis revealed that 39 (65%) of the 60 patients were classified as responders and 21 (35%) as nonresponders when response was defined as more than a 30% decrease in total CAPS score. The nonresponders had higher levels of dissociation (depersonalization and derealization) and numbing symptoms, but other PTSD symptoms, such as avoidance, hyperarousal, and intrusion, were not significantly different. The number of psychiatric comorbidities was also associated with treatment nonresponse. The final logistic regression model yielded 2 significant variables: dissociation (p < .001) and more than 2 comorbidities compared to none (p < .05). These results indicate that complex symptom patterns in PTSD may predict treatment response and support the inclusion of the dissociative subtype of PTSD in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.

  10. A Systematic Review of Studies Comparing Diagnostic Clinical Prediction Rules with Clinical Judgment

    PubMed Central

    Sanders, Sharon; Doust, Jenny; Glasziou, Paul

    2015-01-01

    Background Diagnostic clinical prediction rules (CPRs) are developed to improve diagnosis or decrease diagnostic testing. Whether, and in what situations diagnostic CPRs improve upon clinical judgment is unclear. Methods and Findings We searched MEDLINE, Embase and CINAHL, with supplementary citation and reference checking for studies comparing CPRs and clinical judgment against a current objective reference standard. We report 1) the proportion of study participants classified as not having disease who hence may avoid further testing and or treatment and 2) the proportion, among those classified as not having disease, who do (missed diagnoses) by both approaches. 31 studies of 13 medical conditions were included, with 46 comparisons between CPRs and clinical judgment. In 2 comparisons (4%), CPRs reduced the proportion of missed diagnoses, but this was offset by classifying a larger proportion of study participants as having disease (more false positives). In 36 comparisons (78%) the proportion of diagnoses missed by CPRs and clinical judgment was similar, and in 9 of these, the CPRs classified a larger proportion of participants as not having disease (fewer false positives). In 8 comparisons (17%) the proportion of diagnoses missed by the CPRs was greater. This was offset by classifying a smaller proportion of participants as having the disease (fewer false positives) in 2 comparisons. There were no comparisons where the CPR missed a smaller proportion of diagnoses than clinical judgment and classified more participants as not having the disease. The design of the included studies allows evaluation of CPRs when their results are applied independently of clinical judgment. The performance of CPRs, when implemented by clinicians as a support to their judgment may be different. Conclusions In the limited studies to date, CPRs are rarely superior to clinical judgment and there is generally a trade-off between the proportion classified as not having disease and the

  11. Stress responsiveness predicts individual variation in mate selectivity.

    PubMed

    Vitousek, Maren N; Romero, L Michael

    2013-06-15

    Steroid hormones, including glucocorticoids, mediate a variety of behavioral and physiological processes. Circulating hormone concentrations vary substantially within populations, and although hormone titers predict reproductive success in several species, little is known about how individual variation in circulating hormone concentrations is linked with most reproductive behaviors in free-living organisms. Mate choice is an important and often costly component of reproduction that also varies substantially within populations. We examined whether energetically costly mate selection behavior in female Galápagos marine iguanas (Amblyrhynchus cristatus) was associated with individual variation in the concentrations of hormones previously shown to differ between reproductive and non-reproductive females during the breeding season (corticosterone and testosterone). Stress-induced corticosterone levels - which are suppressed in female marine iguanas during reproduction - were individually repeatable throughout the seven-week breeding period. Mate selectivity was strongly predicted by individual variation in stress-induced corticosterone: reproductive females that secreted less corticosterone in response to a standardized stressor assessed more displaying males. Neither baseline corticosterone nor testosterone predicted variation in mate selectivity. Scaled body mass was not significantly associated with mate selectivity, but females that began the breeding period in lower body condition showed a trend towards being less selective about potential mates. These results provide the first evidence that individual variation in the corticosterone stress response is associated with how selective females are in their choice of a mate, an important contributor to fitness in many species. Future research is needed to determine the functional basis of this association, and whether transient acute increases in circulating corticosterone directly mediate mate choice behaviors.

  12. Recommendations for imaging tumor response in neurofibromatosis clinical trials

    PubMed Central

    Ardern-Holmes, Simone L.; Babovic-Vuksanovic, Dusica; Barker, Fred G.; Connor, Steve; Evans, D. Gareth; Fisher, Michael J.; Goutagny, Stephane; Harris, Gordon J.; Jaramillo, Diego; Karajannis, Matthias A.; Korf, Bruce R.; Mautner, Victor; Plotkin, Scott R.; Poussaint, Tina Y.; Robertson, Kent; Shih, Chie-Schin; Widemann, Brigitte C.

    2013-01-01

    Objective: Neurofibromatosis (NF)-related benign tumors such as plexiform neurofibromas (PN) and vestibular schwannomas (VS) can cause substantial morbidity. Clinical trials directed at these tumors have become available. Due to differences in disease manifestations and the natural history of NF-related tumors, response criteria used for solid cancers (1-dimensional/RECIST [Response Evaluation Criteria in Solid Tumors] and bidimensional/World Health Organization) have limited applicability. No standardized response criteria for benign NF tumors exist. The goal of the Tumor Measurement Working Group of the REiNS (Response Evaluation in Neurofibromatosis and Schwannomatosis) committee is to propose consensus guidelines for the evaluation of imaging response in clinical trials for NF tumors. Methods: Currently used imaging endpoints, designs of NF clinical trials, and knowledge of the natural history of NF-related tumors, in particular PN and VS, were reviewed. Consensus recommendations for response evaluation for future studies were developed based on this review and the expertise of group members. Results: MRI with volumetric analysis is recommended to sensitively and reproducibly evaluate changes in tumor size in clinical trials. Volumetric analysis requires adherence to specific imaging recommendations. A 20% volume change was chosen to indicate a decrease or increase in tumor size. Use of these criteria in future trials will enable meaningful comparison of results across studies. Conclusions: The proposed imaging response evaluation guidelines, along with validated clinical outcome measures, will maximize the ability to identify potentially active agents for patients with NF and benign tumors. PMID:24249804

