Sample records for external validation set

  1. Assessing Discriminative Performance at External Validation of Clinical Prediction Models

    PubMed Central

    Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W.

    2016-01-01

    Introduction External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. Methods We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. Results The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. Conclusion The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients. PMID:26881753

  2. Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

    PubMed

    Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W

    2016-01-01

    External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

  3. Does rational selection of training and test sets improve the outcome of QSAR modeling?

    PubMed

    Martin, Todd M; Harten, Paul; Young, Douglas M; Muratov, Eugene N; Golbraikh, Alexander; Zhu, Hao; Tropsha, Alexander

    2012-10-22

    Prior to using a quantitative structure activity relationship (QSAR) model for external predictions, its predictive power should be established and validated. In the absence of a true external data set, the best way to validate the predictive ability of a model is to perform its statistical external validation. In statistical external validation, the overall data set is divided into training and test sets. Commonly, this splitting is performed using random division. Rational splitting methods can divide data sets into training and test sets in an intelligent fashion. The purpose of this study was to determine whether rational division methods lead to more predictive models compared to random division. A special data splitting procedure was used to facilitate the comparison between random and rational division methods. For each toxicity end point, the overall data set was divided into a modeling set (80% of the overall set) and an external evaluation set (20% of the overall set) using random division. The modeling set was then subdivided into a training set (80% of the modeling set) and a test set (20% of the modeling set) using rational division methods and by using random division. The Kennard-Stone, minimal test set dissimilarity, and sphere exclusion algorithms were used as the rational division methods. The hierarchical clustering, random forest, and k-nearest neighbor (kNN) methods were used to develop QSAR models based on the training sets. For kNN QSAR, multiple training and test sets were generated, and multiple QSAR models were built. The results of this study indicate that models based on rational division methods generate better statistical results for the test sets than models based on random division, but the predictive power of both types of models are comparable.

  4. A new framework to enhance the interpretation of external validation studies of clinical prediction models.

    PubMed

    Debray, Thomas P A; Vergouwe, Yvonne; Koffijberg, Hendrik; Nieboer, Daan; Steyerberg, Ewout W; Moons, Karel G M

    2015-03-01

    It is widely acknowledged that the performance of diagnostic and prognostic prediction models should be assessed in external validation studies with independent data from "different but related" samples as compared with that of the development sample. We developed a framework of methodological steps and statistical methods for analyzing and enhancing the interpretation of results from external validation studies of prediction models. We propose to quantify the degree of relatedness between development and validation samples on a scale ranging from reproducibility to transportability by evaluating their corresponding case-mix differences. We subsequently assess the models' performance in the validation sample and interpret the performance in view of the case-mix differences. Finally, we may adjust the model to the validation setting. We illustrate this three-step framework with a prediction model for diagnosing deep venous thrombosis using three validation samples with varying case mix. While one external validation sample merely assessed the model's reproducibility, two other samples rather assessed model transportability. The performance in all validation samples was adequate, and the model did not require extensive updating to correct for miscalibration or poor fit to the validation settings. The proposed framework enhances the interpretation of findings at external validation of prediction models. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  5. Developing Enhanced Blood–Brain Barrier Permeability Models: Integrating External Bio-Assay Data in QSAR Modeling

    PubMed Central

    Wang, Wenyi; Kim, Marlene T.; Sedykh, Alexander

    2015-01-01

    Purpose Experimental Blood–Brain Barrier (BBB) permeability models for drug molecules are expensive and time-consuming. As alternative methods, several traditional Quantitative Structure-Activity Relationship (QSAR) models have been developed previously. In this study, we aimed to improve the predictivity of traditional QSAR BBB permeability models by employing relevant public bio-assay data in the modeling process. Methods We compiled a BBB permeability database consisting of 439 unique compounds from various resources. The database was split into a modeling set of 341 compounds and a validation set of 98 compounds. Consensus QSAR modeling workflow was employed on the modeling set to develop various QSAR models. A five-fold cross-validation approach was used to validate the developed models, and the resulting models were used to predict the external validation set compounds. Furthermore, we used previously published membrane transporter models to generate relevant transporter profiles for target compounds. The transporter profiles were used as additional biological descriptors to develop hybrid QSAR BBB models. Results The consensus QSAR models have R2=0.638 for fivefold cross-validation and R2=0.504 for external validation. The consensus model developed by pooling chemical and transporter descriptors showed better predictivity (R2=0.646 for five-fold cross-validation and R2=0.526 for external validation). Moreover, several external bio-assays that correlate with BBB permeability were identified using our automatic profiling tool. Conclusions The BBB permeability models developed in this study can be useful for early evaluation of new compounds (e.g., new drug candidates). The combination of chemical and biological descriptors shows a promising direction to improve the current traditional QSAR models. PMID:25862462

  6. Modern modeling techniques had limited external validity in predicting mortality from traumatic brain injury.

    PubMed

    van der Ploeg, Tjeerd; Nieboer, Daan; Steyerberg, Ewout W

    2016-10-01

    Prediction of medical outcomes may potentially benefit from using modern statistical modeling techniques. We aimed to externally validate modeling strategies for prediction of 6-month mortality of patients suffering from traumatic brain injury (TBI) with predictor sets of increasing complexity. We analyzed individual patient data from 15 different studies including 11,026 TBI patients. We consecutively considered a core set of predictors (age, motor score, and pupillary reactivity), an extended set with computed tomography scan characteristics, and a further extension with two laboratory measurements (glucose and hemoglobin). With each of these sets, we predicted 6-month mortality using default settings with five statistical modeling techniques: logistic regression (LR), classification and regression trees, random forests (RFs), support vector machines (SVM) and neural nets. For external validation, a model developed on one of the 15 data sets was applied to each of the 14 remaining sets. This process was repeated 15 times for a total of 630 validations. The area under the receiver operating characteristic curve (AUC) was used to assess the discriminative ability of the models. For the most complex predictor set, the LR models performed best (median validated AUC value, 0.757), followed by RF and support vector machine models (median validated AUC value, 0.735 and 0.732, respectively). With each predictor set, the classification and regression trees models showed poor performance (median validated AUC value, <0.7). The variability in performance across the studies was smallest for the RF- and LR-based models (inter quartile range for validated AUC values from 0.07 to 0.10). In the area of predicting mortality from TBI, nonlinear and nonadditive effects are not pronounced enough to make modern prediction methods beneficial. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Review and evaluation of performance measures for survival prediction models in external validation settings.

    PubMed

    Rahman, M Shafiqur; Ambler, Gareth; Choodari-Oskooei, Babak; Omar, Rumana Z

    2017-04-18

    When developing a prediction model for survival data it is essential to validate its performance in external validation settings using appropriate performance measures. Although a number of such measures have been proposed, there is only limited guidance regarding their use in the context of model validation. This paper reviewed and evaluated a wide range of performance measures to provide some guidelines for their use in practice. An extensive simulation study based on two clinical datasets was conducted to investigate the performance of the measures in external validation settings. Measures were selected from categories that assess the overall performance, discrimination and calibration of a survival prediction model. Some of these have been modified to allow their use with validation data, and a case study is provided to describe how these measures can be estimated in practice. The measures were evaluated with respect to their robustness to censoring and ease of interpretation. All measures are implemented, or are straightforward to implement, in statistical software. Most of the performance measures were reasonably robust to moderate levels of censoring. One exception was Harrell's concordance measure which tended to increase as censoring increased. We recommend that Uno's concordance measure is used to quantify concordance when there are moderate levels of censoring. Alternatively, Gönen and Heller's measure could be considered, especially if censoring is very high, but we suggest that the prediction model is re-calibrated first. We also recommend that Royston's D is routinely reported to assess discrimination since it has an appealing interpretation. The calibration slope is useful for both internal and external validation settings and recommended to report routinely. Our recommendation would be to use any of the predictive accuracy measures and provide the corresponding predictive accuracy curves. In addition, we recommend to investigate the characteristics of the validation data such as the level of censoring and the distribution of the prognostic index derived in the validation setting before choosing the performance measures.

  8. CADASTER QSPR Models for Predictions of Melting and Boiling Points of Perfluorinated Chemicals.

    PubMed

    Bhhatarai, Barun; Teetz, Wolfram; Liu, Tao; Öberg, Tomas; Jeliazkova, Nina; Kochev, Nikolay; Pukalov, Ognyan; Tetko, Igor V; Kovarich, Simona; Papa, Ester; Gramatica, Paola

    2011-03-14

    Quantitative structure property relationship (QSPR) studies on per- and polyfluorinated chemicals (PFCs) on melting point (MP) and boiling point (BP) are presented. The training and prediction chemicals used for developing and validating the models were selected from Syracuse PhysProp database and literatures. The available experimental data sets were split in two different ways: a) random selection on response value, and b) structural similarity verified by self-organizing-map (SOM), in order to propose reliable predictive models, developed only on the training sets and externally verified on the prediction sets. Individual linear and non-linear approaches based models developed by different CADASTER partners on 0D-2D Dragon descriptors, E-state descriptors and fragment based descriptors as well as consensus model and their predictions are presented. In addition, the predictive performance of the developed models was verified on a blind external validation set (EV-set) prepared using PERFORCE database on 15 MP and 25 BP data respectively. This database contains only long chain perfluoro-alkylated chemicals, particularly monitored by regulatory agencies like US-EPA and EU-REACH. QSPR models with internal and external validation on two different external prediction/validation sets and study of applicability-domain highlighting the robustness and high accuracy of the models are discussed. Finally, MPs for additional 303 PFCs and BPs for 271 PFCs were predicted for which experimental measurements are unknown. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure.

    PubMed

    Zhu, Hao; Martin, Todd M; Ye, Lin; Sedykh, Alexander; Young, Douglas M; Tropsha, Alexander

    2009-12-01

    Few quantitative structure-activity relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity end points. In this study, a comprehensive data set of 7385 compounds with their most conservative lethal dose (LD(50)) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire data set was selected that included all 3472 compounds used in TOPKAT's training set. The remaining 3913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R(2) of linear regression between actual and predicted LD(50) values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R(2) ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD(50) for every compound using all five models. The consensus models afforded higher prediction accuracy for the external validation data set with the higher coverage as compared to individual constituent models. The validated consensus LD(50) models developed in this study can be used as reliable computational predictors of in vivo acute toxicity.

  10. Does Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?

    EPA Science Inventory

    Prior to using a quantitative structure activity relationship (QSAR) model for external predictions, its predictive power should be established and validated. In the absence of a true external dataset, the best way to validate the predictive ability of a model is to perform its s...

  11. Selecting and Improving Quasi-Experimental Designs in Effectiveness and Implementation Research.

    PubMed

    Handley, Margaret A; Lyles, Courtney R; McCulloch, Charles; Cattamanchi, Adithya

    2018-04-01

    Interventional researchers face many design challenges when assessing intervention implementation in real-world settings. Intervention implementation requires holding fast on internal validity needs while incorporating external validity considerations (such as uptake by diverse subpopulations, acceptability, cost, and sustainability). Quasi-experimental designs (QEDs) are increasingly employed to achieve a balance between internal and external validity. Although these designs are often referred to and summarized in terms of logistical benefits, there is still uncertainty about (a) selecting from among various QEDs and (b) developing strategies to strengthen the internal and external validity of QEDs. We focus here on commonly used QEDs (prepost designs with nonequivalent control groups, interrupted time series, and stepped-wedge designs) and discuss several variants that maximize internal and external validity at the design, execution and implementation, and analysis stages.

  12. Robustness of near-infrared calibration models for the prediction of milk constituents during the milking process.

    PubMed

    Melfsen, Andreas; Hartung, Eberhard; Haeussermann, Angelika

    2013-02-01

    The robustness of in-line raw milk analysis with near-infrared spectroscopy (NIRS) was tested with respect to the prediction of the raw milk contents fat, protein and lactose. Near-infrared (NIR) spectra of raw milk (n = 3119) were acquired on three different farms during the milking process of 354 milkings over a period of six months. Calibration models were calculated for: a random data set of each farm (fully random internal calibration); first two thirds of the visits per farm (internal calibration); whole datasets of two of the three farms (external calibration), and combinations of external and internal datasets. Validation was done either on the remaining data set per farm (internal validation) or on data of the remaining farms (external validation). Excellent calibration results were obtained when fully randomised internal calibration sets were used for milk analysis. In this case, RPD values of around ten, five and three for the prediction of fat, protein and lactose content, respectively, were achieved. Farm internal calibrations achieved much poorer prediction results especially for the prediction of protein and lactose with RPD values of around two and one respectively. The prediction accuracy improved when validation was done on spectra of an external farm, mainly due to the higher sample variation in external calibration sets in terms of feeding diets and individual cow effects. The results showed that further improvements were achieved when additional farm information was added to the calibration set. One of the main requirements towards a robust calibration model is the ability to predict milk constituents in unknown future milk samples. The robustness and quality of prediction increases with increasing variation of, e.g., feeding and cow individual milk composition in the calibration model.

  13. Achieving external validity in home advantage research: generalizing crowd noise effects

    PubMed Central

    Myers, Tony D.

    2014-01-01

    Different factors have been postulated to explain the home advantage phenomenon in sport. One plausible explanation investigated has been the influence of a partisan home crowd on sports officials' decisions. Different types of studies have tested the crowd influence hypothesis including purposefully designed experiments. However, while experimental studies investigating crowd influences have high levels of internal validity, they suffer from a lack of external validity; decision-making in a laboratory setting bearing little resemblance to decision-making in live sports settings. This focused review initially considers threats to external validity in applied and theoretical experimental research. Discussing how such threats can be addressed using representative design by focusing on a recently published study that arguably provides the first experimental evidence of the impact of live crowd noise on officials in sport. The findings of this controlled experiment conducted in a real tournament setting offer a level of confirmation of the findings of laboratory studies in the area. Finally directions for future research and the future conduct of crowd noise studies are discussed. PMID:24917839

  14. The Utrecht questionnaire (U-CEP) measuring knowledge on clinical epidemiology proved to be valid.

    PubMed

    Kortekaas, Marlous F; Bartelink, Marie-Louise E L; de Groot, Esther; Korving, Helen; de Wit, Niek J; Grobbee, Diederick E; Hoes, Arno W

    2017-02-01

    Knowledge on clinical epidemiology is crucial to practice evidence-based medicine. We describe the development and validation of the Utrecht questionnaire on knowledge on Clinical epidemiology for Evidence-based Practice (U-CEP); an assessment tool to be used in the training of clinicians. The U-CEP was developed in two formats: two sets of 25 questions and a combined set of 50. The validation was performed among postgraduate general practice (GP) trainees, hospital trainees, GP supervisors, and experts. Internal consistency, internal reliability (item-total correlation), item discrimination index, item difficulty, content validity, construct validity, responsiveness, test-retest reliability, and feasibility were assessed. The questionnaire was externally validated. Internal consistency was good with a Cronbach alpha of 0.8. The median item-total correlation and mean item discrimination index were satisfactory. Both sets were perceived as relevant to clinical practice. Construct validity was good. Both sets were responsive but failed on test-retest reliability. One set took 24 minutes and the other 33 minutes to complete, on average. External GP trainees had comparable results. The U-CEP is a valid questionnaire to assess knowledge on clinical epidemiology, which is a prerequisite for practicing evidence-based medicine in daily clinical practice. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. A RE-AIM evaluation of theory-based physical activity interventions.

    PubMed

    Antikainen, Iina; Ellis, Rebecca

    2011-04-01

    Although physical activity interventions have been shown to effectively modify behavior, little research has examined the potential of these interventions for adoption in real-world settings. The purpose of this literature review was to evaluate the external validity of 57 theory-based physical activity interventions using the RE-AIM framework. The physical activity interventions included were more likely to report on issues of internal, rather than external validity and on individual, rather than organizational components of the RE-AIM framework, making the translation of many interventions into practice difficult. Furthermore, most studies included motivated, healthy participants, thus reducing the generalizability of the interventions to real-world settings that provide services to more diverse populations. To determine if a given intervention is feasible and effective in translational research, more information should be reported about the factors that affect external validity.

  16. Interaction of Theory and Practice to Assess External Validity.

    PubMed

    Leviton, Laura C; Trujillo, Mathew D

    2016-01-18

    Variations in local context bedevil the assessment of external validity: the ability to generalize about effects of treatments. For evaluation, the challenges of assessing external validity are intimately tied to the translation and spread of evidence-based interventions. This makes external validity a question for decision makers, who need to determine whether to endorse, fund, or adopt interventions that were found to be effective and how to ensure high quality once they spread. To present the rationale for using theory to assess external validity and the value of more systematic interaction of theory and practice. We review advances in external validity, program theory, practitioner expertise, and local adaptation. Examples are provided for program theory, its adaptation to diverse contexts, and generalizing to contexts that have not yet been studied. The often critical role of practitioner experience is illustrated in these examples. Work is described that the Robert Wood Johnson Foundation is supporting to study treatment variation and context more systematically. Researchers and developers generally see a limited range of contexts in which the intervention is implemented. Individual practitioners see a different and often a wider range of contexts, albeit not a systematic sample. Organized and taken together, however, practitioner experiences can inform external validity by challenging the developers and researchers to consider a wider range of contexts. Researchers have developed a variety of ways to adapt interventions in light of such challenges. In systematic programs of inquiry, as opposed to individual studies, the problems of context can be better addressed. Evaluators have advocated an interaction of theory and practice for many years, but the process can be made more systematic and useful. Systematic interaction can set priorities for assessment of external validity by examining the prevalence and importance of context features and treatment variations. Practitioner interaction with researchers and developers can assist in sharpening program theory, reducing uncertainty about treatment variations that are consistent or inconsistent with the theory, inductively ruling out the ones that are harmful or irrelevant, and helping set priorities for more rigorous study of context and treatment variation. © The Author(s) 2016.

  17. Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient.

    PubMed

    Chirico, Nicola; Gramatica, Paola

    2011-09-26

    The main utility of QSAR models is their ability to predict activities/properties for new chemicals, and this external prediction ability is evaluated by means of various validation criteria. As a measure for such evaluation the OECD guidelines have proposed the predictive squared correlation coefficient Q(2)(F1) (Shi et al.). However, other validation criteria have been proposed by other authors: the Golbraikh-Tropsha method, r(2)(m) (Roy), Q(2)(F2) (Schüürmann et al.), Q(2)(F3) (Consonni et al.). In QSAR studies these measures are usually in accordance, though this is not always the case, thus doubts can arise when contradictory results are obtained. It is likely that none of the aforementioned criteria is the best in every situation, so a comparative study using simulated data sets is proposed here, using threshold values suggested by the proponents or those widely used in QSAR modeling. In addition, a different and simple external validation measure, the concordance correlation coefficient (CCC), is proposed and compared with other criteria. Huge data sets were used to study the general behavior of validation measures, and the concordance correlation coefficient was shown to be the most restrictive. On using simulated data sets of a more realistic size, it was found that CCC was broadly in agreement, about 96% of the time, with other validation measures in accepting models as predictive, and in almost all the examples it was the most precautionary. The proposed concordance correlation coefficient also works well on real data sets, where it seems to be more stable, and helps in making decisions when the validation measures are in conflict. Since it is conceptually simple, and given its stability and restrictiveness, we propose the concordance correlation coefficient as a complementary, or alternative, more prudent measure of a QSAR model to be externally predictive.

  18. Number of organ dysfunctions predicts mortality in emergency department patients with suspected infection: a multicenter validation study.

    PubMed

    Jessen, Marie K; Skibsted, Simon; Shapiro, Nathan I

    2017-06-01

    The aim of this study was to validate the association between number of organ dysfunctions and mortality in emergency department (ED) patients with suspected infection. This study was conducted at two medical care center EDs. The internal validation set was a prospective cohort study conducted in Boston, USA. The external validation set was a retrospective case-control study conducted in Aarhus, Denmark. The study included adult patients (>18 years) with clinically suspected infection. Laboratory results and clinical data were used to assess organ dysfunctions. Inhospital mortality was the outcome measure. Multivariate logistic regression was used to determine the independent mortality odds for number and types of organ dysfunctions. We enrolled 4952 (internal) and 483 (external) patients. The mortality rate significantly increased with increasing number of organ dysfunctions: internal validation: 0 organ dysfunctions: 0.5% mortality, 1: 3.6%, 2: 9.5%, 3: 17%, and 4 or more: 37%; external validation: 2.2, 6.7, 17, 41, and 57% mortality (both P<0.001 for trend). Age-adjusted and comorbidity-adjusted number of organ dysfunctions remained an independent predictor. The effect of specific types of organ dysfunction on mortality was most pronounced for hematologic [odds ratio (OR) 3.3 (95% confidence interval (CI) 2.0-5.4)], metabolic [OR 3.3 (95% CI 2.4-4.6); internal validation], and cardiovascular dysfunctions [OR 14 (95% CI 3.7-50); external validation]. The number of organ dysfunctions predicts sepsis mortality.

  19. External Validity of the New York University Caregiver Intervention: Key Caregiver Outcomes Across Multiple Demonstration Projects.

    PubMed

    Fauth, Elizabeth B; Jackson, Mark A; Walberg, Donna K; Lee, Nancy E; Easom, Leisa R; Alston, Gayle; Ramos, Angel; Felten, Kristen; LaRue, Asenath; Mittelman, Mary

    2017-06-01

    The Administration on Aging funded six New York University Caregiver Intervention (NYUCI) demonstration projects, a counseling/support intervention targeting dementia caregivers and families. Three sites (Georgia, Utah, Wisconsin) pooled data to inform external validity in nonresearch settings. This study (a) assesses collective changes over time, and (b) compares outcomes across sites on caregiver burden, depressive symptoms, satisfaction with social support, family conflict, and quality of life. Data included baseline/preintervention ( N = 294) and follow-up visits (approximately 4, 8, 12 months). Linear mixed models showed that social support satisfaction increased ( p < .05) and family conflict decreased ( p < .05; Cohen's d = 0.49 and 0.35, respectively). Marginally significant findings emerged for quality of life increases ( p = .05) and burden decreases ( p < .10). Depressive symptoms remained stable. Slopes did not differ much by site. NYUCI demonstrated external validity in nonresearch settings across diverse caregiver samples.

  20. Prediction of pelvic organ prolapse using an artificial neural network.

    PubMed

    Robinson, Christopher J; Swift, Steven; Johnson, Donna D; Almeida, Jonas S

    2008-08-01

    The objective of this investigation was to test the ability of a feedforward artificial neural network (ANN) to differentiate patients who have pelvic organ prolapse (POP) from those who retain good pelvic organ support. Following institutional review board approval, patients with POP (n = 87) and controls with good pelvic organ support (n = 368) were identified from the urogynecology research database. Historical and clinical information was extracted from the database. Data analysis included the training of a feedforward ANN, variable selection, and external validation of the model with an independent data set. Twenty variables were used. The median-performing ANN model used a median of 3 (quartile 1:3 to quartile 3:5) variables and achieved an area under the receiver operator curve of 0.90 (external, independent validation set). Ninety percent sensitivity and 83% specificity were obtained in the external validation by ANN classification. Feedforward ANN modeling is applicable to the identification and prediction of POP.

  1. The Development and Piloting of Parallel Scales Measuring External and Internal HIV and Tuberculosis Stigma Among Healthcare Workers in the Free State Province, South Africa.

    PubMed

    Wouters, Edwin; Rau, Asta; Engelbrecht, Michelle; Uebel, Kerry; Siegel, Jacob; Masquillier, Caroline; Kigozi, Gladys; Sommerland, Nina; Yassi, Annalee

    2016-05-15

    The dual burden of tuberculosis and human immunodeficiency virus (HIV) is severely impacting the South African healthcare workforce. However, the use of on-site occupational health services is hampered by stigma among the healthcare workforce. The success of stigma-reduction interventions is difficult to evaluate because of a dearth of appropriate scientific tools to measure stigma in this specific professional setting. The current pilot study aimed to develop and test a range of scales measuring different aspects of stigma-internal and external stigma toward tuberculosis as well as HIV-in a South African healthcare setting. The study employed data of a sample of 200 staff members of a large hospital in Bloemfontein, South Africa. Confirmatory factor analysis produced 7 scales, displaying internal construct validity: (1) colleagues' external HIV stigma, (2) colleagues' actions against external HIV stigma, (3) respondent's external HIV stigma, (4) respondent's internal HIV stigma, (5) colleagues' external tuberculosis stigma, (6) respondent's external tuberculosis stigma, and (7) respondent's internal tuberculosis stigma. Subsequent analyses (reliability analysis, structural equation modeling) demonstrated that the scales displayed good psychometric properties in terms of reliability and external construct validity. The study outcomes support the use of the developed scales as a valid and reliable means to measure levels of tuberculosis- and HIV-related stigma among the healthcare workforce in a resource-limited context. Future studies should build on these findings to fine-tune the instruments and apply them to larger study populations across a range of different resource-limited healthcare settings with high HIV and tuberculosis prevalence. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

  2. The Development and Piloting of Parallel Scales Measuring External and Internal HIV and Tuberculosis Stigma Among Healthcare Workers in the Free State Province, South Africa

    PubMed Central

    Wouters, Edwin; Rau, Asta; Engelbrecht, Michelle; Uebel, Kerry; Siegel, Jacob; Masquillier, Caroline; Kigozi, Gladys; Sommerland, Nina; Yassi, Annalee

    2016-01-01

    Background The dual burden of tuberculosis and human immunodeficiency virus (HIV) is severely impacting the South African healthcare workforce. However, the use of on-site occupational health services is hampered by stigma among the healthcare workforce. The success of stigma-reduction interventions is difficult to evaluate because of a dearth of appropriate scientific tools to measure stigma in this specific professional setting. Methods The current pilot study aimed to develop and test a range of scales measuring different aspects of stigma—internal and external stigma toward tuberculosis as well as HIV—in a South African healthcare setting. The study employed data of a sample of 200 staff members of a large hospital in Bloemfontein, South Africa. Results Confirmatory factor analysis produced 7 scales, displaying internal construct validity: (1) colleagues’ external HIV stigma, (2) colleagues’ actions against external HIV stigma, (3) respondent’s external HIV stigma, (4) respondent’s internal HIV stigma, (5) colleagues’ external tuberculosis stigma, (6) respondent’s external tuberculosis stigma, and (7) respondent’s internal tuberculosis stigma. Subsequent analyses (reliability analysis, structural equation modeling) demonstrated that the scales displayed good psychometric properties in terms of reliability and external construct validity. Conclusions The study outcomes support the use of the developed scales as a valid and reliable means to measure levels of tuberculosis- and HIV-related stigma among the healthcare workforce in a resource-limited context. Future studies should build on these findings to fine-tune the instruments and apply them to larger study populations across a range of different resource-limited healthcare settings with high HIV and tuberculosis prevalence. PMID:27118854

  3. QSAR Modeling of Rat Acute Toxicity by Oral Exposure

    PubMed Central

    Zhu, Hao; Martin, Todd M.; Ye, Lin; Sedykh, Alexander; Young, Douglas M.; Tropsha, Alexander

    2009-01-01

    Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity endpoints. In this study, a comprehensive dataset of 7,385 compounds with their most conservative lethal dose (LD50) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire dataset was selected that included all 3,472 compounds used in the TOPKAT’s training set. The remaining 3,913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R2 of linear regression between actual and predicted LD50 values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R2 ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD50 for every compound using all 5 models. The consensus models afforded higher prediction accuracy for the external validation dataset with the higher coverage as compared to individual constituent models. The validated consensus LD50 models developed in this study can be used as reliable computational predictors of in vivo acute toxicity. PMID:19845371

  4. Comparison between genetic parameters of cheese yield and nutrient recovery or whey loss traits measured from individual model cheese-making methods or predicted from unprocessed bovine milk samples using Fourier-transform infrared spectroscopy.

    PubMed

    Bittante, G; Ferragina, A; Cipolat-Gotet, C; Cecchinato, A

    2014-10-01

    Cheese yield is an important technological trait in the dairy industry. The aim of this study was to infer the genetic parameters of some cheese yield-related traits predicted using Fourier-transform infrared (FTIR) spectral analysis and compare the results with those obtained using an individual model cheese-producing procedure. A total of 1,264 model cheeses were produced using 1,500-mL milk samples collected from individual Brown Swiss cows, and individual measurements were taken for 10 traits: 3 cheese yield traits (fresh curd, curd total solids, and curd water as a percent of the weight of the processed milk), 4 milk nutrient recovery traits (fat, protein, total solids, and energy of the curd as a percent of the same nutrient in the processed milk), and 3 daily cheese production traits per cow (fresh curd, total solids, and water weight of the curd). Each unprocessed milk sample was analyzed using a MilkoScan FT6000 (Foss, Hillerød, Denmark) over the spectral range, from 5,000 to 900 wavenumber × cm(-1). The FTIR spectrum-based prediction models for the previously mentioned traits were developed using modified partial least-square regression. Cross-validation of the whole data set yielded coefficients of determination between the predicted and measured values in cross-validation of 0.65 to 0.95 for all traits, except for the recovery of fat (0.41). A 3-fold external validation was also used, in which the available data were partitioned into 2 subsets: a training set (one-third of the herds) and a testing set (two-thirds). The training set was used to develop calibration equations, whereas the testing subsets were used for external validation of the calibration equations and to estimate the heritabilities and genetic correlations of the measured and FTIR-predicted phenotypes. The coefficients of determination between the predicted and measured values in cross-validation results obtained from the training sets were very similar to those obtained from the whole data set, but the coefficient of determination of validation values for the external validation sets were much lower for all traits (0.30 to 0.73), and particularly for fat recovery (0.05 to 0.18), for the training sets compared with the full data set. For each testing subset, the (co)variance components for the measured and FTIR-predicted phenotypes were estimated using bivariate Bayesian analyses and linear models. The intraherd heritabilities for the predicted traits obtained from our internal cross-validation using the whole data set ranged from 0.085 for daily yield of curd solids to 0.576 for protein recovery, and were similar to those obtained from the measured traits (0.079 to 0.586, respectively). The heritabilities estimated from the testing data set used for external validation were more variable but similar (on average) to the corresponding values obtained from the whole data set. Moreover, the genetic correlations between the predicted and measured traits were high in general (0.791 to 0.996), and they were always higher than the corresponding phenotypic correlations (0.383 to 0.995), especially for the external validation subset. In conclusion, we herein report that application of the cross-validation technique to the whole data set tended to overestimate the predictive ability of FTIR spectra, give more precise phenotypic predictions than the calibrations obtained using smaller data sets, and yield genetic correlations similar to those obtained from the measured traits. Collectively, our findings indicate that FTIR predictions have the potential to be used as indicator traits for the rapid and inexpensive selection of dairy populations for improvement of cheese yield, milk nutrient recovery in curd, and daily cheese production per cow. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  5. The impact of crowd noise on officiating in muay thai: achieving external validity in an experimental setting.

    PubMed

    Myers, Tony; Balmer, Nigel

    2012-01-01

    Numerous factors have been proposed to explain the home advantage in sport. Several authors have suggested that a partisan home crowd enhances home advantage and that this is at least in part a consequence of their influence on officiating. However, while experimental studies examining this phenomenon have high levels of internal validity (since only the "crowd noise" intervention is allowed to vary), they suffer from a lack of external validity, with decision-making in a laboratory setting typically bearing little resemblance to decision-making in live sports settings. Conversely, observational and quasi-experimental studies with high levels of external validity suffer from low levels of internal validity as countless factors besides crowd noise vary. The present study provides a unique opportunity to address these criticisms, by conducting a controlled experiment on the impact of crowd noise on officiating in a live tournament setting. Seventeen qualified judges officiated on thirty Thai boxing bouts in a live international tournament setting featuring "home" and "away" boxers. In each bout, judges were randomized into a "noise" (live sound) or "no crowd noise" (noise-canceling headphones and white noise) condition, resulting in 59 judgments in the "no crowd noise" and 61 in the "crowd noise" condition. The results provide the first experimental evidence of the impact of live crowd noise on officials in sport. A cross-classified statistical model indicated that crowd noise had a statistically significant impact, equating to just over half a point per bout (in the context of five round bouts with the "10-point must" scoring system shared with professional boxing). The practical significance of the findings, their implications for officiating and for the future conduct of crowd noise studies are discussed.

  6. The Impact of Crowd Noise on Officiating in Muay Thai: Achieving External Validity in an Experimental Setting

    PubMed Central

    Myers, Tony; Balmer, Nigel

    2012-01-01

    Numerous factors have been proposed to explain the home advantage in sport. Several authors have suggested that a partisan home crowd enhances home advantage and that this is at least in part a consequence of their influence on officiating. However, while experimental studies examining this phenomenon have high levels of internal validity (since only the “crowd noise” intervention is allowed to vary), they suffer from a lack of external validity, with decision-making in a laboratory setting typically bearing little resemblance to decision-making in live sports settings. Conversely, observational and quasi-experimental studies with high levels of external validity suffer from low levels of internal validity as countless factors besides crowd noise vary. The present study provides a unique opportunity to address these criticisms, by conducting a controlled experiment on the impact of crowd noise on officiating in a live tournament setting. Seventeen qualified judges officiated on thirty Thai boxing bouts in a live international tournament setting featuring “home” and “away” boxers. In each bout, judges were randomized into a “noise” (live sound) or “no crowd noise” (noise-canceling headphones and white noise) condition, resulting in 59 judgments in the “no crowd noise” and 61 in the “crowd noise” condition. The results provide the first experimental evidence of the impact of live crowd noise on officials in sport. A cross-classified statistical model indicated that crowd noise had a statistically significant impact, equating to just over half a point per bout (in the context of five round bouts with the “10-point must” scoring system shared with professional boxing). The practical significance of the findings, their implications for officiating and for the future conduct of crowd noise studies are discussed. PMID:23049520

  7. Multisite external validation of a risk prediction model for the diagnosis of blood stream infections in febrile pediatric oncology patients without severe neutropenia.

    PubMed

    Esbenshade, Adam J; Zhao, Zhiguo; Aftandilian, Catherine; Saab, Raya; Wattier, Rachel L; Beauchemin, Melissa; Miller, Tamara P; Wilkes, Jennifer J; Kelly, Michael J; Fernbach, Alison; Jeng, Michael; Schwartz, Cindy L; Dvorak, Christopher C; Shyr, Yu; Moons, Karl G M; Sulis, Maria-Luisa; Friedman, Debra L

    2017-10-01

    Pediatric oncology patients are at an increased risk of invasive bacterial infection due to immunosuppression. The risk of such infection in the absence of severe neutropenia (absolute neutrophil count ≥ 500/μL) is not well established and a validated prediction model for blood stream infection (BSI) risk offers clinical usefulness. A 6-site retrospective external validation was conducted using a previously published risk prediction model for BSI in febrile pediatric oncology patients without severe neutropenia: the Esbenshade/Vanderbilt (EsVan) model. A reduced model (EsVan2) excluding 2 less clinically reliable variables also was created using the initial EsVan model derivative cohort, and was validated using all 5 external validation cohorts. One data set was used only in sensitivity analyses due to missing some variables. From the 5 primary data sets, there were a total of 1197 febrile episodes and 76 episodes of bacteremia. The overall C statistic for predicting bacteremia was 0.695, with a calibration slope of 0.50 for the original model and a calibration slope of 1.0 when recalibration was applied to the model. The model performed better in predicting high-risk bacteremia (gram-negative or Staphylococcus aureus infection) versus BSI alone, with a C statistic of 0.801 and a calibration slope of 0.65. The EsVan2 model outperformed the EsVan model across data sets with a C statistic of 0.733 for predicting BSI and a C statistic of 0.841 for high-risk BSI. The results of this external validation demonstrated that the EsVan and EsVan2 models are able to predict BSI across multiple performance sites and, once validated and implemented prospectively, could assist in decision making in clinical practice. Cancer 2017;123:3781-3790. © 2017 American Cancer Society. © 2017 American Cancer Society.

  8. Multiple Versus Single Set Validation of Multivariate Models to Avoid Mistakes.

    PubMed

    Harrington, Peter de Boves

    2018-01-02

    Validation of multivariate models is of current importance for a wide range of chemical applications. Although important, it is neglected. The common practice is to use a single external validation set for evaluation. This approach is deficient and may mislead investigators with results that are specific to the single validation set of data. In addition, no statistics are available regarding the precision of a derived figure of merit (FOM). A statistical approach using bootstrapped Latin partitions is advocated. This validation method makes an efficient use of the data because each object is used once for validation. It was reviewed a decade earlier but primarily for the optimization of chemometric models this review presents the reasons it should be used for generalized statistical validation. Average FOMs with confidence intervals are reported and powerful, matched-sample statistics may be applied for comparing models and methods. Examples demonstrate the problems with single validation sets.

  9. Assessment of generalizability, applicability and predictability (GAP) for evaluating external validity in studies of universal family-based prevention of alcohol misuse in young people: systematic methodological review of randomized controlled trials.

    PubMed

    Fernandez-Hermida, Jose Ramon; Calafat, Amador; Becoña, Elisardo; Tsertsvadze, Alexander; Foxcroft, David R

    2012-09-01

    To assess external validity characteristics of studies from two Cochrane Systematic Reviews of the effectiveness of universal family-based prevention of alcohol misuse in young people. Two reviewers used an a priori developed external validity rating form and independently assessed three external validity dimensions of generalizability, applicability and predictability (GAP) in randomized controlled trials. The majority (69%) of the included 29 studies were rated 'unclear' on the reporting of sufficient information for judging generalizability from sample to study population. Ten studies (35%) were rated 'unclear' on the reporting of sufficient information for judging applicability to other populations and settings. No study provided an assessment of the validity of the trial end-point measures for subsequent mortality, morbidity, quality of life or other economic or social outcomes. Similarly, no study reported on the validity of surrogate measures using established criteria for assessing surrogate end-points. Studies evaluating the benefits of family-based prevention of alcohol misuse in young people are generally inadequate at reporting information relevant to generalizability of the findings or implications for health or social outcomes. Researchers, study authors, peer reviewers, journal editors and scientific societies should take steps to improve the reporting of information relevant to external validity in prevention trials. © 2012 The Authors. Addiction © 2012 Society for the Study of Addiction.

  10. External validity of a generic safety climate scale for lone workers across different industries and companies.

    PubMed

    Lee, Jin; Huang, Yueng-hsiang; Robertson, Michelle M; Murphy, Lauren A; Garabet, Angela; Chang, Wen-Ruey

    2014-02-01

    The goal of this study was to examine the external validity of a 12-item generic safety climate scale for lone workers in order to evaluate the appropriateness of generalized use of the scale in the measurement of safety climate across various lone work settings. External validity evidence was established by investigating the measurement equivalence (ME) across different industries and companies. Confirmatory factor analysis (CFA)-based and item response theory (IRT)-based perspectives were adopted to examine the ME of the generic safety climate scale for lone workers across 11 companies from the trucking, electrical utility, and cable television industries. Fairly strong evidence of ME was observed for both organization- and group-level generic safety climate sub-scales. Although significant invariance was observed in the item intercepts across the different lone work settings, absolute model fit indices remained satisfactory in the most robust step of CFA-based ME testing. IRT-based ME testing identified only one differentially functioning item from the organization-level generic safety climate sub-scale, but its impact was minimal and strong ME was supported. The generic safety climate scale for lone workers reported good external validity and supported the presence of a common feature of safety climate among lone workers. The scale can be used as an effective safety evaluation tool in various lone work situations. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. 42 CFR 438.358 - Activities related to external quality review.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...) Validation of performance improvement projects required by the State to comply with requirements set forth in § 438.240(b)(1) and that were underway during the preceding 12 months. (2) Validation of MCO or PIHP... derived during the preceding 12 months from the following optional activities: (1) Validation of encounter...

  12. 42 CFR 438.358 - Activities related to external quality review.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...) Validation of performance improvement projects required by the State to comply with requirements set forth in § 438.240(b)(1) and that were underway during the preceding 12 months. (2) Validation of MCO or PIHP... derived during the preceding 12 months from the following optional activities: (1) Validation of encounter...

  13. 42 CFR 438.358 - Activities related to external quality review.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...) Validation of performance improvement projects required by the State to comply with requirements set forth in § 438.240(b)(1) and that were underway during the preceding 12 months. (2) Validation of MCO or PIHP... derived during the preceding 12 months from the following optional activities: (1) Validation of encounter...

  14. 42 CFR 438.358 - Activities related to external quality review.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...) Validation of performance improvement projects required by the State to comply with requirements set forth in § 438.240(b)(1) and that were underway during the preceding 12 months. (2) Validation of MCO or PIHP... derived during the preceding 12 months from the following optional activities: (1) Validation of encounter...

  15. Development of Decision Support Formulas for the Prediction of Bladder Outlet Obstruction and Prostatic Surgery in Patients With Lower Urinary Tract Symptom/Benign Prostatic Hyperplasia: Part II, External Validation and Usability Testing of a Smartphone App.

    PubMed

    Choo, Min Soo; Jeong, Seong Jin; Cho, Sung Yong; Yoo, Changwon; Jeong, Chang Wook; Ku, Ja Hyeon; Oh, Seung-June

    2017-04-01

    We aimed to externally validate the prediction model we developed for having bladder outlet obstruction (BOO) and requiring prostatic surgery using 2 independent data sets from tertiary referral centers, and also aimed to validate a mobile app for using this model through usability testing. Formulas and nomograms predicting whether a subject has BOO and needs prostatic surgery were validated with an external validation cohort from Seoul National University Bundang Hospital and Seoul Metropolitan Government-Seoul National University Boramae Medical Center between January 2004 and April 2015. A smartphone-based app was developed, and 8 young urologists were enrolled for usability testing to identify any human factor issues of the app. A total of 642 patients were included in the external validation cohort. No significant differences were found in the baseline characteristics of major parameters between the original (n=1,179) and the external validation cohort, except for the maximal flow rate. Predictions of requiring prostatic surgery in the validation cohort showed a sensitivity of 80.6%, a specificity of 73.2%, a positive predictive value of 49.7%, and a negative predictive value of 92.0%, and area under receiver operating curve of 0.84. The calibration plot indicated that the predictions have good correspondence. The decision curve showed also a high net benefit. Similar evaluation results using the external validation cohort were seen in the predictions of having BOO. Overall results of the usability test demonstrated that the app was user-friendly with no major human factor issues. External validation of these newly developed a prediction model demonstrated a moderate level of discrimination, adequate calibration, and high net benefit gains for predicting both having BOO and requiring prostatic surgery. Also a smartphone app implementing the prediction model was user-friendly with no major human factor issue.

  16. Novel naïve Bayes classification models for predicting the chemical Ames mutagenicity.

    PubMed

    Zhang, Hui; Kang, Yan-Li; Zhu, Yuan-Yuan; Zhao, Kai-Xia; Liang, Jun-Yu; Ding, Lan; Zhang, Teng-Guo; Zhang, Ji

    2017-06-01

    Prediction of drug candidates for mutagenicity is a regulatory requirement since mutagenic compounds could pose a toxic risk to humans. The aim of this investigation was to develop a novel prediction model of mutagenicity by using a naïve Bayes classifier. The established model was validated by the internal 5-fold cross validation and external test sets. For comparison, the recursive partitioning classifier prediction model was also established and other various reported prediction models of mutagenicity were collected. Among these methods, the prediction performance of naïve Bayes classifier established here displayed very well and stable, which yielded average overall prediction accuracies for the internal 5-fold cross validation of the training set and external test set I set were 89.1±0.4% and 77.3±1.5%, respectively. The concordance of the external test set II with 446 marketed drugs was 90.9±0.3%. In addition, four simple molecular descriptors (e.g., Apol, No. of H donors, Num-Rings and Wiener) related to mutagenicity and five representative substructures of mutagens (e.g., aromatic nitro, hydroxyl amine, nitroso, aromatic amine and N-methyl-N-methylenemethanaminum) produced by ECFP_14 fingerprints were identified. We hope the established naïve Bayes prediction model can be applied to risk assessment processes; and the obtained important information of mutagenic chemicals can guide the design of chemical libraries for hit and lead optimization. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Place and Child Health: The Interaction of Population Density and Sanitation in Developing Countries.

    PubMed

    Hathi, Payal; Haque, Sabrina; Pant, Lovey; Coffey, Diane; Spears, Dean

    2017-02-01

    A long literature in demography has debated the importance of place for health, especially children's health. In this study, we assess whether the importance of dense settlement for infant mortality and child height is moderated by exposure to local sanitation behavior. Is open defecation (i.e., without a toilet or latrine) worse for infant mortality and child height where population density is greater? Is poor sanitation is an important mechanism by which population density influences child health outcomes? We present two complementary analyses using newly assembled data sets, which represent two points in a trade-off between external and internal validity. First, we concentrate on external validity by studying infant mortality and child height in a large, international child-level data set of 172 Demographic and Health Surveys, matched to census population density data for 1,800 subnational regions. Second, we concentrate on internal validity by studying child height in Bangladeshi districts, using a new data set constructed with GIS techniques that allows us to control for fixed effects at a high level of geographic resolution. We find a statistically robust and quantitatively comparable interaction between sanitation and population density with both approaches: open defecation externalities are more important for child health outcomes where people live more closely together.