  13. Recommendations for imaging tumor response in neurofibromatosis clinical trials.

    PubMed

    Dombi, Eva; Ardern-Holmes, Simone L; Babovic-Vuksanovic, Dusica; Barker, Fred G; Connor, Steve; Evans, D Gareth; Fisher, Michael J; Goutagny, Stephane; Harris, Gordon J; Jaramillo, Diego; Karajannis, Matthias A; Korf, Bruce R; Mautner, Victor; Plotkin, Scott R; Poussaint, Tina Y; Robertson, Kent; Shih, Chie-Schin; Widemann, Brigitte C

    2013-11-19

    Neurofibromatosis (NF)-related benign tumors such as plexiform neurofibromas (PN) and vestibular schwannomas (VS) can cause substantial morbidity. Clinical trials directed at these tumors have become available. Due to differences in disease manifestations and the natural history of NF-related tumors, response criteria used for solid cancers (1-dimensional/RECIST [Response Evaluation Criteria in Solid Tumors] and bidimensional/World Health Organization) have limited applicability. No standardized response criteria for benign NF tumors exist. The goal of the Tumor Measurement Working Group of the REiNS (Response Evaluation in Neurofibromatosis and Schwannomatosis) committee is to propose consensus guidelines for the evaluation of imaging response in clinical trials for NF tumors. Currently used imaging endpoints, designs of NF clinical trials, and knowledge of the natural history of NF-related tumors, in particular PN and VS, were reviewed. Consensus recommendations for response evaluation for future studies were developed based on this review and the expertise of group members. MRI with volumetric analysis is recommended to sensitively and reproducibly evaluate changes in tumor size in clinical trials. Volumetric analysis requires adherence to specific imaging recommendations. A 20% volume change was chosen to indicate a decrease or increase in tumor size. Use of these criteria in future trials will enable meaningful comparison of results across studies. The proposed imaging response evaluation guidelines, along with validated clinical outcome measures, will maximize the ability to identify potentially active agents for patients with NF and benign tumors.

  14. High Proliferation Predicts Pathological Complete Response to Neoadjuvant Chemotherapy in Early Breast Cancer.

    PubMed

    Alba, Emilio; Lluch, Ana; Ribelles, Nuria; Anton-Torres, Antonio; Sanchez-Rovira, Pedro; Albanell, Joan; Calvo, Lourdes; García-Asenjo, Jose Antonio Lopez; Palacios, Jose; Chacon, Jose Ignacio; Ruiz, Amparo; De la Haba-Rodriguez, Juan; Segui-Palmer, Miguel A; Cirauqui, Beatriz; Margeli, Mireia; Plazaola, Arrate; Barnadas, Agusti; Casas, Maribel; Caballero, Rosalia; Carrasco, Eva; Rojo, Federico

    2016-02-01

    In the neoadjuvant setting, changes in the proliferation marker Ki67 are associated with primary endocrine treatment efficacy, but its value as a predictor of response to chemotherapy is still controversial. We analyzed 262 patients with centralized basal Ki67 immunohistochemical evaluation derived from 4 GEICAM (Spanish Breast Cancer Group) clinical trials of neoadjuvant chemotherapy for breast cancer. The objective was to identify the optimal threshold for Ki67 using the receiver-operating characteristic curve method to maximize its predictive value for chemotherapy benefit. We also evaluated the predictive role of the defined Ki67 cutoffs for molecular subtypes defined by estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2). A basal Ki67 cutpoint of 50% predicted pathological complete response (pCR). Patients with Ki67 >50% achieved a pCR rate of 40% (36 of 91) versus a pCR rate of 19% in patients with Ki67 ≤ 50% (33 of 171) (p = .0004). Ki67 predictive value was especially relevant in ER-HER2- and ER-HER2+ patients (pCR rates of 42% and 64%, respectively, in patients with Ki67 >50% versus 15% and 45%, respectively, in patients with Ki67 ≤ 50%; p = .0337 and .3238, respectively). Both multivariate analyses confirmed the independent predictive value of the Ki67 cutpoint of 50%. Basal Ki67 proliferation index >50% should be considered an independent predictive factor for pCR reached after neoadjuvant chemotherapy, suggesting that cell proliferation is a phenomenon closely related to chemosensitivity. These findings could help to identify a group of patients with a potentially favorable long-term prognosis. The use of basal Ki67 status as a predictive factor of chemotherapy benefit could facilitate the identification of a patient subpopulation with high probability of achieving pathological complete response when treated with primary chemotherapy, and thus with a potentially favorable long-term prognosis. ©AlphaMed Press.

  15. New Paradigm for Translational Modeling to Predict Long‐term Tuberculosis Treatment Response

    PubMed Central

    Bartelink, IH; Zhang, N; Keizer, RJ; Strydom, N; Converse, PJ; Dooley, KE; Nuermberger, EL

    2017-01-01

    Abstract Disappointing results of recent tuberculosis chemotherapy trials suggest that knowledge gained from preclinical investigations was not utilized to maximal effect. A mouse‐to‐human translational pharmacokinetics (PKs) – pharmacodynamics (PDs) model built on a rich mouse database may improve clinical trial outcome predictions. The model included Mycobacterium tuberculosis growth function in mice, adaptive immune response effect on bacterial growth, relationships among moxifloxacin, rifapentine, and rifampin concentrations accelerating bacterial death, clinical PK data, species‐specific protein binding, drug‐drug interactions, and patient‐specific pathology. Simulations of recent trials testing 4‐month regimens predicted 65% (95% confidence interval [CI], 55–74) relapse‐free patients vs. 80% observed in the REMox‐TB trial, and 79% (95% CI, 72–87) vs. 82% observed in the Rifaquin trial. Simulation of 6‐month regimens predicted 97% (95% CI, 93–99) vs. 92% and 95% observed in 2RHZE/4RH control arms, and 100% predicted and observed in the 35 mg/kg rifampin arm of PanACEA MAMS. These results suggest that the model can inform regimen optimization and predict outcomes of ongoing trials. PMID:28561946

  16. Predicting Non-Response to Juvenile Drug Court Interventions

    PubMed Central

    Halliday-Boykins, Colleen A.; Schaeffer, Cindy M.; Henggeler, Scott W.; Chapman, Jason E.; Cunningham, Phillippe B.; Randall, Jeff; Shapiro, Steven B.