  18. Modification of the random forest algorithm to avoid statistical dependence problems when classifying remote sensing imagery

    NASA Astrophysics Data System (ADS)

    Cánovas-García, Fulgencio; Alonso-Sarría, Francisco; Gomariz-Castillo, Francisco; Oñate-Valdivieso, Fernando

    2017-06-01

    Random forest is a classification technique widely used in remote sensing. One of its advantages is that it produces an estimation of classification accuracy based on the so called out-of-bag cross-validation method. It is usually assumed that such estimation is not biased and may be used instead of validation based on an external data-set or a cross-validation external to the algorithm. In this paper we show that this is not necessarily the case when classifying remote sensing imagery using training areas with several pixels or objects. According to our results, out-of-bag cross-validation clearly overestimates accuracy, both overall and per class. The reason is that, in a training patch, pixels or objects are not independent (from a statistical point of view) of each other; however, they are split by bootstrapping into in-bag and out-of-bag as if they were really independent. We believe that putting whole patch, rather than pixels/objects, in one or the other set would produce a less biased out-of-bag cross-validation. To deal with the problem, we propose a modification of the random forest algorithm to split training patches instead of the pixels (or objects) that compose them. This modified algorithm does not overestimate accuracy and has no lower predictive capability than the original. When its results are validated with an external data-set, the accuracy is not different from that obtained with the original algorithm. We analysed three remote sensing images with different classification approaches (pixel and object based); in the three cases reported, the modification we propose produces a less biased accuracy estimation.

  19. How do we estimate survival? External validation of a tool for survival estimation in patients with metastatic bone disease-decision analysis and comparison of three international patient populations.

    PubMed

    Piccioli, Andrea; Spinelli, M Silvia; Forsberg, Jonathan A; Wedin, Rikard; Healey, John H; Ippolito, Vincenzo; Daolio, Primo Andrea; Ruggieri, Pietro; Maccauro, Giulio; Gasbarrini, Alessandro; Biagini, Roberto; Piana, Raimondo; Fazioli, Flavio; Luzzati, Alessandro; Di Martino, Alberto; Nicolosi, Francesco; Camnasio, Francesco; Rosa, Michele Attilio; Campanacci, Domenico Andrea; Denaro, Vincenzo; Capanna, Rodolfo

    2015-05-22

    We recently developed a clinical decision support tool, capable of estimating the likelihood of survival at 3 and 12 months following surgery for patients with operable skeletal metastases. After making it publicly available on www.PATHFx.org , we attempted to externally validate it using independent, international data. We collected data from patients treated at 13 Italian orthopaedic oncology referral centers between 2010 and 2013, then applied to PATHFx, which generated a probability of survival at three and 12-months for each patient. We assessed accuracy using the area under the receiver-operating characteristic curve (AUC), clinical utility using Decision Curve Analysis (DCA), and compared the Italian patient data to the training set (United States) and first external validation set (Scandinavia). The Italian dataset contained 287 records with at least 12 months follow-up information. The AUCs for the three-month and 12-month estimates was 0.80 and 0.77, respectively. There were missing data, including the surgeon's estimate of survival that was missing in the majority of records. Physiologically, Italian patients were similar to patients in the training and first validation sets. However notable differences were observed in the proportion of those surviving three and 12-months, suggesting differences in referral patterns and perhaps indications for surgery. PATHFx was successfully validated in an Italian dataset containing missing data. This study demonstrates its broad applicability to European patients, even in centers with differing treatment philosophies from those previously studied.

  20. Derivation and external validation of a case mix model for the standardized reporting of 30-day stroke mortality rates.

    PubMed

    Bray, Benjamin D; Campbell, James; Cloud, Geoffrey C; Hoffman, Alex; James, Martin; Tyrrell, Pippa J; Wolfe, Charles D A; Rudd, Anthony G

    2014-11-01

    Case mix adjustment is required to allow valid comparison of outcomes across care providers. However, there is a lack of externally validated models suitable for use in unselected stroke admissions. We therefore aimed to develop and externally validate prediction models to enable comparison of 30-day post-stroke mortality outcomes using routine clinical data. Models were derived (n=9000 patients) and internally validated (n=18 169 patients) using data from the Sentinel Stroke National Audit Program, the national register of acute stroke in England and Wales. External validation (n=1470 patients) was performed in the South London Stroke Register, a population-based longitudinal study. Models were fitted using general estimating equations. Discrimination and calibration were assessed using receiver operating characteristic curve analysis and correlation plots. Two final models were derived. Model A included age (<60, 60-69, 70-79, 80-89, and ≥90 years), National Institutes of Health Stroke Severity Score (NIHSS) on admission, presence of atrial fibrillation on admission, and stroke type (ischemic versus primary intracerebral hemorrhage). Model B was similar but included only the consciousness component of the NIHSS in place of the full NIHSS. Both models showed excellent discrimination and calibration in internal and external validation. The c-statistics in external validation were 0.87 (95% confidence interval, 0.84-0.89) and 0.86 (95% confidence interval, 0.83-0.89) for models A and B, respectively. We have derived and externally validated 2 models to predict mortality in unselected patients with acute stroke using commonly collected clinical variables. In settings where the ability to record the full NIHSS on admission is limited, the level of consciousness component of the NIHSS provides a good approximation of the full NIHSS for mortality prediction. © 2014 American Heart Association, Inc.

  1. Prediction of prostate cancer in unscreened men: external validation of a risk calculator.

    PubMed

    van Vugt, Heidi A; Roobol, Monique J; Kranse, Ries; Määttänen, Liisa; Finne, Patrik; Hugosson, Jonas; Bangma, Chris H; Schröder, Fritz H; Steyerberg, Ewout W

    2011-04-01

    Prediction models need external validation to assess their value beyond the setting where the model was derived from. To assess the external validity of the European Randomized study of Screening for Prostate Cancer (ERSPC) risk calculator (www.prostatecancer-riskcalculator.com) for the probability of having a positive prostate biopsy (P(posb)). The ERSPC risk calculator was based on data of the initial screening round of the ERSPC section Rotterdam and validated in 1825 and 531 men biopsied at the initial screening round in the Finnish and Swedish sections of the ERSPC respectively. P(posb) was calculated using serum prostate specific antigen (PSA), outcome of digital rectal examination (DRE), transrectal ultrasound and ultrasound assessed prostate volume. The external validity was assessed for the presence of cancer at biopsy by calibration (agreement between observed and predicted outcomes), discrimination (separation of those with and without cancer), and decision curves (for clinical usefulness). Prostate cancer was detected in 469 men (26%) of the Finnish cohort and in 124 men (23%) of the Swedish cohort. Systematic miscalibration was present in both cohorts (mean predicted probability 34% versus 26% observed, and 29% versus 23% observed, both p<0.001). The areas under the curves were 0.76 and 0.78, and substantially lower for the model with PSA only (0.64 and 0.68 respectively). The model proved clinically useful for any decision threshold compared with a model with PSA only, PSA and DRE, or biopsying all men. A limitation is that the model is based on sextant biopsies results. The ERSPC risk calculator discriminated well between those with and without prostate cancer among initially screened men, but overestimated the risk of a positive biopsy. Further research is necessary to assess the performance and applicability of the ERSPC risk calculator when a clinical setting is considered rather than a screening setting. Copyright © 2010 Elsevier Ltd. All rights reserved.

  2. A Quantitative Structure Activity Relationship for acute oral toxicity of pesticides on rats: Validation, domain of application and prediction.

    PubMed

    Hamadache, Mabrouk; Benkortbi, Othmane; Hanini, Salah; Amrane, Abdeltif; Khaouane, Latifa; Si Moussa, Cherif

    2016-02-13

    Quantitative Structure Activity Relationship (QSAR) models are expected to play an important role in the risk assessment of chemicals on humans and the environment. In this study, we developed a validated QSAR model to predict acute oral toxicity of 329 pesticides to rats because a few QSAR models have been devoted to predict the Lethal Dose 50 (LD50) of pesticides on rats. This QSAR model is based on 17 molecular descriptors, and is robust, externally predictive and characterized by a good applicability domain. The best results were obtained with a 17/9/1 Artificial Neural Network model trained with the Quasi Newton back propagation (BFGS) algorithm. The prediction accuracy for the external validation set was estimated by the Q(2)ext and the root mean square error (RMS) which are equal to 0.948 and 0.201, respectively. 98.6% of external validation set is correctly predicted and the present model proved to be superior to models previously published. Accordingly, the model developed in this study provides excellent predictions and can be used to predict the acute oral toxicity of pesticides, particularly for those that have not been tested as well as new pesticides. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. A calibration hierarchy for risk models was defined: from utopia to empirical data.

    PubMed

    Van Calster, Ben; Nieboer, Daan; Vergouwe, Yvonne; De Cock, Bavo; Pencina, Michael J; Steyerberg, Ewout W

    2016-06-01

    Calibrated risk models are vital for valid decision support. We define four levels of calibration and describe implications for model development and external validation of predictions. We present results based on simulated data sets. A common definition of calibration is "having an event rate of R% among patients with a predicted risk of R%," which we refer to as "moderate calibration." Weaker forms of calibration only require the average predicted risk (mean calibration) or the average prediction effects (weak calibration) to be correct. "Strong calibration" requires that the event rate equals the predicted risk for every covariate pattern. This implies that the model is fully correct for the validation setting. We argue that this is unrealistic: the model type may be incorrect, the linear predictor is only asymptotically unbiased, and all nonlinear and interaction effects should be correctly modeled. In addition, we prove that moderate calibration guarantees nonharmful decision making. Finally, results indicate that a flexible assessment of calibration in small validation data sets is problematic. Strong calibration is desirable for individualized decision support but unrealistic and counter productive by stimulating the development of overly complex models. Model development and external validation should focus on moderate calibration. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Analysis of model development strategies: predicting ventral hernia recurrence.

    PubMed

    Holihan, Julie L; Li, Linda T; Askenasy, Erik P; Greenberg, Jacob A; Keith, Jerrod N; Martindale, Robert G; Roth, J Scott; Liang, Mike K

    2016-11-01

    There have been many attempts to identify variables associated with ventral hernia recurrence; however, it is unclear which statistical modeling approach results in models with greatest internal and external validity. We aim to assess the predictive accuracy of models developed using five common variable selection strategies to determine variables associated with hernia recurrence. Two multicenter ventral hernia databases were used. Database 1 was randomly split into "development" and "internal validation" cohorts. Database 2 was designated "external validation". The dependent variable for model development was hernia recurrence. Five variable selection strategies were used: (1) "clinical"-variables considered clinically relevant, (2) "selective stepwise"-all variables with a P value <0.20 were assessed in a step-backward model, (3) "liberal stepwise"-all variables were included and step-backward regression was performed, (4) "restrictive internal resampling," and (5) "liberal internal resampling." Variables were included with P < 0.05 for the Restrictive model and P < 0.10 for the Liberal model. A time-to-event analysis using Cox regression was performed using these strategies. The predictive accuracy of the developed models was tested on the internal and external validation cohorts using Harrell's C-statistic where C > 0.70 was considered "reasonable". The recurrence rate was 32.9% (n = 173/526; median/range follow-up, 20/1-58 mo) for the development cohort, 36.0% (n = 95/264, median/range follow-up 20/1-61 mo) for the internal validation cohort, and 12.7% (n = 155/1224, median/range follow-up 9/1-50 mo) for the external validation cohort. Internal validation demonstrated reasonable predictive accuracy (C-statistics = 0.772, 0.760, 0.767, 0.757, 0.763), while on external validation, predictive accuracy dipped precipitously (C-statistic = 0.561, 0.557, 0.562, 0.553, 0.560). Predictive accuracy was equally adequate on internal validation among models; however, on external validation, all five models failed to demonstrate utility. Future studies should report multiple variable selection techniques and demonstrate predictive accuracy on external data sets for model validation. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. A New Structure-Activity Relationship (SAR) Model for Predicting Drug-Induced Liver Injury, Based on Statistical and Expert-Based Structural Alerts

    PubMed Central

    Pizzo, Fabiola; Lombardo, Anna; Manganaro, Alberto; Benfenati, Emilio

    2016-01-01

    The prompt identification of chemical molecules with potential effects on liver may help in drug discovery and in raising the levels of protection for human health. Besides in vitro approaches, computational methods in toxicology are drawing attention. We built a structure-activity relationship (SAR) model for evaluating hepatotoxicity. After compiling a data set of 950 compounds using data from the literature, we randomly split it into training (80%) and test sets (20%). We also compiled an external validation set (101 compounds) for evaluating the performance of the model. To extract structural alerts (SAs) related to hepatotoxicity and non-hepatotoxicity we used SARpy, a statistical application that automatically identifies and extracts chemical fragments related to a specific activity. We also applied the chemical grouping approach for manually identifying other SAs. We calculated accuracy, specificity, sensitivity and Matthews correlation coefficient (MCC) on the training, test and external validation sets. Considering the complexity of the endpoint, the model performed well. In the training, test and external validation sets the accuracy was respectively 81, 63, and 68%, specificity 89, 33, and 33%, sensitivity 93, 88, and 80% and MCC 0.63, 0.27, and 0.13. Since it is preferable to overestimate hepatotoxicity rather than not to recognize unsafe compounds, the model's architecture followed a conservative approach. As it was built using human data, it might be applied without any need for extrapolation from other species. This model will be freely available in the VEGA platform. PMID:27920722

  6. Building a Practically Useful Theory of Goal Setting and Task Motivation.

    ERIC Educational Resources Information Center

    Locke, Edwin A.; Latham, Gary P.

    2002-01-01

    Summarizes 35 years of empirical research on goal-setting theory, describing core findings of the theory, mechanisms by which goals operate, moderators of goal effects, the relation of goals and satisfaction, and the role of goals as mediators of incentives. Explains the external validity and practical significance of goal setting theory,…

  7. An Experimental Study of the Internal Consistency of Judgments Made in Bookmark Standard Setting

    ERIC Educational Resources Information Center

    Clauser, Brian E.; Baldwin, Peter; Margolis, Melissa J.; Mee, Janet; Winward, Marcia

    2017-01-01

    Validating performance standards is challenging and complex. Because of the difficulties associated with collecting evidence related to external criteria, validity arguments rely heavily on evidence related to internal criteria--especially evidence that expert judgments are internally consistent. Given its importance, it is somewhat surprising…

  8. Multiple Score Comparison: a network meta-analysis approach to comparison and external validation of prognostic scores.

    PubMed

    Haile, Sarah R; Guerra, Beniamino; Soriano, Joan B; Puhan, Milo A

    2017-12-21

    Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them. Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC) which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD) arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined. We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small. We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties of clinical scores. Our large-scale external validation indicates that the scores with the best discriminative properties to predict 3 year mortality in patients with COPD are ADO and eBODE.

  9. Development and validation of a scoring index to predict the presence of lesions in capsule endoscopy in patients with suspected Crohn's disease of the small bowel: a Spanish multicenter study.

    PubMed

    Egea-Valenzuela, Juan; González Suárez, Begoña; Sierra Bernal, Cristian; Juanmartiñena Fernández, José Francisco; Luján-Sanchís, Marisol; San Juan Acosta, Mileidis; Martínez Andrés, Blanca; Pons Beltrán, Vicente; Sastre Lozano, Violeta; Carretero Ribón, Cristina; de Vera Almenar, Félix; Sánchez Cuenca, Joaquín; Alberca de Las Parras, Fernando; Rodríguez de Miguel, Cristina; Valle Muñoz, Julio; Férnandez-Urién Sainz, Ignacio; Torres González, Carolina; Borque Barrera, Pilar; Pérez-Cuadrado Robles, Enrique; Alonso Lázaro, Noelia; Martínez García, Pilar; Prieto de Frías, César; Carballo Álvarez, Fernando

    2018-05-01

    Capsule endoscopy (CE) is the first-line investigation in cases of suspected Crohn's disease (CD) of the small bowel, but the factors associated with a higher diagnostic yield remain unclear. Our aim is to develop and validate a scoring index to assess the risk of the patients in this setting on the basis of biomarkers. Data on fecal calprotectin, C-reactive protein, and other biomarkers from a population of 124 patients with suspected CD of the small bowel studied by CE and included in a PhD study were used to build a scoring index. This was first used on this population (internal validation process) and after that on a different set of patients from a multicenter study (external validation process). An index was designed in which every biomarker is assigned a score. Three risk groups have been established (low, intermediate, and high). In the internal validation analysis (124 individuals), patients had a 10, 46.5, and 81% probability of showing inflammatory lesions in CE in the low-risk, intermediate-risk, and high-risk groups, respectively. In the external validation analysis, including 410 patients from 12 Spanish hospitals, this probability was 15.8, 49.7, and 80.6% for the low-risk, intermediate-risk, and high-risk groups, respectively. Results from the internal validation process show that the scoring index is coherent, and results from the external validation process confirm its reliability. This index can be a useful tool for selecting patients before CE studies in cases of suspected CD of the small bowel.

  10. The Perils of Ignoring Design Effects in Experimental Studies: Lessons from a Mammography Screening Trial

    PubMed Central

    Glenn, Beth A.; Bastani, Roshan; Maxwell, Annette E.

    2013-01-01

    Objective Threats to external validity including pretest sensitization and the interaction of selection and an intervention are frequently overlooked by researchers despite their potential to significantly influence study outcomes. The purpose of this investigation was to conduct secondary data analyses to assess the presence of external validity threats in the setting of a randomized trial designed to promote mammography use in a high risk sample of women. Design During the trial, recruitment and intervention implementation took place in three cohorts (with different ethnic composition), utilizing two different designs (pretest-posttest control group design; posttest only control group design). Results Results reveal that the intervention produced different outcomes across cohorts, dependent upon the research design used and the characteristics of the sample. Conclusion These results illustrate the importance of weighing the pros and cons of potential research designs before making a selection and attending more closely to issues of external validity. PMID:23289517

  11. The perils of ignoring design effects in experimental studies: lessons from a mammography screening trial.

    PubMed

    Glenn, Beth A; Bastani, Roshan; Maxwell, Annette E

    2013-01-01

    Threats to external validity, including pretest sensitisation and the interaction of selection and an intervention, are frequently overlooked by researchers despite their potential to significantly influence study outcomes. The purpose of this investigation was to conduct secondary data analyses to assess the presence of external validity threats in the setting of a randomised trial designed to promote mammography use in a high-risk sample of women. During the trial, recruitment and intervention, implementation took place in three cohorts (with different ethnic composition), utilising two different designs (pretest-posttest control group design and posttest only control group design). Results reveal that the intervention produced different outcomes across cohorts, dependent upon the research design used and the characteristics of the sample. These results illustrate the importance of weighing the pros and cons of potential research designs before making a selection and attending more closely to issues of external validity.

  12. External Validation of Bifactor Model of ADHD: Explaining Heterogeneity in Psychiatric Comorbidity, Cognitive Control, and Personality Trait Profiles Within DSM-IV ADHD

    PubMed Central

    Martel, Michelle M.; Roberts, Bethan; Gremillion, Monica; von Eye, Alexander; Nigg, Joel T.

    2011-01-01

    The current paper provides external validation of the bifactor model of ADHD by examining associations between ADHD latent factor/profile scores and external validation indices. 548 children (321 boys; 302 with ADHD), 6 to 18 years old, recruited from the community participated in a comprehensive diagnostic procedure. Mothers completed the Child Behavior Checklist, Early Adolescent Temperament Questionnaire, and California Q-Sort. Children completed the Stop and Trail-Making Task. Specific inattention was associated with depression/withdrawal, slower cognitive task performance, introversion, agreeableness, and high reactive control; specific hyperactivity-impulsivity was associated with rule-breaking/aggressive behavior, social problems, errors during set-shifting, extraversion, disagreeableness, and low reactive control. It is concluded that the bifactor model provides better explanation of heterogeneity within ADHD than DSM-IV ADHD symptom counts or subtypes. PMID:21735050

  13. Context matters: the experience of 14 research teams in systematically reporting contextual factors important for practice change.

    PubMed

    Tomoaia-Cotisel, Andrada; Scammon, Debra L; Waitzman, Norman J; Cronholm, Peter F; Halladay, Jacqueline R; Driscoll, David L; Solberg, Leif I; Hsu, Clarissa; Tai-Seale, Ming; Hiratsuka, Vanessa; Shih, Sarah C; Fetters, Michael D; Wise, Christopher G; Alexander, Jeffrey A; Hauser, Diane; McMullen, Carmit K; Scholle, Sarah Hudson; Tirodkar, Manasi A; Schmidt, Laura; Donahue, Katrina E; Parchman, Michael L; Stange, Kurt C

    2013-01-01

    We aimed to advance the internal and external validity of research by sharing our empirical experience and recommendations for systematically reporting contextual factors. Fourteen teams conducting research on primary care practice transformation retrospectively considered contextual factors important to interpreting their findings (internal validity) and transporting or reinventing their findings in other settings/situations (external validity). Each team provided a table or list of important contextual factors and interpretive text included as appendices to the articles in this supplement. Team members identified the most important contextual factors for their studies. We grouped the findings thematically and developed recommendations for reporting context. The most important contextual factors sorted into 5 domains: (1) the practice setting, (2) the larger organization, (3) the external environment, (4) implementation pathway, and (5) the motivation for implementation. To understand context, investigators recommend (1) engaging diverse perspectives and data sources, (2) considering multiple levels, (3) evaluating history and evolution over time, (4) looking at formal and informal systems and culture, and (5) assessing the (often nonlinear) interactions between contextual factors and both the process and outcome of studies. We include a template with tabular and interpretive elements to help study teams engage research participants in reporting relevant context. These findings demonstrate the feasibility and potential utility of identifying and reporting contextual factors. Involving diverse stakeholders in assessing context at multiple stages of the research process, examining their association with outcomes, and consistently reporting critical contextual factors are important challenges for a field interested in improving the internal and external validity and impact of health care research.

  14. External validity of post-stroke interventional gait rehabilitation studies.

    PubMed

    Kafri, Michal; Dickstein, Ruth

    2017-01-01

    Gait rehabilitation is a major component of stroke rehabilitation, and is supported by extensive research. The objective of this review was to examine the external validity of intervention studies aimed at improving gait in individuals post-stroke. To that end, two aspects of these studies were assessed: subjects' exclusion criteria and the ecological validity of the intervention, as manifested by the intervention's technological complexity and delivery setting. Additionally, we examined whether the target population as inferred from the titles/abstracts is broader than the population actually represented by the reported samples. We systematically researched PubMed for intervention studies to improve gait post-stroke, working backwards from the beginning of 2014. Exclusion criteria, the technological complexity of the intervention (defined as either elaborate or simple), setting, and description of the target population in the titles/abstracts were recorded. Fifty-two studies were reviewed. The samples were exclusive, with recurrent stroke, co-morbidities, cognitive status, walking level, and residency being major reasons for exclusion. In one half of the studies, the intervention was elaborate. Descriptions of participants in the title/abstract in almost one half of the studies included only the diagnosis (stroke or comparable terms) and its stage (acute, subacute, and chronic). The external validity of a substantial number of intervention studies about rehabilitation of gait post-stroke appears to be limited by exclusivity of the samples as well as by deficiencies in ecological validity of the interventions. These limitations are not accurately reflected in the titles or abstracts of the studies.

  15. Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do.

    PubMed

    Zhao, Linlin; Wang, Wenyi; Sedykh, Alexander; Zhu, Hao

    2017-06-30

    Numerous chemical data sets have become available for quantitative structure-activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting.

  16. Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do

    PubMed Central

    2017-01-01

    Numerous chemical data sets have become available for quantitative structure–activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting. PMID:28691113

  17. 42 CFR 438.358 - Activities related to external quality review.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...) Mandatory activities. For each MCO and PIHP, the EQR must use information from the following activities: (1) Validation of performance improvement projects required by the State to comply with requirements set forth in § 438.240(b)(1) and that were underway during the preceding 12 months. (2) Validation of MCO or PIHP...

  18. The relationship between external and internal validity of randomized controlled trials: A sample of hypertension trials from China.

    PubMed

    Zhang, Xin; Wu, Yuxia; Ren, Pengwei; Liu, Xueting; Kang, Deying

    2015-10-30

    To explore the relationship between the external validity and the internal validity of hypertension RCTs conducted in China. Comprehensive literature searches were performed in Medline, Embase, Cochrane Central Register of Controlled Trials (CCTR), CBMdisc (Chinese biomedical literature database), CNKI (China National Knowledge Infrastructure/China Academic Journals Full-text Database) and VIP (Chinese scientific journals database) as well as advanced search strategies were used to locate hypertension RCTs. The risk of bias in RCTs was assessed by a modified scale, Jadad scale respectively, and then studies with 3 or more grading scores were included for the purpose of evaluating of external validity. A data extract form including 4 domains and 25 items was used to explore relationship of the external validity and the internal validity. Statistic analyses were performed by using SPSS software, version 21.0 (SPSS, Chicago, IL). 226 hypertension RCTs were included for final analysis. RCTs conducted in university affiliated hospitals (P < 0.001) or secondary/tertiary hospitals (P < 0.001) were scored at higher internal validity. Multi-center studies (median = 4.0, IQR = 2.0) were scored higher internal validity score than single-center studies (median = 3.0, IQR = 1.0) (P < 0.001). Funding-supported trials had better methodological quality (P < 0.001). In addition, the reporting of inclusion criteria also leads to better internal validity (P = 0.004). Multivariate regression indicated sample size, industry-funding, quality of life (QOL) taken as measure and the university affiliated hospital as trial setting had statistical significance (P < 0.001, P < 0.001, P = 0.001, P = 0.006 respectively). Several components relate to the external validity of RCTs do associate with the internal validity, that do not stand in an easy relationship to each other. Regarding the poor reporting, other possible links between two variables need to trace in the future methodological researches.

  19. Updating Risk Prediction Tools: A Case Study in Prostate Cancer

    PubMed Central

    Ankerst, Donna P.; Koniarski, Tim; Liang, Yuanyuan; Leach, Robin J.; Feng, Ziding; Sanda, Martin G.; Partin, Alan W.; Chan, Daniel W; Kagan, Jacob; Sokoll, Lori; Wei, John T; Thompson, Ian M.

    2013-01-01

    Online risk prediction tools for common cancers are now easily accessible and widely used by patients and doctors for informed decision-making concerning screening and diagnosis. A practical problem is as cancer research moves forward and new biomarkers and risk factors are discovered, there is a need to update the risk algorithms to include them. Typically the new markers and risk factors cannot be retrospectively measured on the same study participants used to develop the original prediction tool, necessitating the merging of a separate study of different participants, which may be much smaller in sample size and of a different design. Validation of the updated tool on a third independent data set is warranted before the updated tool can go online. This article reports on the application of Bayes rule for updating risk prediction tools to include a set of biomarkers measured in an external study to the original study used to develop the risk prediction tool. The procedure is illustrated in the context of updating the online Prostate Cancer Prevention Trial Risk Calculator to incorporate the new markers %freePSA and [−2]proPSA measured on an external case control study performed in Texas, U.S.. Recent state-of-the art methods in validation of risk prediction tools and evaluation of the improvement of updated to original tools are implemented using an external validation set provided by the U.S. Early Detection Research Network. PMID:22095849

  20. Updating risk prediction tools: a case study in prostate cancer.

    PubMed

    Ankerst, Donna P; Koniarski, Tim; Liang, Yuanyuan; Leach, Robin J; Feng, Ziding; Sanda, Martin G; Partin, Alan W; Chan, Daniel W; Kagan, Jacob; Sokoll, Lori; Wei, John T; Thompson, Ian M

    2012-01-01

    Online risk prediction tools for common cancers are now easily accessible and widely used by patients and doctors for informed decision-making concerning screening and diagnosis. A practical problem is as cancer research moves forward and new biomarkers and risk factors are discovered, there is a need to update the risk algorithms to include them. Typically, the new markers and risk factors cannot be retrospectively measured on the same study participants used to develop the original prediction tool, necessitating the merging of a separate study of different participants, which may be much smaller in sample size and of a different design. Validation of the updated tool on a third independent data set is warranted before the updated tool can go online. This article reports on the application of Bayes rule for updating risk prediction tools to include a set of biomarkers measured in an external study to the original study used to develop the risk prediction tool. The procedure is illustrated in the context of updating the online Prostate Cancer Prevention Trial Risk Calculator to incorporate the new markers %freePSA and [-2]proPSA measured on an external case-control study performed in Texas, U.S.. Recent state-of-the art methods in validation of risk prediction tools and evaluation of the improvement of updated to original tools are implemented using an external validation set provided by the U.S. Early Detection Research Network. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. In silico prediction of ROCK II inhibitors by different classification approaches.

    PubMed

    Cai, Chuipu; Wu, Qihui; Luo, Yunxia; Ma, Huili; Shen, Jiangang; Zhang, Yongbin; Yang, Lei; Chen, Yunbo; Wen, Zehuai; Wang, Qi

    2017-11-01

    ROCK II is an important pharmacological target linked to central nervous system disorders such as Alzheimer's disease. The purpose of this research is to generate ROCK II inhibitor prediction models by machine learning approaches. Firstly, four sets of descriptors were calculated with MOE 2010 and PaDEL-Descriptor, and optimized by F-score and linear forward selection methods. In addition, four classification algorithms were used to initially build 16 classifiers with k-nearest neighbors [Formula: see text], naïve Bayes, Random forest, and support vector machine. Furthermore, three sets of structural fingerprint descriptors were introduced to enhance the predictive capacity of classifiers, which were assessed with fivefold cross-validation, test set validation and external test set validation. The best two models, MFK + MACCS and MLR + SubFP, have both MCC values of 0.925 for external test set. After that, a privileged substructure analysis was performed to reveal common chemical features of ROCK II inhibitors. Finally, binding modes were analyzed to identify relationships between molecular descriptors and activity, while main interactions were revealed by comparing the docking interaction of the most potent and the weakest ROCK II inhibitors. To the best of our knowledge, this is the first report on ROCK II inhibitors utilizing machine learning approaches that provides a new method for discovering novel ROCK II inhibitors.

  2. Development of novel in silico model for developmental toxicity assessment by using naïve Bayes classifier method.

    PubMed

    Zhang, Hui; Ren, Ji-Xia; Kang, Yan-Li; Bo, Peng; Liang, Jun-Yu; Ding, Lan; Kong, Wei-Bao; Zhang, Ji

    2017-08-01

    Toxicological testing associated with developmental toxicity endpoints are very expensive, time consuming and labor intensive. Thus, developing alternative approaches for developmental toxicity testing is an important and urgent task in the drug development filed. In this investigation, the naïve Bayes classifier was applied to develop a novel prediction model for developmental toxicity. The established prediction model was evaluated by the internal 5-fold cross validation and external test set. The overall prediction results for the internal 5-fold cross validation of the training set and external test set were 96.6% and 82.8%, respectively. In addition, four simple descriptors and some representative substructures of developmental toxicants were identified. Thus, we hope the established in silico prediction model could be used as alternative method for toxicological assessment. And these obtained molecular information could afford a deeper understanding on the developmental toxicants, and provide guidance for medicinal chemists working in drug discovery and lead optimization. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Decoy receptor 1 (DCR1) promoter hypermethylation and response to irinotecan in metastatic colorectal cancer

    PubMed Central

    Bosch, Linda J.W.; Coupé, Veerle M.H.; Mongera, Sandra; Haan, Josien C.; Richman, Susan D.; Koopman, Miriam; Tol, Jolien; de Meyer, Tim; Louwagie, Joost; Dehaspe, Luc; van Grieken, Nicole C.T.; Ylstra, Bauke; Verheul, Henk M.W.; van Engeland, Manon; Nagtegaal, Iris D.; Herman, James G.; Quirke, Philip; Seymour, Matthew T.; Punt, Cornelis J.A.; van Criekinge, Wim; Carvalho, Beatriz; Meijer, Gerrit A.

    2017-01-01

    Diversity in colorectal cancer biology is associated with variable responses to standard chemotherapy. We aimed to identify and validate DNA hypermethylated genes as predictive biomarkers for irinotecan treatment of metastatic CRC patients. Candidate genes were selected from 389 genes involved in DNA Damage Repair by correlation analyses between gene methylation status and drug response in 32 cell lines. A large series of samples (n=818) from two phase III clinical trials was used to evaluate these candidate genes by correlating methylation status to progression-free survival after treatment with first-line single-agent fluorouracil (Capecitabine or 5-fluorouracil) or combination chemotherapy (Capecitabine or 5-fluorouracil plus irinotecan (CAPIRI/FOLFIRI)). In the discovery (n=185) and initial validation set (n=166), patients with methylated Decoy Receptor 1 (DCR1) did not benefit from CAPIRI over Capecitabine treatment (discovery set: HR=1.2 (95%CI 0.7-1.9, p=0.6), validation set: HR=0.9 (95%CI 0.6-1.4, p=0.5)), whereas patients with unmethylated DCR1 did (discovery set: HR=0.4 (95%CI 0.3-0.6, p=0.00001), validation set: HR=0.5 (95%CI 0.3-0.7, p=0.0008)). These results could not be replicated in the external data set (n=467), where a similar effect size was found in patients with methylated and unmethylated DCR1 for FOLFIRI over 5FU treatment (methylated DCR1: HR=0.7 (95%CI 0.5-0.9, p=0.01), unmethylated DCR1: HR=0.8 (95%CI 0.6-1.2, p=0.4)). In conclusion, DCR1 promoter hypermethylation status is a potential predictive biomarker for response to treatment with irinotecan, when combined with capecitabine. This finding could not be replicated in an external validation set, in which irinotecan was combined with 5FU. These results underline the challenge and importance of extensive clinical evaluation of candidate biomarkers in multiple trials. PMID:28968978

  4. Decoy receptor 1 (DCR1) promoter hypermethylation and response to irinotecan in metastatic colorectal cancer.

    PubMed

    Bosch, Linda J W; Trooskens, Geert; Snaebjornsson, Petur; Coupé, Veerle M H; Mongera, Sandra; Haan, Josien C; Richman, Susan D; Koopman, Miriam; Tol, Jolien; de Meyer, Tim; Louwagie, Joost; Dehaspe, Luc; van Grieken, Nicole C T; Ylstra, Bauke; Verheul, Henk M W; van Engeland, Manon; Nagtegaal, Iris D; Herman, James G; Quirke, Philip; Seymour, Matthew T; Punt, Cornelis J A; van Criekinge, Wim; Carvalho, Beatriz; Meijer, Gerrit A

    2017-09-08

    Diversity in colorectal cancer biology is associated with variable responses to standard chemotherapy. We aimed to identify and validate DNA hypermethylated genes as predictive biomarkers for irinotecan treatment of metastatic CRC patients. Candidate genes were selected from 389 genes involved in DNA Damage Repair by correlation analyses between gene methylation status and drug response in 32 cell lines. A large series of samples (n=818) from two phase III clinical trials was used to evaluate these candidate genes by correlating methylation status to progression-free survival after treatment with first-line single-agent fluorouracil (Capecitabine or 5-fluorouracil) or combination chemotherapy (Capecitabine or 5-fluorouracil plus irinotecan (CAPIRI/FOLFIRI)). In the discovery (n=185) and initial validation set (n=166), patients with methylated Decoy Receptor 1 ( DCR1) did not benefit from CAPIRI over Capecitabine treatment (discovery set: HR=1.2 (95%CI 0.7-1.9, p =0.6), validation set: HR=0.9 (95%CI 0.6-1.4, p =0.5)), whereas patients with unmethylated DCR1 did (discovery set: HR=0.4 (95%CI 0.3-0.6, p =0.00001), validation set: HR=0.5 (95%CI 0.3-0.7, p =0.0008)). These results could not be replicated in the external data set (n=467), where a similar effect size was found in patients with methylated and unmethylated DCR1 for FOLFIRI over 5FU treatment (methylated DCR1 : HR=0.7 (95%CI 0.5-0.9, p =0.01), unmethylated DCR1 : HR=0.8 (95%CI 0.6-1.2, p =0.4)). In conclusion, DCR1 promoter hypermethylation status is a potential predictive biomarker for response to treatment with irinotecan, when combined with capecitabine. This finding could not be replicated in an external validation set, in which irinotecan was combined with 5FU. These results underline the challenge and importance of extensive clinical evaluation of candidate biomarkers in multiple trials.

  5. Identifying and Evaluating External Validity Evidence for Passing Scores

    ERIC Educational Resources Information Center

    Davis-Becker, Susan L.; Buckendahl, Chad W.

    2013-01-01

    A critical component of the standard setting process is collecting evidence to evaluate the recommended cut scores and their use for making decisions and classifying students based on test performance. Kane (1994, 2001) proposed a framework by which practitioners can identify and evaluate evidence of the results of the standard setting from (1)…

  6. The Relationship of Task Characteristics to Attitudes, Absenteeism, Stress and Performance Among College Students.

    ERIC Educational Resources Information Center

    Rousseau, Denise M.

    In organizational settings, research has shown the relationship of task characteristics to attitudes and motivation. This study examines the external validity of the task characteristic-outcome relationship in an educational setting. Subjects were 206 undergraduate psychology students. They were given an inventory of seven task characteristics…

  7. Context Matters: The Experience of 14 Research Teams in Systematically Reporting Contextual Factors Important for Practice Change

    PubMed Central

    Tomoaia-Cotisel, Andrada; Scammon, Debra L.; Waitzman, Norman J.; Cronholm, Peter F.; Halladay, Jacqueline R.; Driscoll, David L.; Solberg, Leif I.; Hsu, Clarissa; Tai-Seale, Ming; Hiratsuka, Vanessa; Shih, Sarah C.; Fetters, Michael D.; Wise, Christopher G.; Alexander, Jeffrey A.; Hauser, Diane; McMullen, Carmit K.; Scholle, Sarah Hudson; Tirodkar, Manasi A.; Schmidt, Laura; Donahue, Katrina E.; Parchman, Michael L.; Stange, Kurt C.

    2013-01-01

    PURPOSE We aimed to advance the internal and external validity of research by sharing our empirical experience and recommendations for systematically reporting contextual factors. METHODS Fourteen teams conducting research on primary care practice transformation retrospectively considered contextual factors important to interpreting their findings (internal validity) and transporting or reinventing their findings in other settings/situations (external validity). Each team provided a table or list of important contextual factors and interpretive text included as appendices to the articles in this supplement. Team members identified the most important contextual factors for their studies. We grouped the findings thematically and developed recommendations for reporting context. RESULTS The most important contextual factors sorted into 5 domains: (1) the practice setting, (2) the larger organization, (3) the external environment, (4) implementation pathway, and (5) the motivation for implementation. To understand context, investigators recommend (1) engaging diverse perspectives and data sources, (2) considering multiple levels, (3) evaluating history and evolution over time, (4) looking at formal and informal systems and culture, and (5) assessing the (often nonlinear) interactions between contextual factors and both the process and outcome of studies. We include a template with tabular and interpretive elements to help study teams engage research participants in reporting relevant context. CONCLUSIONS These findings demonstrate the feasibility and potential utility of identifying and reporting contextual factors. Involving diverse stakeholders in assessing context at multiple stages of the research process, examining their association with outcomes, and consistently reporting critical contextual factors are important challenges for a field interested in improving the internal and external validity and impact of health care research. PMID:23690380

  8. Development and Validation of Decision Forest Model for Estrogen Receptor Binding Prediction of Chemicals Using Large Data Sets.

    PubMed

    Ng, Hui Wen; Doughty, Stephen W; Luo, Heng; Ye, Hao; Ge, Weigong; Tong, Weida; Hong, Huixiao

    2015-12-21

    Some chemicals in the environment possess the potential to interact with the endocrine system in the human body. Multiple receptors are involved in the endocrine system; estrogen receptor α (ERα) plays very important roles in endocrine activity and is the most studied receptor. Understanding and predicting estrogenic activity of chemicals facilitates the evaluation of their endocrine activity. Hence, we have developed a decision forest classification model to predict chemical binding to ERα using a large training data set of 3308 chemicals obtained from the U.S. Food and Drug Administration's Estrogenic Activity Database. We tested the model using cross validations and external data sets of 1641 chemicals obtained from the U.S. Environmental Protection Agency's ToxCast project. The model showed good performance in both internal (92% accuracy) and external validations (∼ 70-89% relative balanced accuracies), where the latter involved the validations of the model across different ER pathway-related assays in ToxCast. The important features that contribute to the prediction ability of the model were identified through informative descriptor analysis and were related to current knowledge of ER binding. Prediction confidence analysis revealed that the model had both high prediction confidence and accuracy for most predicted chemicals. The results demonstrated that the model constructed based on the large training data set is more accurate and robust for predicting ER binding of chemicals than the published models that have been developed using much smaller data sets. The model could be useful for the evaluation of ERα-mediated endocrine activity potential of environmental chemicals.

  9. Modeling Liver-Related Adverse Effects of Drugs Using kNN QSAR Method

    PubMed Central

    Rodgers, Amie D.; Zhu, Hao; Fourches, Dennis; Rusyn, Ivan; Tropsha, Alexander

    2010-01-01

    Adverse effects of drugs (AEDs) continue to be a major cause of drug withdrawals both in development and post-marketing. While liver-related AEDs are a major concern for drug safety, there are few in silico models for predicting human liver toxicity for drug candidates. We have applied the Quantitative Structure Activity Relationship (QSAR) approach to model liver AEDs. In this study, we aimed to construct a QSAR model capable of binary classification (active vs. inactive) of drugs for liver AEDs based on chemical structure. To build QSAR models, we have employed an FDA spontaneous reporting database of human liver AEDs (elevations in activity of serum liver enzymes), which contains data on approximately 500 approved drugs. Approximately 200 compounds with wide clinical data coverage, structural similarity and balanced (40/60) active/inactive ratio were selected for modeling and divided into multiple training/test and external validation sets. QSAR models were developed using the k nearest neighbor method and validated using external datasets. Models with high sensitivity (>73%) and specificity (>94%) for prediction of liver AEDs in external validation sets were developed. To test applicability of the models, three chemical databases (World Drug Index, Prestwick Chemical Library, and Biowisdom Liver Intelligence Module) were screened in silico and the validity of predictions was determined, where possible, by comparing model-based classification with assertions in publicly available literature. Validated QSAR models of liver AEDs based on the data from the FDA spontaneous reporting system can be employed as sensitive and specific predictors of AEDs in pre-clinical screening of drug candidates for potential hepatotoxicity in humans. PMID:20192250

  10. A New Local Bipolar Autoassociative Memory Based on External Inputs of Discrete Recurrent Neural Networks With Time Delay.

    PubMed

    Zhou, Caigen; Zeng, Xiaoqin; Luo, Chaomin; Zhang, Huaguang

    In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.

  11. External Validation of the Acoustic Voice Quality Index Version 03.01 With Extended Representativity.

    PubMed

    Barsties, Ben; Maryn, Youri

    2016-07-01

    The Acoustic Voice Quality Index (AVQI) is an objective method to quantify the severity of overall voice quality in concatenated continuous speech and sustained phonation segments. Recently, AVQI was successfully modified to be more representative and ecologically valid because the internal consistency of AVQI was balanced out through equal proportion of the 2 speech types. The present investigation aims to explore its external validation in a large data set. An expert panel of 12 speech-language therapists rated the voice quality of 1058 concatenated voice samples varying from normophonia to severe dysphonia. The Spearman rank-order correlation coefficients (r) were used to measure concurrent validity. The AVQI's diagnostic accuracy was evaluated with several estimates of its receiver operating characteristics (ROC). Finally, 8 of the 12 experts were chosen because of reliability criteria. A strong correlation was identified between AVQI and auditoryperceptual rating (r = 0.815, P = .000). It indicated that 66.4% of the auditory-perceptual rating's variation was explained by AVQI. Additionally, the ROC results showed again the best diagnostic outcome at a threshold of AVQI = 2.43. This study highlights external validation and diagnostic precision of the AVQI version 03.01 as a robust and ecologically valid measurement to objectify voice quality. © The Author(s) 2016.

  12. An externally validated model for predicting long-term survival after exercise treadmill testing in patients with suspected coronary artery disease and a normal electrocardiogram.

    PubMed

    Lauer, Michael S; Pothier, Claire E; Magid, David J; Smith, S Scott; Kattan, Michael W

    2007-12-18

    The exercise treadmill test is recommended for risk stratification among patients with intermediate to high pretest probability of coronary artery disease. Posttest risk stratification is based on the Duke treadmill score, which includes only functional capacity and measures of ischemia. To develop and externally validate a post-treadmill test, multivariable mortality prediction rule for adults with suspected coronary artery disease and normal electrocardiograms. Prospective cohort study conducted from September 1990 to May 2004. Exercise treadmill laboratories in a major medical center (derivation set) and a separate HMO (validation set). 33,268 patients in the derivation set and 5821 in the validation set. All patients had normal electrocardiograms and were referred for evaluation of suspected coronary artery disease. The derivation set patients were followed for a median of 6.2 years. A nomogram-illustrated model was derived on the basis of variables easily obtained in the stress laboratory, including age; sex; history of smoking, hypertension, diabetes, or typical angina; and exercise findings of functional capacity, ST-segment changes, symptoms, heart rate recovery, and frequent ventricular ectopy in recovery. The derivation data set included 1619 deaths. Although both the Duke treadmill score and our nomogram-illustrated model were significantly associated with death (P < 0.001), the nomogram was better at discrimination (concordance index for right-censored data, 0.83 vs. 0.73) and calibration. We reclassified many patients with intermediate- to high-risk Duke treadmill scores as low risk on the basis of the nomogram. The model also predicted 3-year mortality rates well in the validation set: Based on an optimal cut-point for a negative predictive value of 0.97, derivation and validation rates were, respectively, 1.7% and 2.5% below the cut-point and 25% and 29% above the cut-point. Blood test-based measures or left ventricular ejection fraction were not included. The nomogram can be applied only to patients with a normal electrocardiogram. Clinical utility remains to be tested. A simple nomogram based on easily obtained pretest and exercise test variables predicted all-cause mortality in adults with suspected coronary artery disease and normal electrocardiograms.

  13. A Methodological Approach to Small Area Estimation for the Behavioral Risk Factor Surveillance System

    PubMed Central

    Xu, Fang; Wallace, Robyn C.; Garvin, William; Greenlund, Kurt J.; Bartoli, William; Ford, Derek; Eke, Paul; Town, G. Machell

    2016-01-01

    Public health researchers have used a class of statistical methods to calculate prevalence estimates for small geographic areas with few direct observations. Many researchers have used Behavioral Risk Factor Surveillance System (BRFSS) data as a basis for their models. The aims of this study were to 1) describe a new BRFSS small area estimation (SAE) method and 2) investigate the internal and external validity of the BRFSS SAEs it produced. The BRFSS SAE method uses 4 data sets (the BRFSS, the American Community Survey Public Use Microdata Sample, Nielsen Claritas population totals, and the Missouri Census Geographic Equivalency File) to build a single weighted data set. Our findings indicate that internal and external validity tests were successful across many estimates. The BRFSS SAE method is one of several methods that can be used to produce reliable prevalence estimates in small geographic areas. PMID:27418213

  14. Development and validation of the ExPRESS instrument for primary health care providers' evaluation of external supervision.

    PubMed

    Schriver, Michael; Cubaka, Vincent Kalumire; Vedsted, Peter; Besigye, Innocent; Kallestrup, Per

    2018-01-01

    External supervision of primary health care facilities to monitor and improve services is common in low-income countries. Currently there are no tools to measure the quality of support in external supervision in these countries. To develop a provider-reported instrument to assess the support delivered through external supervision in Rwanda and other countries. "External supervision: Provider Evaluation of Supervisor Support" (ExPRESS) was developed in 18 steps, primarily in Rwanda. Content validity was optimised using systematic search for related instruments, interviews, translations, and relevance assessments by international supervision experts as well as local experts in Nigeria, Kenya, Uganda and Rwanda. Construct validity and reliability were examined in two separate field tests, the first using exploratory factor analysis and a test-retest design, the second for confirmatory factor analysis. We included 16 items in section A ('The most recent experience with an external supervisor'), and 13 items in section B ('The overall experience with external supervisors'). Item-content validity index was acceptable. In field test I, test-retest had acceptable kappa values and exploratory factor analysis suggested relevant factors in sections A and B used for model hypotheses. In field test II, models were tested by confirmatory factor analysis fitting a 4-factor model for section A, and a 3-factor model for section B. ExPRESS is a promising tool for evaluation of the quality of support of primary health care providers in external supervision of primary health care facilities in resource-constrained settings. ExPRESS may be used as specific feedback to external supervisors to help identify and address gaps in the supervision they provide. Further studies should determine optimal interpretation of scores and the number of respondents needed per supervisor to obtain precise results, as well as test the functionality of section B.

  15. New public QSAR model for carcinogenicity

    PubMed Central

    2010-01-01

    Background One of the main goals of the new chemical regulation REACH (Registration, Evaluation and Authorization of Chemicals) is to fulfill the gaps in data concerned with properties of chemicals affecting the human health. (Q)SAR models are accepted as a suitable source of information. The EU funded CAESAR project aimed to develop models for prediction of 5 endpoints for regulatory purposes. Carcinogenicity is one of the endpoints under consideration. Results Models for prediction of carcinogenic potency according to specific requirements of Chemical regulation were developed. The dataset of 805 non-congeneric chemicals extracted from Carcinogenic Potency Database (CPDBAS) was used. Counter Propagation Artificial Neural Network (CP ANN) algorithm was implemented. In the article two alternative models for prediction carcinogenicity are described. The first model employed eight MDL descriptors (model A) and the second one twelve Dragon descriptors (model B). CAESAR's models have been assessed according to the OECD principles for the validation of QSAR. For the model validity we used a wide series of statistical checks. Models A and B yielded accuracy of training set (644 compounds) equal to 91% and 89% correspondingly; the accuracy of the test set (161 compounds) was 73% and 69%, while the specificity was 69% and 61%, respectively. Sensitivity in both cases was equal to 75%. The accuracy of the leave 20% out cross validation for the training set of models A and B was equal to 66% and 62% respectively. To verify if the models perform correctly on new compounds the external validation was carried out. The external test set was composed of 738 compounds. We obtained accuracy of external validation equal to 61.4% and 60.0%, sensitivity 64.0% and 61.8% and specificity equal to 58.9% and 58.4% respectively for models A and B. Conclusion Carcinogenicity is a particularly important endpoint and it is expected that QSAR models will not replace the human experts opinions and conventional methods. However, we believe that combination of several methods will provide useful support to the overall evaluation of carcinogenicity. In present paper models for classification of carcinogenic compounds using MDL and Dragon descriptors were developed. Models could be used to set priorities among chemicals for further testing. The models at the CAESAR site were implemented in java and are publicly accessible. PMID:20678182

  16. Lymph nodes ratio based nomogram predicts survival of resectable gastric cancer regardless of the number of examined lymph nodes.

    PubMed

    Chen, Shangxiang; Rao, Huamin; Liu, Jianjun; Geng, Qirong; Guo, Jing; Kong, Pengfei; Li, Shun; Liu, Xuechao; Sun, Xiaowei; Zhan, Youqing; Xu, Dazhi

    2017-07-11

    To develop a nomogram to predict the prognosis of gastric cancer patients on the basis of metastatic lymph nodes ratio (mLNR), especially in the patients with total number of examined lymph nodes (TLN) less than 15. The nomogram was constructed based on a retrospective database that included 2,205 patients underwent curative resection in Cancer Center, Sun Yat-sen University (SYSUCC). Resectable gastric cancer (RGC) patients underwent curative resection before December 31, 2008 were assigned as the training set (n=1,470) and those between January 1, 2009 and December 31, 2012 were selected as the internal validation set (n=735). Additional external validations were also performed separately by an independent data set (n=602) from Jiangxi Provincial Cancer Hospital (JXCH) in Jiangxi, China and a data set (n=3,317) from the Surveillance, Epidemiology, and End Results (SEER) database. The Independent risk factors were identified by Multivariate Cox Regression. In the SYSUCC set, TNM (Tumor-node-metastasis) and TRM-based (Tumor-Positive Nodes Ratio-Metastasis) nomograms were constructed respectively. The TNM-based nomogram showed better discrimination than the AJCC-TNM staging system (C-index: 0.73 versus 0.69, p<0.01). When the mLNR was included in the nomogram, the C-index increased to 0.76. Furthermore, the C-index in the TRM-based nomogram was similar between TLN ≥16 (C-index: 0.77) and TLN ≤15 (C-index: 0.75). The discrimination was further ascertained by internal and external validations. We developed and validated a novel TRM-based nomogram that provided more accurate prediction of survival for gastric cancer patients who underwent curative resection, regardless of the number of examined lymph nodes.

  17. Consensus QSAR model for identifying novel H5N1 inhibitors.

    PubMed

    Sharma, Nitin; Yap, Chun Wei

    2012-08-01

    Due to the importance of neuraminidase in the pathogenesis of influenza virus infection, it has been regarded as the most important drug target for the treatment of influenza. Resistance to currently available drugs and new findings related to structure of the protein requires novel neuraminidase 1 (N1) inhibitors. In this study, a consensus QSAR model with defined applicability domain (AD) was developed using published N1 inhibitors. The consensus model was validated using an external validation set. The model achieved high sensitivity, specificity, and overall accuracy along with low false positive rate (FPR) and false discovery rate (FDR). The performance of model on the external validation set and training set were comparable, thus it was unlikely to be overfitted. The low FPR and low FDR will increase its accuracy in screening large chemical libraries. Screening of ZINC library resulted in 64,772 compounds as probable N1 inhibitors, while 173,674 compounds were defined to be outside the AD of the consensus model. The advantage of the current model is that it was developed using a large and diverse dataset and has a defined AD which prevents its use on compounds that it is not capable of predicting. The consensus model developed in this study is made available via the free software, PaDEL-DDPredictor.

  18. Rapid detection of frozen-then-thawed minced beef using multispectral imaging and Fourier transform infrared spectroscopy.

    PubMed

    Ropodi, Athina I; Panagou, Efstathios Z; Nychas, George-John E

    2018-01-01

    In recent years, fraud detection has become a major priority for food authorities, as fraudulent practices can have various economic and safety consequences. This work explores ways of identifying frozen-then-thawed minced beef labeled as fresh in a rapid, large-scale and cost-effective way. For this reason, freshly-ground beef was purchased from seven separate shops at different times, divided in fifteen portions and placed in Petri dishes. Multi-spectral images and FTIR spectra of the first five were immediately acquired while the remaining were frozen (-20°C) and stored for 7 and 32days (5 samples for each time interval). Samples were thawed and subsequently subjected to similar data acquisition. In total, 105 multispectral images and FTIR spectra were collected which were further analyzed using partial least-squares discriminant analysis and support vector machines. Two meat batches (30 samples) were reserved for independent validation and the remaining five batches were divided in training and test set (75 samples). Results showed 100% overall correct classification for test and external validation MSI data, while FTIR data yielded 93.3 and 96.7% overall correct classification for FTIR test set and external validation set respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Development and external validation of a prediction rule for an unfavorable course of late-life depression: A multicenter cohort study.

    PubMed

    Maarsingh, O R; Heymans, M W; Verhaak, P F; Penninx, B W J H; Comijs, H C

    2018-08-01

    Given the poor prognosis of late-life depression, it is crucial to identify those at risk. Our objective was to construct and validate a prediction rule for an unfavourable course of late-life depression. For development and internal validation of the model, we used The Netherlands Study of Depression in Older Persons (NESDO) data. We included participants with a major depressive disorder (MDD) at baseline (n = 270; 60-90 years), assessed with the Composite International Diagnostic Interview (CIDI). For external validation of the model, we used The Netherlands Study of Depression and Anxiety (NESDA) data (n = 197; 50-66 years). The outcome was MDD after 2 years of follow-up, assessed with the CIDI. Candidate predictors concerned sociodemographics, psychopathology, physical symptoms, medication, psychological determinants, and healthcare setting. Model performance was assessed by calculating calibration and discrimination. 111 subjects (41.1%) had MDD after 2 years of follow-up. Independent predictors of MDD after 2 years were (older) age, (early) onset of depression, severity of depression, anxiety symptoms, comorbid anxiety disorder, fatigue, and loneliness. The final model showed good calibration and reasonable discrimination (AUC of 0.75; 0.70 after external validation). The strongest individual predictor was severity of depression (AUC of 0.69; 0.68 after external validation). The model was developed and validated in The Netherlands, which could affect the cross-country generalizability. Based on rather simple clinical indicators, it is possible to predict the 2-year course of MDD. The prediction rule can be used for monitoring MDD patients and identifying those at risk of an unfavourable outcome. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. Evaluating the predictive accuracy and the clinical benefit of a nomogram aimed to predict survival in node-positive prostate cancer patients: External validation on a multi-institutional database.

    PubMed

    Bianchi, Lorenzo; Schiavina, Riccardo; Borghesi, Marco; Bianchi, Federico Mineo; Briganti, Alberto; Carini, Marco; Terrone, Carlo; Mottrie, Alex; Gacci, Mauro; Gontero, Paolo; Imbimbo, Ciro; Marchioro, Giansilvio; Milanese, Giulio; Mirone, Vincenzo; Montorsi, Francesco; Morgia, Giuseppe; Novara, Giacomo; Porreca, Angelo; Volpe, Alessandro; Brunocilla, Eugenio

    2018-04-06

    To assess the predictive accuracy and the clinical value of a recent nomogram predicting cancer-specific mortality-free survival after surgery in pN1 prostate cancer patients through an external validation. We evaluated 518 prostate cancer patients treated with radical prostatectomy and pelvic lymph node dissection with evidence of nodal metastases at final pathology, at 10 tertiary centers. External validation was carried out using regression coefficients of the previously published nomogram. The performance characteristics of the model were assessed by quantifying predictive accuracy, according to the area under the curve in the receiver operating characteristic curve and model calibration. Furthermore, we systematically analyzed the specificity, sensitivity, positive predictive value and negative predictive value for each nomogram-derived probability cut-off. Finally, we implemented decision curve analysis, in order to quantify the nomogram's clinical value in routine practice. External validation showed inferior predictive accuracy as referred to in the internal validation (65.8% vs 83.3%, respectively). The discrimination (area under the curve) of the multivariable model was 66.7% (95% CI 60.1-73.0%) by testing with receiver operating characteristic curve analysis. The calibration plot showed an overestimation throughout the range of predicted cancer-specific mortality-free survival rates probabilities. However, in decision curve analysis, the nomogram's use showed a net benefit when compared with the scenarios of treating all patients or none. In an external setting, the nomogram showed inferior predictive accuracy and suboptimal calibration characteristics as compared to that reported in the original population. However, decision curve analysis showed a clinical net benefit, suggesting a clinical implication to correctly manage pN1 prostate cancer patients after surgery. © 2018 The Japanese Urological Association.

  1. External validation and clinical utility of a prediction model for 6-month mortality in patients undergoing hemodialysis for end-stage kidney disease.

    PubMed

    Forzley, Brian; Er, Lee; Chiu, Helen Hl; Djurdjev, Ognjenka; Martinusen, Dan; Carson, Rachel C; Hargrove, Gaylene; Levin, Adeera; Karim, Mohamud

    2018-02-01

    End-stage kidney disease is associated with poor prognosis. Health care professionals must be prepared to address end-of-life issues and identify those at high risk for dying. A 6-month mortality prediction model for patients on dialysis derived in the United States is used but has not been externally validated. We aimed to assess the external validity and clinical utility in an independent cohort in Canada. We examined the performance of the published 6-month mortality prediction model, using discrimination, calibration, and decision curve analyses. Data were derived from a cohort of 374 prevalent dialysis patients in two regions of British Columbia, Canada, which included serum albumin, age, peripheral vascular disease, dementia, and answers to the "the surprise question" ("Would I be surprised if this patient died within the next year?"). The observed mortality in the validation cohort was 11.5% at 6 months. The prediction model had reasonable discrimination (c-stat = 0.70) but poor calibration (calibration-in-the-large = -0.53 (95% confidence interval: -0.88, -0.18); calibration slope = 0.57 (95% confidence interval: 0.31, 0.83)) in our data. Decision curve analysis showed the model only has added value in guiding clinical decision in a small range of threshold probabilities: 8%-20%. Despite reasonable discrimination, the prediction model has poor calibration in this external study cohort; thus, it may have limited clinical utility in settings outside of where it was derived. Decision curve analysis clarifies limitations in clinical utility not apparent by receiver operating characteristic curve analysis. This study highlights the importance of external validation of prediction models prior to routine use in clinical practice.

  2. Development and External Validation of a Melanoma Risk Prediction Model Based on Self-assessed Risk Factors.

    PubMed

    Vuong, Kylie; Armstrong, Bruce K; Weiderpass, Elisabete; Lund, Eiliv; Adami, Hans-Olov; Veierod, Marit B; Barrett, Jennifer H; Davies, John R; Bishop, D Timothy; Whiteman, David C; Olsen, Catherine M; Hopper, John L; Mann, Graham J; Cust, Anne E; McGeechan, Kevin

    2016-08-01

    Identifying individuals at high risk of melanoma can optimize primary and secondary prevention strategies. To develop and externally validate a risk prediction model for incident first-primary cutaneous melanoma using self-assessed risk factors. We used unconditional logistic regression to develop a multivariable risk prediction model. Relative risk estimates from the model were combined with Australian melanoma incidence and competing mortality rates to obtain absolute risk estimates. A risk prediction model was developed using the Australian Melanoma Family Study (629 cases and 535 controls) and externally validated using 4 independent population-based studies: the Western Australia Melanoma Study (511 case-control pairs), Leeds Melanoma Case-Control Study (960 cases and 513 controls), Epigene-QSkin Study (44 544, of which 766 with melanoma), and Swedish Women's Lifestyle and Health Cohort Study (49 259 women, of which 273 had melanoma). We validated model performance internally and externally by assessing discrimination using the area under the receiver operating curve (AUC). Additionally, using the Swedish Women's Lifestyle and Health Cohort Study, we assessed model calibration and clinical usefulness. The risk prediction model included hair color, nevus density, first-degree family history of melanoma, previous nonmelanoma skin cancer, and lifetime sunbed use. On internal validation, the AUC was 0.70 (95% CI, 0.67-0.73). On external validation, the AUC was 0.66 (95% CI, 0.63-0.69) in the Western Australia Melanoma Study, 0.67 (95% CI, 0.65-0.70) in the Leeds Melanoma Case-Control Study, 0.64 (95% CI, 0.62-0.66) in the Epigene-QSkin Study, and 0.63 (95% CI, 0.60-0.67) in the Swedish Women's Lifestyle and Health Cohort Study. Model calibration showed close agreement between predicted and observed numbers of incident melanomas across all deciles of predicted risk. In the external validation setting, there was higher net benefit when using the risk prediction model to classify individuals as high risk compared with classifying all individuals as high risk. The melanoma risk prediction model performs well and may be useful in prevention interventions reliant on a risk assessment using self-assessed risk factors.

  3. Prediction of individual milk proteins including free amino acids in bovine milk using mid-infrared spectroscopy and their correlations with milk processing characteristics.

    PubMed

    McDermott, A; Visentin, G; De Marchi, M; Berry, D P; Fenelon, M A; O'Connor, P M; Kenny, O A; McParland, S

    2016-04-01

    The aim of this study was to evaluate the effectiveness of mid-infrared spectroscopy in predicting milk protein and free amino acid (FAA) composition in bovine milk. Milk samples were collected from 7 Irish research herds and represented cows from a range of breeds, parities, and stages of lactation. Mid-infrared spectral data in the range of 900 to 5,000 cm(-1) were available for 730 milk samples; gold standard methods were used to quantify individual protein fractions and FAA of these samples with a view to predicting these gold standard protein fractions and FAA levels with available mid-infrared spectroscopy data. Separate prediction equations were developed for each trait using partial least squares regression; accuracy of prediction was assessed using both cross validation on a calibration data set (n=400 to 591 samples) and external validation on an independent data set (n=143 to 294 samples). The accuracy of prediction in external validation was the same irrespective of whether undertaken on the entire external validation data set or just within the Holstein-Friesian breed. The strongest coefficient of correlation obtained for protein fractions in external validation was 0.74, 0.69, and 0.67 for total casein, total β-lactoglobulin, and β-casein, respectively. Total proteins (i.e., total casein, total whey, and total lactoglobulin) were predicted with greater accuracy then their respective component traits; prediction accuracy using the infrared spectrum was superior to prediction using just milk protein concentration. Weak to moderate prediction accuracies were observed for FAA. The greatest coefficient of correlation in both cross validation and external validation was for Gly (0.75), indicating a moderate accuracy of prediction. Overall, the FAA prediction models overpredicted the gold standard values. Near-unity correlations existed between total casein and β-casein irrespective of whether the traits were based on the gold standard (0.92) or mid-infrared spectroscopy predictions (0.95). Weaker correlations among FAA were observed than the correlations among the protein fractions. Pearson correlations between gold standard protein fractions and the milk processing characteristics of rennet coagulation time, curd firming time, curd firmness, heat coagulating time, pH, and casein micelle size were weak to moderate and ranged from -0.48 (protein and pH) to 0.50 (total casein and a30). Pearson correlations between gold standard FAA and these milk processing characteristics were also weak to moderate and ranged from -0.60 (Val and pH) to 0.49 (Val and K20). Results from this study indicate that mid-infrared spectroscopy has the potential to predict protein fractions and some FAA in milk at a population level. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  4. Near-infrared reflectance spectroscopy predicts protein, starch, and seed weight in intact seeds of common bean ( Phaseolus vulgaris L.).

    PubMed

    Hacisalihoglu, Gokhan; Larbi, Bismark; Settles, A Mark

    2010-01-27

    The objective of this study was to explore the potential of near-infrared reflectance (NIR) spectroscopy to determine individual seed composition in common bean ( Phaseolus vulgaris L.). NIR spectra and analytical measurements of seed weight, protein, and starch were collected from 267 individual bean seeds representing 91 diverse genotypes. Partial least-squares (PLS) regression models were developed with 61 bean accessions randomly assigned to a calibration data set and 30 accessions assigned to an external validation set. Protein gave the most accurate PLS regression, with the external validation set having a standard error of prediction (SEP) = 1.6%. PLS regressions for seed weight and starch had sufficient accuracy for seed sorting applications, with SEP = 41.2 mg and 4.9%, respectively. Seed color had a clear effect on the NIR spectra, with black beans having a distinct spectral type. Seed coat color did not impact the accuracy of PLS predictions. This research demonstrates that NIR is a promising technique for simultaneous sorting of multiple seed traits in single bean seeds with no sample preparation.

  5. Clinical prognostic rules for severe acute respiratory syndrome in low- and high-resource settings.

    PubMed

    Cowling, Benjamin J; Muller, Matthew P; Wong, Irene O L; Ho, Lai-Ming; Lo, Su-Vui; Tsang, Thomas; Lam, Tai Hing; Louie, Marie; Leung, Gabriel M

    2006-07-24

    An accurate prognostic model for patients with severe acute respiratory syndrome (SARS) could provide a practical clinical decision aid. We developed and validated prognostic rules for both high- and low-resource settings based on data available at the time of admission. We analyzed data on all 1755 and 291 patients with SARS in Hong Kong (derivation cohort) and Toronto (validation cohort), respectively, using a multivariable logistic scoring method with internal and external validation. Scores were assigned on the basis of patient history in a basic model, and a full model additionally incorporated radiological and laboratory results. The main outcome measure was death. Predictors for mortality in the basic model included older age, male sex, and the presence of comorbid conditions. Additional predictors in the full model included haziness or infiltrates on chest radiography, less than 95% oxygen saturation on room air, high lactate dehydrogenase level, and high neutrophil and low platelet counts. The basic model had an area under the receiver operating characteristic (ROC) curve of 0.860 in the derivation cohort, which was maintained on external validation with an area under the ROC curve of 0.882. The full model improved discrimination with areas under the ROC curve of 0.877 and 0.892 in the derivation and validation cohorts, respectively. The model performs well and could be useful in assessing prognosis for patients who are infected with re-emergent SARS.

  6. Validation of the Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM).

    PubMed

    Willis, Michael; Johansen, Pierre; Nilsson, Andreas; Asseburg, Christian

    2017-03-01

    The Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM) was developed to address study questions pertaining to the cost-effectiveness of treatment alternatives in the care of patients with type 2 diabetes mellitus (T2DM). Naturally, the usefulness of a model is determined by the accuracy of its predictions. A previous version of ECHO-T2DM was validated against actual trial outcomes and the model predictions were generally accurate. However, there have been recent upgrades to the model, which modify model predictions and necessitate an update of the validation exercises. The objectives of this study were to extend the methods available for evaluating model validity, to conduct a formal model validation of ECHO-T2DM (version 2.3.0) in accordance with the principles espoused by the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Society for Medical Decision Making (SMDM), and secondarily to evaluate the relative accuracy of four sets of macrovascular risk equations included in ECHO-T2DM. We followed the ISPOR/SMDM guidelines on model validation, evaluating face validity, verification, cross-validation, and external validation. Model verification involved 297 'stress tests', in which specific model inputs were modified systematically to ascertain correct model implementation. Cross-validation consisted of a comparison between ECHO-T2DM predictions and those of the seminal National Institutes of Health model. In external validation, study characteristics were entered into ECHO-T2DM to replicate the clinical results of 12 studies (including 17 patient populations), and model predictions were compared to observed values using established statistical techniques as well as measures of average prediction error, separately for the four sets of macrovascular risk equations supported in ECHO-T2DM. Sub-group analyses were conducted for dependent vs. independent outcomes and for microvascular vs. macrovascular vs. mortality endpoints. All stress tests were passed. ECHO-T2DM replicated the National Institutes of Health cost-effectiveness application with numerically similar results. In external validation of ECHO-T2DM, model predictions agreed well with observed clinical outcomes. For all sets of macrovascular risk equations, the results were close to the intercept and slope coefficients corresponding to a perfect match, resulting in high R 2 and failure to reject concordance using an F test. The results were similar for sub-groups of dependent and independent validation, with some degree of under-prediction of macrovascular events. ECHO-T2DM continues to match health outcomes in clinical trials in T2DM, with prediction accuracy similar to other leading models of T2DM.

  7. Predicting human skin absorption of chemicals: development of a novel quantitative structure activity relationship.

    PubMed

    Luo, Wen; Medrek, Sarah; Misra, Jatin; Nohynek, Gerhard J

    2007-02-01

    The objective of this study was to construct and validate a quantitative structure-activity relationship model for skin absorption. Such models are valuable tools for screening and prioritization in safety and efficacy evaluation, and risk assessment of drugs and chemicals. A database of 340 chemicals with percutaneous absorption was assembled. Two models were derived from the training set consisting 306 chemicals (90/10 random split). In addition to the experimental K(ow) values, over 300 2D and 3D atomic and molecular descriptors were analyzed using MDL's QsarIS computer program. Subsequently, the models were validated using both internal (leave-one-out) and external validation (test set) procedures. Using the stepwise regression analysis, three molecular descriptors were determined to have significant statistical correlation with K(p) (R2 = 0.8225): logK(ow), X0 (quantification of both molecular size and the degree of skeletal branching), and SsssCH (count of aromatic carbon groups). In conclusion, two models to estimate skin absorption were developed. When compared to other skin absorption QSAR models in the literature, our model incorporated more chemicals and explored a large number of descriptors. Additionally, our models are reasonably predictive and have met both internal and external statistical validations.

  8. Construction Strategies for Multiscale Personality Inventories

    ERIC Educational Resources Information Center

    Burisch, Matthias

    1978-01-01

    Sets of inventory scales were constructed from a common item pool, using variants of what are here called the Inductive, Deductive, and External strategies. Peer ratings for 21 traits served as criteria. Very little variation in validity was attributable to construction strategies. (Author/CTM)

  9. Building a practically useful theory of goal setting and task motivation. A 35-year odyssey.

    PubMed

    Locke, Edwin A; Latham, Gary P

    2002-09-01

    The authors summarize 35 years of empirical research on goal-setting theory. They describe the core findings of the theory, the mechanisms by which goals operate, moderators of goal effects, the relation of goals and satisfaction, and the role of goals as mediators of incentives. The external validity and practical significance of goal-setting theory are explained, and new directions in goal-setting research are discussed. The relationships of goal setting to other theories are described as are the theory's limitations.

  10. Predictive Models for the Free Energy of Hydrogen Bonded Complexes with Single and Cooperative Hydrogen Bonds.

    PubMed

    Glavatskikh, Marta; Madzhidov, Timur; Solov'ev, Vitaly; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

    2016-12-01

    In this work, we report QSPR modeling of the free energy ΔG of 1 : 1 hydrogen bond complexes of different H-bond acceptors and donors. The modeling was performed on a large and structurally diverse set of 3373 complexes featuring a single hydrogen bond, for which ΔG was measured at 298 K in CCl 4 . The models were prepared using Support Vector Machine and Multiple Linear Regression, with ISIDA fragment descriptors. The marked atoms strategy was applied at fragmentation stage, in order to capture the location of H-bond donor and acceptor centers. Different strategies of model validation have been suggested, including the targeted omission of individual H-bond acceptors and donors from the training set, in order to check whether the predictive ability of the model is not limited to the interpolation of H-bond strength between two already encountered partners. Successfully cross-validating individual models were combined into a consensus model, and challenged to predict external test sets of 629 and 12 complexes, in which donor and acceptor formed single and cooperative H-bonds, respectively. In all cases, SVM models outperform MLR. The SVM consensus model performs well both in 3-fold cross-validation (RMSE=1.50 kJ/mol), and on the external test sets containing complexes with single (RMSE=3.20 kJ/mol) and cooperative H-bonds (RMSE=1.63 kJ/mol). © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Troponin-only Manchester Acute Coronary Syndromes (T-MACS) decision aid: single biomarker re-derivation and external validation in three cohorts

    PubMed Central

    Body, Richard; Sperrin, Matthew; Lewis, Philip S; Burrows, Gillian; Carley, Simon; McDowell, Garry; Buchan, Iain; Greaves, Kim; Mackway-Jones, Kevin

    2017-01-01

    Background The original Manchester Acute Coronary Syndromes model (MACS) ‘rules in’ and ‘rules out’ acute coronary syndromes (ACS) using high sensitivity cardiac troponin T (hs-cTnT) and heart-type fatty acid binding protein (H-FABP) measured at admission. The latter is not always available. We aimed to refine and validate MACS as Troponin-only Manchester Acute Coronary Syndromes (T-MACS), cutting down the biomarkers to just hs-cTnT. Methods We present secondary analyses from four prospective diagnostic cohort studies including patients presenting to the ED with suspected ACS. Data were collected and hs-cTnT measured on arrival. The primary outcome was ACS, defined as prevalent acute myocardial infarction (AMI) or incident death, AMI or coronary revascularisation within 30 days. T-MACS was built in one cohort (derivation set) and validated in three external cohorts (validation set). Results At the ‘rule out’ threshold, in the derivation set (n=703), T-MACS had 99.3% (95% CI 97.3% to 99.9%) negative predictive value (NPV) and 98.7% (95.3%–99.8%) sensitivity for ACS, ‘ruling out’ 37.7% patients (specificity 47.6%, positive predictive value (PPV) 34.0%). In the validation set (n=1459), T-MACS had 99.3% (98.3%–99.8%) NPV and 98.1% (95.2%–99.5%) sensitivity, ‘ruling out’ 40.4% (n=590) patients (specificity 47.0%, PPV 23.9%). T-MACS would ‘rule in’ 10.1% and 4.7% patients in the respective sets, of which 100.0% and 91.3% had ACS. C-statistics for the original and refined rules were similar (T-MACS 0.91 vs MACS 0.90 on validation). Conclusions T-MACS could ‘rule out’ ACS in 40% of patients, while ‘ruling in’ 5% at highest risk using a single hs-cTnT measurement on arrival. As a clinical decision aid, T-MACS could therefore help to conserve healthcare resources. PMID:27565197

  12. QSAR study of curcumine derivatives as HIV-1 integrase inhibitors.

    PubMed

    Gupta, Pawan; Sharma, Anju; Garg, Prabha; Roy, Nilanjan

    2013-03-01

    A QSAR study was performed on curcumine derivatives as HIV-1 integrase inhibitors using multiple linear regression. The statistically significant model was developed with squared correlation coefficients (r(2)) 0.891 and cross validated r(2) (r(2) cv) 0.825. The developed model revealed that electronic, shape, size, geometry, substitution's information and hydrophilicity were important atomic properties for determining the inhibitory activity of these molecules. The model was also tested successfully for external validation (r(2) pred = 0.849) as well as Tropsha's test for model predictability. Furthermore, the domain analysis was carried out to evaluate the prediction reliability of external set molecules. The model was statistically robust and had good predictive power which can be successfully utilized for screening of new molecules.

  13. Risk score to predict gastrointestinal bleeding after acute ischemic stroke.

    PubMed

    Ji, Ruijun; Shen, Haipeng; Pan, Yuesong; Wang, Penglian; Liu, Gaifen; Wang, Yilong; Li, Hao; Singhal, Aneesh B; Wang, Yongjun

    2014-07-25

    Gastrointestinal bleeding (GIB) is a common and often serious complication after stroke. Although several risk factors for post-stroke GIB have been identified, no reliable or validated scoring system is currently available to predict GIB after acute stroke in routine clinical practice or clinical trials. In the present study, we aimed to develop and validate a risk model (acute ischemic stroke associated gastrointestinal bleeding score, the AIS-GIB score) to predict in-hospital GIB after acute ischemic stroke. The AIS-GIB score was developed from data in the China National Stroke Registry (CNSR). Eligible patients in the CNSR were randomly divided into derivation (60%) and internal validation (40%) cohorts. External validation was performed using data from the prospective Chinese Intracranial Atherosclerosis Study (CICAS). Independent predictors of in-hospital GIB were obtained using multivariable logistic regression in the derivation cohort, and β-coefficients were used to generate point scoring system for the AIS-GIB. The area under the receiver operating characteristic curve (AUROC) and the Hosmer-Lemeshow goodness-of-fit test were used to assess model discrimination and calibration, respectively. A total of 8,820, 5,882, and 2,938 patients were enrolled in the derivation, internal validation and external validation cohorts. The overall in-hospital GIB after AIS was 2.6%, 2.3%, and 1.5% in the derivation, internal, and external validation cohort, respectively. An 18-point AIS-GIB score was developed from the set of independent predictors of GIB including age, gender, history of hypertension, hepatic cirrhosis, peptic ulcer or previous GIB, pre-stroke dependence, admission National Institutes of Health stroke scale score, Glasgow Coma Scale score and stroke subtype (Oxfordshire). The AIS-GIB score showed good discrimination in the derivation (0.79; 95% CI, 0.764-0.825), internal (0.78; 95% CI, 0.74-0.82) and external (0.76; 95% CI, 0.71-0.82) validation cohorts. The AIS-GIB score was well calibrated in the derivation (P = 0.42), internal (P = 0.45) and external (P = 0.86) validation cohorts. The AIS-GIB score is a valid clinical grading scale to predict in-hospital GIB after AIS. Further studies on the effect of the AIS-GIB score on reducing GIB and improving outcome after AIS are warranted.

  14. Reconceptualising the external validity of discrete choice experiments.

    PubMed

    Lancsar, Emily; Swait, Joffre

    2014-10-01

    External validity is a crucial but under-researched topic when considering using discrete choice experiment (DCE) results to inform decision making in clinical, commercial or policy contexts. We present the theory and tests traditionally used to explore external validity that focus on a comparison of final outcomes and review how this traditional definition has been empirically tested in health economics and other sectors (such as transport, environment and marketing) in which DCE methods are applied. While an important component, we argue that the investigation of external validity should be much broader than a comparison of final outcomes. In doing so, we introduce a new and more comprehensive conceptualisation of external validity, closely linked to process validity, that moves us from the simple characterisation of a model as being or not being externally valid on the basis of predictive performance, to the concept that external validity should be an objective pursued from the initial conceptualisation and design of any DCE. We discuss how such a broader definition of external validity can be fruitfully used and suggest innovative ways in which it can be explored in practice.

  15. Rational selection of training and test sets for the development of validated QSAR models

    NASA Astrophysics Data System (ADS)

    Golbraikh, Alexander; Shen, Min; Xiao, Zhiyan; Xiao, Yun-De; Lee, Kuo-Hsiung; Tropsha, Alexander

    2003-02-01

    Quantitative Structure-Activity Relationship (QSAR) models are used increasingly to screen chemical databases and/or virtual chemical libraries for potentially bioactive molecules. These developments emphasize the importance of rigorous model validation to ensure that the models have acceptable predictive power. Using k nearest neighbors ( kNN) variable selection QSAR method for the analysis of several datasets, we have demonstrated recently that the widely accepted leave-one-out (LOO) cross-validated R2 (q2) is an inadequate characteristic to assess the predictive ability of the models [Golbraikh, A., Tropsha, A. Beware of q2! J. Mol. Graphics Mod. 20, 269-276, (2002)]. Herein, we provide additional evidence that there exists no correlation between the values of q 2 for the training set and accuracy of prediction ( R 2) for the test set and argue that this observation is a general property of any QSAR model developed with LOO cross-validation. We suggest that external validation using rationally selected training and test sets provides a means to establish a reliable QSAR model. We propose several approaches to the division of experimental datasets into training and test sets and apply them in QSAR studies of 48 functionalized amino acid anticonvulsants and a series of 157 epipodophyllotoxin derivatives with antitumor activity. We formulate a set of general criteria for the evaluation of predictive power of QSAR models.

  16. External validation of the DHAKA score and comparison with the current IMCI algorithm for the assessment of dehydration in children with diarrhoea: a prospective cohort study.

    PubMed

    Levine, Adam C; Glavis-Bloom, Justin; Modi, Payal; Nasrin, Sabiha; Atika, Bita; Rege, Soham; Robertson, Sarah; Schmid, Christopher H; Alam, Nur H

    2016-10-01

    Dehydration due to diarrhoea is a leading cause of child death worldwide, yet no clinical tools for assessing dehydration have been validated in resource-limited settings. The Dehydration: Assessing Kids Accurately (DHAKA) score was derived for assessing dehydration in children with diarrhoea in a low-income country setting. In this study, we aimed to externally validate the DHAKA score in a new population of children and compare its accuracy and reliability to the current Integrated Management of Childhood Illness (IMCI) algorithm. DHAKA was a prospective cohort study done in children younger than 60 months presenting to the International Centre for Diarrhoeal Disease Research, Bangladesh, with acute diarrhoea (defined by WHO as three or more loose stools per day for less than 14 days). Local nurses assessed children and classified their dehydration status using both the DHAKA score and the IMCI algorithm. Serial weights were obtained and dehydration status was established by percentage weight change with rehydration. We did regression analyses to validate the DHAKA score and compared the accuracy and reliability of the DHAKA score and IMCI algorithm with receiver operator characteristic (ROC) curves and the weighted κ statistic. This study was registered with ClinicalTrials.gov, number NCT02007733. Between March 22, 2015, and May 15, 2015, 496 patients were included in our primary analyses. On the basis of our criterion standard, 242 (49%) of 496 children had no dehydration, 184 (37%) of 496 had some dehydration, and 70 (14%) of 496 had severe dehydration. In multivariable regression analyses, each 1-point increase in the DHAKA score predicted an increase of 0·6% in the percentage dehydration of the child and increased the odds of both some and severe dehydration by a factor of 1·4. Both the accuracy and reliability of the DHAKA score were significantly greater than those of the IMCI algorithm. The DHAKA score is the first clinical tool for assessing dehydration in children with acute diarrhoea to be externally validated in a low-income country. Further validation studies in a diverse range of settings and paediatric populations are warranted. National Institutes of Health Fogarty International Center. Copyright © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license. Published by Elsevier Ltd.. All rights reserved.

  17. External validation of the DHAKA score and comparison with the current IMCI algorithm for the assessment of dehydration in children with diarrhoea: a prospective cohort study

    PubMed Central

    Levine, Adam C; Glavis-Bloom, Justin; Modi, Payal; Nasrin, Sabiha; Atika, Bita; Rege, Soham; Robertson, Sarah; Schmid, Christopher H; Alam, Nur H

    2016-01-01

    Summary Background Dehydration due to diarrhoea is a leading cause of child death worldwide, yet no clinical tools for assessing dehydration have been validated in resource-limited settings. The Dehydration: Assessing Kids Accurately (DHAKA) score was derived for assessing dehydration in children with diarrhoea in a low-income country setting. In this study, we aimed to externally validate the DHAKA score in a new population of children and compare its accuracy and reliability to the current Integrated Management of Childhood Illness (IMCI) algorithm. Methods DHAKA was a prospective cohort study done in children younger than 60 months presenting to the International Centre for Diarrhoeal Disease Research, Bangladesh, with acute diarrhoea (defined by WHO as three or more loose stools per day for less than 14 days). Local nurses assessed children and classified their dehydration status using both the DHAKA score and the IMCI algorithm. Serial weights were obtained and dehydration status was established by percentage weight change with rehydration. We did regression analyses to validate the DHAKA score and compared the accuracy and reliability of the DHAKA score and IMCI algorithm with receiver operator characteristic (ROC) curves and the weighted κ statistic. This study was registered with ClinicalTrials.gov, number NCT02007733. Findings Between March 22, 2015, and May 15, 2015, 496 patients were included in our primary analyses. On the basis of our criterion standard, 242 (49%) of 496 children had no dehydration, 184 (37%) of 496 had some dehydration, and 70 (14%) of 496 had severe dehydration. In multivariable regression analyses, each 1-point increase in the DHAKA score predicted an increase of 0·6% in the percentage dehydration of the child and increased the odds of both some and severe dehydration by a factor of 1·4. Both the accuracy and reliability of the DHAKA score were significantly greater than those of the IMCI algorithm. Interpretation The DHAKA score is the first clinical tool for assessing dehydration in children with acute diarrhoea to be externally validated in a low-income country. Further validation studies in a diverse range of settings and paediatric populations are warranted. Funding National Institutes of Health Fogarty International Center. PMID:27567350

  18. hERG blocking potential of acids and zwitterions characterized by three thresholds for acidity, size and reactivity.

    PubMed

    Nikolov, Nikolai G; Dybdahl, Marianne; Jónsdóttir, Svava Ó; Wedebye, Eva B

    2014-11-01

    Ionization is a key factor in hERG K(+) channel blocking, and acids and zwitterions are known to be less probable hERG blockers than bases and neutral compounds. However, a considerable number of acidic compounds block hERG, and the physico-chemical attributes which discriminate acidic blockers from acidic non-blockers have not been fully elucidated. We propose a rule for prediction of hERG blocking by acids and zwitterionic ampholytes based on thresholds for only three descriptors related to acidity, size and reactivity. The training set of 153 acids and zwitterionic ampholytes was predicted with a concordance of 91% by a decision tree based on the rule. Two external validations were performed with sets of 35 and 48 observations, respectively, both showing concordances of 91%. In addition, a global QSAR model of hERG blocking was constructed based on a large diverse training set of 1374 chemicals covering all ionization classes, externally validated showing high predictivity and compared to the decision tree. The decision tree was found to be superior for the acids and zwitterionic ampholytes classes. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Emotional and tangible social support in a German population-based sample: Development and validation of the Brief Social Support Scale (BS6).

    PubMed

    Beutel, Manfred E; Brähler, Elmar; Wiltink, Jörg; Michal, Matthias; Klein, Eva M; Jünger, Claus; Wild, Philipp S; Münzel, Thomas; Blettner, Maria; Lackner, Karl; Nickels, Stefan; Tibubos, Ana N

    2017-01-01

    Aim of the study was the development and validation of the psychometric properties of a six-item bi-factorial instrument for the assessment of social support (emotional and tangible support) with a population-based sample. A cross-sectional data set of N = 15,010 participants enrolled in the Gutenberg Health Study (GHS) in 2007-2012 was divided in two sub-samples. The GHS is a population-based, prospective, observational single-center cohort study in the Rhein-Main-Region in western Mid-Germany. The first sub-sample was used for scale development by performing an exploratory factor analysis. In order to test construct validity, confirmatory factor analyses were run to compare the extracted bi-factorial model with the one-factor solution. Reliability of the scales was indicated by calculating internal consistency. External validity was tested by investigating demographic characteristics health behavior, and distress using analysis of variance, Spearman and Pearson correlation analysis, and logistic regression analysis. Based on an exploratory factor analysis, a set of six items was extracted representing two independent factors. The two-factor structure of the Brief Social Support Scale (BS6) was confirmed by the results of the confirmatory factor analyses. Fit indices of the bi-factorial model were good and better compared to the one-factor solution. External validity was demonstrated for the BS6. The BS6 is a reliable and valid short scale that can be applied in social surveys due to its brevity to assess emotional and practical dimensions of social support.

  20. School Safety: Saving Lives with AEDs

    ERIC Educational Resources Information Center

    Slusser, Greg

    2012-01-01

    Automated external defibrillators (AEDs) on school and university campuses have saved many lives. Students, teachers and community members have been among the fortunate ones pulled from the brink of death. Medical studies validating the effectiveness of AEDs in schools and other public settings have been published in numerous medical journals.…

  1. Estimation model for habitual 24-hour urinary-sodium excretion using simple questionnaires from normotensive Koreans.

    PubMed

    Kong, Ji-Sook; Lee, Yeon-Kyung; Kim, Mi Kyung; Choi, Mi-Kyeong; Heo, Young-Ran; Hyun, Taisun; Kim, Sun Mee; Lyu, Eun-Soon; Oh, Se-Young; Park, Hae-Ryun; Rhee, Moo-Yong; Ro, Hee-Kyong; Song, Mi Kyung

    2018-01-01

    This study was conducted to develop an equation for estimation of 24-h urinary-sodium excretion that can serve as an alternative to 24-h dietary recall and 24-h urine collection for normotensive Korean adults. In total, data on 640 healthy Korean adults aged 19 to 69 years from 4 regions of the country were collected as a training set. In order to externally validate the equation developed from that training set, 200 subjects were recruited independently as a validation set. Due to heterogeneity by gender, we constructed a gender-specific equation for estimation of 24-h urinary-sodium excretion by using a multivariable linear regression model and assessed the performance of the developed equation in validation set. The best model consisted of age, body weight, dietary behavior ('eating salty food', 'Kimchi consumption', 'Korean soup or stew consumption', 'soy sauce or red pepper paste consumption'), and smoking status in men, and age, body weight, dietary behavior ('salt preference', 'eating salty food', 'checking sodium content for processed foods', 'nut consumption'), and smoking status in women, respectively. When this model was tested in the external validation set, the mean bias between the measured and estimated 24-h urinary-sodium excretion from Bland-Altman plots was -1.92 (95% CI: -113, 110) mmol/d for men and -1.51 (95% CI: -90.6, 87.6) mmol/d for women. The cut-points of sodium intake calculated based on the equations were ≥4,000 mg/d for men and ≥3,500 mg/d for women, with 89.8 and 76.6% sensitivity and 29.3 and 64.2% specificity, respectively. In this study, a habitual 24-hour urinary-sodium-excretion-estimation model of normotensive Korean adults based on anthropometric and lifestyle factors was developed and showed feasibility for an asymptomatic population.