    2010-01-01

    Using data from a recent randomized clinical trial involving juvenile drug court (JDC), youth marijuana use trajectories and the predictors of treatment non-response were examined. Participants were 118 juvenile offenders meeting diagnostic criteria for substance use disorders assigned to JDC and their families. Urine drug screen results were gathered from weekly court visits for 6 months, and youth reported their marijuana use over 12 months. Semiparametric mixture modeling jointly estimated and classified trajectories of both marijuana use indices. Youth were classified into responder versus non-responder trajectory groups based on both outcomes. Regression analyses examined pretreatment individual, family, and extrafamilial predictors of non-response. Results indicated that youth whose caregivers reported illegal drug use pretreatment were almost 10 times as likely to be classified into the non-responder trajectory group. No other variable significantly distinguished drug use trajectory groups. Findings have implications for the design of interventions to improve JDC outcomes. PMID:20826076

  17. Genetic studies of DRD4 and clinical response to neuroleptic medications

    SciTech Connect

    Kennedy, J.L.; Petronis, A.; Gao, J.

    1994-09-01

    Clozapine is an atypical antipsychotic drug that, like most other medications, is effective for some people and not for others. This variable response across individuals is likely significantly determined by genetic factors. An important candidate gene to investigate in clozapine response is the dopamine D4 receptor gene (DRD4). The D4 receptor has a higher affinity for clozapine than any of the other dopamine receptors. Furthermore, recent work by our consortium has shown a remarkable level of variability in the part of the gene coding for the third cytoplasmic loop. We have also identified polymorphisms in the upstream 5{prime} putative regulatory region and at two other sites. These polymorphisms were typed in a group of treatment-resistant schizophrenia subjects who were subsequently placed on clozapine (n = 60). In a logistic regression analysis, we compared genotype at the DRD4 polymorphism to response versus non-response to clozapine. Neither the exon-III nor any of the 5{prime} polymorphisms alone significantly predicted response; however, when the information from these polymorphisms was combined, more predictive power was obtained. In a correspondence analysis of the four DRD4 polymorphisms vs. response, we were able to predict 76% of the variance in response. Refinement of the analyses will include assessment of subfactors involved in clinical response phenotype and incorporation of the debrisoquine metabolizing locus (CYP2D6) into the prediction algorithm.

  18. Rorschach Prediction of Success in Clinical Training: A Second Look

    ERIC Educational Resources Information Center

    Carlson, Rae

    1969-01-01

    A Rorschach Index based on ego-psychological conceptualization of an optimal personality picture predicted for 155 trainees was compared with predictions from the Miller Analogies Test (MAT) and the Strong Vocational Interest Blank (SVIB). The Index predicted success and failure more effectively. (Author)

  19. Predicting Drug Response in Human Prostate Cancer from Preclinical Analysis of In Vivo Mouse Models.

    PubMed

    Mitrofanova, Antonina; Aytes, Alvaro; Zou, Min; Shen, Michael M; Abate-Shen, Cory; Califano, Andrea

    2015-09-29

    Although genetically engineered mouse (GEM) models are often used to evaluate cancer therapies, extrapolation of such preclinical data to human cancer can be challenging. Here, we introduce an approach that uses drug perturbation data from GEM models to predict drug efficacy in human cancer. Network-based analysis of expression profiles from in vivo treatment of GEM models identified drugs and drug combinations that inhibit the activity of FOXM1 and CENPF, which are master regulators of prostate cancer malignancy. Validation of mouse and human prostate cancer models confirmed the specificity and synergy of a predicted drug combination to abrogate FOXM1/CENPF activity and inhibit tumorigenicity. Network-based analysis of treatment signatures from GEM models identified treatment-responsive genes in human prostate cancer that are potential biomarkers of patient response. More generally, this approach allows systematic identification of drugs that inhibit tumor dependencies, thereby improving the utility of GEM models for prioritizing drugs for clinical evaluation.

  20. Expression profiles of osteosarcoma that can predict response to chemotherapy.

    PubMed

    Man, Tsz-Kwong; Chintagumpala, Murali; Visvanathan, Jaya; Shen, Jianhe; Perlaky, Laszlo; Hicks, John; Johnson, Mark; Davino, Nelson; Murray, Jeffrey; Helman, Lee; Meyer, William; Triche, Timothy; Wong, Kwong-Kwok; Lau, Ching C

    2005-09-15

    Osteosarcoma is the most common malignant bone tumor in children. After initial diagnosis is made with a biopsy, treatment consists of preoperative chemotherapy followed by definitive surgery and postoperative chemotherapy. The degree of tumor necrosis in response to preoperative chemotherapy is a reliable prognostic factor and is used to guide the choice of postoperative chemotherapy. Patients with tumors, which reveal > or = 90% necrosis (good responders), have a much better prognosis than those with < 90% necrosis (poor responders). Despite previous attempts to improve the outcome of poor responders by modifying the postoperative chemotherapy, their prognosis remains poor. Therefore, there is a need to predict at the time of diagnosis patients' response to preoperative chemotherapy. This will provide the basis for developing potentially effective therapy that can be given at the outset for those who are likely to have a poor response. Here, we report the analysis of 34 pediatric osteosarcoma samples by expression profiling. Using parametric two-sample t test, we identified 45 genes that discriminate between good and poor responders (P < 0.005) in 20 definitive surgery samples. A support vector machine classifier was built using these predictor genes and was tested for its ability to classify initial biopsy samples. Five of six initial biopsy samples that had corresponding definitive surgery samples in the training set were classified correctly (83%; confidence interval, 36%, 100%). When this classifier was used to predict eight independent initial biopsy samples, there was 100% accuracy (confidence interval, 63%, 100%). Many of the predictor genes are implicated in bone development, drug resistance, and tumorigenesis.