  2. Estimation model for habitual 24-hour urinary-sodium excretion using simple questionnaires from normotensive Koreans

    PubMed Central

    Choi, Mi-Kyeong; Heo, Young-Ran; Hyun, Taisun; Kim, Sun Mee; Lyu, Eun-Soon; Oh, Se-Young; Park, Hae-Ryun; Rhee, Moo-Yong; Ro, Hee-Kyong; Song, Mi Kyung

    2018-01-01

    This study was conducted to develop an equation for estimation of 24-h urinary-sodium excretion that can serve as an alternative to 24-h dietary recall and 24-h urine collection for normotensive Korean adults. In total, data on 640 healthy Korean adults aged 19 to 69 years from 4 regions of the country were collected as a training set. In order to externally validate the equation developed from that training set, 200 subjects were recruited independently as a validation set. Due to heterogeneity by gender, we constructed a gender-specific equation for estimation of 24-h urinary-sodium excretion by using a multivariable linear regression model and assessed the performance of the developed equation in validation set. The best model consisted of age, body weight, dietary behavior (‘eating salty food’, ‘Kimchi consumption’, ‘Korean soup or stew consumption’, ‘soy sauce or red pepper paste consumption’), and smoking status in men, and age, body weight, dietary behavior (‘salt preference’, ‘eating salty food’, ‘checking sodium content for processed foods’, ‘nut consumption’), and smoking status in women, respectively. When this model was tested in the external validation set, the mean bias between the measured and estimated 24-h urinary-sodium excretion from Bland-Altman plots was -1.92 (95% CI: -113, 110) mmol/d for men and -1.51 (95% CI: -90.6, 87.6) mmol/d for women. The cut-points of sodium intake calculated based on the equations were ≥4,000 mg/d for men and ≥3,500 mg/d for women, with 89.8 and 76.6% sensitivity and 29.3 and 64.2% specificity, respectively. In this study, a habitual 24-hour urinary-sodium-excretion-estimation model of normotensive Korean adults based on anthropometric and lifestyle factors was developed and showed feasibility for an asymptomatic population. PMID:29447201

  3. The importance of molecular structures, endpoints' values, and predictivity parameters in QSAR research: QSAR analysis of a series of estrogen receptor binders.

    PubMed

    Li, Jiazhong; Gramatica, Paola

    2010-11-01

    Quantitative structure-activity relationship (QSAR) methodology aims to explore the relationship between molecular structures and experimental endpoints, producing a model for the prediction of new data; the predictive performance of the model must be checked by external validation. Clearly, the qualities of chemical structure information and experimental endpoints, as well as the statistical parameters used to verify the external predictivity have a strong influence on QSAR model reliability. Here, we emphasize the importance of these three aspects by analyzing our models on estrogen receptor binders (Endocrine disruptor knowledge base (EDKB) database). Endocrine disrupting chemicals, which mimic or antagonize the endogenous hormones such as estrogens, are a hot topic in environmental and toxicological sciences. QSAR shows great values in predicting the estrogenic activity and exploring the interactions between the estrogen receptor and ligands. We have verified our previously published model for additional external validation on new EDKB chemicals. Having found some errors in the used 3D molecular conformations, we redevelop a new model using the same data set with corrected structures, the same method (ordinary least-square regression, OLS) and DRAGON descriptors. The new model, based on some different descriptors, is more predictive on external prediction sets. Three different formulas to calculate correlation coefficient for the external prediction set (Q2 EXT) were compared, and the results indicated that the new proposal of Consonni et al. had more reasonable results, consistent with the conclusions from regression line, Williams plot and root mean square error (RMSE) values. Finally, the importance of reliable endpoints values has been highlighted by comparing the classification assignments of EDKB with those of another estrogen receptor binders database (METI): we found that 16.1% assignments of the common compounds were opposite (20 among 124 common compounds). In order to verify the real assignments for these inconsistent compounds, we predicted these samples, as a blind external set, by our regression models and compared the results with the two databases. The results indicated that most of the predictions were consistent with METI. Furthermore, we built a kNN classification model using the 104 consistent compounds to predict those inconsistent ones, and most of the predictions were also in agreement with METI database.

  4. MiRNA Expression Analysis of Pretreatment Biopsies Predicts the Pathological Response of Esophageal Squamous Cell Carcinomas to Neoadjuvant Chemoradiotherapy.

    PubMed

    Wen, Jing; Luo, Kongjia; Liu, Hui; Liu, Shiliang; Lin, Guangrong; Hu, Yi; Zhang, Xu; Wang, Geng; Chen, Yuping; Chen, Zhijian; Li, Yi; Lin, Ting; Xie, Xiuying; Liu, Mengzhong; Wang, Huiyun; Yang, Hong; Fu, Jianhua

    2016-05-01

    To identify miRNA markers useful for esophageal squamous cell carcinoma (ESCC) neoadjuvant chemoradiotherapy (neo-CRT) response prediction. Neo-CRT followed by surgery improves ESCC patients' survival compared with surgery alone. However, CRT outcomes are heterogeneous, and no current methods can predict CRT responses. Differentially expressed miRNAs between ESCC pathological responders and nonresponders after neo-CRT were identified by miRNA profiling and verified by real-time quantitative polymerase chain reaction (qPCR) of 27 ESCCs in the training set. Several class prediction algorithms were used to build the response-classifying models with the qPCR data. Predictive powers of the models were further assessed with a second set of 79 ESCCs. Ten miRNAs with greater than a 1.5-fold change between pathological responders and nonresponders were identified and verified, respectively. A support vector machine (SVM) prediction model, composed of 4 miRNAs (miR-145-5p, miR-152, miR-193b-3p, and miR-376a-3p), were developed. It provided overall accuracies of 100% and 87.3% for discriminating pathological responders and nonresponders in the training and external validation sets, respectively. In multivariate analysis, the subgroup determined by the SVM model was the only independent factor significantly associated with neo-CRT response in the external validation sets. Combined qPCR of the 4 miRNAs provides the possibility of ESCC neo-CRT response prediction, which may facilitate individualized ESCC treatment. Further prospective validation in larger independent cohorts is necessary to fully assess its predictive power.

  5. Development and validation of Prediction models for Risks of complications in Early-onset Pre-eclampsia (PREP): a prospective cohort study.

    PubMed

    Thangaratinam, Shakila; Allotey, John; Marlin, Nadine; Mol, Ben W; Von Dadelszen, Peter; Ganzevoort, Wessel; Akkermans, Joost; Ahmed, Asif; Daniels, Jane; Deeks, Jon; Ismail, Khaled; Barnard, Ann Marie; Dodds, Julie; Kerry, Sally; Moons, Carl; Riley, Richard D; Khan, Khalid S

    2017-04-01

    The prognosis of early-onset pre-eclampsia (before 34 weeks' gestation) is variable. Accurate prediction of complications is required to plan appropriate management in high-risk women. To develop and validate prediction models for outcomes in early-onset pre-eclampsia. Prospective cohort for model development, with validation in two external data sets. Model development: 53 obstetric units in the UK. Model transportability: PIERS (Pre-eclampsia Integrated Estimate of RiSk for mothers) and PETRA (Pre-Eclampsia TRial Amsterdam) studies. Pregnant women with early-onset pre-eclampsia. Nine hundred and forty-six women in the model development data set and 850 women (634 in PIERS, 216 in PETRA) in the transportability (external validation) data sets. The predictors were identified from systematic reviews of tests to predict complications in pre-eclampsia and were prioritised by Delphi survey. The primary outcome was the composite of adverse maternal outcomes established using Delphi surveys. The secondary outcome was the composite of fetal and neonatal complications. We developed two prediction models: a logistic regression model (PREP-L) to assess the overall risk of any maternal outcome until postnatal discharge and a survival analysis model (PREP-S) to obtain individual risk estimates at daily intervals from diagnosis until 34 weeks. Shrinkage was used to adjust for overoptimism of predictor effects. For internal validation (of the full models in the development data) and external validation (of the reduced models in the transportability data), we computed the ability of the models to discriminate between those with and without poor outcomes ( c -statistic), and the agreement between predicted and observed risk (calibration slope). The PREP-L model included maternal age, gestational age at diagnosis, medical history, systolic blood pressure, urine protein-to-creatinine ratio, platelet count, serum urea concentration, oxygen saturation, baseline treatment with antihypertensive drugs and administration of magnesium sulphate. The PREP-S model additionally included exaggerated tendon reflexes and serum alanine aminotransaminase and creatinine concentration. Both models showed good discrimination for maternal complications, with anoptimism-adjusted c -statistic of 0.82 [95% confidence interval (CI) 0.80 to 0.84] for PREP-L and 0.75 (95% CI 0.73 to 0.78) for the PREP-S model in the internal validation. External validation of the reduced PREP-L model showed good performance with a c -statistic of 0.81 (95% CI 0.77 to 0.85) in PIERS and 0.75 (95% CI 0.64 to 0.86) in PETRA cohorts for maternal complications, and calibrated well with slopes of 0.93 (95% CI 0.72 to 1.10) and 0.90 (95% CI 0.48 to 1.32), respectively. In the PIERS data set, the reduced PREP-S model had a c -statistic of 0.71 (95% CI 0.67 to 0.75) and a calibration slope of 0.67 (95% CI 0.56 to 0.79). Low gestational age at diagnosis, high urine protein-to-creatinine ratio, increased serum urea concentration, treatment with antihypertensive drugs, magnesium sulphate, abnormal uterine artery Doppler scan findings and estimated fetal weight below the 10th centile were associated with fetal complications. The PREP-L model provided individualised risk estimates in early-onset pre-eclampsia to plan management of high- or low-risk individuals. The PREP-S model has the potential to be used as a triage tool for risk assessment. The impacts of the model use on outcomes need further evaluation. Current Controlled Trials ISRCTN40384046. The National Institute for Health Research Health Technology Assessment programme.

  6. A diagnostic model for the detection of sensitization to wheat allergens was developed and validated in bakery workers.

    PubMed

    Suarthana, Eva; Vergouwe, Yvonne; Moons, Karel G; de Monchy, Jan; Grobbee, Diederick; Heederik, Dick; Meijer, Evert

    2010-09-01

    To develop and validate a prediction model to detect sensitization to wheat allergens in bakery workers. The prediction model was developed in 867 Dutch bakery workers (development set, prevalence of sensitization 13%) and included questionnaire items (candidate predictors). First, principal component analysis was used to reduce the number of candidate predictors. Then, multivariable logistic regression analysis was used to develop the model. Internal validation and extent of optimism was assessed with bootstrapping. External validation was studied in 390 independent Dutch bakery workers (validation set, prevalence of sensitization 20%). The prediction model contained the predictors nasoconjunctival symptoms, asthma symptoms, shortness of breath and wheeze, work-related upper and lower respiratory symptoms, and traditional bakery. The model showed good discrimination with an area under the receiver operating characteristic (ROC) curve area of 0.76 (and 0.75 after internal validation). Application of the model in the validation set gave a reasonable discrimination (ROC area=0.69) and good calibration after a small adjustment of the model intercept. A simple model with questionnaire items only can be used to stratify bakers according to their risk of sensitization to wheat allergens. Its use may increase the cost-effectiveness of (subsequent) medical surveillance.

  7. Mapping the MMPI-2-RF Substantive Scales Onto Internalizing, Externalizing, and Thought Dysfunction Dimensions in a Forensic Inpatient Setting.

    PubMed

    Romero, Isabella E; Toorabally, Nasreen; Burchett, Danielle; Tarescavage, Anthony M; Glassmire, David M

    2017-01-01

    Contemporary models of psychopathology-encompassing internalizing, externalizing, and thought dysfunction factors-have gained significant support. Although research indicates the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF; Ben-Porath & Tellegen, 2008 /2011) measures these domains of psychopathology, this study addresses extant limitations in MMPI-2-RF diagnostic validity research by examining associations between all MMPI-2-RF substantive scales and broad dichotomous indicators of internalizing, externalizing, and thought dysfunction diagnoses in a sample of 1,110 forensic inpatients. Comparing those with and without internalizing diagnoses, notable effects were observed for Negative Emotionality/Neuroticism-Revised (NEGE-r), Emotional/Internalizing Dysfunction (EID), Dysfunctional Negative Emotions (RC7), Demoralization (RCd), and several other internalizing and somatic/cognitive scales. Comparing those with and without thought dysfunction diagnoses, the largest hypothesized differences occurred for Thought Dysfunction (THD), Aberrant Experiences (RC8), and Psychoticism-Revised (PSYC-r), although unanticipated differences were observed on internalizing and interpersonal scales, likely reflecting the high prevalence of internalizing dysfunction in forensic inpatients not experiencing thought dysfunction. Comparing those with and without externalizing diagnoses, the largest effects were for Substance Abuse (SUB), Antisocial Behavior (RC4), Behavioral/Externalizing Dysfunction (BXD), Juvenile Conduct Problems (JCP), and Disconstraint-Revised (DISC-r). Multivariate models evidenced similar results. Findings support the construct validity of MMPI-2-RF scales as measures of internalizing, thought, and externalizing dysfunction.

  8. Validity of proposed DSM-5 diagnostic criteria for nicotine use disorder: results from 734 Israeli lifetime smokers

    PubMed Central

    Shmulewitz, D.; Wall, M.M.; Aharonovich, E.; Spivak, B.; Weizman, A.; Frisch, A.; Grant, B. F.; Hasin, D.

    2013-01-01

    Background The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) proposes aligning nicotine use disorder (NUD) criteria with those for other substances, by including the current DSM fourth edition (DSM-IV) nicotine dependence (ND) criteria, three abuse criteria (neglect roles, hazardous use, interpersonal problems) and craving. Although NUD criteria indicate one latent trait, evidence is lacking on: (1) validity of each criterion; (2) validity of the criteria as a set; (3) comparative validity between DSM-5 NUD and DSM-IV ND criterion sets; and (4) NUD prevalence. Method Nicotine criteria (DSM-IV ND, abuse and craving) and external validators (e.g. smoking soon after awakening, number of cigarettes per day) were assessed with a structured interview in 734 lifetime smokers from an Israeli household sample. Regression analysis evaluated the association between validators and each criterion. Receiver operating characteristic analysis assessed the association of the validators with the DSM-5 NUD set (number of criteria endorsed) and tested whether DSM-5 or DSM-IV provided the most discriminating criterion set. Changes in prevalence were examined. Results Each DSM-5 NUD criterion was significantly associated with the validators, with strength of associations similar across the criteria. As a set, DSM-5 criteria were significantly associated with the validators, were significantly more discriminating than DSM-IV ND criteria, and led to increased prevalence of binary NUD (two or more criteria) over ND. Conclusions All findings address previous concerns about the DSM-IV nicotine diagnosis and its criteria and support the proposed changes for DSM-5 NUD, which should result in improved diagnosis of nicotine disorders. PMID:23312475

  9. Evaluating the External Validity of High-Incidence Special Education Disability Categories

    ERIC Educational Resources Information Center

    Murr, Natalie Simona

    2015-01-01

    The passing of the Education of the Handicapped Act (EHA) of 1970, as well as subsequent education policy, including the Individuals with Disabilities Education Act (2004), have been pivotal to ensuring that both the civil and educational rights of students with disabilities continue to be promoted and protected within educational settings. In…

  10. Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening

    NASA Astrophysics Data System (ADS)

    Hsieh, Jui-Hua; Wang, Xiang S.; Teotico, Denise; Golbraikh, Alexander; Tropsha, Alexander

    2008-09-01

    The use of inaccurate scoring functions in docking algorithms may result in the selection of compounds with high predicted binding affinity that nevertheless are known experimentally not to bind to the target receptor. Such falsely predicted binders have been termed `binding decoys'. We posed a question as to whether true binders and decoys could be distinguished based only on their structural chemical descriptors using approaches commonly used in ligand based drug design. We have applied the k-Nearest Neighbor ( kNN) classification QSAR approach to a dataset of compounds characterized as binders or binding decoys of AmpC beta-lactamase. Models were subjected to rigorous internal and external validation as part of our standard workflow and a special QSAR modeling scheme was employed that took into account the imbalanced ratio of inhibitors to non-binders (1:4) in this dataset. 342 predictive models were obtained with correct classification rate (CCR) for both training and test sets as high as 0.90 or higher. The prediction accuracy was as high as 100% (CCR = 1.00) for the external validation set composed of 10 compounds (5 true binders and 5 decoys) selected randomly from the original dataset. For an additional external set of 50 known non-binders, we have achieved the CCR of 0.87 using very conservative model applicability domain threshold. The validated binary kNN QSAR models were further employed for mining the NCGC AmpC screening dataset (69653 compounds). The consensus prediction of 64 compounds identified as screening hits in the AmpC PubChem assay disagreed with their annotation in PubChem but was in agreement with the results of secondary assays. At the same time, 15 compounds were identified as potential binders contrary to their annotation in PubChem. Five of them were tested experimentally and showed inhibitory activities in millimolar range with the highest binding constant Ki of 135 μM. Our studies suggest that validated QSAR models could complement structure based docking and scoring approaches in identifying promising hits by virtual screening of molecular libraries.

  11. QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation.

    PubMed

    Votano, Joseph R; Parham, Marc; Hall, L Mark; Hall, Lowell H; Kier, Lemont B; Oloff, Scott; Tropsha, Alexander

    2006-11-30

    Four modeling techniques, using topological descriptors to represent molecular structure, were employed to produce models of human serum protein binding (% bound) on a data set of 1008 experimental values, carefully screened from publicly available sources. To our knowledge, this data is the largest set on human serum protein binding reported for QSAR modeling. The data was partitioned into a training set of 808 compounds and an external validation test set of 200 compounds. Partitioning was accomplished by clustering the compounds in a structure descriptor space so that random sampling of 20% of the whole data set produced an external test set that is a good representative of the training set with respect to both structure and protein binding values. The four modeling techniques include multiple linear regression (MLR), artificial neural networks (ANN), k-nearest neighbors (kNN), and support vector machines (SVM). With the exception of the MLR model, the ANN, kNN, and SVM QSARs were ensemble models. Training set correlation coefficients and mean absolute error ranged from r2=0.90 and MAE=7.6 for ANN to r2=0.61 and MAE=16.2 for MLR. Prediction results from the validation set yielded correlation coefficients and mean absolute errors which ranged from r2=0.70 and MAE=14.1 for ANN to a low of r2=0.59 and MAE=18.3 for the SVM model. Structure descriptors that contribute significantly to the models are discussed and compared with those found in other published models. For the ANN model, structure descriptor trends with respect to their affects on predicted protein binding can assist the chemist in structure modification during the drug design process.

  12. Consistency of QSAR models: Correct split of training and test sets, ranking of models and performance parameters.

    PubMed

    Rácz, A; Bajusz, D; Héberger, K

    2015-01-01

    Recent implementations of QSAR modelling software provide the user with numerous models and a wealth of information. In this work, we provide some guidance on how one should interpret the results of QSAR modelling, compare and assess the resulting models, and select the best and most consistent ones. Two QSAR datasets are applied as case studies for the comparison of model performance parameters and model selection methods. We demonstrate the capabilities of sum of ranking differences (SRD) in model selection and ranking, and identify the best performance indicators and models. While the exchange of the original training and (external) test sets does not affect the ranking of performance parameters, it provides improved models in certain cases (despite the lower number of molecules in the training set). Performance parameters for external validation are substantially separated from the other merits in SRD analyses, highlighting their value in data fusion.

  13. The FORBIO Climate data set for climate analyses

    NASA Astrophysics Data System (ADS)

    Delvaux, C.; Journée, M.; Bertrand, C.

    2015-06-01

    In the framework of the interdisciplinary FORBIO Climate research project, the Royal Meteorological Institute of Belgium is in charge of providing high resolution gridded past climate data (i.e. temperature and precipitation). This climate data set will be linked to the measurements on seedlings, saplings and mature trees to assess the effects of climate variation on tree performance. This paper explains how the gridded daily temperature (minimum and maximum) data set was generated from a consistent station network between 1980 and 2013. After station selection, data quality control procedures were developed and applied to the station records to ensure that only valid measurements will be involved in the gridding process. Thereafter, the set of unevenly distributed validated temperature data was interpolated on a 4 km × 4 km regular grid over Belgium. The performance of different interpolation methods has been assessed. The method of kriging with external drift using correlation between temperature and altitude gave the most relevant results.

  14. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

    PubMed Central

    Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

    2015-01-01

    Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using random forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers were 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the ScoreCard database of possible skin or sense organ toxicants as primary candidates for experimental validation. PMID:25560674

  15. Development and validation of a prognostic nomogram for terminally ill cancer patients.

    PubMed

    Feliu, Jaime; Jiménez-Gordo, Ana María; Madero, Rosario; Rodríguez-Aizcorbe, José Ramón; Espinosa, Enrique; Castro, Javier; Acedo, Jesús Domingo; Martínez, Beatriz; Alonso-Babarro, Alberto; Molina, Raquel; Cámara, Juan Carlos; García-Paredes, María Luisa; González-Barón, Manuel

    2011-11-02

    Determining life expectancy in terminally ill cancer patients is a difficult task. We aimed to develop and validate a nomogram to predict the length of survival in patients with terminal disease. From February 1, 2003, to December 31, 2005, 406 consecutive terminally ill patients were entered into the study. We analyzed 38 features prognostic of life expectancy among terminally ill patients by multivariable Cox regression and identified the most accurate and parsimonious model by backward variable elimination according to the Akaike information criterion. Five clinical and laboratory variables were built into a nomogram to estimate the probability of patient survival at 15, 30, and 60 days. We validated and calibrated the nomogram with an external validation cohort of 474 patients who were treated from June 1, 2006, through December 31, 2007. The median overall survival was 29.1 days for the training set and 18.3 days for the validation set. Eastern Cooperative Oncology Group performance status, lactate dehydrogenase levels, lymphocyte levels, albumin levels, and time from initial diagnosis to diagnosis of terminal disease were retained in the multivariable Cox proportional hazards model as independent prognostic factors of survival and formed the basis of the nomogram. The nomogram had high predictive performance, with a bootstrapped corrected concordance index of 0.70, and it showed good calibration. External independent validation revealed 68% predictive accuracy. We developed a highly accurate tool that uses basic clinical and analytical information to predict the probability of survival at 15, 30, and 60 days in terminally ill cancer patients. This tool can help physicians making decisions on clinical care at the end of life.

  16. QSPR model for bioconcentration factors of nonpolar organic compounds using molecular electronegativity distance vector descriptors.

    PubMed

    Qin, Li-Tang; Liu, Shu-Shen; Liu, Hai-Ling

    2010-02-01

    A five-variable model (model M2) was developed for the bioconcentration factors (BCFs) of nonpolar organic compounds (NPOCs) by using molecular electronegativity distance vector (MEDV) to characterize the structures of NPOCs and variable selection and modeling based on prediction (VSMP) to select the optimum descriptors. The estimated correlation coefficient (r (2)) and the leave-one-out cross-validation correlation coefficients (q (2)) of model M2 were 0.9271 and 0.9171, respectively. The model was externally validated by splitting the whole data set into a representative training set of 85 chemicals and a validation set of 29 chemicals. The results show that the main structural factors influencing the BCFs of NPOCs are -cCc, cCcc, -Cl, and -Br (where "-" refers to a single bond and "c" refers to a conjugated bond). The quantitative structure-property relationship (QSPR) model can effectively predict the BCFs of NPOCs, and the predictions of the model can also extend the current BCF database of experimental values.

  17. External Validation Study of First Trimester Obstetric Prediction Models (Expect Study I): Research Protocol and Population Characteristics.

    PubMed

    Meertens, Linda Jacqueline Elisabeth; Scheepers, Hubertina Cj; De Vries, Raymond G; Dirksen, Carmen D; Korstjens, Irene; Mulder, Antonius Lm; Nieuwenhuijze, Marianne J; Nijhuis, Jan G; Spaanderman, Marc Ea; Smits, Luc Jm

    2017-10-26

    A number of first-trimester prediction models addressing important obstetric outcomes have been published. However, most models have not been externally validated. External validation is essential before implementing a prediction model in clinical practice. The objective of this paper is to describe the design of a study to externally validate existing first trimester obstetric prediction models, based upon maternal characteristics and standard measurements (eg, blood pressure), for the risk of pre-eclampsia (PE), gestational diabetes mellitus (GDM), spontaneous preterm birth (PTB), small-for-gestational-age (SGA) infants, and large-for-gestational-age (LGA) infants among Dutch pregnant women (Expect Study I). The results of a pilot study on the feasibility and acceptability of the recruitment process and the comprehensibility of the Pregnancy Questionnaire 1 are also reported. A multicenter prospective cohort study was performed in The Netherlands between July 1, 2013 and December 31, 2015. First trimester obstetric prediction models were systematically selected from the literature. Predictor variables were measured by the Web-based Pregnancy Questionnaire 1 and pregnancy outcomes were established using the Postpartum Questionnaire 1 and medical records. Information about maternal health-related quality of life, costs, and satisfaction with Dutch obstetric care was collected from a subsample of women. A pilot study was carried out before the official start of inclusion. External validity of the models will be evaluated by assessing discrimination and calibration. Based on the pilot study, minor improvements were made to the recruitment process and online Pregnancy Questionnaire 1. The validation cohort consists of 2614 women. Data analysis of the external validation study is in progress. This study will offer insight into the generalizability of existing, non-invasive first trimester prediction models for various obstetric outcomes in a Dutch obstetric population. An impact study for the evaluation of the best obstetric prediction models in the Dutch setting with respect to their effect on clinical outcomes, costs, and quality of life-Expect Study II-is being planned. Netherlands Trial Registry (NTR): NTR4143; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4143 (Archived by WebCite at http://www.webcitation.org/6t8ijtpd9). ©Linda Jacqueline Elisabeth Meertens, Hubertina CJ Scheepers, Raymond G De Vries, Carmen D Dirksen, Irene Korstjens, Antonius LM Mulder, Marianne J Nieuwenhuijze, Jan G Nijhuis, Marc EA Spaanderman, Luc JM Smits. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 26.10.2017.

  18. Novel naïve Bayes classification models for predicting the carcinogenicity of chemicals.

    PubMed

    Zhang, Hui; Cao, Zhi-Xing; Li, Meng; Li, Yu-Zhi; Peng, Cheng

    2016-11-01

    The carcinogenicity prediction has become a significant issue for the pharmaceutical industry. The purpose of this investigation was to develop a novel prediction model of carcinogenicity of chemicals by using a naïve Bayes classifier. The established model was validated by the internal 5-fold cross validation and external test set. The naïve Bayes classifier gave an average overall prediction accuracy of 90 ± 0.8% for the training set and 68 ± 1.9% for the external test set. Moreover, five simple molecular descriptors (e.g., AlogP, Molecular weight (M W ), No. of H donors, Apol and Wiener) considered as important for the carcinogenicity of chemicals were identified, and some substructures related to the carcinogenicity were achieved. Thus, we hope the established naïve Bayes prediction model could be applied to filter early-stage molecules for this potential carcinogenicity adverse effect; and the identified five simple molecular descriptors and substructures of carcinogens would give a better understanding of the carcinogenicity of chemicals, and further provide guidance for medicinal chemists in the design of new candidate drugs and lead optimization, ultimately reducing the attrition rate in later stages of drug development. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. SU-E-T-206: Improving Radiotherapy Toxicity Based On Artificial Neural Network (ANN) for Head and Neck Cancer Patients

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

    Cho, Daniel D; Wernicke, A Gabriella; Nori, Dattatreyudu

    Purpose/Objective(s): The aim of this study is to build the estimator of toxicity using artificial neural network (ANN) for head and neck cancer patients Materials/Methods: An ANN can combine variables into a predictive model during training and considered all possible correlations of variables. We constructed an ANN based on the data from 73 patients with advanced H and N cancer treated with external beam radiotherapy and/or chemotherapy at our institution. For the toxicity estimator we defined input data including age, sex, site, stage, pathology, status of chemo, technique of external beam radiation therapy (EBRT), length of treatment, dose of EBRT,more » status of post operation, length of follow-up, the status of local recurrences and distant metastasis. These data were digitized based on the significance and fed to the ANN as input nodes. We used 20 hidden nodes (for the 13 input nodes) to take care of the correlations of input nodes. For training ANN, we divided data into three subsets such as training set, validation set and test set. Finally, we built the estimator for the toxicity from ANN output. Results: We used 13 input variables including the status of local recurrences and distant metastasis and 20 hidden nodes for correlations. 59 patients for training set, 7 patients for validation set and 7 patients for test set and fed the inputs to Matlab neural network fitting tool. We trained the data within 15% of errors of outcome. In the end we have the toxicity estimation with 74% of accuracy. Conclusion: We proved in principle that ANN can be a very useful tool for predicting the RT outcomes for high risk H and N patients. Currently we are improving the results using cross validation.« less

  20. Development and validation of a set of six adaptable prognosis prediction (SAP) models based on time-series real-world big data analysis for patients with cancer receiving chemotherapy: A multicenter case crossover study

    PubMed Central

    Kanai, Masashi; Okamoto, Kazuya; Yamamoto, Yosuke; Yoshioka, Akira; Hiramoto, Shuji; Nozaki, Akira; Nishikawa, Yoshitaka; Yamaguchi, Daisuke; Tomono, Teruko; Nakatsui, Masahiko; Baba, Mika; Morita, Tatsuya; Matsumoto, Shigemi; Kuroda, Tomohiro; Okuno, Yasushi; Muto, Manabu

    2017-01-01

    Background We aimed to develop an adaptable prognosis prediction model that could be applied at any time point during the treatment course for patients with cancer receiving chemotherapy, by applying time-series real-world big data. Methods Between April 2004 and September 2014, 4,997 patients with cancer who had received systemic chemotherapy were registered in a prospective cohort database at the Kyoto University Hospital. Of these, 2,693 patients with a death record were eligible for inclusion and divided into training (n = 1,341) and test (n = 1,352) cohorts. In total, 3,471,521 laboratory data at 115,738 time points, representing 40 laboratory items [e.g., white blood cell counts and albumin (Alb) levels] that were monitored for 1 year before the death event were applied for constructing prognosis prediction models. All possible prediction models comprising three different items from 40 laboratory items (40C3 = 9,880) were generated in the training cohort, and the model selection was performed in the test cohort. The fitness of the selected models was externally validated in the validation cohort from three independent settings. Results A prognosis prediction model utilizing Alb, lactate dehydrogenase, and neutrophils was selected based on a strong ability to predict death events within 1–6 months and a set of six prediction models corresponding to 1,2, 3, 4, 5, and 6 months was developed. The area under the curve (AUC) ranged from 0.852 for the 1 month model to 0.713 for the 6 month model. External validation supported the performance of these models. Conclusion By applying time-series real-world big data, we successfully developed a set of six adaptable prognosis prediction models for patients with cancer receiving chemotherapy. PMID:28837592

  1. Personalized Estimate of Chemotherapy-Induced Nausea and Vomiting: Development and External Validation of a Nomogram in Cancer Patients Receiving Highly/Moderately Emetogenic Chemotherapy.

    PubMed

    Hu, Zhihuang; Liang, Wenhua; Yang, Yunpeng; Keefe, Dorothy; Ma, Yuxiang; Zhao, Yuanyuan; Xue, Cong; Huang, Yan; Zhao, Hongyun; Chen, Likun; Chan, Alexandre; Zhang, Li

    2016-01-01

    Chemotherapy-induced nausea and vomiting (CINV) is presented in over 30% of cancer patients receiving highly/moderately emetogenic chemotherapy (HEC/MEC). The currently recommended antiemetic therapy is merely based on the emetogenic level of chemotherapy, regardless of patient's individual risk factors. It is, therefore, critical to develop an approach for personalized management of CINV in the era of precision medicine.A number of variables were involved in the development of CINV. In the present study, we pooled the data from 2 multi-institutional investigations of CINV due to HEC/MEC treatment in Asian countries. Demographic and clinical variables of 881 patients were prospectively collected as defined previously, and 862 of them had full documentation of variables of interest. The data of 548 patients from Chinese institutions were used to identify variables associated with CINV using multivariate logistic regression model, and then construct a personalized prediction model of nomogram; while the remaining 314 patients out of China (Singapore, South Korea, and Taiwan) entered the external validation set. C-index was used to measure the discrimination ability of the model.The predictors in the final model included sex, age, alcohol consumption, history of vomiting pregnancy, history of motion sickness, body surface area, emetogenicity of chemotherapy, and antiemetic regimens. The C-index was 0.67 (95% CI, 0.62-0.72) for the training set and 0.65 (95% CI, 0.58-0.72) for the validation set. The C-index was higher than that of any single predictor, including the emetogenic level of chemotherapy according to current antiemetic guidelines. Calibration curves showed good agreement between prediction and actual occurrence of CINV.This easy-to-use prediction model was based on chemotherapeutic regimens as well as patient's individual risk factors. The prediction accuracy of CINV occurrence in this nomogram was well validated by an independent data set. It could facilitate the assessment of individual risk, and thus improve the personalized management of CINV.

  2. Using the epigenetic field defect to detect prostate cancer in biopsy negative patients.

    PubMed

    Truong, Matthew; Yang, Bing; Livermore, Andrew; Wagner, Jennifer; Weeratunga, Puspha; Huang, Wei; Dhir, Rajiv; Nelson, Joel; Lin, Daniel W; Jarrard, David F

    2013-06-01

    We determined whether a novel combination of field defect DNA methylation markers could predict the presence of prostate cancer using histologically normal transrectal ultrasound guided biopsy cores. Methylation was assessed using quantitative Pyrosequencing® in a training set consisting of 65 nontumor and tumor associated prostate tissues from University of Wisconsin. A multiplex model was generated using multivariate logistic regression and externally validated in blinded fashion in a set of 47 nontumor and tumor associated biopsy specimens from University of Washington. We observed robust methylation differences in all genes at all CpGs assayed (p <0.0001). Regression models incorporating individual genes (EVX1, CAV1 and FGF1) and a gene combination (EVX1 and FGF1) discriminated nontumor from tumor associated tissues in the original training set (AUC 0.796-0.898, p <0.001). On external validation uniplex models incorporating EVX1, CAV1 or FGF1 discriminated tumor from nontumor associated biopsy negative specimens (AUC 0.702, 0.696 and 0.658, respectively, p <0.05). A multiplex model (EVX1 and FGF1) identified patients with prostate cancer (AUC 0.774, p = 0.001) and had a negative predictive value of 0.909. Comparison between 2 separate cores in patients in this validation set revealed similar methylation defects, indicating detection of a widespread field defect. A widespread epigenetic field defect can be used to detect prostate cancer in patients with histologically negative biopsies. To our knowledge this assay is unique, in that it detects alterations in nontumor cells. With further validation this marker combination (EVX1 and FGF1) has the potential to decrease the need for repeat prostate biopsies, a procedure associated with cost and complications. Copyright © 2013 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  3. Pooled individual patient data from five countries were used to derive a clinical prediction rule for coronary artery disease in primary care.

    PubMed

    Aerts, Marc; Minalu, Girma; Bösner, Stefan; Buntinx, Frank; Burnand, Bernard; Haasenritter, Jörg; Herzig, Lilli; Knottnerus, J André; Nilsson, Staffan; Renier, Walter; Sox, Carol; Sox, Harold; Donner-Banzhoff, Norbert

    2017-01-01

    To construct a clinical prediction rule for coronary artery disease (CAD) presenting with chest pain in primary care. Meta-Analysis using 3,099 patients from five studies. To identify candidate predictors, we used random forest trees, multiple imputation of missing values, and logistic regression within individual studies. To generate a prediction rule on the pooled data, we applied a regression model that took account of the differing standard data sets collected by the five studies. The most parsimonious rule included six equally weighted predictors: age ≥55 (males) or ≥65 (females) (+1); attending physician suspected a serious diagnosis (+1); history of CAD (+1); pain brought on by exertion (+1); pain feels like "pressure" (+1); pain reproducible by palpation (-1). CAD was considered absent if the prediction score is <2. The area under the ROC curve was 0.84. We applied this rule to a study setting with a CAD prevalence of 13.2% using a prediction score cutoff of <2 (i.e., -1, 0, or +1). When the score was <2, the probability of CAD was 2.1% (95% CI: 1.1-3.9%); when the score was ≥ 2, it was 43.0% (95% CI: 35.8-50.4%). Clinical prediction rules are a key strategy for individualizing care. Large data sets based on electronic health records from diverse sites create opportunities for improving their internal and external validity. Our patient-level meta-analysis from five primary care sites should improve external validity. Our strategy for addressing site-to-site systematic variation in missing data should improve internal validity. Using principles derived from decision theory, we also discuss the problem of setting the cutoff prediction score for taking action. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. A novel QSAR model of Salmonella mutagenicity and its application in the safety assessment of drug impurities

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

    Valencia, Antoni; Prous, Josep; Mora, Oscar

    As indicated in ICH M7 draft guidance, in silico predictive tools including statistically-based QSARs and expert analysis may be used as a computational assessment for bacterial mutagenicity for the qualification of impurities in pharmaceuticals. To address this need, we developed and validated a QSAR model to predict Salmonella t. mutagenicity (Ames assay outcome) of pharmaceutical impurities using Prous Institute's Symmetry℠, a new in silico solution for drug discovery and toxicity screening, and the Mold2 molecular descriptor package (FDA/NCTR). Data was sourced from public benchmark databases with known Ames assay mutagenicity outcomes for 7300 chemicals (57% mutagens). Of these data, 90%more » was used to train the model and the remaining 10% was set aside as a holdout set for validation. The model's applicability to drug impurities was tested using a FDA/CDER database of 951 structures, of which 94% were found within the model's applicability domain. The predictive performance of the model is acceptable for supporting regulatory decision-making with 84 ± 1% sensitivity, 81 ± 1% specificity, 83 ± 1% concordance and 79 ± 1% negative predictivity based on internal cross-validation, while the holdout dataset yielded 83% sensitivity, 77% specificity, 80% concordance and 78% negative predictivity. Given the importance of having confidence in negative predictions, an additional external validation of the model was also carried out, using marketed drugs known to be Ames-negative, and obtained 98% coverage and 81% specificity. Additionally, Ames mutagenicity data from FDA/CFSAN was used to create another data set of 1535 chemicals for external validation of the model, yielding 98% coverage, 73% sensitivity, 86% specificity, 81% concordance and 84% negative predictivity. - Highlights: • A new in silico QSAR model to predict Ames mutagenicity is described. • The model is extensively validated with chemicals from the FDA and the public domain. • Validation tests show desirable high sensitivity and high negative predictivity. • The model predicted 14 reportedly difficult to predict drug impurities with accuracy. • The model is suitable to support risk evaluation of potentially mutagenic compounds.« less

  5. The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study

    PubMed Central

    Hippisley-Cox, Julia; Coupland, Carol; Brindle, Peter

    2014-01-01

    Objectives To validate the performance of a set of risk prediction algorithms developed using the QResearch database, in an independent sample from general practices contributing to the Clinical Research Data Link (CPRD). Setting Prospective open cohort study using practices contributing to the CPRD database and practices contributing to the QResearch database. Participants The CPRD validation cohort consisted of 3.3 million patients, aged 25–99 years registered at 357 general practices between 1 Jan 1998 and 31 July 2012. The validation statistics for QResearch were obtained from the original published papers which used a one-third sample of practices separate to those used to derive the score. A cohort from QResearch was used to compare incidence rates and baseline characteristics and consisted of 6.8 million patients from 753 practices registered between 1 Jan 1998 and until 31 July 2013. Outcome measures Incident events relating to seven different risk prediction scores: QRISK2 (cardiovascular disease); QStroke (ischaemic stroke); QDiabetes (type 2 diabetes); QFracture (osteoporotic fracture and hip fracture); QKidney (moderate and severe kidney failure); QThrombosis (venous thromboembolism); QBleed (intracranial bleed and upper gastrointestinal haemorrhage). Measures of discrimination and calibration were calculated. Results Overall, the baseline characteristics of the CPRD and QResearch cohorts were similar though QResearch had higher recording levels for ethnicity and family history. The validation statistics for each of the risk prediction scores were very similar in the CPRD cohort compared with the published results from QResearch validation cohorts. For example, in women, the QDiabetes algorithm explained 50% of the variation within CPRD compared with 51% on QResearch and the receiver operator curve value was 0.85 on both databases. The scores were well calibrated in CPRD. Conclusions Each of the algorithms performed practically as well in the external independent CPRD validation cohorts as they had in the original published QResearch validation cohorts. PMID:25168040

  6. Modeling ready biodegradability of fragrance materials.

    PubMed

    Ceriani, Lidia; Papa, Ester; Kovarich, Simona; Boethling, Robert; Gramatica, Paola

    2015-06-01

    In the present study, quantitative structure activity relationships were developed for predicting ready biodegradability of approximately 200 heterogeneous fragrance materials. Two classification methods, classification and regression tree (CART) and k-nearest neighbors (kNN), were applied to perform the modeling. The models were validated with multiple external prediction sets, and the structural applicability domain was verified by the leverage approach. The best models had good sensitivity (internal ≥80%; external ≥68%), specificity (internal ≥80%; external 73%), and overall accuracy (≥75%). Results from the comparison with BIOWIN global models, based on group contribution method, show that specific models developed in the present study perform better in prediction than BIOWIN6, in particular for the correct classification of not readily biodegradable fragrance materials. © 2015 SETAC.

  7. Building Capacity to Support Students with Autism Spectrum Disorder: A Modular Approach to Intervention

    ERIC Educational Resources Information Center

    Anderson, Cynthia M.; Smith, Tristram; Iovannone, Rose

    2018-01-01

    There is a large gap between research-based interventions for supporting children with autism spectrum disorder (ASD) and current practices implemented by educators to meet the needs of these children in typical school settings. Myriad reasons for this gap exist including the external validity of existing research, the complexity of ASD, and…

  8. Classification based upon gene expression data: bias and precision of error rates.

    PubMed

    Wood, Ian A; Visscher, Peter M; Mengersen, Kerrie L

    2007-06-01

    Gene expression data offer a large number of potentially useful predictors for the classification of tissue samples into classes, such as diseased and non-diseased. The predictive error rate of classifiers can be estimated using methods such as cross-validation. We have investigated issues of interpretation and potential bias in the reporting of error rate estimates. The issues considered here are optimization and selection biases, sampling effects, measures of misclassification rate, baseline error rates, two-level external cross-validation and a novel proposal for detection of bias using the permutation mean. Reporting an optimal estimated error rate incurs an optimization bias. Downward bias of 3-5% was found in an existing study of classification based on gene expression data and may be endemic in similar studies. Using a simulated non-informative dataset and two example datasets from existing studies, we show how bias can be detected through the use of label permutations and avoided using two-level external cross-validation. Some studies avoid optimization bias by using single-level cross-validation and a test set, but error rates can be more accurately estimated via two-level cross-validation. In addition to estimating the simple overall error rate, we recommend reporting class error rates plus where possible the conditional risk incorporating prior class probabilities and a misclassification cost matrix. We also describe baseline error rates derived from three trivial classifiers which ignore the predictors. R code which implements two-level external cross-validation with the PAMR package, experiment code, dataset details and additional figures are freely available for non-commercial use from http://www.maths.qut.edu.au/profiles/wood/permr.jsp

  9. Computational identification of structural factors affecting the mutagenic potential of aromatic amines: study design and experimental validation.

    PubMed

    Slavov, Svetoslav H; Stoyanova-Slavova, Iva; Mattes, William; Beger, Richard D; Brüschweiler, Beat J

    2018-07-01

    A grid-based, alignment-independent 3D-SDAR (three-dimensional spectral data-activity relationship) approach based on simulated 13 C and 15 N NMR chemical shifts augmented with through-space interatomic distances was used to model the mutagenicity of 554 primary and 419 secondary aromatic amines. A robust modeling strategy supported by extensive validation including randomized training/hold-out test set pairs, validation sets, "blind" external test sets as well as experimental validation was applied to avoid over-parameterization and build Organization for Economic Cooperation and Development (OECD 2004) compliant models. Based on an experimental validation set of 23 chemicals tested in a two-strain Salmonella typhimurium Ames assay, 3D-SDAR was able to achieve performance comparable to 5-strain (Ames) predictions by Lhasa Limited's Derek and Sarah Nexus for the same set. Furthermore, mapping of the most frequently occurring bins on the primary and secondary aromatic amine structures allowed the identification of molecular features that were associated either positively or negatively with mutagenicity. Prominent structural features found to enhance the mutagenic potential included: nitrobenzene moieties, conjugated π-systems, nitrothiophene groups, and aromatic hydroxylamine moieties. 3D-SDAR was also able to capture "true" negative contributions that are particularly difficult to detect through alternative methods. These include sulphonamide, acetamide, and other functional groups, which not only lack contributions to the overall mutagenic potential, but are known to actively lower it, if present in the chemical structures of what otherwise would be potential mutagens.

  10. Quantitative structure-activity relationships for organophosphates binding to acetylcholinesterase.

    PubMed

    Ruark, Christopher D; Hack, C Eric; Robinson, Peter J; Anderson, Paul E; Gearhart, Jeffery M

    2013-02-01

    Organophosphates are a group of pesticides and chemical warfare nerve agents that inhibit acetylcholinesterase, the enzyme responsible for hydrolysis of the excitatory neurotransmitter acetylcholine. Numerous structural variants exist for this chemical class, and data regarding their toxicity can be difficult to obtain in a timely fashion. At the same time, their use as pesticides and military weapons is widespread, which presents a major concern and challenge in evaluating human toxicity. To address this concern, a quantitative structure-activity relationship (QSAR) was developed to predict pentavalent organophosphate oxon human acetylcholinesterase bimolecular rate constants. A database of 278 three-dimensional structures and their bimolecular rates was developed from 15 peer-reviewed publications. A database of simplified molecular input line entry notations and their respective acetylcholinesterase bimolecular rate constants are listed in Supplementary Material, Table I. The database was quite diverse, spanning 7 log units of activity. In order to describe their structure, 675 molecular descriptors were calculated using AMPAC 8.0 and CODESSA 2.7.10. Orthogonal projection to latent structures regression, bootstrap leave-random-many-out cross-validation and y-randomization were used to develop an externally validated consensus QSAR model. The domain of applicability was assessed by the William's plot. Six external compounds were outside the warning leverage indicating potential model extrapolation. A number of compounds had residuals >2 or <-2, indicating potential outliers or activity cliffs. The results show that the HOMO-LUMO energy gap contributed most significantly to the binding affinity. A mean training R (2) of 0.80, a mean test set R (2) of 0.76 and a consensus external test set R (2) of 0.66 were achieved using the QSAR. The training and external test set RMSE values were found to be 0.76 and 0.88. The results suggest that this QSAR model can be used in physiologically based pharmacokinetic/pharmacodynamic models of organophosphate toxicity to determine the rate of acetylcholinesterase inhibition.

  11. Can Findings from Randomized Controlled Trials of Social Skills Training in Autism Spectrum Disorder Be Generalized? The Neglected Dimension of External Validity

    ERIC Educational Resources Information Center

    Jonsson, Ulf; Olsson, Nora Choque; Bölte, Sven

    2016-01-01

    Systematic reviews have traditionally focused on internal validity, while external validity often has been overlooked. In this study, we systematically reviewed determinants of external validity in the accumulated randomized controlled trials of social skills group interventions for children and adolescents with autism spectrum disorder. We…

  12. External Validity, Internal Validity, and Organizational Reality: A Response to Robert L. Cardy (Commentary).

    ERIC Educational Resources Information Center

    Steinfatt, Thomas M.

    1991-01-01

    Responds to an article in the same issue of this journal which defends the applied value of laboratory studies to managers. Agrees that external validity is often irrelevant, and maintains that the problem of making inferences from any subject sample in management communication is one that demands internal, not external, validity. (SR)

  13. Andragogy and medical education: are medical students internally motivated to learn?

    PubMed

    Misch, Donald A

    2002-01-01

    Andragogy - the study of adult education - has been endorsed by many medical educators throughout North America. There remains, however, considerable controversy as to the validity and utility of adult education principles as espoused by the field's founder, Malcolm Knowles. Whatever the utility of andragogic doctrine in general education settings, there is reason to doubt its wholesale applicability to the training of medical professionals. Malcolm Knowles' last tenet of andragogy holds that adult learners are more motivated by internal than by external factors. The validity of this hypothesis in medical education is examined, and it is demonstrated that medical students' internal and external motivation are context-dependent, not easily distinguishable, and interrelate with one another in complex ways. Furthermore, the psychological motivation for medical student learning is determined by a variety of factors that range from internal to external, unconscious to conscious, and individual to societal. The andragogic hypothesis of increased internal motivation to learn on the part of adults in general, and medical trainees in particular, is rejected as simplistic, misleading, and counterproductive to developing a greater understanding of the forces that drive medical students to learn.

  14. External model validation of binary clinical risk prediction models in cardiovascular and thoracic surgery.

    PubMed

    Hickey, Graeme L; Blackstone, Eugene H

    2016-08-01

    Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

  15. Assessing the generalizability of randomized trial results to target populations.

    PubMed

    Stuart, Elizabeth A; Bradshaw, Catherine P; Leaf, Philip J

    2015-04-01

    Recent years have seen increasing interest in and attention to evidence-based practices, where the "evidence" generally comes from well-conducted randomized trials. However, while those trials yield accurate estimates of the effect of the intervention for the participants in the trial (known as "internal validity"), they do not always yield relevant information about the effects in a particular target population (known as "external validity"). This may be due to a lack of specification of a target population when designing the trial, difficulties recruiting a sample that is representative of a prespecified target population, or to interest in considering a target population somewhat different from the population directly targeted by the trial. This paper first provides an overview of existing design and analysis methods for assessing and enhancing the ability of a randomized trial to estimate treatment effects in a target population. It then provides a case study using one particular method, which weights the subjects in a randomized trial to match the population on a set of observed characteristics. The case study uses data from a randomized trial of school-wide positive behavioral interventions and supports (PBIS); our interest is in generalizing the results to the state of Maryland. In the case of PBIS, after weighting, estimated effects in the target population were similar to those observed in the randomized trial. The paper illustrates that statistical methods can be used to assess and enhance the external validity of randomized trials, making the results more applicable to policy and clinical questions. However, there are also many open research questions; future research should focus on questions of treatment effect heterogeneity and further developing these methods for enhancing external validity. Researchers should think carefully about the external validity of randomized trials and be cautious about extrapolating results to specific populations unless they are confident of the similarity between the trial sample and that target population.

  16. An Empiric HIV Risk Scoring Tool to Predict HIV-1 Acquisition in African Women.

    PubMed

    Balkus, Jennifer E; Brown, Elizabeth; Palanee, Thesla; Nair, Gonasagrie; Gafoor, Zakir; Zhang, Jingyang; Richardson, Barbra A; Chirenje, Zvavahera M; Marrazzo, Jeanne M; Baeten, Jared M

    2016-07-01

    To develop and validate an HIV risk assessment tool to predict HIV acquisition among African women. Data were analyzed from 3 randomized trials of biomedical HIV prevention interventions among African women (VOICE, HPTN 035, and FEM-PrEP). We implemented standard methods for the development of clinical prediction rules to generate a risk-scoring tool to predict HIV acquisition over the course of 1 year. Performance of the score was assessed through internal and external validations. The final risk score resulting from multivariable modeling included age, married/living with a partner, partner provides financial or material support, partner has other partners, alcohol use, detection of a curable sexually transmitted infection, and herpes simplex virus 2 serostatus. Point values for each factor ranged from 0 to 2, with a maximum possible total score of 11. Scores ≥5 were associated with HIV incidence >5 per 100 person-years and identified 91% of incident HIV infections from among only 64% of women. The area under the curve (AUC) for predictive ability of the score was 0.71 (95% confidence interval [CI]: 0.68 to 0.74), indicating good predictive ability. Risk score performance was generally similar with internal cross-validation (AUC = 0.69; 95% CI: 0.66 to 0.73) and external validation in HPTN 035 (AUC = 0.70; 95% CI: 0.65 to 0.75) and FEM-PrEP (AUC = 0.58; 95% CI: 0.51 to 0.65). A discrete set of characteristics that can be easily assessed in clinical and research settings was predictive of HIV acquisition over 1 year. The use of a validated risk score could improve efficiency of recruitment into HIV prevention research and inform scale-up of HIV prevention strategies in women at highest risk.

  17. Network evolution model for supply chain with manufactures as the core.

    PubMed

    Fang, Haiyang; Jiang, Dali; Yang, Tinghong; Fang, Ling; Yang, Jian; Li, Wu; Zhao, Jing

    2018-01-01

    Building evolution model of supply chain networks could be helpful to understand its development law. However, specific characteristics and attributes of real supply chains are often neglected in existing evolution models. This work proposes a new evolution model of supply chain with manufactures as the core, based on external market demand and internal competition-cooperation. The evolution model assumes the external market environment is relatively stable, considers several factors, including specific topology of supply chain, external market demand, ecological growth and flow conservation. The simulation results suggest that the networks evolved by our model have similar structures as real supply chains. Meanwhile, the influences of external market demand and internal competition-cooperation to network evolution are analyzed. Additionally, 38 benchmark data sets are applied to validate the rationality of our evolution model, in which, nine manufacturing supply chains match the features of the networks constructed by our model.

  18. Network evolution model for supply chain with manufactures as the core

    PubMed Central

    Jiang, Dali; Fang, Ling; Yang, Jian; Li, Wu; Zhao, Jing

    2018-01-01

    Building evolution model of supply chain networks could be helpful to understand its development law. However, specific characteristics and attributes of real supply chains are often neglected in existing evolution models. This work proposes a new evolution model of supply chain with manufactures as the core, based on external market demand and internal competition-cooperation. The evolution model assumes the external market environment is relatively stable, considers several factors, including specific topology of supply chain, external market demand, ecological growth and flow conservation. The simulation results suggest that the networks evolved by our model have similar structures as real supply chains. Meanwhile, the influences of external market demand and internal competition-cooperation to network evolution are analyzed. Additionally, 38 benchmark data sets are applied to validate the rationality of our evolution model, in which, nine manufacturing supply chains match the features of the networks constructed by our model. PMID:29370201

  19. Predictions of BuChE inhibitors using support vector machine and naive Bayesian classification techniques in drug discovery.

    PubMed

    Fang, Jiansong; Yang, Ranyao; Gao, Li; Zhou, Dan; Yang, Shengqian; Liu, Ai-Lin; Du, Guan-hua

    2013-11-25

    Butyrylcholinesterase (BuChE, EC 3.1.1.8) is an important pharmacological target for Alzheimer's disease (AD) treatment. However, the currently available BuChE inhibitor screening assays are expensive, labor-intensive, and compound-dependent. It is necessary to develop robust in silico methods to predict the activities of BuChE inhibitors for the lead identification. In this investigation, support vector machine (SVM) models and naive Bayesian models were built to discriminate BuChE inhibitors (BuChEIs) from the noninhibitors. Each molecule was initially represented in 1870 structural descriptors (1235 from ADRIANA.Code, 334 from MOE, and 301 from Discovery studio). Correlation analysis and stepwise variable selection method were applied to figure out activity-related descriptors for prediction models. Additionally, structural fingerprint descriptors were added to improve the predictive ability of models, which were measured by cross-validation, a test set validation with 1001 compounds and an external test set validation with 317 diverse chemicals. The best two models gave Matthews correlation coefficient of 0.9551 and 0.9550 for the test set and 0.9132 and 0.9221 for the external test set. To demonstrate the practical applicability of the models in virtual screening, we screened an in-house data set with 3601 compounds, and 30 compounds were selected for further bioactivity assay. The assay results showed that 10 out of 30 compounds exerted significant BuChE inhibitory activities with IC50 values ranging from 0.32 to 22.22 μM, at which three new scaffolds as BuChE inhibitors were identified for the first time. To our best knowledge, this is the first report on BuChE inhibitors using machine learning approaches. The models generated from SVM and naive Bayesian approaches successfully predicted BuChE inhibitors. The study proved the feasibility of a new method for predicting bioactivities of ligands and discovering novel lead compounds.

  20. SET-bullying: presentation of a collaborative project and discussion of its internal and external validity.

    PubMed

    Chalamandaris, Alexandros-Georgios; Wilmet-Dramaix, Michèle; Eslea, Mike; Ertesvåg, Sigrun Karin; Piette, Danielle

    2016-04-12

    Since the early 1980s, several school based anti-bullying interventions (SBABI) have been implemented and evaluated in different countries. Some meta-analyses have also drawn conclusions on the effectiveness of SBABIs. However, the relationship between time and effectiveness of SBABIs has not been fully studied. For this aim, a collaborative project, SET-Bullying, is established by researchers from Greece, Belgium, Norway and United Kingdom. Its primary objective is to further understand and statistically model the relationship between the time and the sustainability of the effectiveness of SBABI. The secondary objective of SET-Bullying is to assess the possibility of predicting the medium-term or long-term effectiveness using as key information the prior measurement and the short-term effectiveness of the intervention. Researchers and owners of potentially eligible databases were asked to participate in this effort. Two studies have contributed data for the purpose of SET-Bullying. This paper summarizes the main characteristics of the participating studies and provides a high level overview of the collaborative project. It also discusses on the extent to which both study and project characteristics may pose threats to the expected internal and external validity of the potential outcomes of the project. Despite these threats, this work represents the first effort to understand the impact of time on the observed effectiveness of SBABIs and assess its predictability, which would allow for better planning, implementation and evaluation of SBABIs.

  1. Determinants of Success on the ETS Business Major Field Exam for Students in an Undergraduate Multisite Regional University Business Program

    ERIC Educational Resources Information Center

    Bagamery, Bruce D.; Lasik, John J.; Nixon, Don R.

    2005-01-01

    Extending previous studies, the authors examined a larger set of variables to identify predictors of student performance on the Educational Testing Service Major Field Exam in Business, which has been shown to be an externally valid measure of student learning outcomes. Significant predictors include gender, whether students took the SAT, and…

  2. QSAR studies on triazole derivatives as sglt inhibitors via CoMFA and CoMSIA

    NASA Astrophysics Data System (ADS)

    Zhi, Hui; Zheng, Junxia; Chang, Yiqun; Li, Qingguo; Liao, Guochao; Wang, Qi; Sun, Pinghua

    2015-10-01

    Forty-six sodium-dependent glucose cotransporters-2 (SGLT-2) inhibitors with hypoglycemic activity were selected to develop three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. A training set of 39 compounds were used to build up the models, which were then evaluated by a series of internal and external cross-validation techniques. A test set of 7 compounds was used for the external validation. The CoMFA model predicted a q2 value of 0.792 and an r2 value of 0.985. The best CoMSIA model predicted a q2 value of 0.633 and an r2 value of 0.895 based on a combination of steric, electrostatic, hydrophobic and hydrogen-bond acceptor effects. The predictive correlation coefficients (rpred2) of CoMFA and CoMSIA models were 0.872 and 0.839, respectively. The analysis of the contour maps from each model provided insight into the structural requirements for the development of more active sglt inhibitors, and on the basis of the models 8 new sglt inhibitors were designed and predicted.

  3. Measuring Eccentric Strength of the Shoulder External Rotators Using a Handheld Dynamometer: Reliability and Validity

    PubMed Central

    Johansson, Fredrik R.; Skillgate, Eva; Lapauw, Mattis L.; Clijmans, Dorien; Deneulin, Valentijn P.; Palmans, Tanneke; Engineer, Human Kinetic; Cools, Ann M.

    2015-01-01

    Context Shoulder strength assessment plays an important role in the clinical examination of the shoulder region. Eccentric strength measurements are of special importance in guiding the clinician in injury prevention or return-to-play decisions after injury. Objective To examine the absolute and relative reliability and validity of a standardized eccentric strength-measurement protocol for the glenohumeral external rotators. Design Descriptive laboratory study. Setting Testing environment at the Department of Rehabilitation Sciences and Physiotherapy of Ghent University, Belgium. Patients or Other Participants Twenty-five healthy participants (9 men and 16 women) without any history of shoulder pain were tested by 2 independent assessors using a handheld dynamometer (HHD) and underwent an isokinetic testing procedure. Intervention(s) The clinical protocol used an HHD, a DynaPort accelerometer to measure acceleration and angular velocity of testing 30°/s over 90° of range of motion, and a Biodex dynamometer to measure isokinetic activity. Main Outcome Measure(s) Three eccentric strength measurements: (1) tester 1 with the HHD, (2) tester 2 with the HHD, and (3) Biodex isokinetic strength measurement. Results The intratester reliability was excellent (0.879 and 0.858), whereas the intertester reliability was good, with an intraclass correlation coefficient between testers of 0.714. Pearson product moment correlation coefficients of 0.78 and 0.70 were noted between the HHD and the isokinetic data, showing good validity of this new procedure. Conclusions Standardized eccentric rotator cuff strength can be tested and measured in the clinical setting with good-to-excellent reliability and validity using an HHD. PMID:25974381

  4. Early detection of lung cancer recurrence after stereotactic ablative radiation therapy: radiomics system design

    NASA Astrophysics Data System (ADS)

    Dammak, Salma; Palma, David; Mattonen, Sarah; Senan, Suresh; Ward, Aaron D.

    2018-02-01

    Stereotactic ablative radiotherapy (SABR) is the standard treatment recommendation for Stage I non-small cell lung cancer (NSCLC) patients who are inoperable or who refuse surgery. This option is well tolerated by even unfit patients and has a low recurrence risk post-treatment. However, SABR induces changes in the lung parenchyma that can appear similar to those of recurrence, and the difference between the two at an early follow-up time point is not easily distinguishable for an expert physician. We hypothesized that a radiomics signature derived from standard-of-care computed tomography (CT) imaging can detect cancer recurrence within six months of SABR treatment. This study reports on the design phase of our work, with external validation planned in future work. In this study, we performed cross-validation experiments with four feature selection approaches and seven classifiers on an 81-patient data set. We extracted 104 radiomics features from the consolidative and the peri-consolidative regions on the follow-up CT scans. The best results were achieved using the sum of estimated Mahalanobis distances (Maha) for supervised forward feature selection and a trainable automatic radial basis support vector classifier (RBSVC). This system produced an area under the receiver operating characteristic curve (AUC) of 0.84, an error rate of 16.4%, a false negative rate of 12.7%, and a false positive rate of 20.0% for leaveone patient out cross-validation. This suggests that once validated on an external data set, radiomics could reliably detect post-SABR recurrence and form the basis of a tool assisting physicians in making salvage treatment decisions.

  5. Temporal and external validation of a prediction model for adverse outcomes among inpatients with diabetes.

    PubMed

    Adderley, N J; Mallett, S; Marshall, T; Ghosh, S; Rayman, G; Bellary, S; Coleman, J; Akiboye, F; Toulis, K A; Nirantharakumar, K

    2018-06-01

    To temporally and externally validate our previously developed prediction model, which used data from University Hospitals Birmingham to identify inpatients with diabetes at high risk of adverse outcome (mortality or excessive length of stay), in order to demonstrate its applicability to other hospital populations within the UK. Temporal validation was performed using data from University Hospitals Birmingham and external validation was performed using data from both the Heart of England NHS Foundation Trust and Ipswich Hospital. All adult inpatients with diabetes were included. Variables included in the model were age, gender, ethnicity, admission type, intensive therapy unit admission, insulin therapy, albumin, sodium, potassium, haemoglobin, C-reactive protein, estimated GFR and neutrophil count. Adverse outcome was defined as excessive length of stay or death. Model discrimination in the temporal and external validation datasets was good. In temporal validation using data from University Hospitals Birmingham, the area under the curve was 0.797 (95% CI 0.785-0.810), sensitivity was 70% (95% CI 67-72) and specificity was 75% (95% CI 74-76). In external validation using data from Heart of England NHS Foundation Trust, the area under the curve was 0.758 (95% CI 0.747-0.768), sensitivity was 73% (95% CI 71-74) and specificity was 66% (95% CI 65-67). In external validation using data from Ipswich, the area under the curve was 0.736 (95% CI 0.711-0.761), sensitivity was 63% (95% CI 59-68) and specificity was 69% (95% CI 67-72). These results were similar to those for the internally validated model derived from University Hospitals Birmingham. The prediction model to identify patients with diabetes at high risk of developing an adverse event while in hospital performed well in temporal and external validation. The externally validated prediction model is a novel tool that can be used to improve care pathways for inpatients with diabetes. Further research to assess clinical utility is needed. © 2018 Diabetes UK.

  6. A score to estimate the likelihood of detecting advanced colorectal neoplasia at colonoscopy

    PubMed Central

    Kaminski, Michal F; Polkowski, Marcin; Kraszewska, Ewa; Rupinski, Maciej; Butruk, Eugeniusz; Regula, Jaroslaw

    2014-01-01

    Objective This study aimed to develop and validate a model to estimate the likelihood of detecting advanced colorectal neoplasia in Caucasian patients. Design We performed a cross-sectional analysis of database records for 40-year-old to 66-year-old patients who entered a national primary colonoscopy-based screening programme for colorectal cancer in 73 centres in Poland in the year 2007. We used multivariate logistic regression to investigate the associations between clinical variables and the presence of advanced neoplasia in a randomly selected test set, and confirmed the associations in a validation set. We used model coefficients to develop a risk score for detection of advanced colorectal neoplasia. Results Advanced colorectal neoplasia was detected in 2544 of the 35 918 included participants (7.1%). In the test set, a logistic-regression model showed that independent risk factors for advanced colorectal neoplasia were: age, sex, family history of colorectal cancer, cigarette smoking (p<0.001 for these four factors), and Body Mass Index (p=0.033). In the validation set, the model was well calibrated (ratio of expected to observed risk of advanced neoplasia: 1.00 (95% CI 0.95 to 1.06)) and had moderate discriminatory power (c-statistic 0.62). We developed a score that estimated the likelihood of detecting advanced neoplasia in the validation set, from 1.32% for patients scoring 0, to 19.12% for patients scoring 7–8. Conclusions Developed and internally validated score consisting of simple clinical factors successfully estimates the likelihood of detecting advanced colorectal neoplasia in asymptomatic Caucasian patients. Once externally validated, it may be useful for counselling or designing primary prevention studies. PMID:24385598

  7. A score to estimate the likelihood of detecting advanced colorectal neoplasia at colonoscopy.

    PubMed

    Kaminski, Michal F; Polkowski, Marcin; Kraszewska, Ewa; Rupinski, Maciej; Butruk, Eugeniusz; Regula, Jaroslaw

    2014-07-01

    This study aimed to develop and validate a model to estimate the likelihood of detecting advanced colorectal neoplasia in Caucasian patients. We performed a cross-sectional analysis of database records for 40-year-old to 66-year-old patients who entered a national primary colonoscopy-based screening programme for colorectal cancer in 73 centres in Poland in the year 2007. We used multivariate logistic regression to investigate the associations between clinical variables and the presence of advanced neoplasia in a randomly selected test set, and confirmed the associations in a validation set. We used model coefficients to develop a risk score for detection of advanced colorectal neoplasia. Advanced colorectal neoplasia was detected in 2544 of the 35,918 included participants (7.1%). In the test set, a logistic-regression model showed that independent risk factors for advanced colorectal neoplasia were: age, sex, family history of colorectal cancer, cigarette smoking (p<0.001 for these four factors), and Body Mass Index (p=0.033). In the validation set, the model was well calibrated (ratio of expected to observed risk of advanced neoplasia: 1.00 (95% CI 0.95 to 1.06)) and had moderate discriminatory power (c-statistic 0.62). We developed a score that estimated the likelihood of detecting advanced neoplasia in the validation set, from 1.32% for patients scoring 0, to 19.12% for patients scoring 7-8. Developed and internally validated score consisting of simple clinical factors successfully estimates the likelihood of detecting advanced colorectal neoplasia in asymptomatic Caucasian patients. Once externally validated, it may be useful for counselling or designing primary prevention studies. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  8. Beware of external validation! - A Comparative Study of Several Validation Techniques used in QSAR Modelling.

    PubMed

    Majumdar, Subhabrata; Basak, Subhash C

    2018-04-26

    Proper validation is an important aspect of QSAR modelling. External validation is one of the widely used validation methods in QSAR where the model is built on a subset of the data and validated on the rest of the samples. However, its effectiveness for datasets with a small number of samples but large number of predictors remains suspect. Calculating hundreds or thousands of molecular descriptors using currently available software has become the norm in QSAR research, owing to computational advances in the past few decades. Thus, for n chemical compounds and p descriptors calculated for each molecule, the typical chemometric dataset today has high value of p but small n (i.e. n < p). Motivated by the evidence of inadequacies of external validation in estimating the true predictive capability of a statistical model in recent literature, this paper performs an extensive and comparative study of this method with several other validation techniques. We compared four validation methods: leave-one-out, K-fold, external and multi-split validation, using statistical models built using the LASSO regression, which simultaneously performs variable selection and modelling. We used 300 simulated datasets and one real dataset of 95 congeneric amine mutagens for this evaluation. External validation metrics have high variation among different random splits of the data, hence are not recommended for predictive QSAR models. LOO has the overall best performance among all validation methods applied in our scenario. Results from external validation are too unstable for the datasets we analyzed. Based on our findings, we recommend using the LOO procedure for validating QSAR predictive models built on high-dimensional small-sample data. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  9. Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data.

    PubMed

    Ribay, Kathryn; Kim, Marlene T; Wang, Wenyi; Pinolini, Daniel; Zhu, Hao

    2016-03-01

    Estrogen receptors (ERα) are a critical target for drug design as well as a potential source of toxicity when activated unintentionally. Thus, evaluating potential ERα binding agents is critical in both drug discovery and chemical toxicity areas. Using computational tools, e.g., Quantitative Structure-Activity Relationship (QSAR) models, can predict potential ERα binding agents before chemical synthesis. The purpose of this project was to develop enhanced predictive models of ERα binding agents by utilizing advanced cheminformatics tools that can integrate publicly available bioassay data. The initial ERα binding agent data set, consisting of 446 binders and 8307 non-binders, was obtained from the Tox21 Challenge project organized by the NIH Chemical Genomics Center (NCGC). After removing the duplicates and inorganic compounds, this data set was used to create a training set (259 binders and 259 non-binders). This training set was used to develop QSAR models using chemical descriptors. The resulting models were then used to predict the binding activity of 264 external compounds, which were available to us after the models were developed. The cross-validation results of training set [Correct Classification Rate (CCR) = 0.72] were much higher than the external predictivity of the unknown compounds (CCR = 0.59). To improve the conventional QSAR models, all compounds in the training set were used to search PubChem and generate a profile of their biological responses across thousands of bioassays. The most important bioassays were prioritized to generate a similarity index that was used to calculate the biosimilarity score between each two compounds. The nearest neighbors for each compound within the set were then identified and its ERα binding potential was predicted by its nearest neighbors in the training set. The hybrid model performance (CCR = 0.94 for cross validation; CCR = 0.68 for external prediction) showed significant improvement over the original QSAR models, particularly for the activity cliffs that induce prediction errors. The results of this study indicate that the response profile of chemicals from public data provides useful information for modeling and evaluation purposes. The public big data resources should be considered along with chemical structure information when predicting new compounds, such as unknown ERα binding agents.

  10. Development and validity of a scale to measure workplace culture of health.

    PubMed

    Kwon, Youngbum; Marzec, Mary L; Edington, Dee W

    2015-05-01

    To describe the development of and test the validity and reliability of the Workplace Culture of Health (COH) scale. Exploratory factor analysis and confirmatory factor analysis were performed on data from a health care organization (N = 627). To verify the factor structure, confirmatory factor analysis was performed on a second data set from a medical equipment manufacturer (N = 226). The COH scale included a structure of five orthogonal factors: senior leadership and polices, programs and rewards, quality assurance, supervisor support, and coworker support. With regard to construct validity (convergent and discriminant) and reliability, two different US companies showed the same factorial structure, satisfactory fit statistics, and suitable internal and external consistency. The COH scale represents a reliable and valid scale to assess the workplace environment and culture for supporting health.

  11. Validation of psychoanalytic theories: towards a conceptualization of references.

    PubMed

    Zachrisson, Anders; Zachrisson, Henrik Daae

    2005-10-01

    The authors discuss criteria for the validation of psychoanalytic theories and develop a heuristic and normative model of the references needed for this. Their core question in this paper is: can psychoanalytic theories be validated exclusively from within psychoanalytic theory (internal validation), or are references to sources of knowledge other than psychoanalysis also necessary (external validation)? They discuss aspects of the classic truth criteria correspondence and coherence, both from the point of view of contemporary psychoanalysis and of contemporary philosophy of science. The authors present arguments for both external and internal validation. Internal validation has to deal with the problems of subjectivity of observations and circularity of reasoning, external validation with the problem of relevance. They recommend a critical attitude towards psychoanalytic theories, which, by carefully scrutinizing weak points and invalidating observations in the theories, reduces the risk of wishful thinking. The authors conclude by sketching a heuristic model of validation. This model combines correspondence and coherence with internal and external validation into a four-leaf model for references for the process of validating psychoanalytic theories.

  12. Are cannabis prevalence estimates comparable across countries and regions? A cross-cultural validation using search engine query data.

    PubMed

    Steppan, Martin; Kraus, Ludwig; Piontek, Daniela; Siciliano, Valeria

    2013-01-01

    Prevalence estimation of cannabis use is usually based on self-report data. Although there is evidence on the reliability of this data source, its cross-cultural validity is still a major concern. External objective criteria are needed for this purpose. In this study, cannabis-related search engine query data are used as an external criterion. Data on cannabis use were taken from the 2007 European School Survey Project on Alcohol and Other Drugs (ESPAD). Provincial data came from three Italian nation-wide studies using the same methodology (2006-2008; ESPAD-Italia). Information on cannabis-related search engine query data was based on Google search volume indices (GSI). (1) Reliability analysis was conducted for GSI. (2) Latent measurement models of "true" cannabis prevalence were tested using perceived availability, web-based cannabis searches and self-reported prevalence as indicators. (3) Structure models were set up to test the influences of response tendencies and geographical position (latitude, longitude). In order to test the stability of the models, analyses were conducted on country level (Europe, US) and on provincial level in Italy. Cannabis-related GSI were found to be highly reliable and constant over time. The overall measurement model was highly significant in both data sets. On country level, no significant effects of response bias indicators and geographical position on perceived availability, web-based cannabis searches and self-reported prevalence were found. On provincial level, latitude had a significant positive effect on availability indicating that perceived availability of cannabis in northern Italy was higher than expected from the other indicators. Although GSI showed weaker associations with cannabis use than perceived availability, the findings underline the external validity and usefulness of search engine query data as external criteria. The findings suggest an acceptable relative comparability of national (provincial) prevalence estimates of cannabis use that are based on a common survey methodology. Search engine query data are a too weak indicator to base prevalence estimations on this source only, but in combination with other sources (waste water analysis, sales of cigarette paper) they may provide satisfactory estimates. Copyright © 2012. Published by Elsevier B.V.

  13. Prediction of biodegradability from chemical structure: Modeling or ready biodegradation test data

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

    Loonen, H.; Lindgren, F.; Hansen, B.

    1999-08-01

    Biodegradation data were collected and evaluated for 894 substances with widely varying chemical structures. All data were determined according to the Japanese Ministry of International Trade and Industry (MITI) I test protocol. The MITI I test is a screening test for ready biodegradability and has been described by Organization for Economic Cooperation and Development (OECD) test guideline 301 C and European Union (EU) test guideline C4F. The chemicals were characterized by a set of 127 predefined structural fragments. This data set was used to develop a model for the prediction of the biodegradability of chemicals under standardized OECD and EUmore » ready biodegradation test conditions. Partial least squares (PLS) discriminant analysis was used for the model development. The model was evaluated by means of internal cross-validation and repeated external validation. The importance of various structural fragments and fragment interactions was investigated. The most important fragments include the presence of a long alkyl chain; hydroxy, ester, and acid groups (enhancing biodegradation); and the presence of one or more aromatic rings and halogen substituents (regarding biodegradation). More than 85% of the model predictions were correct for using the complete data set. The not readily biodegradable predictions were slightly better than the readily biodegradable predictions (86 vs 84%). The average percentage of correct predictions from four external validation studies was 83%. Model optimization by including fragment interactions improve the model predicting capabilities to 89%. It can be concluded that the PLS model provides predictions of high reliability for a diverse range of chemical structures. The predictions conform to the concept of readily biodegradable (or not readily biodegradable) as defined by OECD and EU test guidelines.« less

  14. Survival analysis with error-prone time-varying covariates: a risk set calibration approach

    PubMed Central

    Liao, Xiaomei; Zucker, David M.; Li, Yi; Spiegelman, Donna

    2010-01-01

    Summary Occupational, environmental, and nutritional epidemiologists are often interested in estimating the prospective effect of time-varying exposure variables such as cumulative exposure or cumulative updated average exposure, in relation to chronic disease endpoints such as cancer incidence and mortality. From exposure validation studies, it is apparent that many of the variables of interest are measured with moderate to substantial error. Although the ordinary regression calibration approach is approximately valid and efficient for measurement error correction of relative risk estimates from the Cox model with time-independent point exposures when the disease is rare, it is not adaptable for use with time-varying exposures. By re-calibrating the measurement error model within each risk set, a risk set regression calibration method is proposed for this setting. An algorithm for a bias-corrected point estimate of the relative risk using an RRC approach is presented, followed by the derivation of an estimate of its variance, resulting in a sandwich estimator. Emphasis is on methods applicable to the main study/external validation study design, which arises in important applications. Simulation studies under several assumptions about the error model were carried out, which demonstrated the validity and efficiency of the method in finite samples. The method was applied to a study of diet and cancer from Harvard’s Health Professionals Follow-up Study (HPFS). PMID:20486928

  15. LQTA-QSAR: a new 4D-QSAR methodology.

    PubMed

    Martins, João Paulo A; Barbosa, Euzébio G; Pasqualoto, Kerly F M; Ferreira, Márcia M C

    2009-06-01

    A novel 4D-QSAR approach which makes use of the molecular dynamics (MD) trajectories and topology information retrieved from the GROMACS package is presented in this study. This new methodology, named LQTA-QSAR (LQTA, Laboratório de Quimiometria Teórica e Aplicada), has a module (LQTAgrid) that calculates intermolecular interaction energies at each grid point considering probes and all aligned conformations resulting from MD simulations. These interaction energies are the independent variables or descriptors employed in a QSAR analysis. The comparison of the proposed methodology to other 4D-QSAR and CoMFA formalisms was performed using a set of forty-seven glycogen phosphorylase b inhibitors (data set 1) and a set of forty-four MAP p38 kinase inhibitors (data set 2). The QSAR models for both data sets were built using the ordered predictor selection (OPS) algorithm for variable selection. Model validation was carried out applying y-randomization and leave-N-out cross-validation in addition to the external validation. PLS models for data set 1 and 2 provided the following statistics: q(2) = 0.72, r(2) = 0.81 for 12 variables selected and 2 latent variables and q(2) = 0.82, r(2) = 0.90 for 10 variables selected and 5 latent variables, respectively. Visualization of the descriptors in 3D space was successfully interpreted from the chemical point of view, supporting the applicability of this new approach in rational drug design.

  16. The MMPI-2-RF Personality Psychopathology Five (PSY-5-RF) scales: development and validity research.

    PubMed

    Harkness, Allan R; McNulty, John L; Finn, Jacob A; Reynolds, Shannon M; Shields, Susan M; Arbisi, Paul

    2014-01-01

    This article describes the development, internal psychometric, and external validation studies on scales designed to measure the Personality Psychopathology Five (PSY-5) from MMPI-2 Restructured Form (MMPI-2-RF) items. Diverse and comprehensive data sets, representing various clinical and nonclinical populations, were classified into development and validation research samples. Item selection, retention, and exclusion procedures are detailed. The final set of PSY-5-RF scales contain 104 items, with no item overlap between scales (same as the original MMPI-2 PSY-5 scales), and no item overlap with the Demoralization scale. Internal consistency estimates are comparable to the longer MMPI-2 PSY-5 scales. Appropriate convergent and discriminant validity findings utilizing various self-report, collateral rating, and record review data are reported and discussed. A particular emphasis is offered for the unique aspects of the PSY-5 model: psychoticism and disconstraint. The findings are connected to the broader PSY-5 literature and the recommended review of systems (Harkness, Reynolds, & Lilienfeld, this issue) presented in this series of articles.

  17. Quantitative structure-toxicity relationship (QSTR) studies on the organophosphate insecticides.

    PubMed

    Can, Alper

    2014-11-04

    Organophosphate insecticides are the most commonly used pesticides in the world. In this study, quantitative structure-toxicity relationship (QSTR) models were derived for estimating the acute oral toxicity of organophosphate insecticides to male rats. The 20 chemicals of the training set and the seven compounds of the external testing set were described by means of using descriptors. Descriptors for lipophilicity, polarity and molecular geometry, as well as quantum chemical descriptors for energy were calculated. Model development to predict toxicity of organophosphate insecticides in different matrices was carried out using multiple linear regression. The model was validated internally and externally. In the present study, QSTR model was used for the first time to understand the inherent relationships between the organophosphate insecticide molecules and their toxicity behavior. Such studies provide mechanistic insight about structure-toxicity relationship and help in the design of less toxic insecticides. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  18. Personalized Estimate of Chemotherapy-Induced Nausea and Vomiting: Development and External Validation of a Nomogram in Cancer Patients Receiving Highly/Moderately Emetogenic Chemotherapy

    PubMed Central

    Hu, Zhihuang; Liang, Wenhua; Yang, Yunpeng; Keefe, Dorothy; Ma, Yuxiang; Zhao, Yuanyuan; Xue, Cong; Huang, Yan; Zhao, Hongyun; Chen, Likun; Chan, Alexandre; Zhang, Li

    2016-01-01

    Abstract Chemotherapy-induced nausea and vomiting (CINV) is presented in over 30% of cancer patients receiving highly/moderately emetogenic chemotherapy (HEC/MEC). The currently recommended antiemetic therapy is merely based on the emetogenic level of chemotherapy, regardless of patient's individual risk factors. It is, therefore, critical to develop an approach for personalized management of CINV in the era of precision medicine. A number of variables were involved in the development of CINV. In the present study, we pooled the data from 2 multi-institutional investigations of CINV due to HEC/MEC treatment in Asian countries. Demographic and clinical variables of 881 patients were prospectively collected as defined previously, and 862 of them had full documentation of variables of interest. The data of 548 patients from Chinese institutions were used to identify variables associated with CINV using multivariate logistic regression model, and then construct a personalized prediction model of nomogram; while the remaining 314 patients out of China (Singapore, South Korea, and Taiwan) entered the external validation set. C-index was used to measure the discrimination ability of the model. The predictors in the final model included sex, age, alcohol consumption, history of vomiting pregnancy, history of motion sickness, body surface area, emetogenicity of chemotherapy, and antiemetic regimens. The C-index was 0.67 (95% CI, 0.62–0.72) for the training set and 0.65 (95% CI, 0.58–0.72) for the validation set. The C-index was higher than that of any single predictor, including the emetogenic level of chemotherapy according to current antiemetic guidelines. Calibration curves showed good agreement between prediction and actual occurrence of CINV. This easy-to-use prediction model was based on chemotherapeutic regimens as well as patient's individual risk factors. The prediction accuracy of CINV occurrence in this nomogram was well validated by an independent data set. It could facilitate the assessment of individual risk, and thus improve the personalized management of CINV. PMID:26765450

  19. External validity of a hierarchical dimensional model of child and adolescent psychopathology: Tests using confirmatory factor analyses and multivariate behavior genetic analyses.

    PubMed

    Waldman, Irwin D; Poore, Holly E; van Hulle, Carol; Rathouz, Paul J; Lahey, Benjamin B

    2016-11-01

    Several recent studies of the hierarchical phenotypic structure of psychopathology have identified a General psychopathology factor in addition to the more expected specific Externalizing and Internalizing dimensions in both youth and adult samples and some have found relevant unique external correlates of this General factor. We used data from 1,568 twin pairs (599 MZ & 969 DZ) age 9 to 17 to test hypotheses for the underlying structure of youth psychopathology and the external validity of the higher-order factors. Psychopathology symptoms were assessed via structured interviews of caretakers and youth. We conducted phenotypic analyses of competing structural models using Confirmatory Factor Analysis and used Structural Equation Modeling and multivariate behavior genetic analyses to understand the etiology of the higher-order factors and their external validity. We found that both a General factor and specific Externalizing and Internalizing dimensions are necessary for characterizing youth psychopathology at both the phenotypic and etiologic levels, and that the 3 higher-order factors differed substantially in the magnitudes of their underlying genetic and environmental influences. Phenotypically, the specific Externalizing and Internalizing dimensions were slightly negatively correlated when a General factor was included, which reflected a significant inverse correlation between the nonshared environmental (but not genetic) influences on Internalizing and Externalizing. We estimated heritability of the general factor of psychopathology for the first time. Its moderate heritability suggests that it is not merely an artifact of measurement error but a valid construct. The General, Externalizing, and Internalizing factors differed in their relations with 3 external validity criteria: mother's smoking during pregnancy, parent's harsh discipline, and the youth's association with delinquent peers. Multivariate behavior genetic analyses supported the external validity of the 3 higher-order factors by suggesting that the General, Externalizing, and Internalizing factors were correlated with peer delinquency and parent's harsh discipline for different etiologic reasons. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  20. A modified TNM staging system for non-metastatic colorectal cancer based on nomogram analysis of SEER database.

    PubMed

    Kong, Xiangxing; Li, Jun; Cai, Yibo; Tian, Yu; Chi, Shengqiang; Tong, Danyang; Hu, Yeting; Yang, Qi; Li, Jingsong; Poston, Graeme; Yuan, Ying; Ding, Kefeng

    2018-01-08

    To revise the American Joint Committee on Cancer TNM staging system for colorectal cancer (CRC) based on a nomogram analysis of Surveillance, Epidemiology, and End Results (SEER) database, and to prove the rationality of enhancing T stage's weighting in our previously proposed T-plus staging system. Total 115,377 non-metastatic CRC patients from SEER were randomly grouped as training and testing set by ratio 1:1. The Nomo-staging system was established via three nomograms based on 1-year, 2-year and 3-year disease specific survival (DSS) Logistic regression analysis of the training set. The predictive value of Nomo-staging system for the testing set was evaluated by concordance index (c-index), likelihood ratio (L.R.) and Akaike information criteria (AIC) for 1-year, 2-year, 3-year overall survival (OS) and DSS. Kaplan-Meier survival curve was used to valuate discrimination and gradient monotonicity. And an external validation was performed on database from the Second Affiliated Hospital of Zhejiang University (SAHZU). Patients with T1-2 N1 and T1N2a were classified into stage II while T4 N0 patients were classified into stage III in Nomo-staging system. Kaplan-Meier survival curves of OS and DSS in testing set showed Nomo-staging system performed better in discrimination and gradient monotonicity, and the external validation in SAHZU database also showed distinctly better discrimination. The Nomo-staging system showed higher value in L.R. and c-index, and lower value in AIC when predicting OS and DSS in testing set. The Nomo-staging system showed better performance in prognosis prediction and the weight of lymph nodes status in prognosis prediction should be cautiously reconsidered.

  1. An artificial neural network to predict resting energy expenditure in obesity.

    PubMed

    Disse, Emmanuel; Ledoux, Séverine; Bétry, Cécile; Caussy, Cyrielle; Maitrepierre, Christine; Coupaye, Muriel; Laville, Martine; Simon, Chantal

    2017-09-01

    The resting energy expenditure (REE) determination is important in nutrition for adequate dietary prescription. The gold standard i.e. indirect calorimetry is not available in clinical settings. Thus, several predictive equations have been developed, but they lack of accuracy in subjects with extreme weight including obese populations. Artificial neural networks (ANN) are useful predictive tools in the area of artificial intelligence, used in numerous clinical fields. The aim of this study was to determine the relevance of ANN in predicting REE in obesity. A Multi-Layer Perceptron (MLP) feed-forward neural network with a back propagation algorithm was created and cross-validated in a cohort of 565 obese subjects (BMI within 30-50 kg m -2 ) with weight, height, sex and age as clinical inputs and REE measured by indirect calorimetry as output. The predictive performances of ANN were compared to those of 23 predictive REE equations in the training set and in two independent sets of 100 and 237 obese subjects for external validation. Among the 23 established prediction equations for REE evaluated, the Harris & Benedict equations recalculated by Roza were the most accurate for the obese population, followed by the USA DRI, Müller and the original Harris & Benedict equations. The final 5-fold cross-validated three-layer 4-3-1 feed-forward back propagation ANN model developed in that study improved precision and accuracy of REE prediction over linear equations (precision = 68.1%, MAPE = 8.6% and RMSPE = 210 kcal/d), independently from BMI subgroups within 30-50 kg m -2 . External validation confirmed the better predictive performances of ANN model (precision = 73% and 65%, MAPE = 7.7% and 8.6%, RMSPE = 187 kcal/d and 200 kcal/d in the 2 independent datasets) for the prediction of REE in obese subjects. We developed and validated an ANN model for the prediction of REE in obese subjects that is more precise and accurate than established REE predictive equations independent from BMI subgroups. For convenient use in clinical settings, we provide a simple ANN-REE calculator available at: https://www.crnh-rhone-alpes.fr/fr/ANN-REE-Calculator. Copyright © 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

  2. Interpersonal problems across anxiety, depression, and eating disorders: a transdiagnostic examination.

    PubMed

    McEvoy, Peter M; Burgess, Melissa M; Page, Andrew C; Nathan, Paula; Fursland, Anthea

    2013-06-01

    Integrative models of psychopathology suggest that quality of interpersonal relationships is a key determinant of psychological well-being. However, there is a relative paucity of research evaluating the association between interpersonal problems and psychopathology within cognitive behavioural therapy. Partly, this may be due to lack of brief, well-validated, and easily interpretable measures of interpersonal problems that can be used within clinical settings. The aim of the present study was to evaluate the psychometric properties, factor invariance, and external validity of the Inventory of Interpersonal Problems 32 (IIP-32) across anxiety, depression, and eating disorders. Two treatment-seeking samples with principal anxiety and depressive disorders (AD sample, n = 504) and eating disorders (ED sample, n = 339) completed the IIP-32 along with measures of anxiety, depression, and eating disorder symptoms, as well as quality of life (QoL). The previously established eight-factor structure of the IIP-32 provided the best fit for both the AD and ED groups, and was robustly invariant across the two samples. The IIP-32 also demonstrated excellent external validity against well-validated measures of anxiety, depression, and eating disorder symptoms, as well as QoL. The IIP-32 provides a clinically useful measure of interpersonal problems across emotional and ED. © Commonwealth of Australia 2012.

  3. Development and external validation of new ultrasound-based mathematical models for preoperative prediction of high-risk endometrial cancer.