  1. Predicting drug response and toxicity based on gene polymorphisms.

    PubMed

    Robert, Jacques; Morvan, Valérie Le; Smith, Denis; Pourquier, Philippe; Bonnet, Jacques

    2005-06-01

    The sequencing of the human genome has allowed the identification of thousands of gene polymorphisms, most often single nucleotide polymorphims (SNP), which may play an important role in the expression level and activity of the corresponding proteins. When these polymorphisms occur at the level of drug metabolising enzymes or transporters, the disposition of the drug may be altered and, consequently, its efficacy may be compromised or its toxicity enhanced. Polymorphisms can also occur at the level of proteins directly involved in drug action, either when the protein is the target of the drug or when the protein is involved in the repair of drug-induced lesions. There again, these polymorphisms may lead to alterations in drug efficacy and/or toxicity. The identification of functional polymorphisms in patients undergoing chemotherapy may help the clinician prescribe the optimal drug combination or schedule and predict with more accuracy the response to these prescriptions. We have recorded in this review the polymorphisms that have been identified up till now in genes involved in anticancer drug activity. Some of them appear especially important in predicting drug toxicity and should be determined in routine before drug administration; this is the case of the most common variations of thiopurine methyltransferase for 6-mercaptopurine and of dihydropyrimidine dehydrogenase for fluorouracil. Other appear determinant for drug response, such as the common SNPs found in glutathione S-transferase P1 or xereoderma pigmentosum group D enzyme for the activity of oxaliplatin. However, confusion factors may exist between the role of gene polymorphisms in cancer risk or overall prognosis and their role in drug response.

  2. Prediction and Early Evaluation of Anticancer Therapy Response: From Imaging of Drug Efflux Pumps to Targeted Therapy Response.

    PubMed

    Meng, Qingqing; Li, Zheng; Li, Shaoshun

    2016-01-01

    Multidrug resistance (MDR) describes the resistance of tumor cells to chemotherapy and has been ascribed to the overexpression of drug efflux pumps. Molecular imaging of drug efflux pumps is helpful to identify the patients who may be resistant to the chemotherapy and thus will avoid the unnecessary treatment and increase the therapeutic effectiveness. Imaging probes targeting drug efflux pumps can non-invasively evaluate the Pgp function and play an important role in identification of MDR, prediction of response, and monitoring MDR modulation. On the other hand, new anticancer agents based on molecular targets such as epidermal growth factor receptor (EGFR) and angiogenic factor receptor may potentially be combined with chemotherapeutic drugs to overcome the MDR. Imaging of molecular targets visualize treatment response of patients at molecular level vividly and help to select right patients for certain targeted anticancer therapy. Among all the imaging modalities, nuclear imaging including positron emission tomography (PET) and single photon emission computed tomography (SPECT) imaging has the greatest promise for rapid translation to the clinic and can realize quantitative visualization of biochemical processes in vivo. In this review, we will summarize the nuclear imaging probes utilized for predicting and evaluating the early anticancer therapy response.99mTc labeled agents and PET based radiopharmaceuticals like 18F-Paclitaxel, 11C-Verapamil for drug efflux pumps imaging will be discussed here. Moreover, molecular imaging probes used for targeted therapy response evaluation like 18F-Tamoxifen,89Zr-Trastuzumab will also be introduced in this review.

  3. Shrinking the Psoriasis Assessment Gap: Early Gene-Expression Profiling Accurately Predicts Response to Long-Term Treatment.

    PubMed

    Correa da Rosa, Joel; Kim, Jaehwan; Tian, Suyan; Tomalin, Lewis E; Krueger, James G; Suárez-Fariñas, Mayte

    2017-02-01

    There is an "assessment gap" between the moment a patient's response to treatment is biologically determined and when a response can actually be determined clinically. Patients' biochemical profiles are a major determinant of clinical outcome for a given treatment. It is therefore feasible that molecular-level patient information could be used to decrease the assessment gap. Thanks to clinically accessible biopsy samples, high-quality molecular data for psoriasis patients are widely available. Psoriasis is therefore an excellent disease for testing the prospect of predicting treatment outcome from molecular data. Our study shows that gene-expression profiles of psoriasis skin lesions, taken in the first 4 weeks of treatment, can be used to accurately predict (>80% area under the receiver operating characteristic curve) the clinical endpoint at 12 weeks. This could decrease the psoriasis assessment gap by 2 months. We present two distinct prediction modes: a universal predictor, aimed at forecasting the efficacy of untested drugs, and specific predictors aimed at forecasting clinical response to treatment with four specific drugs: etanercept, ustekinumab, adalimumab, and methotrexate. We also develop two forms of prediction: one from detailed, platform-specific data and one from platform-independent, pathway-based data. We show that key biomarkers are associated with responses to drugs and doses and thus provide insight into the biology of pathogenesis reversion.

  4. Predicting the Response of the Mars Ionosphere to Solar Flares

    NASA Astrophysics Data System (ADS)

    Fallows, K.; Withers, P.; Gonzalez, G.

    2015-12-01

    The increased soft X-ray irradiance during solar flares generates increased electron densities in the lower ionosphere of Mars. The relative changes in electron density during a flare are greater for larger flares and also at lower altitudes and larger flares, due to the wavelength dependence of both the flux increase during the flare and the absorption of flux by the neutral atmosphere. These relationships have been explored [Bougher et al. 2001, Fox et al. 2004, Mendillo et al. 2006, Mahajan et al. 2011, Lollo et al. 2012] but not quantified, which has impeded the validation of simulations of the ionospheric effects of solar flares. Such simulations are necessary for developing accurate descriptions of the physical processes governing ionospheric behavior under extreme conditions. We present a response function, a mathematical expression for the change in electron density during a solar flare as a function of the change in solar flux and an optical depth proxy. This response function is based on analysis of 20 Mars Global Surveyor (MGS) radio occultation electron density profiles measured during solar flares. Characterizing the response as a function of optical depth, rather than altitude, provides the best description of ionospheric variability during a flare; otherwise non-negligible solar zenith angle effects are present. We demonstrate that the response function can be used to predict ionospheric electron densities during a specified solar flare by reproducing profiles known to be disturbed by a solar flare. We also demonstrate that the response function can be used to infer the strength of solar flares not visible at Earth by finding the flux enhancement required to reproduce an apparently flare affected profile given an undisturbed profile on the same date.