    PubMed

    Van Holsbeke, C; Ameye, L; Testa, A C; Mascilini, F; Lindqvist, P; Fischerova, D; Frühauf, F; Fransis, S; de Jonge, E; Timmerman, D; Epstein, E

    2014-05-01

    To develop and validate strategies, using new ultrasound-based mathematical models, for the prediction of high-risk endometrial cancer and compare them with strategies using previously developed models or the use of preoperative grading only. Women with endometrial cancer were prospectively examined using two-dimensional (2D) and three-dimensional (3D) gray-scale and color Doppler ultrasound imaging. More than 25 ultrasound, demographic and histological variables were analyzed. Two logistic regression models were developed: one 'objective' model using mainly objective variables; and one 'subjective' model including subjective variables (i.e. subjective impression of myometrial and cervical invasion, preoperative grade and demographic variables). The following strategies were validated: a one-step strategy using only preoperative grading and two-step strategies using preoperative grading as the first step and one of the new models, subjective assessment or previously developed models as a second step. One-hundred and twenty-five patients were included in the development set and 211 were included in the validation set. The 'objective' model retained preoperative grade and minimal tumor-free myometrium as variables. The 'subjective' model retained preoperative grade and subjective assessment of myometrial invasion. On external validation, the performance of the new models was similar to that on the development set. Sensitivity for the two-step strategy with the 'objective' model was 78% (95% CI, 69-84%) at a cut-off of 0.50, 82% (95% CI, 74-88%) for the strategy with the 'subjective' model and 83% (95% CI, 75-88%) for that with subjective assessment. Specificity was 68% (95% CI, 58-77%), 72% (95% CI, 62-80%) and 71% (95% CI, 61-79%) respectively. The two-step strategies detected up to twice as many high-risk cases as preoperative grading only. The new models had a significantly higher sensitivity than did previously developed models, at the same specificity. Two-step strategies with 'new' ultrasound-based models predict high-risk endometrial cancers with good accuracy and do this better than do previously developed models. Copyright © 2013 ISUOG. Published by John Wiley & Sons Ltd.

  4. Correlation between external and internal respiratory motion: a validation study.

    PubMed

    Ernst, Floris; Bruder, Ralf; Schlaefer, Alexander; Schweikard, Achim

    2012-05-01

    In motion-compensated image-guided radiotherapy, accurate tracking of the target region is required. This tracking process includes building a correlation model between external surrogate motion and the motion of the target region. A novel correlation method is presented and compared with the commonly used polynomial model. The CyberKnife system (Accuray, Inc., Sunnyvale/CA) uses a polynomial correlation model to relate externally measured surrogate data (optical fibres on the patient's chest emitting red light) to infrequently acquired internal measurements (X-ray data). A new correlation algorithm based on ɛ -Support Vector Regression (SVR) was developed. Validation and comparison testing were done with human volunteers using live 3D ultrasound and externally measured infrared light-emitting diodes (IR LEDs). Seven data sets (5:03-6:27 min long) were recorded from six volunteers. Polynomial correlation algorithms were compared to the SVR-based algorithm demonstrating an average increase in root mean square (RMS) accuracy of 21.3% (0.4 mm). For three signals, the increase was more than 29% and for one signal as much as 45.6% (corresponding to more than 1.5 mm RMS). Further analysis showed the improvement to be statistically significant. The new SVR-based correlation method outperforms traditional polynomial correlation methods for motion tracking. This method is suitable for clinical implementation and may improve the overall accuracy of targeted radiotherapy.

  5. Predictive Accuracy of the Liverpool Lung Project Risk Model for Stratifying Patients for Computed Tomography Screening for Lung Cancer

    PubMed Central

    Raji, Olaide Y.; Duffy, Stephen W.; Agbaje, Olorunshola F.; Baker, Stuart G.; Christiani, David C.; Cassidy, Adrian; Field, John K.

    2013-01-01

    Background External validation of existing lung cancer risk prediction models is limited. Using such models in clinical practice to guide the referral of patients for computed tomography (CT) screening for lung cancer depends on external validation and evidence of predicted clinical benefit. Objective To evaluate the discrimination of the Liverpool Lung Project (LLP) risk model and demonstrate its predicted benefit for stratifying patients for CT screening by using data from 3 independent studies from Europe and North America. Design Case–control and prospective cohort study. Setting Europe and North America. Patients Participants in the European Early Lung Cancer (EUELC) and Harvard case–control studies and the LLP population-based prospective cohort (LLPC) study. Measurements 5-year absolute risks for lung cancer predicted by the LLP model. Results The LLP risk model had good discrimination in both the Harvard (area under the receiver-operating characteristic curve [AUC], 0.76 [95% CI, 0.75 to 0.78]) and the LLPC (AUC, 0.82 [CI, 0.80 to 0.85]) studies and modest discrimination in the EUELC (AUC, 0.67 [CI, 0.64 to 0.69]) study. The decision utility analysis, which incorporates the harms and benefit of using a risk model to make clinical decisions, indicates that the LLP risk model performed better than smoking duration or family history alone in stratifying high-risk patients for lung cancer CT screening. Limitations The model cannot assess whether including other risk factors, such as lung function or genetic markers, would improve accuracy. Lack of information on asbestos exposure in the LLPC limited the ability to validate the complete LLP risk model. Conclusion Validation of the LLP risk model in 3 independent external data sets demonstrated good discrimination and evidence of predicted benefits for stratifying patients for lung cancer CT screening. Further studies are needed to prospectively evaluate model performance and evaluate the optimal population risk thresholds for initiating lung cancer screening. Primary Funding Source Roy Castle Lung Cancer Foundation. PMID:22910935

  6. External Validation of Bifactor Model of ADHD: Explaining Heterogeneity in Psychiatric Comorbidity, Cognitive Control, and Personality Trait Profiles within DSM-IV ADHD

    ERIC Educational Resources Information Center

    Martel, Michelle M.; Roberts, Bethan; Gremillion, Monica; von Eye, Alexander; Nigg, Joel T.

    2011-01-01

    The current paper provides external validation of the bifactor model of ADHD by examining associations between ADHD latent factor/profile scores and external validation indices. 548 children (321 boys; 302 with ADHD), 6 to 18 years old, recruited from the community participated in a comprehensive diagnostic procedure. Mothers completed the Child…

  7. An empirical assessment of validation practices for molecular classifiers

    PubMed Central

    Castaldi, Peter J.; Dahabreh, Issa J.

    2011-01-01

    Proposed molecular classifiers may be overfit to idiosyncrasies of noisy genomic and proteomic data. Cross-validation methods are often used to obtain estimates of classification accuracy, but both simulations and case studies suggest that, when inappropriate methods are used, bias may ensue. Bias can be bypassed and generalizability can be tested by external (independent) validation. We evaluated 35 studies that have reported on external validation of a molecular classifier. We extracted information on study design and methodological features, and compared the performance of molecular classifiers in internal cross-validation versus external validation for 28 studies where both had been performed. We demonstrate that the majority of studies pursued cross-validation practices that are likely to overestimate classifier performance. Most studies were markedly underpowered to detect a 20% decrease in sensitivity or specificity between internal cross-validation and external validation [median power was 36% (IQR, 21–61%) and 29% (IQR, 15–65%), respectively]. The median reported classification performance for sensitivity and specificity was 94% and 98%, respectively, in cross-validation and 88% and 81% for independent validation. The relative diagnostic odds ratio was 3.26 (95% CI 2.04–5.21) for cross-validation versus independent validation. Finally, we reviewed all studies (n = 758) which cited those in our study sample, and identified only one instance of additional subsequent independent validation of these classifiers. In conclusion, these results document that many cross-validation practices employed in the literature are potentially biased and genuine progress in this field will require adoption of routine external validation of molecular classifiers, preferably in much larger studies than in current practice. PMID:21300697

  8. Measuring strategies for learning regulation in medical education: scale reliability and dimensionality in a Swedish sample.

    PubMed

    Edelbring, Samuel

    2012-08-15

    The degree of learners' self-regulated learning and dependence on external regulation influence learning processes in higher education. These regulation strategies are commonly measured by questionnaires developed in other settings than in which they are being used, thereby requiring renewed validation. The aim of this study was to psychometrically evaluate the learning regulation strategy scales from the Inventory of Learning Styles with Swedish medical students (N = 206). The regulation scales were evaluated regarding their reliability, scale dimensionality and interrelations. The primary evaluation focused on dimensionality and was performed with Mokken scale analysis. To assist future scale refinement, additional item analysis, such as item-to-scale correlations, was performed. Scale scores in the Swedish sample displayed good reliability in relation to published results: Cronbach's alpha: 0.82, 0.72, and 0.65 for self-regulation, external regulation and lack of regulation scales respectively. The dimensionalities in scales were adequate for self-regulation and its subscales, whereas external regulation and lack of regulation displayed less unidimensionality. The established theoretical scales were largely replicated in the exploratory analysis. The item analysis identified two items that contributed little to their respective scales. The results indicate that these scales have an adequate capacity for detecting the three theoretically proposed learning regulation strategies in the medical education sample. Further construct validity should be sought by interpreting scale scores in relation to specific learning activities. Using established scales for measuring students' regulation strategies enables a broad empirical base for increasing knowledge on regulation strategies in relation to different disciplinary settings and contributes to theoretical development.

  9. Temporal and geographical external validation study and extension of the Mayo Clinic prediction model to predict eGFR in the younger population of Swiss ADPKD patients.

    PubMed

    Girardat-Rotar, Laura; Braun, Julia; Puhan, Milo A; Abraham, Alison G; Serra, Andreas L

    2017-07-17

    Prediction models in autosomal dominant polycystic kidney disease (ADPKD) are useful in clinical settings to identify patients with greater risk of a rapid disease progression in whom a treatment may have more benefits than harms. Mayo Clinic investigators developed a risk prediction tool for ADPKD patients using a single kidney value. Our aim was to perform an independent geographical and temporal external validation as well as evaluate the potential for improving the predictive performance by including additional information on total kidney volume. We used data from the on-going Swiss ADPKD study from 2006 to 2016. The main analysis included a sample size of 214 patients with Typical ADPKD (Class 1). We evaluated the Mayo Clinic model performance calibration and discrimination in our external sample and assessed whether predictive performance could be improved through the addition of subsequent kidney volume measurements beyond the baseline assessment. The calibration of both versions of the Mayo Clinic prediction model using continuous Height adjusted total kidney volume (HtTKV) and using risk subclasses was good, with R 2 of 78% and 70%, respectively. Accuracy was also good with 91.5% and 88.7% of the predicted within 30% of the observed, respectively. Additional information regarding kidney volume did not substantially improve the model performance. The Mayo Clinic prediction models are generalizable to other clinical settings and provide an accurate tool based on available predictors to identify patients at high risk for rapid disease progression.

  10. A new casemix adjustment index for hospital mortality among patients with congestive heart failure.

    PubMed

    Polanczyk, C A; Rohde, L E; Philbin, E A; Di Salvo, T G

    1998-10-01

    Comparative analysis of hospital outcomes requires reliable adjustment for casemix. Although congestive heart failure is one of the most common indications for hospitalization, congestive heart failure casemix adjustment has not been widely studied. The purposes of this study were (1) to describe and validate a new congestive heart failure-specific casemix adjustment index to predict in-hospital mortality and (2) to compare its performance to the Charlson comorbidity index. Data from all 4,608 admissions to the Massachusetts General Hospital from January 1990 to July 1996 with a principal ICD-9-CM discharge diagnosis of congestive heart failure were evaluated. Massachusetts General Hospital patients were randomly divided in a derivation and a validation set. By logistic regression, odds ratios for in-hospital death were computed and weights were assigned to construct a new predictive index in the derivation set. The performance of the index was tested in an internal Massachusetts General Hospital validation set and in a non-Massachusetts General Hospital external validation set incorporating data from all 1995 New York state hospital discharges with a primary discharge diagnosis of congestive heart failure. Overall in-hospital mortality was 6.4%. Based on the new index, patients were assigned to six categories with incrementally increasing hospital mortality rates ranging from 0.5% to 31%. By logistic regression, "c" statistics of the congestive heart failure-specific index (0.83 and 0.78, derivation and validation set) were significantly superior to the Charlson index (0.66). Similar incrementally increasing hospital mortality rates were observed in the New York database with the congestive heart failure-specific index ("c" statistics 0.75). In an administrative database, this congestive heart failure-specific index may be a more adequate casemix adjustment tool to predict hospital mortality in patients hospitalized for congestive heart failure.

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

    Chen, X; Wang, J; Hu, W

    Purpose: The Varian RapidPlan™ is a commercial knowledge-based optimization process which uses a set of clinically used treatment plans to train a model that can predict individualized dose-volume objectives. The purpose of this study is to evaluate the performance of RapidPlan to generate intensity modulated radiation therapy (IMRT) plans for cervical cancer. Methods: Totally 70 IMRT plans for cervical cancer with varying clinical and physiological indications were enrolled in this study. These patients were all previously treated in our institution. There were two prescription levels usually used in our institution: 45Gy/25 fractions and 50.4Gy/28 fractions. 50 of these plans weremore » selected to train the RapidPlan model for predicting dose-volume constraints. After model training, this model was validated with 10 plans from training pool(internal validation) and additional other 20 new plans(external validation). All plans used for the validation were re-optimized with the original beam configuration and the generated priorities from RapidPlan were manually adjusted to ensure that re-optimized DVH located in the range of the model prediction. DVH quantitative analysis was performed to compare the RapidPlan generated and the original manual optimized plans. Results: For all the validation cases, RapidPlan based plans (RapidPlan) showed similar or superior results compared to the manual optimized ones. RapidPlan increased the result of D98% and homogeneity in both two validations. For organs at risk, the RapidPlan decreased mean doses of bladder by 1.25Gy/1.13Gy (internal/external validation) on average, with p=0.12/p<0.01. The mean dose of rectum and bowel were also decreased by an average of 2.64Gy/0.83Gy and 0.66Gy/1.05Gy,with p<0.01/ p<0.01and p=0.04/<0.01 for the internal/external validation, respectively. Conclusion: The RapidPlan model based cervical cancer plans shows ability to systematically improve the IMRT plan quality. It suggests that RapidPlan has great potential to make the treatment planning process more efficient.« less

  12. Subtyping attention-deficit/hyperactivity disorder using temperament dimensions: toward biologically based nosologic criteria

    PubMed Central

    Karalunas, Sarah L.; Fair, Damien; Musser, Erica D.; Aykes, Kamari; Iyer, Swathi P.; Nigg, Joel T.

    2014-01-01

    Importance Psychiatric nosology is limited by behavioral and biological heterogeneity within existing disorder categories. The imprecise nature of current nosological distinctions limits both mechanistic understanding and clinical prediction. Here, we demonstrate an approach consistent with the NIMH Research Domain Criteria (RDoC) initiative to identifying superior, neurobiologically-valid subgroups with better predictive capacity than existing psychiatric categories for childhood Attention-Deficit Hyperactivity Disorder (ADHD). Objective Refine subtyping of childhood ADHD by using biologically-based behavioral dimensions (i.e. temperament), novel classification algorithms, and multiple external validators. In doing so, we demonstrate how refined nosology is capable of improving on current predictive capacity of long-term outcomes relative to current DSM-based nosology. Design, Setting, Participants 437 clinically well-characterized, community-recruited children with and without ADHD participated in an on-going longitudinal study. Baseline data were used to classify children into subgroups based on temperament dimensions and to examine external validators including physiological and MRI measures. One-year longitudinal follow-up data are reported for a subgroup of the ADHD sample to address stability and clinical prediction. Main Outcome Measures Parent/guardian ratings of children on a measure of temperament were used as input features in novel community detection analyses to identify subgroups within the sample. Groups were validated using three widely-accepted external validators: peripheral physiology (cardiac measures of respiratory sinus arrhythmia and pre-ejection period), central nervous system functioning (via resting-state functional connectivity MRI), and clinical outcomes (at one-year longitudinal follow-up). Results The community detection algorithm suggested three novel types of ADHD, labeled as “Mild” (normative emotion regulation); “Surgent” (extreme levels of positive approach-motivation); and “Irritable” (extreme levels of negative emotionality, anger, and poor soothability). Types were independent of existing clinical demarcations, including DSM-5 presentations or symptom severity. These types showed stability over time and were distinguished by unique patterns of cardiac physiological response, resting-state functional brain connectivity, and clinical outcome one year later. Conclusions and Relevance Results suggest that a biologically-informed temperament-based typology, developed with a discovery-based community detection algorithm, provided a superior description of heterogeneity in the ADHD population than any current clinical nosology. This demonstration sets the stage for more aggressive attempts at a tractable, biologically-based nosology. PMID:25006969

  13. Does Maximal External Tibial Component Rotation Influence Tibiofemoral Load Distribution in the Primary Knee Arthroplasty Setting: A Comparison of Neutral vs Maximal Anatomical External Rotatory States.

    PubMed

    Manning, William A; Ghosh, Kanishka M; Blain, Alasdair P; Longstaff, Lee M; Rushton, Steven P; Deehan, David J

    2017-06-01

    Tibial component rotation at time of knee arthroplasty can influence conformity, load transmission across the polyethylene surface, and perhaps ultimately determined survivorship. Optimal tibial component rotation on the cut surface is reliant on standard per operative manual stressing. This subjective assessment aims to balance constraint and stability of the articulation through a full arc of movement. Using a cadaveric model, computer navigation and under defined, previously validated loaded conditions mimicking the in vivo setting, the influence of maximal tibial component external rotation compared with the neutral state was examined for changes in laxity and tibiofemoral continuous load using 3D displacement measurement and an orthosensor continuous load sensor implanted within the polyethylene spacer in a simulated single radius total knee arthroplasty. No significant difference was found throughout arc of motion (0-115 degrees of flexion) for maximal varus and/or valgus or rotatory laxity between the 2 states. The neutral state achieved equivalence for mediolateral load distribution at each point of flexion. We have found that external rotation of the tibial component increased medial compartment load in comparison with the neutral position. Compared with the neutral state, external rotation consistently effected a marginal, but not significant reduction in lateral load under similar loading conditions. The effects were most pronounced in midflexion. On the basis of these findings, we would advocate for the midtibial tubercle point to determine tibial component rotation and caution against component external rotation. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Validation of a scenario-based assessment of critical thinking using an externally validated tool.

    PubMed

    Buur, Jennifer L; Schmidt, Peggy; Smylie, Dean; Irizarry, Kris; Crocker, Carlos; Tyler, John; Barr, Margaret

    2012-01-01

    With medical education transitioning from knowledge-based curricula to competency-based curricula, critical thinking skills have emerged as a major competency. While there are validated external instruments for assessing critical thinking, many educators have created their own custom assessments of critical thinking. However, the face validity of these assessments has not been challenged. The purpose of this study was to compare results from a custom assessment of critical thinking with the results from a validated external instrument of critical thinking. Students from the College of Veterinary Medicine at Western University of Health Sciences were administered a custom assessment of critical thinking (ACT) examination and the externally validated instrument, California Critical Thinking Skills Test (CCTST), in the spring of 2011. Total scores and sub-scores from each exam were analyzed for significant correlations using Pearson correlation coefficients. Significant correlations between ACT Blooms 2 and deductive reasoning and total ACT score and deductive reasoning were demonstrated with correlation coefficients of 0.24 and 0.22, respectively. No other statistically significant correlations were found. The lack of significant correlation between the two examinations illustrates the need in medical education to externally validate internal custom assessments. Ultimately, the development and validation of custom assessments of non-knowledge-based competencies will produce higher quality medical professionals.

  15. [Internal consistency and criterion validity and reliability of the Mexican Version of the Child Behavior Checklist 1.5-5 (CBCL/1.5-5)].

    PubMed

    Albores-Gallo, Lilia; Hernández-Guzmán, Laura; Hasfura-Buenaga, Cecilia; Navarro-Luna, Enrique

    To investigate the validity and internal consistency of the Mexican version of the CBCL/1.5 -5 that assesses the most common psychopathology in pre-school children in clinical and epidemiological settings. A total of 438 parents from two groups, clinical-psychiatric (N= 62) and community (N= 376) completed the CBCL/1.5-5/Mexican version. The internal consistency was high for total problems α=0.95, and internalized α=0.89 and externalized α=0.91 subscales. The test re-test (one week) using the intraclass correlation coefficient (ICC) was ≥ 0.95 for the internalized, externalized, and total problems subscales. The ROC curve for the criterion status of clinically-referred vs. non-referred using the total problems scale ≥ 24 resulted in an AUC (area under curve) of 0.77, a specificity 0.73, and a sensitivity of 0.70. The CBCL/1.5 -5/Mexican version is a reliable and valid tool. Copyright © 2016 Sociedad Chilena de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.

  16. External validation of a Cox prognostic model: principles and methods

    PubMed Central

    2013-01-01

    Background A prognostic model should not enter clinical practice unless it has been demonstrated that it performs a useful role. External validation denotes evaluation of model performance in a sample independent of that used to develop the model. Unlike for logistic regression models, external validation of Cox models is sparsely treated in the literature. Successful validation of a model means achieving satisfactory discrimination and calibration (prediction accuracy) in the validation sample. Validating Cox models is not straightforward because event probabilities are estimated relative to an unspecified baseline function. Methods We describe statistical approaches to external validation of a published Cox model according to the level of published information, specifically (1) the prognostic index only, (2) the prognostic index together with Kaplan-Meier curves for risk groups, and (3) the first two plus the baseline survival curve (the estimated survival function at the mean prognostic index across the sample). The most challenging task, requiring level 3 information, is assessing calibration, for which we suggest a method of approximating the baseline survival function. Results We apply the methods to two comparable datasets in primary breast cancer, treating one as derivation and the other as validation sample. Results are presented for discrimination and calibration. We demonstrate plots of survival probabilities that can assist model evaluation. Conclusions Our validation methods are applicable to a wide range of prognostic studies and provide researchers with a toolkit for external validation of a published Cox model. PMID:23496923

  17. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

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

    Alves, Vinicius M.; Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599; Muratov, Eugene

    Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putativemore » sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative chemical hazards in the Scorecard database were found using our models.« less

  18. Development and Validation of Personality Disorder Spectra Scales for the MMPI-2-RF.

    PubMed

    Sellbom, Martin; Waugh, Mark H; Hopwood, Christopher J

    2018-01-01

    The purpose of this study was to develop and validate a set of MMPI-2-RF (Ben-Porath & Tellegen, 2008/2011) personality disorder (PD) spectra scales. These scales could serve the purpose of assisting with DSM-5 PD diagnosis and help link categorical and dimensional conceptions of personality pathology within the MMPI-2-RF. We developed and provided initial validity results for scales corresponding to the 10 PD constructs listed in the DSM-5 using data from student, community, clinical, and correctional samples. Initial validation efforts indicated good support for criterion validity with an external PD measure as well as with dimensional personality traits included in the DSM-5 alternative model for PDs. Construct validity results using psychosocial history and therapists' ratings in a large clinical sample were generally supportive as well. Overall, these brief scales provide clinicians using MMPI-2-RF data with estimates of DSM-5 PD constructs that can support cross-model connections between categorical and dimensional assessment approaches.

  19. The Validation of Version 8 Ozone Profiles: Is SBUV Ready for Prime Time?

    NASA Technical Reports Server (NTRS)

    McPeters, R. D.; Wellemeyer, C. G.; Ahn, C.

    2004-01-01

    Ozone profile data are now available from a series of BUV instruments - SBUV on Nimbus 7 and SBW/2 instruments on NOAA 9, NOAA 11, and NOAA 16. The data have been processed through the new version 8 algorithm, which is designed to be more accurate and, more importantly, to reduce the influence of the a priori on ozone trends. As a part of the version 8 reprocessing we have attempted to apply a consistent calibration to the individual instruments so that their data records can be used together in a time series analysis. Validation consists of examining not only the mean difference from external datasets (i.e trends) but also consistency in the interannual variability of the data. Here we validate the v8 BUV data through comparison with ECC sondes, lidar and microwave measurements, and with SAGE II and HALOE satellite data records. We find that individual profiles generally agree with external data sets within +/-10% between 30 hPa and 1 hPa (approx. 24 - 50 km) and frequently agree within +/-5%. The interannual variability of the BUV ozone time series agrees well with that of SAGE II . On the average, different B W instruments usually agree within +/-5% with each other, though the relative error increases near the ends of the Nimbus 7 and NOAA 16 data records as a result of instrument problems. The combined v8 BUV data sets cover the 1979-2003 time period giving daily global coverage of the ozone vertical distribution to better accuracy than has ever been possible before.

  20. Automatic classification of tissue malignancy for breast carcinoma diagnosis.

    PubMed

    Fondón, Irene; Sarmiento, Auxiliadora; García, Ana Isabel; Silvestre, María; Eloy, Catarina; Polónia, António; Aguiar, Paulo

    2018-05-01

    Breast cancer is the second leading cause of cancer death among women. Its early diagnosis is extremely important to prevent avoidable deaths. However, malignancy assessment of tissue biopsies is complex and dependent on observer subjectivity. Moreover, hematoxylin and eosin (H&E)-stained histological images exhibit a highly variable appearance, even within the same malignancy level. In this paper, we propose a computer-aided diagnosis (CAD) tool for automated malignancy assessment of breast tissue samples based on the processing of histological images. We provide four malignancy levels as the output of the system: normal, benign, in situ and invasive. The method is based on the calculation of three sets of features related to nuclei, colour regions and textures considering local characteristics and global image properties. By taking advantage of well-established image processing techniques, we build a feature vector for each image that serves as an input to an SVM (Support Vector Machine) classifier with a quadratic kernel. The method has been rigorously evaluated, first with a 5-fold cross-validation within an initial set of 120 images, second with an external set of 30 different images and third with images with artefacts included. Accuracy levels range from 75.8% when the 5-fold cross-validation was performed to 75% with the external set of new images and 61.11% when the extremely difficult images were added to the classification experiment. The experimental results indicate that the proposed method is capable of distinguishing between four malignancy levels with high accuracy. Our results are close to those obtained with recent deep learning-based methods. Moreover, it performs better than other state-of-the-art methods based on feature extraction, and it can help improve the CAD of breast cancer. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

    PubMed

    Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

    2007-12-01

    We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

  2. Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

    PubMed

    Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

    2007-09-01

    We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

  3. Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

    NASA Astrophysics Data System (ADS)

    Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

    2007-12-01

    We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

  4. Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

    NASA Astrophysics Data System (ADS)

    Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

    2007-09-01

    We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

  5. Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride.

    PubMed

    Katsarov, Plamen; Gergov, Georgi; Alin, Aylin; Pilicheva, Bissera; Al-Degs, Yahya; Simeonov, Vasil; Kassarova, Margarita

    2018-03-01

    The prediction power of partial least squares (PLS) and multivariate curve resolution-alternating least squares (MCR-ALS) methods have been studied for simultaneous quantitative analysis of the binary drug combination - doxylamine succinate and pyridoxine hydrochloride. Analysis of first-order UV overlapped spectra was performed using different PLS models - classical PLS1 and PLS2 as well as partial robust M-regression (PRM). These linear models were compared to MCR-ALS with equality and correlation constraints (MCR-ALS-CC). All techniques operated within the full spectral region and extracted maximum information for the drugs analysed. The developed chemometric methods were validated on external sample sets and were applied to the analyses of pharmaceutical formulations. The obtained statistical parameters were satisfactory for calibration and validation sets. All developed methods can be successfully applied for simultaneous spectrophotometric determination of doxylamine and pyridoxine both in laboratory-prepared mixtures and commercial dosage forms.

  6. Derivation and External Validation of Prediction Models for Advanced Chronic Kidney Disease Following Acute Kidney Injury

    PubMed Central

    Pannu, Neesh; Hemmelgarn, Brenda R.; Austin, Peter C.; Tan, Zhi; McArthur, Eric; Manns, Braden J.; Tonelli, Marcello; Wald, Ron; Quinn, Robert R.; Ravani, Pietro; Garg, Amit X.

    2017-01-01

    Importance Some patients will develop chronic kidney disease after a hospitalization with acute kidney injury; however, no risk-prediction tools have been developed to identify high-risk patients requiring follow-up. Objective To derive and validate predictive models for progression of acute kidney injury to advanced chronic kidney disease. Design, Setting, and Participants Data from 2 population-based cohorts of patients with a prehospitalization estimated glomerular filtration rate (eGFR) of more than 45 mL/min/1.73 m2 and who had survived hospitalization with acute kidney injury (defined by a serum creatinine increase during hospitalization > 0.3 mg/dL or > 50% of their prehospitalization baseline), were used to derive and validate multivariable prediction models. The risk models were derived from 9973 patients hospitalized in Alberta, Canada (April 2004-March 2014, with follow-up to March 2015). The risk models were externally validated with data from a cohort of 2761 patients hospitalized in Ontario, Canada (June 2004-March 2012, with follow-up to March 2013). Exposures Demographic, laboratory, and comorbidity variables measured prior to discharge. Main Outcomes and Measures Advanced chronic kidney disease was defined by a sustained reduction in eGFR less than 30 mL/min/1.73 m2 for at least 3 months during the year after discharge. All participants were followed up for up to 1 year. Results The participants (mean [SD] age, 66 [15] years in the derivation and internal validation cohorts and 69 [11] years in the external validation cohort; 40%-43% women per cohort) had a mean (SD) baseline serum creatinine level of 1.0 (0.2) mg/dL and more than 20% had stage 2 or 3 acute kidney injury. Advanced chronic kidney disease developed in 408 (2.7%) of 9973 patients in the derivation cohort and 62 (2.2%) of 2761 patients in the external validation cohort. In the derivation cohort, 6 variables were independently associated with the outcome: older age, female sex, higher baseline serum creatinine value, albuminuria, greater severity of acute kidney injury, and higher serum creatinine value at discharge. In the external validation cohort, a multivariable model including these 6 variables had a C statistic of 0.81 (95% CI, 0.75-0.86) and improved discrimination and reclassification compared with reduced models that included age, sex, and discharge serum creatinine value alone (integrated discrimination improvement, 2.6%; 95% CI, 1.1%-4.0%; categorical net reclassification index, 13.5%; 95% CI, 1.9%-25.1%) or included age, sex, and acute kidney injury stage alone (integrated discrimination improvement, 8.0%; 95% CI, 5.1%-11.0%; categorical net reclassification index, 79.9%; 95% CI, 60.9%-98.9%). Conclusions and Relevance A multivariable model using routine laboratory data was able to predict advanced chronic kidney disease following hospitalization with acute kidney injury. The utility of this model in clinical care requires further research. PMID:29136443

  7. The Development of Novel Chemical Fragment-Based Descriptors Using Frequent Common Subgraph Mining Approach and Their Application in QSAR Modeling.

    PubMed

    Khashan, Raed; Zheng, Weifan; Tropsha, Alexander

    2014-03-01

    We present a novel approach to generating fragment-based molecular descriptors. The molecules are represented by labeled undirected chemical graph. Fast Frequent Subgraph Mining (FFSM) is used to find chemical-fragments (subgraphs) that occur in at least a subset of all molecules in a dataset. The collection of frequent subgraphs (FSG) forms a dataset-specific descriptors whose values for each molecule are defined by the number of times each frequent fragment occurs in this molecule. We have employed the FSG descriptors to develop variable selection k Nearest Neighbor (kNN) QSAR models of several datasets with binary target property including Maximum Recommended Therapeutic Dose (MRTD), Salmonella Mutagenicity (Ames Genotoxicity), and P-Glycoprotein (PGP) data. Each dataset was divided into training, test, and validation sets to establish the statistical figures of merit reflecting the model validated predictive power. The classification accuracies of models for both training and test sets for all datasets exceeded 75 %, and the accuracy for the external validation sets exceeded 72 %. The model accuracies were comparable or better than those reported earlier in the literature for the same datasets. Furthermore, the use of fragment-based descriptors affords mechanistic interpretation of validated QSAR models in terms of essential chemical fragments responsible for the compounds' target property. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. [Introduction of an accreditation system for hospital informed consent forms].

    PubMed

    López-Picazo, J J; Tomás-Garcia, N; Calle-Urra, J E; Parra-Hidalgo, P; Valverde-Iniesta, J J

    2015-01-01

    To describe an accreditation system for informed consent forms (ICF) in a tertiary hospital, as an intervention to improve their quality, and to check the improvements achieved. Following an external evaluation of the ICF quality in a public hospital in Murcia (Spain), an accreditation committee set the ICF requirements and associated procedures. Effectiveness is assessed by comparing two external evaluations carried out by the EMCA Program (2011 and 2013) and based on 19 criteria and a sample of 60 ICF for every public hospital in Murcia Region. To be accredited, every ICF must meet the 19 external criteria plus 5 based on legibility, readability and scientific and technical validity. A form to fill in the contents of every ICF was agreed, which would be reviewed, approved and validated for five years. Before the implementation, 8.2 defects/ICF were detected. The accreditation system obtained an 89% improvement (0.9 defects/ICF) and achieved significant improvements in 18 criteria, 16 of which are benchmarked. The accreditation system achieved a substantial improvement in the ICF (obtaining a better result in external evaluations) and guarantees their contents, legibility and readability. This system needs to be extended to other hospitals, since it is not clear whether common ICFs would be suitable. However, this improvement is structural and does not guarantee that the overall information/consent procedure is done properly, thus complementary strategies for measurement and improvement are required. Copyright © 2014 SECA. Published by Elsevier Espana. All rights reserved.

  9. Development and validation of a casemix classification to predict costs of specialist palliative care provision across inpatient hospice, hospital and community settings in the UK: a study protocol

    PubMed Central

    Guo, Ping; Dzingina, Mendwas; Firth, Alice M; Davies, Joanna M; Douiri, Abdel; O’Brien, Suzanne M; Pinto, Cathryn; Pask, Sophie; Higginson, Irene J; Eagar, Kathy; Murtagh, Fliss E M

    2018-01-01

    Introduction Provision of palliative care is inequitable with wide variations across conditions and settings in the UK. Lack of a standard way to classify by case complexity is one of the principle obstacles to addressing this. We aim to develop and validate a casemix classification to support the prediction of costs of specialist palliative care provision. Methods and analysis Phase I: A cohort study to determine the variables and potential classes to be included in a casemix classification. Data are collected from clinicians in palliative care services across inpatient hospice, hospital and community settings on: patient demographics, potential complexity/casemix criteria and patient-level resource use. Cost predictors are derived using multivariate regression and then incorporated into a classification using classification and regression trees. Internal validation will be conducted by bootstrapping to quantify any optimism in the predictive performance (calibration and discrimination) of the developed classification. Phase II: A mixed-methods cohort study across settings for external validation of the classification developed in phase I. Patient and family caregiver data will be collected longitudinally on demographics, potential complexity/casemix criteria and patient-level resource use. This will be triangulated with data collected from clinicians on potential complexity/casemix criteria and patient-level resource use, and with qualitative interviews with patients and caregivers about care provision across difference settings. The classification will be refined on the basis of its performance in the validation data set. Ethics and dissemination The study has been approved by the National Health Service Health Research Authority Research Ethics Committee. The results are expected to be disseminated in 2018 through papers for publication in major palliative care journals; policy briefs for clinicians, commissioning leads and policy makers; and lay summaries for patients and public. Trial registration number ISRCTN90752212. PMID:29550781

  10. Development and validation of a casemix classification to predict costs of specialist palliative care provision across inpatient hospice, hospital and community settings in the UK: a study protocol.

    PubMed

    Guo, Ping; Dzingina, Mendwas; Firth, Alice M; Davies, Joanna M; Douiri, Abdel; O'Brien, Suzanne M; Pinto, Cathryn; Pask, Sophie; Higginson, Irene J; Eagar, Kathy; Murtagh, Fliss E M

    2018-03-17

    Provision of palliative care is inequitable with wide variations across conditions and settings in the UK. Lack of a standard way to classify by case complexity is one of the principle obstacles to addressing this. We aim to develop and validate a casemix classification to support the prediction of costs of specialist palliative care provision. Phase I: A cohort study to determine the variables and potential classes to be included in a casemix classification. Data are collected from clinicians in palliative care services across inpatient hospice, hospital and community settings on: patient demographics, potential complexity/casemix criteria and patient-level resource use. Cost predictors are derived using multivariate regression and then incorporated into a classification using classification and regression trees. Internal validation will be conducted by bootstrapping to quantify any optimism in the predictive performance (calibration and discrimination) of the developed classification. Phase II: A mixed-methods cohort study across settings for external validation of the classification developed in phase I. Patient and family caregiver data will be collected longitudinally on demographics, potential complexity/casemix criteria and patient-level resource use. This will be triangulated with data collected from clinicians on potential complexity/casemix criteria and patient-level resource use, and with qualitative interviews with patients and caregivers about care provision across difference settings. The classification will be refined on the basis of its performance in the validation data set. The study has been approved by the National Health Service Health Research Authority Research Ethics Committee. The results are expected to be disseminated in 2018 through papers for publication in major palliative care journals; policy briefs for clinicians, commissioning leads and policy makers; and lay summaries for patients and public. ISRCTN90752212. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  11. Updated Prognostic Model for Predicting Overall Survival in First-Line Chemotherapy for Patients With Metastatic Castration-Resistant Prostate Cancer

    PubMed Central

    Halabi, Susan; Lin, Chen-Yen; Kelly, W. Kevin; Fizazi, Karim S.; Moul, Judd W.; Kaplan, Ellen B.; Morris, Michael J.; Small, Eric J.

    2014-01-01

    Purpose Prognostic models for overall survival (OS) for patients with metastatic castration-resistant prostate cancer (mCRPC) are dated and do not reflect significant advances in treatment options available for these patients. This work developed and validated an updated prognostic model to predict OS in patients receiving first-line chemotherapy. Methods Data from a phase III trial of 1,050 patients with mCRPC were used (Cancer and Leukemia Group B CALGB-90401 [Alliance]). The data were randomly split into training and testing sets. A separate phase III trial served as an independent validation set. Adaptive least absolute shrinkage and selection operator selected eight factors prognostic for OS. A predictive score was computed from the regression coefficients and used to classify patients into low- and high-risk groups. The model was assessed for its predictive accuracy using the time-dependent area under the curve (tAUC). Results The model included Eastern Cooperative Oncology Group performance status, disease site, lactate dehydrogenase, opioid analgesic use, albumin, hemoglobin, prostate-specific antigen, and alkaline phosphatase. Median OS values in the high- and low-risk groups, respectively, in the testing set were 17 and 30 months (hazard ratio [HR], 2.2; P < .001); in the validation set they were 14 and 26 months (HR, 2.9; P < .001). The tAUCs were 0.73 (95% CI, 0.70 to 0.73) and 0.76 (95% CI, 0.72 to 0.76) in the testing and validation sets, respectively. Conclusion An updated prognostic model for OS in patients with mCRPC receiving first-line chemotherapy was developed and validated on an external set. This model can be used to predict OS, as well as to better select patients to participate in trials on the basis of their prognosis. PMID:24449231

  12. Breaking Out of the Lab: Measuring Real-Time Responses to Televised Political Content in Real-World Settings.

    PubMed

    Maier, Jürgen; Hampe, J Felix; Jahn, Nico

    2016-01-01

    Real-time response (RTR) measurement is an important technique for analyzing human processing of electronic media stimuli. Although it has been demonstrated that RTR data are reliable and internally valid, some argue that they lack external validity. The reason for this is that RTR measurement is restricted to a laboratory environment due to its technical requirements. This paper introduces a smartphone app that 1) captures real-time responses using the dial technique and 2) provides a solution for one of the most important problems in RTR measurement, the (automatic) synchronization of RTR data. In addition, it explores the reliability and validity of mobile RTR measurement by comparing the real-time reactions of two samples of young and well-educated voters to the 2013 German televised debate. Whereas the first sample participated in a classical laboratory study, the second sample was equipped with our mobile RTR system and watched the debate at home. Results indicate that the mobile RTR system yields similar results to the lab-based RTR measurement, providing evidence that laboratory studies using RTR are externally valid. In particular, the argument that the artificial reception situation creates artificial results has to be questioned. In addition, we conclude that RTR measurement outside the lab is possible. Hence, mobile RTR opens the door for large-scale studies to better understand the processing and impact of electronic media content.

  13. External validation of the ability of the DRAGON score to predict outcome after thrombolysis treatment.

    PubMed

    Ovesen, C; Christensen, A; Nielsen, J K; Christensen, H

    2013-11-01

    Easy-to-perform and valid assessment scales for the effect of thrombolysis are essential in hyperacute stroke settings. Because of this we performed an external validation of the DRAGON scale proposed by Strbian et al. in a Danish cohort. All patients treated with intravenous recombinant plasminogen activator between 2009 and 2011 were included. Upon admission all patients underwent physical and neurological examination using the National Institutes of Health Stroke Scale along with non-contrast CT scans and CT angiography. Patients were followed up through the Outpatient Clinic and their modified Rankin Scale (mRS) was assessed after 3 months. Three hundred and three patients were included in the analysis. The DRAGON scale proved to have a good discriminative ability for predicting highly unfavourable outcome (mRS 5-6) (area under the curve-receiver operating characteristic [AUC-ROC]: 0.89; 95% confidence interval [CI] 0.81-0.96; p<0.001) and good outcome (mRS 0-2) (AUC-ROC: 0.79; 95% CI 0.73-0.85; p<0.001). When only patients with M1 occlusions were selected the DRAGON scale provided good discriminative capability (AUC-ROC: 0.89; 95% CI 0.78-1.0; p=0.003) for highly unfavourable outcome. We confirmed the validity of the DRAGON scale in predicting outcome after thrombolysis treatment. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Development of models for classification of action between heat-clearing herbs and blood-activating stasis-resolving herbs based on theory of traditional Chinese medicine.

    PubMed

    Chen, Zhao; Cao, Yanfeng; He, Shuaibing; Qiao, Yanjiang

    2018-01-01

    Action (" gongxiao " in Chinese) of traditional Chinese medicine (TCM) is the high recapitulation for therapeutic and health-preserving effects under the guidance of TCM theory. TCM-defined herbal properties (" yaoxing " in Chinese) had been used in this research. TCM herbal property (TCM-HP) is the high generalization and summary for actions, both of which come from long-term effective clinical practice in two thousands of years in China. However, the specific relationship between TCM-HP and action of TCM is complex and unclear from a scientific perspective. The research about this is conducive to expound the connotation of TCM-HP theory and is of important significance for the development of the TCM-HP theory. One hundred and thirty-three herbs including 88 heat-clearing herbs (HCHs) and 45 blood-activating stasis-resolving herbs (BAHRHs) were collected from reputable TCM literatures, and their corresponding TCM-HPs/actions information were collected from Chinese pharmacopoeia (2015 edition). The Kennard-Stone (K-S) algorithm was used to split 133 herbs into 100 calibration samples and 33 validation samples. Then, machine learning methods including supported vector machine (SVM), k-nearest neighbor (kNN) and deep learning methods including deep belief network (DBN), convolutional neutral network (CNN) were adopted to develop action classification models based on TCM-HP theory, respectively. In order to ensure robustness, these four classification methods were evaluated by using the method of tenfold cross validation and 20 external validation samples for prediction. As results, 72.7-100% of 33 validation samples including 17 HCHs and 16 BASRHs were correctly predicted by these four types of methods. Both of the DBN and CNN methods gave out the best results and their sensitivity, specificity, precision, accuracy were all 100.00%. Especially, the predicted results of external validation set showed that the performance of deep learning methods (DBN, CNN) were better than traditional machine learning methods (kNN, SVM) in terms of their sensitivity, specificity, precision, accuracy. Moreover, the distribution patterns of TCM-HPs of HCHs and BASRHs were also analyzed to detect the featured TCM-HPs of these two types of herbs. The result showed that the featured TCM-HPs of HCHs were cold, bitter, liver and stomach meridians entered, while those of BASRHs were warm, bitter and pungent, liver meridian entered. The performance on validation set and external validation set of deep learning methods (DBN, CNN) were better than machine learning models (kNN, SVM) in sensitivity, specificity, precision, accuracy when predicting the actions of heat-clearing and blood-activating stasis-resolving based on TCM-HP theory. The deep learning classification methods owned better generalization ability and accuracy when predicting the actions of heat-clearing and blood-activating stasis-resolving based on TCM-HP theory. Besides, the methods of deep learning would help us to improve our understanding about the relationship between herbal property and action, as well as to enrich and develop the theory of TCM-HP scientifically.

  15. External validation of urinary PCA3-based nomograms to individually predict prostate biopsy outcome.

    PubMed

    Auprich, Marco; Haese, Alexander; Walz, Jochen; Pummer, Karl; de la Taille, Alexandre; Graefen, Markus; de Reijke, Theo; Fisch, Margit; Kil, Paul; Gontero, Paolo; Irani, Jacques; Chun, Felix K-H

    2010-11-01

    Prior to safely adopting risk stratification tools, their performance must be tested in an external patient cohort. To assess accuracy and generalizability of previously reported, internally validated, prebiopsy prostate cancer antigen 3 (PCA3) gene-based nomograms when applied to a large, external, European cohort of men at risk of prostate cancer (PCa). Biopsy data, including urinary PCA3 score, were available for 621 men at risk of PCa who were participating in a European multi-institutional study. All patients underwent a ≥10-core prostate biopsy. Biopsy indication was based on suspicious digital rectal examination, persistently elevated prostate-specific antigen level (2.5-10 ng/ml) and/or suspicious histology (atypical small acinar proliferation of the prostate, >/= two cores affected by high-grade prostatic intraepithelial neoplasia in first set of biopsies). PCA3 scores were assessed using the Progensa assay (Gen-Probe Inc, San Diego, CA, USA). According to the previously reported nomograms, different PCA3 score codings were used. The probability of a positive biopsy was calculated using previously published logistic regression coefficients. Predicted outcomes were compared to the actual biopsy results. Accuracy was calculated using the area under the curve as a measure of discrimination; calibration was explored graphically. Biopsy-confirmed PCa was detected in 255 (41.1%) men. Median PCA3 score of biopsy-negative versus biopsy-positive men was 20 versus 48 in the total cohort, 17 versus 47 at initial biopsy, and 37 versus 53 at repeat biopsy (all p≤0.002). External validation of all four previously reported PCA3-based nomograms demonstrated equally high accuracy (0.73-0.75) and excellent calibration. The main limitations of the study reside in its early detection setting, referral scenario, and participation of only tertiary-care centers. In accordance with the original publication, previously developed PCA3-based nomograms achieved high accuracy and sufficient calibration. These novel nomograms represent robust tools and are thus generalizable to European men at risk of harboring PCa. Consequently, in presence of a PCA3 score, these nomograms may be safely used to assist clinicians when prostate biopsy is contemplated. Copyright © 2010 European Association of Urology. Published by Elsevier B.V. All rights reserved.

  16. Discovery and Validation of Novel Expression Signature for Postcystectomy Recurrence in High-Risk Bladder Cancer

    PubMed Central

    Lam, Lucia L.; Ghadessi, Mercedeh; Erho, Nicholas; Vergara, Ismael A.; Alshalalfa, Mohammed; Buerki, Christine; Haddad, Zaid; Sierocinski, Thomas; Triche, Timothy J.; Skinner, Eila C.; Davicioni, Elai; Daneshmand, Siamak; Black, Peter C.

    2014-01-01

    Background Nearly half of muscle-invasive bladder cancer patients succumb to their disease following cystectomy. Selecting candidates for adjuvant therapy is currently based on clinical parameters with limited predictive power. This study aimed to develop and validate genomic-based signatures that can better identify patients at risk for recurrence than clinical models alone. Methods Transcriptome-wide expression profiles were generated using 1.4 million feature-arrays on archival tumors from 225 patients who underwent radical cystectomy and had muscle-invasive and/or node-positive bladder cancer. Genomic (GC) and clinical (CC) classifiers for predicting recurrence were developed on a discovery set (n = 133). Performances of GC, CC, an independent clinical nomogram (IBCNC), and genomic-clinicopathologic classifiers (G-CC, G-IBCNC) were assessed in the discovery and independent validation (n = 66) sets. GC was further validated on four external datasets (n = 341). Discrimination and prognostic abilities of classifiers were compared using area under receiver-operating characteristic curves (AUCs). All statistical tests were two-sided. Results A 15-feature GC was developed on the discovery set with area under curve (AUC) of 0.77 in the validation set. This was higher than individual clinical variables, IBCNC (AUC = 0.73), and comparable to CC (AUC = 0.78). Performance was improved upon combining GC with clinical nomograms (G-IBCNC, AUC = 0.82; G-CC, AUC = 0.86). G-CC high-risk patients had elevated recurrence probabilities (P < .001), with GC being the best predictor by multivariable analysis (P = .005). Genomic-clinicopathologic classifiers outperformed clinical nomograms by decision curve and reclassification analyses. GC performed the best in validation compared with seven prior signatures. GC markers remained prognostic across four independent datasets. Conclusions The validated genomic-based classifiers outperform clinical models for predicting postcystectomy bladder cancer recurrence. This may be used to better identify patients who need more aggressive management. PMID:25344601

  17. A classification prognostic score to predict OS in stage IV well-differentiated neuroendocrine tumors

    PubMed Central

    Pusceddu, Sara; Barretta, Francesco; Trama, Annalisa; Botta, Laura; Milione, Massimo; Buzzoni, Roberto; De Braud, Filippo; Mazzaferro, Vincenzo; Pastorino, Ugo; Seregni, Ettore; Mariani, Luigi; Gatta, Gemma; Di Bartolomeo, Maria; Femia, Daniela; Prinzi, Natalie; Coppa, Jorgelina; Panzuto, Francesco; Antonuzzo, Lorenzo; Bajetta, Emilio; Brizzi, Maria Pia; Campana, Davide; Catena, Laura; Comber, Harry; Dwane, Fiona; Fazio, Nicola; Faggiano, Antongiulio; Giuffrida, Dario; Henau, Kris; Ibrahim, Toni; Marconcini, Riccardo; Massironi, Sara; Žakelj, Maja Primic; Spada, Francesca; Tafuto, Salvatore; Van Eycken, Elizabeth; Van der Zwan, Jan Maaten; Žagar, Tina; Giacomelli, Luca; Miceli, Rosalba; Aroldi, Francesca; Bongiovanni, Alberto; Berardi, Rossana; Brighi, Nicole; Cingarlini, Sara; Cauchi, Carolina; Cavalcoli, Federica; Carnaghi, Carlo; Corti, Francesca; Duro, Marilina; Davì, Maria Vittoria; De Divitiis, Chiara; Ermacora, Paola; La Salvia, Anna; Luppi, Gabriele; Lo Russo, Giuseppe; Nichetti, Federico; Raimondi, Alessandra; Perfetti, Vittorio; Razzore, Paola; Rinzivillo, Maria; Siesling, Sabine; Torchio, Martina; Van Dijk, Boukje; Visser, Otto; Vernieri, Claudio

    2018-01-01

    No validated prognostic tool is available for predicting overall survival (OS) of patients with well-differentiated neuroendocrine tumors (WDNETs). This study, conducted in three independent cohorts of patients from five different European countries, aimed to develop and validate a classification prognostic score for OS in patients with stage IV WDNETs. We retrospectively collected data on 1387 patients: (i) patients treated at the Istituto Nazionale Tumori (Milan, Italy; n = 515); (ii) European cohort of rare NET patients included in the European RARECAREnet database (n = 457); (iii) Italian multicentric cohort of pancreatic NET (pNETs) patients treated at 24 Italian institutions (n = 415). The score was developed using data from patients included in cohort (i) (training set); external validation was performed by applying the score to the data of the two independent cohorts (ii) and (iii) evaluating both calibration and discriminative ability (Harrell C statistic). We used data on age, primary tumor site, metastasis (synchronous vs metachronous), Ki-67, functional status and primary surgery to build the score, which was developed for classifying patients into three groups with differential 10-year OS: (I) favorable risk group: 10-year OS ≥70%; (II) intermediate risk group: 30% ≤ 10-year OS < 70%; (III) poor risk group: 10-year OS <30%. The Harrell C statistic was 0.661 in the training set, and 0.626 and 0.601 in the RARECAREnet and Italian multicentric validation sets, respectively. In conclusion, based on the analysis of three ‘field-practice’ cohorts collected in different settings, we defined and validated a prognostic score to classify patients into three groups with different long-term prognoses. PMID:29559553

  18. Developing a Brief Cross-Culturally Validated Screening Tool for Externalizing Disorders in Children

    ERIC Educational Resources Information Center

    Zwirs, Barbara W. C.; Burger, Huibert; Schulpen, Tom W. J.; Buitelaar, Jan K.

    2008-01-01

    The study aims at developing and validating a brief, easy-to-use screening instrument for teachers to predict externalizing disorders in children and recommending them for timely referral. The scores are compared between Dutch and non-Dutch immigrant children and a significant amount of cases for externalizing disorders were identified but sex and…

  19. Development and validation of a new instrument for testing functional health literacy in Japanese adults.

    PubMed

    Nakagami, Katsuyuki; Yamauchi, Toyoaki; Noguchi, Hiroyuki; Maeda, Tohru; Nakagami, Tomoko

    2014-06-01

    This study aimed to develop a reliable and valid measure of functional health literacy in a Japanese clinical setting. Test development consisted of three phases: generation of an item pool, consultation with experts to assess content validity, and comparison with external criteria (the Japanese Health Knowledge Test) to assess criterion validity. A trial version of the test was administered to 535 Japanese outpatients. Internal consistency reliability, calculated by Cronbach's alpha, was 0.81, and concurrent validity was moderate. Receiver Operating Characteristics and Item Response Theory were used to classify patients as having adequate, marginal, or inadequate functional health literacy. Both inadequate and marginal functional health literacy were associated with older age, lower income, lower educational attainment, and poor health knowledge. The time required to complete the test was 10-15 min. This test should enable health workers to better identify patients with inadequate health literacy. © 2013 Wiley Publishing Asia Pty Ltd.

  20. New clues on carcinogenicity-related substructures derived from mining two large datasets of chemical compounds.

    PubMed

    Golbamaki, Azadi; Benfenati, Emilio; Golbamaki, Nazanin; Manganaro, Alberto; Merdivan, Erinc; Roncaglioni, Alessandra; Gini, Giuseppina

    2016-04-02

    In this study, new molecular fragments associated with genotoxic and nongenotoxic carcinogens are introduced to estimate the carcinogenic potential of compounds. Two rule-based carcinogenesis models were developed with the aid of SARpy: model R (from rodents' experimental data) and model E (from human carcinogenicity data). Structural alert extraction method of SARpy uses a completely automated and unbiased manner with statistical significance. The carcinogenicity models developed in this study are collections of carcinogenic potential fragments that were extracted from two carcinogenicity databases: the ANTARES carcinogenicity dataset with information from bioassay on rats and the combination of ISSCAN and CGX datasets, which take into accounts human-based assessment. The performance of these two models was evaluated in terms of cross-validation and external validation using a 258 compound case study dataset. Combining R and H predictions and scoring a positive or negative result when both models are concordant on a prediction, increased accuracy to 72% and specificity to 79% on the external test set. The carcinogenic fragments present in the two models were compared and analyzed from the point of view of chemical class. The results of this study show that the developed rule sets will be a useful tool to identify some new structural alerts of carcinogenicity and provide effective information on the molecular structures of carcinogenic chemicals.

  1. Authentication of organic feed by near-infrared spectroscopy combined with chemometrics: a feasibility study.

    PubMed

    Tres, A; van der Veer, G; Perez-Marin, M D; van Ruth, S M; Garrido-Varo, A

    2012-08-22

    Organic products tend to retail at a higher price than their conventional counterparts, which makes them susceptible to fraud. In this study we evaluate the application of near-infrared spectroscopy (NIRS) as a rapid, cost-effective method to verify the organic identity of feed for laying hens. For this purpose a total of 36 organic and 60 conventional feed samples from The Netherlands were measured by NIRS. A binary classification model (organic vs conventional feed) was developed using partial least squares discriminant analysis. Models were developed using five different data preprocessing techniques, which were externally validated by a stratified random resampling strategy using 1000 realizations. Spectral regions related to the protein and fat content were among the most important ones for the classification model. The models based on data preprocessed using direct orthogonal signal correction (DOSC), standard normal variate (SNV), and first and second derivatives provided the most successful results in terms of median sensitivity (0.91 in external validation) and median specificity (1.00 for external validation of SNV models and 0.94 for DOSC and first and second derivative models). A previously developed model, which was based on fatty acid fingerprinting of the same set of feed samples, provided a higher sensitivity (1.00). This shows that the NIRS-based approach provides a rapid and low-cost screening tool, whereas the fatty acid fingerprinting model can be used for further confirmation of the organic identity of feed samples for laying hens. These methods provide additional assurance to the administrative controls currently conducted in the organic feed sector.

  2. Quantitative parameters of CT texture analysis as potential markersfor early prediction of spontaneous intracranial hemorrhage enlargement.

    PubMed

    Shen, Qijun; Shan, Yanna; Hu, Zhengyu; Chen, Wenhui; Yang, Bing; Han, Jing; Huang, Yanfang; Xu, Wen; Feng, Zhan

    2018-04-30

    To objectively quantify intracranial hematoma (ICH) enlargement by analysing the image texture of head CT scans and to provide objective and quantitative imaging parameters for predicting early hematoma enlargement. We retrospectively studied 108 ICH patients with baseline non-contrast computed tomography (NCCT) and 24-h follow-up CT available. Image data were assessed by a chief radiologist and a resident radiologist. Consistency analysis between observers was tested. The patients were divided into training set (75%) and validation set (25%) by stratified sampling. Patients in the training set were dichotomized according to 24-h hematoma expansion ≥ 33%. Using the Laplacian of Gaussian bandpass filter, we chose different anatomical spatial domains ranging from fine texture to coarse texture to obtain a series of derived parameters (mean grayscale intensity, variance, uniformity) in order to quantify and evaluate all data. The parameters were externally validated on validation set. Significant differences were found between the two groups of patients within variance at V 1.0 and in uniformity at U 1.0 , U 1.8 and U 2.5 . The intraclass correlation coefficients for the texture parameters were between 0.67 and 0.99. The area under the ROC curve between the two groups of ICH cases was between 0.77 and 0.92. The accuracy of validation set by CTTA was 0.59-0.85. NCCT texture analysis can objectively quantify the heterogeneity of ICH and independently predict early hematoma enlargement. • Heterogeneity is helpful in predicting ICH enlargement. • CTTA could play an important role in predicting early ICH enlargement. • After filtering, fine texture had the best diagnostic performance. • The histogram-based uniformity parameters can independently predict ICH enlargement. • CTTA is more objective, more comprehensive, more independently operable, than previous methods.

  3. A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients.

    PubMed

    Oberije, Cary; De Ruysscher, Dirk; Houben, Ruud; van de Heuvel, Michel; Uyterlinde, Wilma; Deasy, Joseph O; Belderbos, Jose; Dingemans, Anne-Marie C; Rimner, Andreas; Din, Shaun; Lambin, Philippe

    2015-07-15

    Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can overcome this but are currently lacking. A DSS for stage III NSCLC requires the development and integration of multiple models. The current study takes the first step in this process by developing and validating a model that can provide physicians with a survival probability for an individual NSCLC patient. Data from 548 patients with stage III NSCLC were available to enable the development of a prediction model, using stratified Cox regression. Variables were selected by using a bootstrap procedure. Performance of the model was expressed as the c statistic, assessed internally and on 2 external data sets (n=174 and n=130). The final multivariate model, stratified for treatment, consisted of age, gender, World Health Organization performance status, overall treatment time, equivalent radiation dose, number of positive lymph node stations, and gross tumor volume. The bootstrapped c statistic was 0.62. The model could identify risk groups in external data sets. Nomograms were constructed to predict an individual patient's survival probability (www.predictcancer.org). The data set can be downloaded at https://www.cancerdata.org/10.1016/j.ijrobp.2015.02.048. The prediction model for overall survival of patients with stage III NSCLC highlights the importance of combining patient, clinical, and treatment variables. Nomograms were developed and validated. This tool could be used as a first building block for a decision support system. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  4. New Model for Estimating Glomerular Filtration Rate in Patients With Cancer

    PubMed Central

    Janowitz, Tobias; Williams, Edward H.; Marshall, Andrea; Ainsworth, Nicola; Thomas, Peter B.; Sammut, Stephen J.; Shepherd, Scott; White, Jeff; Mark, Patrick B.; Lynch, Andy G.; Jodrell, Duncan I.; Tavaré, Simon; Earl, Helena

    2017-01-01

    Purpose The glomerular filtration rate (GFR) is essential for carboplatin chemotherapy dosing; however, the best method to estimate GFR in patients with cancer is unknown. We identify the most accurate and least biased method. Methods We obtained data on age, sex, height, weight, serum creatinine concentrations, and results for GFR from chromium-51 (51Cr) EDTA excretion measurements (51Cr-EDTA GFR) from white patients ≥ 18 years of age with histologically confirmed cancer diagnoses at the Cambridge University Hospital NHS Trust, United Kingdom. We developed a new multivariable linear model for GFR using statistical regression analysis. 51Cr-EDTA GFR was compared with the estimated GFR (eGFR) from seven published models and our new model, using the statistics root-mean-squared-error (RMSE) and median residual and on an internal and external validation data set. We performed a comparison of carboplatin dosing accuracy on the basis of an absolute percentage error > 20%. Results Between August 2006 and January 2013, data from 2,471 patients were obtained. The new model improved the eGFR accuracy (RMSE, 15.00 mL/min; 95% CI, 14.12 to 16.00 mL/min) compared with all published models. Body surface area (BSA)–adjusted chronic kidney disease epidemiology (CKD-EPI) was the most accurate published model for eGFR (RMSE, 16.30 mL/min; 95% CI, 15.34 to 17.38 mL/min) for the internal validation set. Importantly, the new model reduced the fraction of patients with a carboplatin dose absolute percentage error > 20% to 14.17% in contrast to 18.62% for the BSA-adjusted CKD-EPI and 25.51% for the Cockcroft-Gault formula. The results were externally validated. Conclusion In a large data set from patients with cancer, BSA-adjusted CKD-EPI is the most accurate published model to predict GFR. The new model improves this estimation and may present a new standard of care. PMID:28686534

  5. New Model for Estimating Glomerular Filtration Rate in Patients With Cancer.

    PubMed

    Janowitz, Tobias; Williams, Edward H; Marshall, Andrea; Ainsworth, Nicola; Thomas, Peter B; Sammut, Stephen J; Shepherd, Scott; White, Jeff; Mark, Patrick B; Lynch, Andy G; Jodrell, Duncan I; Tavaré, Simon; Earl, Helena

    2017-08-20

    Purpose The glomerular filtration rate (GFR) is essential for carboplatin chemotherapy dosing; however, the best method to estimate GFR in patients with cancer is unknown. We identify the most accurate and least biased method. Methods We obtained data on age, sex, height, weight, serum creatinine concentrations, and results for GFR from chromium-51 ( 51 Cr) EDTA excretion measurements ( 51 Cr-EDTA GFR) from white patients ≥ 18 years of age with histologically confirmed cancer diagnoses at the Cambridge University Hospital NHS Trust, United Kingdom. We developed a new multivariable linear model for GFR using statistical regression analysis. 51 Cr-EDTA GFR was compared with the estimated GFR (eGFR) from seven published models and our new model, using the statistics root-mean-squared-error (RMSE) and median residual and on an internal and external validation data set. We performed a comparison of carboplatin dosing accuracy on the basis of an absolute percentage error > 20%. Results Between August 2006 and January 2013, data from 2,471 patients were obtained. The new model improved the eGFR accuracy (RMSE, 15.00 mL/min; 95% CI, 14.12 to 16.00 mL/min) compared with all published models. Body surface area (BSA)-adjusted chronic kidney disease epidemiology (CKD-EPI) was the most accurate published model for eGFR (RMSE, 16.30 mL/min; 95% CI, 15.34 to 17.38 mL/min) for the internal validation set. Importantly, the new model reduced the fraction of patients with a carboplatin dose absolute percentage error > 20% to 14.17% in contrast to 18.62% for the BSA-adjusted CKD-EPI and 25.51% for the Cockcroft-Gault formula. The results were externally validated. Conclusion In a large data set from patients with cancer, BSA-adjusted CKD-EPI is the most accurate published model to predict GFR. The new model improves this estimation and may present a new standard of care.

  6. French Multicenter Study Evaluating the Risk of Lymph Node Metastases in Early-Stage Endometrial Cancer: Contribution of a Risk Scoring System.

    PubMed

    Bendifallah, Sofiane; Canlorbe, Geoffroy; Arsène, Emmanuelle; Collinet, Pierre; Huguet, Florence; Coutant, Charles; Hudry, Delphine; Graesslin, Olivier; Raimond, Emilie; Touboul, Cyril; Daraï, Emile; Ballester, Marcos

    2015-08-01

    This study was designed to develop a risk scoring system (RSS) for predicting lymph node (LN) metastases in patients with early-stage endometrial cancer (EC). Data of 457 patients with early-stage EC who received primary surgical treatment between January 2001 and December 2012 were abstracted from a prospective, multicentre database (training set). A risk model based on factors impacting LN metastases was developed. To assess the discrimination of the RSS, both internal by the bootstrap approach and external validation (validation set) were adopted. Overall the LN metastasis rate was 11.8 % (54/457). LN metastases were associated with five variables: age ≥60 years, histological grade 3 and/or type 2, primary tumor diameter ≥1.5 cm, depth of myometrial invasion ≥50 %, and the positive lymphovascular space involvement status. These variables were included in the RSS and assigned scores ranging from 0 to 9. The discrimination of the RSS was 0.81 [95 % confidence interval (CI) 0.78-0.84] in the training set. The area under the curve of the receiver-operating characteristics for predicting LN metastases after internal and external validation was 0.80 (95 % CI 0.77-0.83) and 0.85 (95 % CI 0.81-0.89), respectively. A total score of 6 points corresponded to the optimal threshold of the RSS with a rate of LN metastases of 7.5 % (29/385) and 34.7 % (25/72) for low-risk (≤6 points) and high-risk patients (>6 points), respectively. At this threshold, the diagnostic accuracy was 83 %. This RSS could be useful in clinical practice to determine which patients with early-stage EC should benefit from secondary surgical staging including complete lymphadenectomy.

  7. An External Archive-Guided Multiobjective Particle Swarm Optimization Algorithm.

    PubMed

    Zhu, Qingling; Lin, Qiuzhen; Chen, Weineng; Wong, Ka-Chun; Coello Coello, Carlos A; Li, Jianqiang; Chen, Jianyong; Zhang, Jun

    2017-09-01

    The selection of swarm leaders (i.e., the personal best and global best), is important in the design of a multiobjective particle swarm optimization (MOPSO) algorithm. Such leaders are expected to effectively guide the swarm to approach the true Pareto optimal front. In this paper, we present a novel external archive-guided MOPSO algorithm (AgMOPSO), where the leaders for velocity update are all selected from the external archive. In our algorithm, multiobjective optimization problems (MOPs) are transformed into a set of subproblems using a decomposition approach, and then each particle is assigned accordingly to optimize each subproblem. A novel archive-guided velocity update method is designed to guide the swarm for exploration, and the external archive is also evolved using an immune-based evolutionary strategy. These proposed approaches speed up the convergence of AgMOPSO. The experimental results fully demonstrate the superiority of our proposed AgMOPSO in solving most of the test problems adopted, in terms of two commonly used performance measures. Moreover, the effectiveness of our proposed archive-guided velocity update method and immune-based evolutionary strategy is also experimentally validated on more than 30 test MOPs.

  8. Can hip and knee kinematics be improved by eliminating thigh markers?

    PubMed Central

    Schulz, Brian W.; Kimmel, Wendy L.

    2017-01-01

    Background Marker sets developed for gait analysis are often applied to more dynamic tasks with little or no validation, despite known complications of soft tissue artifact. Methods This study presents a comparison of hip and knee kinematics as calculated by five concurrently-worn tracking marker sets during eight different tasks. The first three marker sets were based on Helen Hayes but used 1) proximal thigh wands, 2) distal thigh wands, and 3) patellar markers instead of thigh wands. The remaining two marker sets used rigid clusters on the 4) thighs and shanks and 5) only shanks. Pelvis and foot segments were shared by all marker sets. The first three tasks were maximal femoral rotations using different knee and hip positions to quantify the ability of each marker set to capture this motion. The remaining five tasks were walking, walking a 1m radius circle, running, jumping, and lunging. Findings In general, few and small differences in knee and hip flexion-extension were observed between marker sets, while many and large differences in adduction-abduction and external-internal rotations were observed. The shank-only tracking marker set was capable of detecting the greatest hip external-internal rotation, yet only did so during dynamic tasks where greater hip axial motions would be expected. All data are available as supplementary material. Interpretation Marker set selection is critical to non-sagittal hip and knee motions. The shank-only tracking marker set presented here is a viable alternative that may improve knee and hip kinematics by eliminating errors from thigh soft tissue artifact. PMID:20493599

  9. Demonstrating Experimenter "Ineptitude" as a Means of Teaching Internal and External Validity

    ERIC Educational Resources Information Center

    Treadwell, Kimberli R.H.

    2008-01-01

    Internal and external validity are key concepts in understanding the scientific method and fostering critical thinking. This article describes a class demonstration of a "botched" experiment to teach validity to undergraduates. Psychology students (N = 75) completed assessments at the beginning of the semester, prior to and immediately following…

  10. The internal and external validity of the Major Depression Inventory in measuring severity of depressive states.

    PubMed

    Olsen, L R; Jensen, D V; Noerholm, V; Martiny, K; Bech, P

    2003-02-01

    We have developed the Major Depression Inventory (MDI), consisting of 10 items, covering the DSM-IV as well as the ICD-10 symptoms of depressive illness. We aimed to evaluate this as a scale measuring severity of depressive states with reference to both internal and external validity. Patients representing the score range from no depression to marked depression on the Hamilton Depression Scale (HAM-D) completed the MDI. Both classical and modern psychometric methods were applied for the evaluation of validity, including the Rasch analysis. In total, 91 patients were included. The results showed that the MDI had an adequate internal validity in being a unidimensional scale (the total score an appropriate or sufficient statistic). The external validity of the MDI was also confirmed as the total score of the MDI correlated significantly with the HAM-D (Pearson's coefficient 0.86, P < or = 0.01, Spearman 0.80, P < or = 0.01). When used in a sample of patients with different states of depression the MDI has an adequate internal and external validity.

  11. 3D-quantitative structure-activity relationship studies on benzothiadiazepine hydroxamates as inhibitors of tumor necrosis factor-alpha converting enzyme.

    PubMed

    Murumkar, Prashant R; Giridhar, Rajani; Yadav, Mange Ram

    2008-04-01

    A set of 29 benzothiadiazepine hydroxamates having selective tumor necrosis factor-alpha converting enzyme inhibitory activity were used to compare the quality and predictive power of 3D-quantitative structure-activity relationship, comparative molecular field analysis, and comparative molecular similarity indices models for the atom-based, centroid/atom-based, data-based, and docked conformer-based alignment. Removal of two outliers from the initial training set of molecules improved the predictivity of models. Among the 3D-quantitative structure-activity relationship models developed using the above four alignments, the database alignment provided the optimal predictive comparative molecular field analysis model for the training set with cross-validated r(2) (q(2)) = 0.510, non-cross-validated r(2) = 0.972, standard error of estimates (s) = 0.098, and F = 215.44 and the optimal comparative molecular similarity indices model with cross-validated r(2) (q(2)) = 0.556, non-cross-validated r(2) = 0.946, standard error of estimates (s) = 0.163, and F = 99.785. These models also showed the best test set prediction for six compounds with predictive r(2) values of 0.460 and 0.535, respectively. The contour maps obtained from 3D-quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular similarity indices models exhibited good external predictivity as compared with that of comparative molecular field analysis models. The data generated from the present study helped us to further design and report some novel and potent tumor necrosis factor-alpha converting enzyme inhibitors.

  12. International validation of the consensus Immunoscore for the classification of colon cancer: a prognostic and accuracy study.

    PubMed

    Pagès, Franck; Mlecnik, Bernhard; Marliot, Florence; Bindea, Gabriela; Ou, Fang-Shu; Bifulco, Carlo; Lugli, Alessandro; Zlobec, Inti; Rau, Tilman T; Berger, Martin D; Nagtegaal, Iris D; Vink-Börger, Elisa; Hartmann, Arndt; Geppert, Carol; Kolwelter, Julie; Merkel, Susanne; Grützmann, Robert; Van den Eynde, Marc; Jouret-Mourin, Anne; Kartheuser, Alex; Léonard, Daniel; Remue, Christophe; Wang, Julia Y; Bavi, Prashant; Roehrl, Michael H A; Ohashi, Pamela S; Nguyen, Linh T; Han, SeongJun; MacGregor, Heather L; Hafezi-Bakhtiari, Sara; Wouters, Bradly G; Masucci, Giuseppe V; Andersson, Emilia K; Zavadova, Eva; Vocka, Michal; Spacek, Jan; Petruzelka, Lubos; Konopasek, Bohuslav; Dundr, Pavel; Skalova, Helena; Nemejcova, Kristyna; Botti, Gerardo; Tatangelo, Fabiana; Delrio, Paolo; Ciliberto, Gennaro; Maio, Michele; Laghi, Luigi; Grizzi, Fabio; Fredriksen, Tessa; Buttard, Bénédicte; Angelova, Mihaela; Vasaturo, Angela; Maby, Pauline; Church, Sarah E; Angell, Helen K; Lafontaine, Lucie; Bruni, Daniela; El Sissy, Carine; Haicheur, Nacilla; Kirilovsky, Amos; Berger, Anne; Lagorce, Christine; Meyers, Jeffrey P; Paustian, Christopher; Feng, Zipei; Ballesteros-Merino, Carmen; Dijkstra, Jeroen; van de Water, Carlijn; van Lent-van Vliet, Shannon; Knijn, Nikki; Mușină, Ana-Maria; Scripcariu, Dragos-Viorel; Popivanova, Boryana; Xu, Mingli; Fujita, Tomonobu; Hazama, Shoichi; Suzuki, Nobuaki; Nagano, Hiroaki; Okuno, Kiyotaka; Torigoe, Toshihiko; Sato, Noriyuki; Furuhata, Tomohisa; Takemasa, Ichiro; Itoh, Kyogo; Patel, Prabhu S; Vora, Hemangini H; Shah, Birva; Patel, Jayendrakumar B; Rajvik, Kruti N; Pandya, Shashank J; Shukla, Shilin N; Wang, Yili; Zhang, Guanjun; Kawakami, Yutaka; Marincola, Francesco M; Ascierto, Paolo A; Sargent, Daniel J; Fox, Bernard A; Galon, Jérôme

    2018-05-26

    The estimation of risk of recurrence for patients with colon carcinoma must be improved. A robust immune score quantification is needed to introduce immune parameters into cancer classification. The aim of the study was to assess the prognostic value of total tumour-infiltrating T-cell counts and cytotoxic tumour-infiltrating T-cells counts with the consensus Immunoscore assay in patients with stage I-III colon cancer. An international consortium of 14 centres in 13 countries, led by the Society for Immunotherapy of Cancer, assessed the Immunoscore assay in patients with TNM stage I-III colon cancer. Patients were randomly assigned to a training set, an internal validation set, or an external validation set. Paraffin sections of the colon tumour and invasive margin from each patient were processed by immunohistochemistry, and the densities of CD3+ and cytotoxic CD8+ T cells in the tumour and in the invasive margin were quantified by digital pathology. An Immunoscore for each patient was derived from the mean of four density percentiles. The primary endpoint was to evaluate the prognostic value of the Immunoscore for time to recurrence, defined as time from surgery to disease recurrence. Stratified multivariable Cox models were used to assess the associations between Immunoscore and outcomes, adjusting for potential confounders. Harrell's C-statistics was used to assess model performance. Tissue samples from 3539 patients were processed, and samples from 2681 patients were included in the analyses after quality controls (700 patients in the training set, 636 patients in the internal validation set, and 1345 patients in the external validation set). The Immunoscore assay showed a high level of reproducibility between observers and centres (r=0·97 for colon tumour; r=0·97 for invasive margin; p<0·0001). In the training set, patients with a high Immunoscore had the lowest risk of recurrence at 5 years (14 [8%] patients with a high Immunoscore vs 65 (19%) patients with an intermediate Immunoscore vs 51 (32%) patients with a low Immunoscore; hazard ratio [HR] for high vs low Immunoscore 0·20, 95% CI 0·10-0·38; p<0·0001). The findings were confirmed in the two validation sets (n=1981). In the stratified Cox multivariable analysis, the Immunoscore association with time to recurrence was independent of patient age, sex, T stage, N stage, microsatellite instability, and existing prognostic factors (p<0·0001). Of 1434 patients with stage II cancer, the difference in risk of recurrence at 5 years was significant (HR for high vs low Immunoscore 0·33, 95% CI 0·21-0·52; p<0·0001), including in Cox multivariable analysis (p<0·0001). Immunoscore had the highest relative contribution to the risk of all clinical parameters, including the American Joint Committee on Cancer and Union for International Cancer Control TNM classification system. The Immunoscore provides a reliable estimate of the risk of recurrence in patients with colon cancer. These results support the implementation of the consensus Immunoscore as a new component of a TNM-Immune classification of cancer. French National Institute of Health and Medical Research, the LabEx Immuno-oncology, the Transcan ERAnet Immunoscore European project, Association pour la Recherche contre le Cancer, CARPEM, AP-HP, Institut National du Cancer, Italian Association for Cancer Research, national grants and the Society for Immunotherapy of Cancer. Copyright © 2018 Elsevier Ltd. All rights reserved.

  13. Development of a novel fingerprint for chemical reactions and its application to large-scale reaction classification and similarity.

    PubMed

    Schneider, Nadine; Lowe, Daniel M; Sayle, Roger A; Landrum, Gregory A

    2015-01-26

    Fingerprint methods applied to molecules have proven to be useful for similarity determination and as inputs to machine-learning models. Here, we present the development of a new fingerprint for chemical reactions and validate its usefulness in building machine-learning models and in similarity assessment. Our final fingerprint is constructed as the difference of the atom-pair fingerprints of products and reactants and includes agents via calculated physicochemical properties. We validated the fingerprints on a large data set of reactions text-mined from granted United States patents from the last 40 years that have been classified using a substructure-based expert system. We applied machine learning to build a 50-class predictive model for reaction-type classification that correctly predicts 97% of the reactions in an external test set. Impressive accuracies were also observed when applying the classifier to reactions from an in-house electronic laboratory notebook. The performance of the novel fingerprint for assessing reaction similarity was evaluated by a cluster analysis that recovered 48 out of 50 of the reaction classes with a median F-score of 0.63 for the clusters. The data sets used for training and primary validation as well as all python scripts required to reproduce the analysis are provided in the Supporting Information.

  14. Construct Validity of the MMPI-2-RF Triarchic Psychopathy Scales in Correctional and Collegiate Samples.

    PubMed

    Kutchen, Taylor J; Wygant, Dustin B; Tylicki, Jessica L; Dieter, Amy M; Veltri, Carlo O C; Sellbom, Martin

    2017-01-01

    This study examined the MMPI-2-RF (Ben-Porath & Tellegen, 2008/2011) Triarchic Psychopathy scales recently developed by Sellbom et al. ( 2016 ) in 3 separate groups of male correctional inmates and 2 college samples. Participants were administered a diverse battery of psychopathy specific measures (e.g., Psychopathy Checklist-Revised [Hare, 2003 ], Psychopathic Personality Inventory-Revised [Lilienfeld & Widows, 2005 ], Triarchic Psychopathy Measure [Patrick, 2010 ]), omnibus personality and psychopathology measures such as the Personality Assessment Inventory (Morey, 2007 ) and Personality Inventory for DSM-5 (Krueger, Derringer, Markon, Watson, & Skodol, 2012 ), and narrow-band measures that capture conceptually relevant constructs. Our results generally evidenced strong support for the convergent and discriminant validity for the MMPI-2-RF Triarchic scales. Boldness was largely associated with measures of fearless dominance, social potency, and stress immunity. Meanness showed strong relationships with measures of callousness, aggression, externalizing tendencies, and poor interpersonal functioning. Disinhibition exhibited strong associations with poor impulse control, stimulus seeking, and general externalizing proclivities. Our results provide additional construct validation to both the triarchic model and MMPI-2-RF Triarchic scales. Given the widespread use of the MMPI-2-RF in correctional and forensic settings, our results have important implications for clinical assessment in these 2 areas, where psychopathy is a highly relevant construct.

  15. External Validity in the Study of Human Development: Theoretical and Methodological Issues

    ERIC Educational Resources Information Center

    Hultsch, David F.; Hickey, Tom

    1978-01-01

    An examination of the concept of external validity from two theoretical perspectives: a traditional mechanistic approach and a dialectical organismic approach. Examines the theoretical and methodological implications of these perspectives. (BD)

  16. Physical activity promotion in Latin American populations: a systematic review on issues of internal and external validity

    PubMed Central

    2014-01-01

    The purpose of this review was to determine the degree to which physical activity interventions for Latin American populations reported on internal and external validity factors using the RE-AIM framework (reach & representativeness, effectiveness, adoption, implementation, maintenance). We systematically identified English (PubMed; EbscoHost) and Spanish (SCIELO; Biblioteca Virtual en Salud) language studies published between 2001 and 2012 that tested physical activity, exercise, or fitness promotion interventions in Latin American populations. Cross-sectional/descriptive studies, conducted in Brazil or Spain, published in Portuguese, not including a physical activity/fitness/exercise outcome, and with one time point assessment were excluded. We reviewed 192 abstracts and identified 46 studies that met the eligibility criteria (34 in English, 12 in Spanish). A validated 21-item RE-AIM abstraction tool was used to determine the quality of reporting across studies (0-7 = low, 8-14 = moderate, and 15-21 = high). The number of indicators reported ranged from 3–14 (mean = 8.1 ± 2.6), with the majority of studies falling in the moderate quality reporting category. English and Spanish language articles did not differ on the number of indicators reported (8.1 vs. 8.3, respectively). However, Spanish articles reported more across reach indicators (62% vs. 43% of indicators), while English articles reported more across effectiveness indicators (69% vs 62%). Across RE-AIM dimensions, indicators for reach (48%), efficacy/effectiveness (67%), and implementation (41%) were reported more often than indicators of adoption (25%) and maintenance (10%). Few studies reported on the representativeness of participants, staff that delivered interventions, or the settings where interventions were adopted. Only 13% of the studies reported on quality of life and/or potential negative outcomes, 20% reported on intervention fidelity, and 11% on cost of implementation. Outcomes measured after six months of intervention, information on continued delivery and institutionalization of interventions, were also seldom reported. Regardless of language of publication, physical activity intervention research for Latin Americans should increase attention to and measurement of external validity and cost factors that are critical in the decision making process in practice settings and can increase the likelihood of translation into community or clinical practice. PMID:24938641

  17. Physical activity promotion in Latin American populations: a systematic review on issues of internal and external validity.

    PubMed

    Galaviz, Karla I; Harden, Samantha M; Smith, Erin; Blackman, Kacie Ca; Berrey, Leanna M; Mama, Scherezade K; Almeida, Fabio A; Lee, Rebecca E; Estabrooks, Paul A

    2014-06-17

    The purpose of this review was to determine the degree to which physical activity interventions for Latin American populations reported on internal and external validity factors using the RE-AIM framework (reach & representativeness, effectiveness, adoption, implementation, maintenance). We systematically identified English (PubMed; EbscoHost) and Spanish (SCIELO; Biblioteca Virtual en Salud) language studies published between 2001 and 2012 that tested physical activity, exercise, or fitness promotion interventions in Latin American populations. Cross-sectional/descriptive studies, conducted in Brazil or Spain, published in Portuguese, not including a physical activity/fitness/exercise outcome, and with one time point assessment were excluded. We reviewed 192 abstracts and identified 46 studies that met the eligibility criteria (34 in English, 12 in Spanish). A validated 21-item RE-AIM abstraction tool was used to determine the quality of reporting across studies (0-7 = low, 8-14 = moderate, and 15-21 = high). The number of indicators reported ranged from 3-14 (mean = 8.1 ± 2.6), with the majority of studies falling in the moderate quality reporting category. English and Spanish language articles did not differ on the number of indicators reported (8.1 vs. 8.3, respectively). However, Spanish articles reported more across reach indicators (62% vs. 43% of indicators), while English articles reported more across effectiveness indicators (69% vs 62%). Across RE-AIM dimensions, indicators for reach (48%), efficacy/effectiveness (67%), and implementation (41%) were reported more often than indicators of adoption (25%) and maintenance (10%). Few studies reported on the representativeness of participants, staff that delivered interventions, or the settings where interventions were adopted. Only 13% of the studies reported on quality of life and/or potential negative outcomes, 20% reported on intervention fidelity, and 11% on cost of implementation. Outcomes measured after six months of intervention, information on continued delivery and institutionalization of interventions, were also seldom reported. Regardless of language of publication, physical activity intervention research for Latin Americans should increase attention to and measurement of external validity and cost factors that are critical in the decision making process in practice settings and can increase the likelihood of translation into community or clinical practice.

  18. Development and External Validation of the Korean Prostate Cancer Risk Calculator for High-Grade Prostate Cancer: Comparison with Two Western Risk Calculators in an Asian Cohort

    PubMed Central

    Yoon, Sungroh; Park, Man Sik; Choi, Hoon; Bae, Jae Hyun; Moon, Du Geon; Hong, Sung Kyu; Lee, Sang Eun; Park, Chanwang

    2017-01-01

    Purpose We developed the Korean Prostate Cancer Risk Calculator for High-Grade Prostate Cancer (KPCRC-HG) that predicts the probability of prostate cancer (PC) of Gleason score 7 or higher at the initial prostate biopsy in a Korean cohort (http://acl.snu.ac.kr/PCRC/RISC/). In addition, KPCRC-HG was validated and compared with internet-based Western risk calculators in a validation cohort. Materials and Methods Using a logistic regression model, KPCRC-HG was developed based on the data from 602 previously unscreened Korean men who underwent initial prostate biopsies. Using 2,313 cases in a validation cohort, KPCRC-HG was compared with the European Randomized Study of Screening for PC Risk Calculator for high-grade cancer (ERSPCRC-HG) and the Prostate Cancer Prevention Trial Risk Calculator 2.0 for high-grade cancer (PCPTRC-HG). The predictive accuracy was assessed using the area under the receiver operating characteristic curve (AUC) and calibration plots. Results PC was detected in 172 (28.6%) men, 120 (19.9%) of whom had PC of Gleason score 7 or higher. Independent predictors included prostate-specific antigen levels, digital rectal examination findings, transrectal ultrasound findings, and prostate volume. The AUC of the KPCRC-HG (0.84) was higher than that of the PCPTRC-HG (0.79, p<0.001) but not different from that of the ERSPCRC-HG (0.83) on external validation. Calibration plots also revealed better performance of KPCRC-HG and ERSPCRC-HG than that of PCPTRC-HG on external validation. At a cut-off of 5% for KPCRC-HG, 253 of the 2,313 men (11%) would not have been biopsied, and 14 of the 614 PC cases with Gleason score 7 or higher (2%) would not have been diagnosed. Conclusions KPCRC-HG is the first web-based high-grade prostate cancer prediction model in Korea. It had higher predictive accuracy than PCPTRC-HG in a Korean population and showed similar performance with ERSPCRC-HG in a Korean population. This prediction model could help avoid unnecessary biopsy and reduce overdiagnosis and overtreatment in clinical settings. PMID:28046017

  19. Development and External Validation of the Korean Prostate Cancer Risk Calculator for High-Grade Prostate Cancer: Comparison with Two Western Risk Calculators in an Asian Cohort.

    PubMed

    Park, Jae Young; Yoon, Sungroh; Park, Man Sik; Choi, Hoon; Bae, Jae Hyun; Moon, Du Geon; Hong, Sung Kyu; Lee, Sang Eun; Park, Chanwang; Byun, Seok-Soo

    2017-01-01

    We developed the Korean Prostate Cancer Risk Calculator for High-Grade Prostate Cancer (KPCRC-HG) that predicts the probability of prostate cancer (PC) of Gleason score 7 or higher at the initial prostate biopsy in a Korean cohort (http://acl.snu.ac.kr/PCRC/RISC/). In addition, KPCRC-HG was validated and compared with internet-based Western risk calculators in a validation cohort. Using a logistic regression model, KPCRC-HG was developed based on the data from 602 previously unscreened Korean men who underwent initial prostate biopsies. Using 2,313 cases in a validation cohort, KPCRC-HG was compared with the European Randomized Study of Screening for PC Risk Calculator for high-grade cancer (ERSPCRC-HG) and the Prostate Cancer Prevention Trial Risk Calculator 2.0 for high-grade cancer (PCPTRC-HG). The predictive accuracy was assessed using the area under the receiver operating characteristic curve (AUC) and calibration plots. PC was detected in 172 (28.6%) men, 120 (19.9%) of whom had PC of Gleason score 7 or higher. Independent predictors included prostate-specific antigen levels, digital rectal examination findings, transrectal ultrasound findings, and prostate volume. The AUC of the KPCRC-HG (0.84) was higher than that of the PCPTRC-HG (0.79, p<0.001) but not different from that of the ERSPCRC-HG (0.83) on external validation. Calibration plots also revealed better performance of KPCRC-HG and ERSPCRC-HG than that of PCPTRC-HG on external validation. At a cut-off of 5% for KPCRC-HG, 253 of the 2,313 men (11%) would not have been biopsied, and 14 of the 614 PC cases with Gleason score 7 or higher (2%) would not have been diagnosed. KPCRC-HG is the first web-based high-grade prostate cancer prediction model in Korea. It had higher predictive accuracy than PCPTRC-HG in a Korean population and showed similar performance with ERSPCRC-HG in a Korean population. This prediction model could help avoid unnecessary biopsy and reduce overdiagnosis and overtreatment in clinical settings.

  20. Dry selection and wet evaluation for the rational discovery of new anthelmintics

    NASA Astrophysics Data System (ADS)

    Marrero-Ponce, Yovani; Castañeda, Yeniel González; Vivas-Reyes, Ricardo; Vergara, Fredy Máximo; Arán, Vicente J.; Castillo-Garit, Juan A.; Pérez-Giménez, Facundo; Torrens, Francisco; Le-Thi-Thu, Huong; Pham-The, Hai; Montenegro, Yolanda Vera; Ibarra-Velarde, Froylán

    2017-09-01

    Helminths infections remain a major problem in medical and public health. In this report, atom-based 2D bilinear indices, a TOMOCOMD-CARDD (QuBiLs-MAS module) molecular descriptor family and linear discriminant analysis (LDA) were used to find models that differentiate among anthelmintic and non-anthelmintic compounds. Two classification models obtained by using non-stochastic and stochastic 2D bilinear indices, classified correctly 86.64% and 84.66%, respectively, in the training set. Equation 1(2) correctly classified 141(135) out of 165 [85.45%(81.82%)] compounds in external validation set. Another LDA models were performed in order to get the most likely mechanism of action of anthelmintics. The model shows an accuracy of 86.84% in the training set and 94.44% in the external prediction set. Finally, we carry out an experiment to predict the biological profile of our 'in-house' collections of indole, indazole, quinoxaline and cinnoline derivatives (∼200 compounds). Subsequently, we selected a group of nine of the theoretically most active structures. Then, these chemicals were tested in an in vitro assay and one good candidate (VA5-5c) as fasciolicide compound (100% of reduction at concentrations of 50 and 10 mg/L) was discovered.

  1. An Experimental and Numerical Study of a Supersonic Burner for CFD Model Development

    NASA Technical Reports Server (NTRS)

    Magnotti, G.; Cutler, A. D.

    2008-01-01

    A laboratory scale supersonic burner has been developed for validation of computational fluid dynamics models. Detailed numerical simulations were performed for the flow inside the combustor, and coupled with finite element thermal analysis to obtain more accurate outflow conditions. A database of nozzle exit profiles for a wide range of conditions of interest was generated to be used as boundary conditions for simulation of the external jet, or for validation of non-intrusive measurement techniques. A set of experiments was performed to validate the numerical results. In particular, temperature measurements obtained by using an infrared camera show that the computed heat transfer was larger than the measured value. Relaminarization in the convergent part of the nozzle was found to be responsible for this discrepancy, and further numerical simulations sustained this conclusion.