  5. A germline predictive signature of response to platinum chemotherapy in esophageal cancer.

    PubMed

    Rumiato, Enrica; Boldrin, Elisa; Malacrida, Sandro; Battaglia, Giorgio; Bocus, Paolo; Castoro, Carlo; Cagol, Matteo; Chiarion-Sileni, Vanna; Ruol, Alberto; Amadori, Alberto; Saggioro, Daniela

    2016-05-01

    Platinum-based neoadjuvant therapy is the standard treatment for esophageal cancer (EC). At present, no reliable response markers exist, and patient therapeutic outcome is variable and very often unpredictable. The aim of this study was to understand the contribution of host constitutive DNA polymorphisms in discriminating between responder and nonresponder patients. DNA collected from 120 EC patients treated with platinum-based neoadjuvant chemotherapy was analyzed using drug metabolism enzymes and transporters (DMET) array platform that interrogates polymorphisms in 225 genes of drug metabolism and disposition. Four gene variants of DNA repair machinery, 2 in ERCC1 (rs11615; rs3212986), and 2 in XPD (rs1799793; rs13181) were also studied. Association analysis was performed with pTest software and corrected by permutation test. Predictive models of response were created using the receiver-operating characteristics curve approach and adjusted by the bootstrap procedure. Sixteen single nucleotide polymorphisms (SNPs) of the DMET array resulted significantly associated with either good or poor response; no association was found for the 4 variants mapping in DNA repair genes. The predictive power of 5 DMET SNPs mapping in ABCC2, ABCC3, CYP2A6, PPARG, and SLC7A8 genes was greater than that of clinical factors alone (area under the curve [AUC] = 0.74 vs 0.62). Interestingly, their combination with the clinical variables significantly increased the predictivity of the model (AUC = 0.78 vs 0.62, P = 0.0016). In conclusion, we identified a genetic signature of response to platinum-based neoadjuvant chemotherapy in EC patients. Our results also disclose the potential benefit of combining genetic and clinical variables for personalized EC management.

  6. Photopheresis: a clinically relevant immunobiologic response modifier.

    PubMed

    Edelson, R L

    1991-12-30

    pathogenic clone(s), the return of these cells to an immunocompetent individual, the removal of the photo-damaged cells from the blood by the reticuloendothelial system and the preferential induction of an immune response against cells of the pathologically expanded clone(s).

  7. Prediction of cortical responses to simultaneous electrical stimulation of the retina

    NASA Astrophysics Data System (ADS)

    Halupka, Kerry J.; Shivdasani, Mohit N.; Cloherty, Shaun L.; Grayden, David B.; Wong, Yan T.; Burkitt, Anthony N.; Meffin, Hamish

    2017-02-01

    Objective. Simultaneous electrical stimulation of multiple electrodes has shown promise in diversifying the responses that can be elicited by retinal prostheses compared to interleaved single electrode stimulation. However, the effects of interactions between electrodes are not well understood and clinical trials with simultaneous stimulation have produced inconsistent results. We investigated the effects of multiple electrode stimulation of the retina by developing a model of cortical responses to retinal stimulation. Approach. Electrical stimuli consisting of temporally sparse, biphasic current pulses, with amplitudes sampled from a bi-dimensional Gaussian distribution, were simultaneously delivered to the retina across a 42-channel electrode array implanted in the suprachoroidal space of anesthetized cats. Visual cortex activity was recorded using penetrating microelectrode arrays. These data were used to identify a linear-nonlinear model of cortical responses to retinal stimulation. The ability of the model to generalize was tested by predicting responses to non-white patterned stimuli. Main results. The model accurately predicted two cortical activity measures: multi-unit neural responses and evoked potential responses to white noise stimuli. The model also provides information about electrical receptive fields, including the relative effects of each stimulating electrode on every recording site. Significance. We have demonstrated a simple model that accurately describes cortical responses to simultaneous stimulation of a suprachoroidal retinal prosthesis. Overall, our results demonstrate that cortical responses to simultaneous multi-electrode stimulation of the retina are repeatable and predictable, and that interactions between electrodes during simultaneous stimulation are predominantly linear. The model shows promise for determining optimal stimulation paradigms for exploiting interactions between electrodes to shape neural activity, thereby improving

  8. COX-2 verexpression in pretreatment biopsies predicts response of rectal cancers to neoadjuvant radiochemotherapy

    SciTech Connect

    Smith, Fraser M.; Reynolds, John V. . E-mail: reynoldsjv@stjames.ie; Kay, Elaine W.; Crotty, Paul; Murphy, James O.; Hollywood, Donal; Gaffney, Eoin F.; Stephens, Richard B.; Kennedy, M. John

    2006-02-01

    Purpose: To determine the utility of COX-2 expression as a response predictor for patients with rectal cancer who are undergoing neoadjuvant radiochemotherapy (RCT). Methods and Materials: Pretreatment biopsies (PTB) from 49 patients who underwent RCT were included. COX-2 and proliferation in PTB were assessed by immunohistochemistry (IHC) and apoptosis was detected by TUNEL stain. Response to treatment was assessed by a 5-point tumor-regression grade (TRG) based on the ratio of residual tumor to fibrosis. Results: Good response (TRG 1 + 2), moderate response (TRG 3), and poor response (TRG 4 + 5) were seen in 21 patients (42%), 11 patients (22%), and 17 patients (34%), respectively. Patients with COX-2 overexpression in PTB were more likely to demonstrate moderate or poor response (TRG 3 + 4) to treatment than were those with normal COX-2 expression (p = 0.026, chi-square test). Similarly, poor response was more likely if patients had low levels of spontaneous apoptosis in PTBs (p = 0.0007, chi-square test). Conclusions: COX-2 overexpression and reduced apoptosis in PTB can predict poor response of rectal cancer to RCT. As COX-2 inhibitors are commercially available, their administration to patients who overexpress COX-2 warrants assessment in clinical trials in an attempt to increase overall response rates.

  9. Clinical characteristics and predictive factors of subclinical diabetic nephropathy.

    PubMed

    Zhang, Y; Yang, J; Zheng, M; Wang, Y; Ren, H; Xu, Y; Yang, Y; Cheng, J; Han, F; Yang, X; Chen, L; Shan, C; Chang, B

    2015-02-01

    To investigate the clinical characteristics and predictive factors of subclinical diabetic nephropathy in type 2 diabetes patients. A total of 298 type 2 diabetes patients were divided into 3 groups based on 24-h urinary microalbumin and estimated glomerular filtration rate: patients with normal albuminuria and glomerular filtration rate (NC), patients with normoalbuminuria and glomerular hyperfiltration (SDN) and patients with microalbuminuria (EDN). The renal size, tubular injury markers and ambulatory blood pressure were analyzed. Renal size increased in the SDN and EDN groups compared to the NC group (P<0.05), while renal length in the SDN group was greater than the EDN group (P<0.05). Patients in the SDN and EDN groups had higher level of urine retinol binding protein and N-acetyl-β-D-glucosaminidase and most of them developed proximal tubular dysfunction. The SDN group had higher 24-h mean and nocturnal diastolic blood pressure than the NC group (P<0.05), while the EDN group had higher systolic blood pressure and pulse pressure than the SDN group (P<0.01). More patients developed abnormal blood pressure rhythm in the SDN and EDN groups. The likelihood of a decrease in nocturnal systolic blood pressure was lower as the microalbuminuria increased. Increased renal size, more abnormal tubular injury markers and higher 24-h mean and nocturnal blood pressure were all risk factors of subclinical diabetic nephropathy. Patients with subclinical diabetic nephropathy had increased renal size, abnormal tubular injury markers, high blood pressure and abnormal circadian rhythm. © Georg Thieme Verlag KG Stuttgart · New York.

  10. Clinical prediction rules for children: a systematic review.

    PubMed

    Maguire, Jonathon L; Kulik, Dina M; Laupacis, Andreas; Kuppermann, Nathan; Uleryk, Elizabeth M; Parkin, Patricia C

    2011-09-01

    The degree to which clinical prediction rules (CPRs) for children meet published standards is unclear. To systematically review the quality, performance, and validation of published CPRs for children, compare them with adult CPRs, and suggest pediatric-specific changes to CPR methodology. Medline was searched from 1950 to 2011. Studies were selected if they included the development of a CPR involving children younger than 18 years. Two investigators assessed study quality, rule performance, and rule validation as methodologic standards. Of 7298 titles and abstracts assessed, 137 eligible studies were identified. They describe the development of 101 CPRs addressing 36 pediatric conditions. Quality standards met in fewer than half of the studies were blind assessment of predictors (47%), reproducibility of predictors (18%), blind assessment of outcomes (42%), adequate follow-up of outcomes (36%), adequate power (43%), adequate reporting of results (49%), and 95% confidence intervals reported (36%). For rule performance, 48% had a sensitivity greater than 0.95, and 43% had a negative likelihood ratio less than 0.1. For rule validation, 76% had no validation, 17% had narrow validation, 8% had broad validation, and none had impact analysis performed. Compared with CPRs for adult health conditions, quality and rule validation seem to be lower. Many CPRs have been derived for children, but few have been validated. Relative to adult CPRs, several quality indicators demonstrated weaknesses. Existing performance standards may prove elusive for CPRs that involve children. CPRs for children that are more assistive and less directive and include patients' values and preferences in decision-making may be helpful.

  11. Clinical Prediction of Fall Risk and White Matter Abnormalities

    PubMed Central

    Koo, Bang-Bon; Bergethon, Peter; Qiu, Wei Qiao; Scott, Tammy; Hussain, Mohammed; Rosenberg, Irwin; Caplan, Louis R.; Bhadelia, Rafeeque A.

    2015-01-01

    Background The Tinetti scale is a simple clinical tool designed to predict risk of falling by focusing on gait and stance impairment in elderly persons. Gait impairment is also associated with white matter (WM) abnormalities. Objective To test the hypothesis that elderly subjects at risk for falling, as determined by the Tinetti scale, have specific patterns of WM abnormalities on diffusion tensor imaging. Design, Setting, and Patients Community-based cohort of 125 homebound elderly individuals. Main Outcome Measures Diffusion tensor imaging scans were analyzed using tract-based spatial statistics analysis to determine the location of WM abnormalities in subjects with Tinetti scale scores of 25 or higher (without risk of falls) and lower than 25 (with risk of falls). Multivariate linear least squares correlation analysis was performed to determine the association between Tinetti scale scores and local fractional anisotropy values on each skeletal voxel controlling for possible confounders. Results In subjects with risk of falls (Tinetti scale score <25), clusters of abnormal WM were seen in the medial frontal and parietal subcortical pathways, genu and splenium of corpus callosum, posterior cingulum, prefrontal and orbitofrontal pathways, and longitudinal pathways that connect frontal-parietal-temporal lobes. Among these abnormalities, those in medial frontal and parietal subcortical pathways correlated with Mini-Mental State Examination scores, while the other locations were unrelated to these scores. Conclusions Elderly individuals at risk for falls as determined by the Tinetti scale have WM abnormalities in specific locations on diffusion tensor imaging, some of which correlate with cognitive function scores. PMID:22332181

  12. Music-related reward responses predict episodic memory performance.

    PubMed

    Ferreri, Laura; Rodriguez-Fornells, Antoni

    2017-09-22

    Music represents a special type of reward involving the recruitment of the mesolimbic dopaminergic system. According to recent theories on episodic memory formation, as dopamine strengthens the synaptic potentiation produced by learning, stimuli triggering dopamine release could result in long-term memory improvements. Here, we behaviourally test whether music-related reward responses could modulate episodic memory performance. Thirty participants rated (in terms of arousal, familiarity, emotional valence, and reward) and encoded unfamiliar classical music excerpts. Twenty-four hours later, their episodic memory was tested (old/new recognition and remember/know paradigm). Results revealed an influence of music-related reward responses on memory: excerpts rated as more rewarding were significantly better recognized and remembered. Furthermore, inter-individual differences in the ability to experience musical reward, measured through the Barcelona Music Reward Questionnaire, positively predicted memory performance. Taken together, these findings shed new light on the relationship between music, reward and memory, showing for the first time that music-driven reward responses are directly implicated in higher cognitive functions and can account for individual differences in memory performance.

  13. Prediction of treatment response to rivastigmine in Alzheimer's dementia

    PubMed Central

    Adler, G; Brassen, S; Chwalek, K; Dieter, B; Teufel, M

    2004-01-01

    Methods: A neuropsychological examination and a quantitative EEG study were done in 20 patients with Alzheimer's dementia before initiating treatment with rivastigmine. After one week of treatment a second EEG examination was done. Therapeutic efficacy was determined six months after treatment initiation. Treatment response was defined as improvement in short term memory after six months of rivastigmine treatment. Results: For the group of patients as a whole, there was a significant improvement in short term memory and orientation during rivastigmine treatment. The mini-mental state score improved from 20.2 to 21.7 (NS). In the EEG, theta power decreased significantly after one week of treatment. Treatment responders had a greater decrease in theta power after one week of treatment and a better short term memory at baseline than non-responders. Decrease in theta power during rivastigmine treatment and baseline short term memory were good predictors of treatment response. Conclusions: Generally available neuropsychological and EEG data may be useful for predicting response to rivastigmine in patients with Alzheimer's disease. PMID:14742608

  14. Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care

    Cancer.gov

    Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care, a 2010 workshop sponsored by the Epidemiology and Genomics Research Program.

  15. An oracle: antituberculosis pharmacokinetics-pharmacodynamics, clinical correlation, and clinical trial simulations to predict the future.

    PubMed

    Pasipanodya, Jotam; Gumbo, Tawanda

    2011-01-01

    Antimicrobial pharmacokinetic-pharmacodynamic (PK/PD) science and clinical trial simulations have not been adequately applied to the design of doses and dose schedules of antituberculosis regimens because many researchers are skeptical about their clinical applicability. We compared findings of preclinical PK/PD studies of current first-line antituberculosis drugs to findings from several clinical publications that included microbiologic outcome and pharmacokinetic data or had a dose-scheduling design. Without exception, the antimicrobial PK/PD parameters linked to optimal effect were similar in preclinical models and in tuberculosis patients. Thus, exposure-effect relationships derived in the preclinical models can be used in the design of optimal antituberculosis doses, by incorporating population pharmacokinetics of the drugs and MIC distributions in Monte Carlo simulations. When this has been performed, doses and dose schedules of rifampin, isoniazid, pyrazinamide, and moxifloxacin with the potential to shorten antituberculosis therapy have been identified. In addition, different susceptibility breakpoints than those in current use have been identified. These steps outline a more rational approach than that of current methods for designing regimens and predicting outcome so that both new and older antituberculosis agents can shorten therapy duration.

  16. The dexamethasone suppression test (DST) in predicting response to desipramine and amitriptyline in depressed outpatients.

    PubMed

    Peselow, E D; Goldring, N; Stanley, M; Barouche, F; Fieve, R R

    1986-01-01

    The predictive value of the dexamethasone suppression test (DST) was evaluated in two consecutive clinical trials involving 99 individuals treated with amitriptyline or desipramine. Following one week observation, and following one week on low-dose desipramine or amitriptyline (50 mg), all patients who remained depressed (Hamilton score 16 or greater) were given a full clinical trial of either desipramine or amitriptyline (150-300 mg/day) over a minimum 3-5 week period. In all, 68 patients required this trial, 31 receiving amitriptyline and 37 receiving desipramine. For these patients there was no relationship between DST suppression/non-suppression vs clinical response to either desipramine or amitriptyline. There was a non-significant trend for suppressors (negative DST) to respond either spontaneously or to low-dose desipramine or amitriptyline as opposed to non-suppressors (positive DST).

  17. Prediction of peak pressure from clinical and radiological measurements in patients with diabetes

    PubMed Central

    Guldemond, Nick A; Leffers, Pieter; Walenkamp, Geert HIM; Schaper, Nicolaas C; Sanders, Antal P; Nieman, Fred HM; van Rhijn, Lodewijk W

    2008-01-01

    Background Various structural and functional factors of foot function have been associated with high local plantar pressures. The therapist focuses on these features which are thought to be responsible for plantar ulceration in patients with diabetes. Risk assessment of the diabetic foot would be made easier if locally elevated plantar pressure could be indicated with a minimum set of clinical measures. Methods Ninety three patients were evaluated through vascular, orthopaedic, neurological and radiological assessment. A pressure platform was used to quantify the barefoot peak pressure for six forefoot regions: big toe (BT) and metatarsals one (MT-1) to five (MT-5). Stepwise regression modelling was performed to determine which set of the clinical and radiological measures explained most variability in local barefoot plantar peak pressure in each of the six forefoot regions. Comprehensive models were computed with independent variables from the clinical and radiological measurements. The difference between the actual plantar pressure and the predicted value was examined through Bland-Altman analysis. Results Forefoot pressures were significant higher in patients with neuropathy, compared to patients without neuropathy for the whole forefoot, the MT-1 region and the MT-5 region (respectively 138 kPa, 173 kPa and 88 kPa higher: mean difference). The clinical models explained up to 39 percent of the variance in local peak pressures. Callus formation and toe deformity were identified as relevant clinical predictors for all forefoot regions. Regression models with radiological variables explained about 26 percent of the variance in local peak pressures. For most regions the combination of clinical and radiological variables resulted in a higher explained variance. The Bland and Altman analysis showed a major discrepancy between the predicted and the actual peak pressure values. Conclusion At best, clinical and radiological measurements could only explain about 34

  18. Clinical nutrition management position: responsibilities and skill development strategies.

    PubMed

    Witte, S S; Messersmith, A M

    1995-10-01

    To determine the duties of clinical nutrition managers, the factors associated with the performance of the duties, the job specifications for the position, and the skill development strategies used by clinical nutrition managers. Clinical nutrition managers from 700 randomly selected, acute-care hospitals in the United States (with 300 or more beds) received a survey questionnaire. Respondents were asked to indicate performance or nonperformance, perceived importance, and methods used to develop skills for 54 duties related to clinical nutrition management. We requested additional information about position requirements, position characteristics, and demographic information. An 82% response rate with 67% usable responses (n = 472) was achieved. Frequencies for performance and nonperformance, mean importance, and frequencies for methods of skill development were determined for each duty. chi 2 Analysis with P < .10 was used to determine if an association existed between performance of a duty and time allotted to the position, number of personnel supervised, and type of personnel supervised. This study validated 46 of the duties as responsibilities of practicing clinical nutrition manager. Three duties not validated were related to financial management. The duty performed least often was conducting research/investigative studies. The number and type of personnel supervised was found to influence performance of duties, but time allotted to position was not an influence. The major strategies used for skill development were continuing education, networking, work experience in clinical dietetics, work experience in management dietetics, and their present job. These results can be used by clinical nutrition managers to assess the characteristics of their current position and develop a plan for enhancing their scope of responsibility. The identification of duties actually performed by clinical nutrition managers can also be used to develop standards of practice with

  19. Could Eosinophilia predict clinical severity in nasal polyps?

    PubMed

    Aslan, Figen; Altun, Eren; Paksoy, Serpil; Turan, Gulay

    2017-01-01

    Although nasal polyps are one of the most frequent diseases, their etiopathogenesis remains unclear.Since eosinophils are the main inflammatory cells in the substantial proportion of nasal polyp tissues, they are considered potentially responsible for the etiopathogenesis and prognosis of the disease. Aim of this study was to investigate the relation between mucosal and peripheral eosinophilia and their relation with disease severity in nasal polyps. The study included 53 patients with nasal polyps who underwent endoscopic sinus surgery. Preoperative Lund-MacKay computed tomography (CT) scores and the Lund-Kennedy endoscopic scores of the patients were recorded. Nasal polyp tissues were stained with hematoxylin and eosin, eosinophil counts were performed using high-power field (HPF, 400×) under the light microscope, and the patients were grouped as those with high mucosal eosinophil count and those with low mucosal eosinophil count. The mean Lund-MacKay CT score and the mean Lund-Kennedy endoscopic score were higher in the patients with high mucosal eosinophil count than in those with low mucosal eosinophil count. Likewise, the mean Lund-MacKay CT score and the mean Lund-Kennedy endoscopic scores were significantly higher in the patients with high peripheral eosinophil count than in those with low peripheral eosinophil count (p < 0.05 for both). Moreover, the mean peripheral eosinophil count was significantly higher in the patients with high mucosal eosinophil count than in those with low mucosal eosinophil count (p < 0.05). Mucosal and peripheral eosinophilia can be used as a marker to predict disease severity in nasal polyps.

  20. Etiology of Cellulitis and Clinical Prediction of Streptococcal Disease: A Prospective Study

    PubMed Central

    Bruun, Trond; Oppegaard, Oddvar; Kittang, Bård R.; Mylvaganam, Haima; Langeland, Nina; Skrede, Steinar

    2016-01-01

    Background. The importance of bacteria other than group A streptococci (GAS) in different clinical presentations of cellulitis is unclear, commonly leading to treatment with broad-spectrum antibiotics. The aim of this study was to describe the etiological and clinical spectrum of cellulitis and identify clinical features predicting streptococcal etiology. Methods. We prospectively enrolled 216 patients hospitalized with cellulitis. Clinical details were registered. Bacterial culture was performed from blood, cutaneous or subcutaneous tissue, and/or swabs from skin lesions. Paired serum samples were analyzed for anti-streptolysin O and anti-deoxyribonuclease B antibodies. Results. Serology or blood or tissue culture confirmed β-hemolytic streptococcal (BHS) etiology in 72% (146 of 203) of cases. An additional 13% (27 of 203) of cases had probable BHS infection, indicated by penicillin response or BHS cultured from skin swabs. β-hemolytic streptococcal etiology was predominant in all clinical subgroups, including patients without sharply demarcated erythema. β-hemolytic group C or G streptococci (GCS/GGS) were more commonly isolated than GAS (36 vs 22 cases). This predominance was found in the lower extremity infections. Group C or G streptococci in swabs were associated with seropositivity just as often as GAS. Staphylococcus aureus was cultured from swabs as a single pathogen in 24 cases, 14 (64%) of which had confirmed BHS etiology. Individual BHS-associated clinical characteristics increased the likelihood of confirmed BHS disease only slightly; positive likelihood ratios did not exceed 2.1. Conclusions. β-hemolytic streptococci were the dominating cause of cellulitis in all clinical subgroups and among cases with S aureus in cutaneous swabs. Group C or G streptococci were more frequently detected than GAS. No single clinical feature substantially increased the probability of confirmed BHS etiology. PMID:26734653

  1. A new paradigm for the prediction of antidepressant treatment response

    PubMed Central

    Leuchter, Andrew F.; Cook, Ian A.; Hunter, Aimee M.; Korb, Alexander S.

    2009-01-01

    Current treatment of Major Depressive Disorder utilizes a trial-and-error sequential treatment strategy that results in delays in achieving response and remission for a majority of patients. Protracted ineffective treatment prolongs patient suffering and increases health care costs. In addition, long and unsuccessful antidepressant trials may diminish patient expectations, reinforce negative cognitions, and condition patients not to respond during subsequent antidepressant trials, thus contributing to further treatment resistance. For these reasons, it is critical to identify reliable predictors of antidepressant treatment response that can be used to shorten or eliminate lengthy and ineffective trials. Research on possible endophenotypic as well as genomic predictors has not yet yielded reliable predictors. The most reliable predictors identified thus far are symptomatic and physiologic characteristics of patients that emerge early in the course of treatment. We propose here the term “response endophenotypes” (REs) to describe this class of predictors, defin