  2. Time from Prior Chemotherapy Enhances Prognostic Risk Grouping in the Second-line Setting of Advanced Urothelial Carcinoma: A Retrospective Analysis of Pooled, Prospective Phase 2 Trials

    PubMed Central

    Sonpavde, Guru; Pond, Gregory R.; Fougeray, Ronan; Choueiri, Toni K.; Qu, Angela Q.; Vaughn, David J.; Niegisch, Guenter; Albers, Peter; James, Nicholas D.; Wong, Yu-Ning; Ko, Yoo-Joung; Sridhar, Srikala S.; Galsky, Matthew D.; Petrylak, Daniel P.; Vaishampayan, Ulka N.; Khan, Awais; Vogelzang, Nicholas J.; Beer, Tomasz M.; Stadler, Walter M.; O’Donnell, Peter H.; Sternberg, Cora N.; Rosenberg, Jonathan E.; Bellmunt, Joaquim

    2014-01-01

    Background Outcomes for patients in the second-line setting of advanced urothelial carcinoma (UC) are dismal. The recognized prognostic factors in this context are Eastern Cooperative Oncology Group (ECOG) performance status (PS) >0, hemoglobin level (Hb) <10 g/dl, and liver metastasis (LM). Objectives The purpose of this retrospective study of prospective trials was to investigate the prognostic value of time from prior chemotherapy (TFPC) independent of known prognostic factors. Design, setting, and participants: Data from patients from seven prospective trials with available baseline TFPC, Hb, PS, and LM values were used for retrospective analysis (n = 570). External validation was conducted in a second-line phase 3 trial comparing best supportive care (BSC) versus vinflunine plus BSC (n = 352). Outcome measurements and statistical analysis Cox proportional hazards regression was used to evaluate the association of factors, with overall survival (OS) and progression-free survival (PFS) being the respective primary and secondary outcome measures. Results and limitations ECOG-PS >0, LM, Hb <10 g/dl, and shorter TFPC were significant prognostic factors for OS and PFS on multivariable analysis. Patients with zero, one, two, and three to four factors demonstrated median OS of 12.2, 6.7, 5.1, and 3.0 mo, respectively (concordance statistic = 0.638). Setting of prior chemotherapy (metastatic disease vs perioperative) and prior platinum agent (cisplatin or carboplatin) were not prognostic factors. External validation demonstrated a significant association of TFPC with PFS on univariable and most multivariable analyses, and with OS on univariable analyses. Limitations of retrospective analyses are applicable. Conclusions Shorter TFPC enhances prognostic classification independent of ECOG-PS>0, Hb<10 g/ dl, and LM in the setting of second-line therapy for advanced UC. These data may facilitate drug development and interpretation of trials. PMID:23206856

  3. Validating the cross-cultural factor structure and invariance property of the Insomnia Severity Index: evidence based on ordinal EFA and CFA.

    PubMed

    Chen, Po-Yi; Yang, Chien-Ming; Morin, Charles M

    2015-05-01

    The purpose of this study is to examine the factor structure of the Insomnia Severity Index (ISI) across samples recruited from different countries. We tried to identify the most appropriate factor model for the ISI and further examined the measurement invariance property of the ISI across samples from different countries. Our analyses included one data set collected from a Taiwanese sample and two data sets obtained from samples in Hong Kong and Canada. The data set collected in Taiwan was analyzed with ordinal exploratory factor analysis (EFA) to obtain the appropriate factor model for the ISI. After that, we conducted a series of confirmatory factor analyses (CFAs), which is a special case of the structural equation model (SEM) that concerns the parameters in the measurement model, to the statistics collected in Canada and Hong Kong. The purposes of these CFA were to cross-validate the result obtained from EFA and further examine the cross-cultural measurement invariance of the ISI. The three-factor model outperforms other models in terms of global fit indices in Taiwan's population. Its external validity is also supported by confirmatory factor analyses. Furthermore, the measurement invariance analyses show that the strong invariance property between the samples from different cultures holds, providing evidence that the ISI results obtained in different cultures are comparable. The factorial validity of the ISI is stable in different populations. More importantly, its invariance property across cultures suggests that the ISI is a valid measure of the insomnia severity construct across countries. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. A new IRT-based standard setting method: application to eCat-listening.

    PubMed

    García, Pablo Eduardo; Abad, Francisco José; Olea, Julio; Aguado, David

    2013-01-01

    Criterion-referenced interpretations of tests are highly necessary, which usually involves the difficult task of establishing cut scores. Contrasting with other Item Response Theory (IRT)-based standard setting methods, a non-judgmental approach is proposed in this study, in which Item Characteristic Curve (ICC) transformations lead to the final cut scores. eCat-Listening, a computerized adaptive test for the evaluation of English Listening, was administered to 1,576 participants, and the proposed standard setting method was applied to classify them into the performance standards of the Common European Framework of Reference for Languages (CEFR). The results showed a classification closely related to relevant external measures of the English language domain, according to the CEFR. It is concluded that the proposed method is a practical and valid standard setting alternative for IRT-based tests interpretations.

  5. Relationship between chemical structure and the occupational asthma hazard of low molecular weight organic compounds

    PubMed Central

    Jarvis, J; Seed, M; Elton, R; Sawyer, L; Agius, R

    2005-01-01

    Aims: To investigate quantitatively, relationships between chemical structure and reported occupational asthma hazard for low molecular weight (LMW) organic compounds; to develop and validate a model linking asthma hazard with chemical substructure; and to generate mechanistic hypotheses that might explain the relationships. Methods: A learning dataset used 78 LMW chemical asthmagens reported in the literature before 1995, and 301 control compounds with recognised occupational exposures and hazards other than respiratory sensitisation. The chemical structures of the asthmagens and control compounds were characterised by the presence of chemical substructure fragments. Odds ratios were calculated for these fragments to determine which were associated with a likelihood of being reported as an occupational asthmagen. Logistic regression modelling was used to identify the independent contribution of these substructures. A post-1995 set of 21 asthmagens and 77 controls were selected to externally validate the model. Results: Nitrogen or oxygen containing functional groups such as isocyanate, amine, acid anhydride, and carbonyl were associated with an occupational asthma hazard, particularly when the functional group was present twice or more in the same molecule. A logistic regression model using only statistically significant independent variables for occupational asthma hazard correctly assigned 90% of the model development set. The external validation showed a sensitivity of 86% and specificity of 99%. Conclusions: Although a wide variety of chemical structures are associated with occupational asthma, bifunctional reactivity is strongly associated with occupational asthma hazard across a range of chemical substructures. This suggests that chemical cross-linking is an important molecular mechanism leading to the development of occupational asthma. The logistic regression model is freely available on the internet and may offer a useful but inexpensive adjunct to the prediction of occupational asthma hazard. PMID:15778257

  6. Scoring Methods for Building Genotypic Scores: An Application to Didanosine Resistance in a Large Derivation Set

    PubMed Central

    Houssaini, Allal; Assoumou, Lambert; Miller, Veronica; Calvez, Vincent; Marcelin, Anne-Geneviève; Flandre, Philippe

    2013-01-01

    Background Several attempts have been made to determine HIV-1 resistance from genotype resistance testing. We compare scoring methods for building weighted genotyping scores and commonly used systems to determine whether the virus of a HIV-infected patient is resistant. Methods and Principal Findings Three statistical methods (linear discriminant analysis, support vector machine and logistic regression) are used to determine the weight of mutations involved in HIV resistance. We compared these weighted scores with known interpretation systems (ANRS, REGA and Stanford HIV-db) to classify patients as resistant or not. Our methodology is illustrated on the Forum for Collaborative HIV Research didanosine database (N = 1453). The database was divided into four samples according to the country of enrolment (France, USA/Canada, Italy and Spain/UK/Switzerland). The total sample and the four country-based samples allow external validation (one sample is used to estimate a score and the other samples are used to validate it). We used the observed precision to compare the performance of newly derived scores with other interpretation systems. Our results show that newly derived scores performed better than or similar to existing interpretation systems, even with external validation sets. No difference was found between the three methods investigated. Our analysis identified four new mutations associated with didanosine resistance: D123S, Q207K, H208Y and K223Q. Conclusions We explored the potential of three statistical methods to construct weighted scores for didanosine resistance. Our proposed scores performed at least as well as already existing interpretation systems and previously unrecognized didanosine-resistance associated mutations were identified. This approach could be used for building scores of genotypic resistance to other antiretroviral drugs. PMID:23555613

  7. Developing and validating risk prediction models in an individual participant data meta-analysis

    PubMed Central

    2014-01-01

    Background Risk prediction models estimate the risk of developing future outcomes for individuals based on one or more underlying characteristics (predictors). We review how researchers develop and validate risk prediction models within an individual participant data (IPD) meta-analysis, in order to assess the feasibility and conduct of the approach. Methods A qualitative review of the aims, methodology, and reporting in 15 articles that developed a risk prediction model using IPD from multiple studies. Results The IPD approach offers many opportunities but methodological challenges exist, including: unavailability of requested IPD, missing patient data and predictors, and between-study heterogeneity in methods of measurement, outcome definitions and predictor effects. Most articles develop their model using IPD from all available studies and perform only an internal validation (on the same set of data). Ten of the 15 articles did not allow for any study differences in baseline risk (intercepts), potentially limiting their model’s applicability and performance in some populations. Only two articles used external validation (on different data), including a novel method which develops the model on all but one of the IPD studies, tests performance in the excluded study, and repeats by rotating the omitted study. Conclusions An IPD meta-analysis offers unique opportunities for risk prediction research. Researchers can make more of this by allowing separate model intercept terms for each study (population) to improve generalisability, and by using ‘internal-external cross-validation’ to simultaneously develop and validate their model. Methodological challenges can be reduced by prospectively planned collaborations that share IPD for risk prediction. PMID:24397587

  8. The PEARL score predicts 90-day readmission or death after hospitalisation for acute exacerbation of COPD

    PubMed Central

    Echevarria, C; Steer, J; Heslop-Marshall, K; Stenton, S C; Hughes, R; Wijesinghe, M; Harrison, R N; Steen, N; Simpson, A J; Gibson, G J; Bourke, S C

    2017-01-01

    Background One in three patients hospitalised due to acute exacerbation of COPD (AECOPD) is readmitted within 90 days. No tool has been developed specifically in this population to predict readmission or death. Clinicians are unable to identify patients at particular risk, yet resources to prevent readmission are allocated based on clinical judgement. Methods In participating hospitals, consecutive admissions of patients with AECOPD were identified by screening wards and reviewing coding records. A tool to predict 90-day readmission or death without readmission was developed in two hospitals (the derivation cohort) and validated in: (a) the same hospitals at a later timeframe (internal validation cohort) and (b) four further UK hospitals (external validation cohort). Performance was compared with ADO, BODEX, CODEX, DOSE and LACE scores. Results Of 2417 patients, 936 were readmitted or died within 90 days of discharge. The five independent variables in the final model were: Previous admissions, eMRCD score, Age, Right-sided heart failure and Left-sided heart failure (PEARL). The PEARL score was consistently discriminative and accurate with a c-statistic of 0.73, 0.68 and 0.70 in the derivation, internal validation and external validation cohorts. Higher PEARL scores were associated with a shorter time to readmission. Conclusions The PEARL score is a simple tool that can effectively stratify patients' risk of 90-day readmission or death, which could help guide readmission avoidance strategies within the clinical and research setting. It is superior to other scores that have been used in this population. Trial registration number UKCRN ID 14214. PMID:28235886

  9. Constructing a question bank based on script concordance approach as a novel assessment methodology in surgical education.

    PubMed

    Aldekhayel, Salah A; Alselaim, Nahar A; Magzoub, Mohi Eldin; Al-Qattan, Mohammad M; Al-Namlah, Abdullah M; Tamim, Hani; Al-Khayal, Abdullah; Al-Habdan, Sultan I; Zamakhshary, Mohammed F

    2012-10-24

    Script Concordance Test (SCT) is a new assessment tool that reliably assesses clinical reasoning skills. Previous descriptions of developing SCT-question banks were merely subjective. This study addresses two gaps in the literature: 1) conducting the first phase of a multistep validation process of SCT in Plastic Surgery, and 2) providing an objective methodology to construct a question bank based on SCT. After developing a test blueprint, 52 test items were written. Five validation questions were developed and a validation survey was established online. Seven reviewers were asked to answer this survey. They were recruited from two countries, Saudi Arabia and Canada, to improve the test's external validity. Their ratings were transformed into percentages. Analysis was performed to compare reviewers' ratings by looking at correlations, ranges, means, medians, and overall scores. Scores of reviewers' ratings were between 76% and 95% (mean 86% ± 5). We found poor correlations between reviewers (Pearson's: +0.38 to -0.22). Ratings of individual validation questions ranged between 0 and 4 (on a scale 1-5). Means and medians of these ranges were computed for each test item (mean: 0.8 to 2.4; median: 1 to 3). A subset of test items comprising 27 items was generated based on a set of inclusion and exclusion criteria. This study proposes an objective methodology for validation of SCT-question bank. Analysis of validation survey is done from all angles, i.e., reviewers, validation questions, and test items. Finally, a subset of test items is generated based on a set of criteria.

  10. Assessing the Generalizability of Randomized Trial Results to Target Populations

    PubMed Central

    Stuart, Elizabeth A.; Bradshaw, Catherine P.; Leaf, Philip J.

    2014-01-01

    Recent years have seen increasing interest in and attention to evidence-based practices, where the “evidence” generally comes from well-conducted randomized trials. However, while those trials yield accurate estimates of the effect of the intervention for the participants in the trial (known as “internal validity”), they do not always yield relevant information about the effects in a particular target population (known as “external validity”). This may be due to a lack of specification of a target population when designing the trial, difficulties recruiting a sample that is representative of a pre-specified target population, or to interest in considering a target population somewhat different from the population directly targeted by the trial. This paper first provides an overview of existing design and analysis methods for assessing and enhancing the ability of a randomized trial to estimate treatment effects in a target population. It then provides a case study using one particular method, which weights the subjects in a randomized trial to match the population on a set of observed characteristics. The case study uses data from a randomized trial of School-wide Positive Behavioral Interventions and Supports (PBIS); our interest is in generalizing the results to the state of Maryland. In the case of PBIS, after weighting, estimated effects in the target population were similar to those observed in the randomized trial. The paper illustrates that statistical methods can be used to assess and enhance the external validity of randomized trials, making the results more applicable to policy and clinical questions. However, there are also many open research questions; future research should focus on questions of treatment effect heterogeneity and further developing these methods for enhancing external validity. Researchers should think carefully about the external validity of randomized trials and be cautious about extrapolating results to specific populations unless they are confident of the similarity between the trial sample and that target population. PMID:25307417

  11. Calibration and Validation Plan for the L2A Processor and Products of the SENTINEL-2 Mission

    NASA Astrophysics Data System (ADS)

    Main-Knorn, M.; Pflug, B.; Debaecker, V.; Louis, J.

    2015-04-01

    The Copernicus programme, is a European initiative for the implementation of information services based on observation data received from Earth Observation (EO) satellites and ground based information. In the frame of this programme, ESA is developing the Sentinel-2 optical imaging mission that will deliver optical data products designed to feed downstream services mainly related to land monitoring, emergency management and security. To ensure the highest quality of service, ESA sets up the Sentinel-2 Mission Performance Centre (MPC) in charge of the overall performance monitoring of the Sentinel-2 mission. TPZ F and DLR have teamed up in order to provide the best added-value support to the MPC for calibration and validation of the Level-2A processor (Sen2Cor) and products. This paper gives an overview over the planned L2A calibration and validation activities. Level-2A processing is applied to Top-Of-Atmosphere (TOA) Level-1C ortho-image reflectance products. Level-2A main output is the Bottom-Of-Atmosphere (BOA) corrected reflectance product. Additional outputs are an Aerosol Optical Thickness (AOT) map, a Water Vapour (WV) map and a Scene Classification (SC) map with Quality Indicators for cloud and snow probabilities. Level-2A BOA, AOT and WV outputs are calibrated and validated using ground-based data of automatic operating stations and data of in-situ campaigns. Scene classification is validated by the visual inspection of test datasets and cross-sensor comparison, supplemented by meteorological data, if available. Contributions of external in-situ campaigns would enlarge the reference dataset and enable extended validation exercise. Therefore, we are highly interested in and welcome external contributors.

  12. Predicting the need for institutional care shortly after admission to rehabilitation: Rasch analysis and predictive validity of the BRASS Index.

    PubMed

    Panella, L; La Porta, F; Caselli, S; Marchisio, S; Tennant, A

    2012-09-01

    Effective discharge planning is increasingly recognised as a critical component of hospital-based Rehabilitation. The BRASS index is a risk screening tool for identification, shortly after hospital admission, of patients who are at risk of post-discharge problems. To evaluate the internal construct validity and reliability of the Blaylock Risk Assessment Screening Score (BRASS) within the rehabilitation setting. Observational prospective study. Rehabilitation ward of an Italian district hospital. One hundred and four consecutively admitted patients. Using classical psychometric methods and Rasch analysis (RA), the internal construct validity and reliability of the BRASS were examined. Also, external and predictive validity of the Rasch-modified BRASS (RMB) score were determined. Reliability of the original BRASS was low (Cronbach's alpha=0.595) and factor analyses showed that it was clearly multidimensional. A RA, based on a reduced 7-BRASS item set (RMB), satisfied model's expectations. Reliability was 0.777. The RMB scores strongly correlated with the original BRASS (rho=0.952; P<0.000) and with FIM™ admission scores (rho=-0.853; P<0.000). A RMB score of 12 was associated with an increased risk of nursing home admission (RR=2.1, 95%CI=1.7-2.5), whereas a score of 17 was associated to a higher risk of length of stay >28 days (RR=7.6, 95%CI=1.8-31.9). This study demonstrated that the original BRASS was multidimensional and unreliable. However, the RMB holds adequate internal construct validity and is sufficiently reliable as a predictor of discharge problems for group, but not individual use. The application of tools and methods (such as the BRASS Index) developed under the biomedical paradigm in a Physical and Rehabilitation Medicine setting may have limitations. Further research is needed to develop, within the rehabilitation setting, a valid measuring tool of risk of post-discharge problems at the individual level.

  13. Application of the QSPR approach to the boiling points of azeotropes.

    PubMed

    Katritzky, Alan R; Stoyanova-Slavova, Iva B; Tämm, Kaido; Tamm, Tarmo; Karelson, Mati

    2011-04-21

    CODESSA Pro derivative descriptors were calculated for a data set of 426 azeotropic mixtures by the centroid approximation and the weighted-contribution-factor approximation. The two approximations produced almost identical four-descriptor QSPR models relating the structural characteristic of the individual components of azeotropes to the azeotropic boiling points. These models were supported by internal and external validations. The descriptors contributing to the QSPR models are directly related to the three components of the enthalpy (heat) of vaporization.

  14. KSC-07pd3649

    NASA Image and Video Library

    2007-12-15

    KENNEDY SPACE CENTER, FLA. -- On Launch Pad 39A at NASA's Kennedy Space Center, the wiring is checked and validated before the tanking test on space shuttle Atlantis' external tank set for Dec. 18. The test wiring has been spliced into an electrical harness in the aft main engine compartment connected with the engine cut-off, or ECO, sensor system. The attached wiring leads to the interior of the mobile launcher platform where the time domain reflectometry, or TDR, test equipment is located. Photo credit: NASA/Kim Shiflett

  15. KSC-07pd3651

    NASA Image and Video Library

    2007-12-15

    KENNEDY SPACE CENTER, FLA. -- On Launch Pad 39A at NASA's Kennedy Space Center, the wiring is checked and validated before the tanking test on space shuttle Atlantis' external tank set for Dec. 18. The test wiring has been spliced into an electrical harness in the aft main engine compartment connected with the engine cut-off, or ECO, sensor system. The attached wiring leads to the interior of the mobile launcher platform where the time domain reflectometry, or TDR, test equipment is located. Photo credit: NASA/Kim Shiflett

  16. KSC-07pd3648

    NASA Image and Video Library

    2007-12-15

    KENNEDY SPACE CENTER, FLA. -- On Launch Pad 39A at NASA's Kennedy Space Center, the wiring is checked and validated before the tanking test on space shuttle Atlantis' external tank set for Dec. 18. The test wiring has been spliced into an electrical harness in the aft main engine compartment connected with the engine cut-off, or ECO, sensor system. The attached wiring leads to the interior of the mobile launcher platform where the time domain reflectometry, or TDR, test equipment is located. Photo credit: NASA/Kim Shiflett

  17. KSC-07pd3647

    NASA Image and Video Library

    2007-12-15

    KENNEDY SPACE CENTER, FLA. -- On Launch Pad 39A at NASA's Kennedy Space Center, the wiring is checked and validated before the tanking test on space shuttle Atlantis' external tank set for Dec. 18. The test wiring has been spliced into an electrical harness in the aft main engine compartment connected with the engine cut-off, or ECO, sensor system. The attached wiring leads to the interior of the mobile launcher platform where the time domain reflectometry, or TDR, test equipment is located. Photo credit: NASA/Kim Shiflett

  18. KSC-07pd3650

    NASA Image and Video Library

    2007-12-15

    KENNEDY SPACE CENTER, FLA. -- On Launch Pad 39A at NASA's Kennedy Space Center, the wiring is checked and validated before the tanking test on space shuttle Atlantis' external tank set for Dec. 18. The test wiring has been spliced into an electrical harness in the aft main engine compartment connected with the engine cut-off, or ECO, sensor system. The attached wiring leads to the interior of the mobile launcher platform where the time domain reflectometry, or TDR, test equipment is located. Photo credit: NASA/Kim Shiflett

  19. Externalizing disorders: cluster 5 of the proposed meta-structure for DSM-V and ICD-11.

    PubMed

    Krueger, R F; South, S C

    2009-12-01

    The extant major psychiatric classifications DSM-IV and ICD-10 are purportedly atheoretical and largely descriptive. Although this achieves good reliability, the validity of a medical diagnosis is greatly enhanced by an understanding of the etiology. In an attempt to group mental disorders on the basis of etiology, five clusters have been proposed. We consider the validity of the fifth cluster, externalizing disorders, within this proposal. We reviewed the literature in relation to 11 validating criteria proposed by the Study Group of the DSM-V Task Force, in terms of the extent to which these criteria support the idea of a coherent externalizing spectrum of disorders. This cluster distinguishes itself by the central role of disinhibitory personality in mental disorders spread throughout sections of the current classifications, including substance dependence, antisocial personality disorder and conduct disorder. Shared biomarkers, co-morbidity and course offer additional evidence for a valid cluster of externalizing disorders. Externalizing disorders meet many of the salient criteria proposed by the Study Group of the DSM-V Task Force to suggest a classification cluster.

  20. [The Amsterdam wrist rules: the multicenter prospective derivation and external validation of a clinical decision rule for the use of radiography in acute wrist trauma].

    PubMed

    Walenkamp, Monique M J; Bentohami, Abdelali; Slaar, Annelie; Beerekamp, M S H Suzan; Maas, Mario; Jager, L C Cara; Sosef, Nico L; van Velde, Romuald; Ultee, Jan M; Steyerberg, Ewout W; Goslings, J C Carel; Schep, Niels W L

    2016-01-01

    Although only 39% of patients with wrist trauma have sustained a fracture, the majority of patients is routinely referred for radiography. The purpose of this study was to derive and externally validate a clinical decision rule that selects patients with acute wrist trauma in the Emergency Department (ED) for radiography. This multicenter prospective study consisted of three components: (1) derivation of a clinical prediction model for detecting wrist fractures in patients following wrist trauma; (2) external validation of this model; and (3) design of a clinical decision rule. The study was conducted in the EDs of five Dutch hospitals: one academic hospital (derivation cohort) and four regional hospitals (external validation cohort). We included all adult patients with acute wrist trauma. The main outcome was fracture of the wrist (distal radius, distal ulna or carpal bones) diagnosed on conventional X-rays. A total of 882 patients were analyzed; 487 in the derivation cohort and 395 in the validation cohort. We derived a clinical prediction model with eight variables: age; sex, swelling of the wrist; swelling of the anatomical snuffbox, visible deformation; distal radius tender to palpation; pain on radial deviation and painful axial compression of the thumb. The Area Under the Curve at external validation of this model was 0.81 (95% CI: 0.77-0.85). The sensitivity and specificity of the Amsterdam Wrist Rules (AWR) in the external validation cohort were 98% (95% CI: 95-99%) and 21% (95% CI: 15%-28). The negative predictive value was 90% (95% CI: 81-99%). The Amsterdam Wrist Rules is a clinical prediction rule with a high sensitivity and negative predictive value for fractures of the wrist. Although external validation showed low specificity and 100 % sensitivity could not be achieved, the Amsterdam Wrist Rules can provide physicians in the Emergency Department with a useful screening tool to select patients with acute wrist trauma for radiography. The upcoming implementation study will further reveal the impact of the Amsterdam Wrist Rules on the anticipated reduction of X-rays requested, missed fractures, Emergency Department waiting times and health care costs.

  1. External validation of change formulae in neuropsychology with neuroimaging biomarkers: a methodological recommendation and preliminary clinical data.

    PubMed

    Duff, Kevin; Suhrie, Kayla R; Dalley, Bonnie C A; Anderson, Jeffrey S; Hoffman, John M

    2018-06-08

    Within neuropsychology, a number of mathematical formulae (e.g. reliable change index, standardized regression based) have been used to determine if change across time has reliably occurred. When these formulae have been compared, they often produce different results, but 'different' results do not necessarily indicate which formulae are 'best.' The current study sought to further our understanding of change formulae by comparing them to clinically relevant external criteria (amyloid deposition and hippocampal volume). In a sample of 25 older adults with varying levels of cognitive intactness, participants were tested twice across one week with a brief cognitive battery. Seven different change scores were calculated for each participant. An amyloid PET scan (to get a composite of amyloid deposition) and an MRI (to get hippocampal volume) were also obtained. Deviation-based change formulae (e.g. simple discrepancy score, reliable change index with or without correction for practice effects) were all identical in their relationship to the two neuroimaging biomarkers, and all were non-significant. Conversely, regression-based change formulae (e.g. simple and complex indices) showed stronger relationships to amyloid deposition and hippocampal volume. These results highlight the need for external validation of the various change formulae used by neuropsychologists in clinical settings and research projects. The findings also preliminarily suggest that regression-based change formulae may be more relevant than deviation-based change formulae in this context.

  2. Assistive technology for promoting adaptive skills of children with cerebral palsy: ten cases evaluation.

    PubMed

    Stasolla, Fabrizio; Caffò, Alessandro O; Perilli, Viviana; Boccasini, Adele; Damiani, Rita; D'Amico, Fiora

    2018-05-06

    To extend the use of assistive technology for promoting adaptive skills of children with cerebral palsy. To assess its effects on positive participation of ten participants involved. To carry out a social validation recruiting parents, physiotherapists and support teachers as external raters. A multiple probe design was implemented for Studies I and II. Study I involved five participants exposed to a combined program aimed at enhancing choice process of preferred items and locomotion fluency. Study II involved five further children for a combined intervention finalized at ensuring them with literacy access and ambulation responses. Study III recruited 60 external raters for a social validation assessment. All participants improved their performance, although differences among children occurred. Indices of positive participation increased as well. Social raters favorably scored the use of both technology and programs. Assistive technology-based programs were effective for promoting independence of children with cerebral palsy. Implications for Rehabilitation A basic form of assistive technology such as a microswitch-based program may be useful and helpful for supporting adaptive skills of children with cerebral palsy and different levels of functioning. The same program may improve the participants' indices of positive participation and constructive engagement with beneficial effects on their quality of life. The positive social rating provided by external experts sensitive to the matter may recommend a favorable acceptance and implementation of the program in daily settings.

  3. A metabolic fingerprinting approach based on selected ion flow tube mass spectrometry (SIFT-MS) and chemometrics: A reliable tool for Mediterranean origin-labeled olive oils authentication.

    PubMed

    Bajoub, Aadil; Medina-Rodríguez, Santiago; Ajal, El Amine; Cuadros-Rodríguez, Luis; Monasterio, Romina Paula; Vercammen, Joeri; Fernández-Gutiérrez, Alberto; Carrasco-Pancorbo, Alegría

    2018-04-01

    Selected Ion flow tube mass spectrometry (SIFT-MS) in combination with chemometrics was used to authenticate the geographical origin of Mediterranean virgin olive oils (VOOs) produced under geographical origin labels. In particular, 130 oil samples from six different Mediterranean regions (Kalamata (Greece); Toscana (Italy); Meknès and Tyout (Morocco); and Priego de Córdoba and Baena (Spain)) were considered. The headspace volatile fingerprints were measured by SIFT-MS in full scan with H 3 O + , NO + and O 2 + as precursor ions and the results were subjected to chemometric treatments. Principal Component Analysis (PCA) was used for preliminary multivariate data analysis and Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to build different models (considering the three reagent ions) to classify samples according to the country of origin and regions (within the same country). The multi-class PLS-DA models showed very good performance in terms of fitting accuracy (98.90-100%) and prediction accuracy (96.70-100% accuracy for cross validation and 97.30-100% accuracy for external validation (test set)). Considering the two-class PLS-DA models, the one for the Spanish samples showed 100% sensitivity, specificity and accuracy in calibration, cross validation and external validation; the model for Moroccan oils also showed very satisfactory results (with perfect scores for almost every parameter in all the cases). Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. External validation of the bilirubin-atazanavir nomogram for assessment of atazanavir plasma exposure in HIV-1-infected patients.

    PubMed

    Rekić, Dinko; Röshammar, Daniel; Bergstrand, Martin; Tarning, Joel; Calcagno, Andrea; D'Avolio, Antonio; Ormaasen, Vidar; Vigan, Marie; Barrail-Tran, Aurélie; Ashton, Michael; Gisslén, Magnus; Äbelö, Angela

    2013-04-01

    Atazanavir increases plasma bilirubin levels in a concentration-dependent manner. Due to less costly and readily available assays, bilirubin has been proposed as a marker of atazanavir exposure. In this work, a previously developed nomogram for detection of suboptimal atazanavir exposure is validated against external patient populations. The bilirubin nomogram was validated against 311 matching bilirubin and atazanavir samples from 166 HIV-1-infected Norwegian, French, and Italian patients on a ritonavir-boosted regimen. In addition, the nomogram was evaluated in 56 Italian patients on an unboosted regimen. The predictive properties of the nomogram were validated against observed atazanavir plasma concentrations. The use of the nomogram to detect non-adherence was also investigated by simulation. The bilirubin nomogram predicted suboptimal exposure in the patient populations on a ritonavir-boosted regimen with a negative predictive value of 97% (95% CI 95-100). The bilirubin nomogram and monitoring of atazanavir concentrations had similar predictive properties for detecting non-adherence based on simulations. Although both methods performed adequately during a period of non-adherence, they had lower predictive power to detect past non-adherence episodes. Using the bilirubin nomogram for detection of suboptimal atazanavir exposure in patients on a ritonavir-boosted regimen is a rapid and cost-effective alternative to routine measurements of the actual atazanavir exposure in plasma. Its application may be useful in clinical settings if atazanavir concentrations are not available.

  5. Development and external validation of nomograms to predict the risk of skeletal metastasis at the time of diagnosis and skeletal metastasis-free survival in nasopharyngeal carcinoma.

    PubMed

    Yang, Lin; Xia, Liangping; Wang, Yan; He, Shasha; Chen, Haiyang; Liang, Shaobo; Peng, Peijian; Hong, Shaodong; Chen, Yong

    2017-09-06

    The skeletal system is the most common site of distant metastasis in nasopharyngeal carcinoma (NPC); various prognostic factors have been reported for skeletal metastasis, though most studies have focused on a single factor. We aimed to establish nomograms to effectively predict skeletal metastasis at initial diagnosis (SMAD) and skeletal metastasis-free survival (SMFS) in NPC. A total of 2685 patients with NPC who received bone scintigraphy (BS) and/or 18F-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and 2496 patients without skeletal metastasis were retrospectively assessed to develop individual nomograms for SMAD and SMFS. The models were validated externally using separate cohorts of 1329 and 1231 patients treated at two other institutions. Five independent prognostic factors were included in each nomogram. The SMAD nomogram had a significantly higher c-index than the TNM staging system (training cohort, P = 0.005; validation cohort, P < 0.001). The SMFS nomogram had significantly higher c-index values in the training and validation sets than the TNM staging system (P < 0.001 and P = 0.005, respectively). Three proposed risk stratification groups were created using the nomograms, and enabled significant discrimination of SMFS for each risk group. The prognostic nomograms established in this study enable accurate stratification of distinct risk groups for skeletal metastasis, which may improve counseling and facilitate individualized management of patients with NPC.

  6. The bottom-up approach to integrative validity: a new perspective for program evaluation.

    PubMed

    Chen, Huey T

    2010-08-01

    The Campbellian validity model and the traditional top-down approach to validity have had a profound influence on research and evaluation. That model includes the concepts of internal and external validity and within that model, the preeminence of internal validity as demonstrated in the top-down approach. Evaluators and researchers have, however, increasingly recognized that in an evaluation, the over-emphasis on internal validity reduces that evaluation's usefulness and contributes to the gulf between academic and practical communities regarding interventions. This article examines the limitations of the Campbellian validity model and the top-down approach and provides a comprehensive, alternative model, known as the integrative validity model for program evaluation. The integrative validity model includes the concept of viable validity, which is predicated on a bottom-up approach to validity. This approach better reflects stakeholders' evaluation views and concerns, makes external validity workable, and becomes therefore a preferable alternative for evaluation of health promotion/social betterment programs. The integrative validity model and the bottom-up approach enable evaluators to meet scientific and practical requirements, facilitate in advancing external validity, and gain a new perspective on methods. The new perspective also furnishes a balanced view of credible evidence, and offers an alternative perspective for funding. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

  7. [External and internal validity of a multidimensional Locus of control scale of eating attitudes for athletes (LOCSCAS)].

    PubMed

    Paquet, Y; Scoffier, S; d'Arripe-Longueville, F

    2016-10-01

    In the field of health psychology, the control has consistently been considered as a protective factor. This protective role has been also highlighted in eating attitudes' domain. However, current studies use the one-dimensional scale of Rotter or the multidimensional health locus of control scale, and no specific eating attitudes' scale in the sport context exists. Moreover, the social influence in previous scales is limited. According to recent works, the purpose of this study was to test the internal and external validity of a multidimensional locus of control scale of eating attitudes for athletes. One hundred and seventy-nine participants were solicited. A confirmatory factorial analysis was conducted in order to test the internal validity of the scale. The scale external validity was tested in relation to eating attitudes. The internal validity of the scale was verified as well as the external validity, which confirmed the importance of taking into consideration social influences. Indeed, the 2 subscales "Trainers, friends" and "Parents, family" are related respectively positively and negatively in eating disorders. Copyright © 2016 L'Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

  8. The virtual people set: developing computer-generated stimuli for the assessment of pedophilic sexual interest.

    PubMed

    Dombert, Beate; Mokros, Andreas; Brückner, Eva; Schlegl, Verena; Antfolk, Jan; Bäckström, Anna; Zappalà, Angelo; Osterheider, Michael; Santtila, Pekka

    2013-12-01

    The implicit assessment of pedophilic sexual interest through viewing-time methods necessitates visual stimuli. There are grave ethical and legal concerns against using pictures of real children, however. The present report is a summary of findings on a new set of 108 computer-generated stimuli. The images vary in terms of gender (female/male), explicitness (naked/clothed), and physical maturity (prepubescent, pubescent, and adult) of the persons depicted. A series of three studies tested the internal and external validity of the picture set. Studies 1 and 2 yielded good-to-high estimates of observer agreement with regard to stimulus maturity levels by two methods (categorization and paired comparison). Study 3 extended these findings with regard to judgments made by convicted child sexual offenders.

  9. External validation of the Cairns Prediction Model (CPM) to predict conversion from laparoscopic to open cholecystectomy.

    PubMed

    Hu, Alan Shiun Yew; Donohue, Peter O'; Gunnarsson, Ronny K; de Costa, Alan

    2018-03-14

    Valid and user-friendly prediction models for conversion to open cholecystectomy allow for proper planning prior to surgery. The Cairns Prediction Model (CPM) has been in use clinically in the original study site for the past three years, but has not been tested at other sites. A retrospective, single-centred study collected ultrasonic measurements and clinical variables alongside with conversion status from consecutive patients who underwent laparoscopic cholecystectomy from 2013 to 2016 in The Townsville Hospital, North Queensland, Australia. An area under the curve (AUC) was calculated to externally validate of the CPM. Conversion was necessary in 43 (4.2%) out of 1035 patients. External validation showed an area under the curve of 0.87 (95% CI 0.82-0.93, p = 1.1 × 10 -14 ). In comparison with most previously published models, which have an AUC of approximately 0.80 or less, the CPM has the highest AUC of all published prediction models both for internal and external validation. Crown Copyright © 2018. Published by Elsevier Inc. All rights reserved.

  10. Validation of EncephalApp, Smartphone-Based Stroop Test, for the Diagnosis of Covert Hepatic Encephalopathy.

    PubMed

    Bajaj, Jasmohan S; Heuman, Douglas M; Sterling, Richard K; Sanyal, Arun J; Siddiqui, Muhammad; Matherly, Scott; Luketic, Velimir; Stravitz, R Todd; Fuchs, Michael; Thacker, Leroy R; Gilles, HoChong; White, Melanie B; Unser, Ariel; Hovermale, James; Gavis, Edith; Noble, Nicole A; Wade, James B

    2015-10-01

    Detection of covert hepatic encephalopathy (CHE) is difficult, but point-of-care testing could increase rates of diagnosis. We aimed to validate the ability of the smartphone app EncephalApp, a streamlined version of Stroop App, to detect CHE. We evaluated face validity, test-retest reliability, and external validity. Patients with cirrhosis (n = 167; 38% with overt HE [OHE]; mean age, 55 years; mean Model for End-Stage Liver Disease score, 12) and controls (n = 114) were each given a paper and pencil cognitive battery (standard) along with EncephalApp. EncephalApp has Off and On states; results measured were OffTime, OnTime, OffTime+OnTime, and number of runs required to complete 5 off and on runs. Thirty-six patients with cirrhosis underwent driving simulation tests, and EncephalApp results were correlated with results. Test-retest reliability was analyzed in a subgroup of patients. The test was performed before and after transjugular intrahepatic portosystemic shunt placement, and before and after correction for hyponatremia, to determine external validity. All patients with cirrhosis performed worse on paper and pencil and EncephalApp tests than controls. Patients with cirrhosis and OHE performed worse than those without OHE. Age-dependent EncephalApp cutoffs (younger or older than 45 years) were set. An OffTime+OnTime value of >190 seconds identified all patients with CHE with an area under the receiver operator characteristic value of 0.91; the area under the receiver operator characteristic value was 0.88 for diagnosis of CHE in those without OHE. EncephalApp times correlated with crashes and illegal turns in driving simulation tests. Test-retest reliability was high (intraclass coefficient, 0.83) among 30 patients retested 1-3 months apart. OffTime+OnTime increased significantly (206 vs 255 seconds, P = .007) among 10 patients retested 33 ± 7 days after transjugular intrahepatic portosystemic shunt placement. OffTime+OnTime decreased significantly (242 vs 225 seconds, P = .03) in 7 patients tested before and after correction for hyponatremia (126 ± 3 to 132 ± 4 meq/L, P = .01) 10 ± 5 days apart. A smartphone app called EncephalApp has good face validity, test-retest reliability, and external validity for the diagnosis of CHE. Copyright © 2015 AGA Institute. Published by Elsevier Inc. All rights reserved.

  11. Validation of EncephalApp, Smartphone-based Stroop Test, for the Diagnosis of Covert Hepatic Encephalopathy

    PubMed Central

    Bajaj, Jasmohan S; Heuman, Douglas M; Sterling, Richard K; Sanyal, Arun J; Siddiqui, Muhammad; Matherly, Scott; Luketic, Velimir; Stravitz, R Todd; Fuchs, Michael; Thacker, Leroy R; Gilles, HoChong; White, Melanie B; Unser, Ariel; Hovermale, James; Gavis, Edith; Noble, Nicole A; Wade, James B

    2014-01-01

    Background & Aims Detection of covert hepatic encephalopathy (CHE) is difficult but point of care testing could increase rates of diagnosis. We aimed to validate the ability of the smartphone app EncephalApp, a streamlined version of Stroop App, to detect CHE. We evaluated face validity, test–retest reliability, and external validity. Methods Patients with cirrhosis (n=167; 38% with overt HE [OHE]; mean age, 55 years; mean model for end-stage liver disease score, 12) and controls (n=114) were each given a paper and pencil cognitive battery (standard) along with EncephalApp. EncephalApp has Off and On states; results measured were: OffTime, OnTime, OffTime+OnTime, and number of runs required to complete 5 off and on runs. Thirty-six patients with cirrhosis underwent driving simulation tests, and EncephalApp results were correlated with results. Test–retest reliability was analyzed in a subgroup of patients. The test was performed before and after transjugular intra-hepatic portosystemic shunt placement, before and after correction for hyponatremia, to determine external validity. Results All patients with cirrhosis performed worse on paper and pencil and EncephalApp tests than controls. Patients with cirrhosis and OHE performed worse than those without OHE. Age-dependent EncephalApp cut-offs (younger or older than 45 years) were set. An OffTime+OnTime value of >190 seconds identified all patients with CHE with an area under the receiver operator characteristic (AUROC) value of 0.91; the AUROC value was 0.88 for diagnosis of CHE in those without OHE. EncephalApp times correlated with crashes and illegal turns in driving simulation tests. Test–retest reliability was high (intra-class coefficient, 0.83) among 30 patients retested 1–3 months apart. OffTime+OnTime increased significantly (206 vs 255, P=.007) among 10 patients retested 33±7 days after transjugular intra-hepatic portosystemic shunt placement. OffTime+OnTime decreased significantly (242 vs 225, P=.03) in 7 patients tested before and after correction for hyponatremia (126±3 to 132±4 meq/L, P=.01), 10±5 days apart. Conclusions A smartphone app called EncephalApp has good face validity, test–retest reliability, and external validity for the diagnosis of CHE. PMID:24846278

  12. Assessment of the External Validity of the National Comprehensive Cancer Network and European Society for Medical Oncology Guidelines for Non-Small-Cell Lung Cancer in a Population of Patients Aged 80 Years and Older.

    PubMed

    Battisti, Nicolò Matteo Luca; Sehovic, Marina; Extermann, Martine

    2017-09-01

    Non-small-cell lung cancer (NSCLC) is a disease of the elderly, who are under-represented in clinical trials. This challenges the external validity of the evidence base for its management and of current guidelines, that we evaluated in a population of older patients. We retrieved randomized clinical trials (RCTs) supporting the guidelines and identified 18 relevant topics. We matched a cohort of NSCLC patients aged older than 80 years from the Moffitt Cancer Center database with the studies' eligibility criteria to check their qualification for at least 2 studies. Eligibility > 60% was rated full validity, 30% to 60% partial validity, and < 30% limited validity. We obtained data from 760 elderly patients in stage-adjusted groups and collected 244 RCTs from the National Comprehensive Cancer Network (NCCN) and 148 from the European Society for Medical Oncology (ESMO) guidelines. External validity was deemed insufficient for neoadjuvant chemotherapy in stage III disease (27.37% and 25.26% of patients eligible for NCCN and ESMO guidelines, respectively) and use of bevacizumab (13.86% and 16.27% of patients eligible). For ESMO guidelines, it was inadequate regarding double-agent chemotherapy (25.90% of patients eligible), its duration (24.10%) and therapy for Eastern Cooperative Oncology Group performance status 2 patients (17.74%). For NCCN guidelines external validity was lacking for neoadjuvant chemoradiotherapy in stage IIIA disease (25.86% of patients eligible). Our analysis highlighted the effect of RCT eligibility criteria on guidelines' external validity in elderly patients. Eligibility criteria should be carefully considered in trial design and more studies that do not exclude elderly patients should be included in guidelines. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. External validation of the diffuse intrinsic pontine glioma survival prediction model: a collaborative report from the International DIPG Registry and the SIOPE DIPG Registry.

    PubMed

    Veldhuijzen van Zanten, Sophie E M; Lane, Adam; Heymans, Martijn W; Baugh, Joshua; Chaney, Brooklyn; Hoffman, Lindsey M; Doughman, Renee; Jansen, Marc H A; Sanchez, Esther; Vandertop, William P; Kaspers, Gertjan J L; van Vuurden, Dannis G; Fouladi, Maryam; Jones, Blaise V; Leach, James

    2017-08-01

    We aimed to perform external validation of the recently developed survival prediction model for diffuse intrinsic pontine glioma (DIPG), and discuss its utility. The DIPG survival prediction model was developed in a cohort of patients from the Netherlands, United Kingdom and Germany, registered in the SIOPE DIPG Registry, and includes age <3 years, longer symptom duration and receipt of chemotherapy as favorable predictors, and presence of ring-enhancement on MRI as unfavorable predictor. Model performance was evaluated by analyzing the discrimination and calibration abilities. External validation was performed using an unselected cohort from the International DIPG Registry, including patients from United States, Canada, Australia and New Zealand. Basic comparison with the results of the original study was performed using descriptive statistics, and univariate- and multivariable regression analyses in the validation cohort. External validation was assessed following a variety of analyses described previously. Baseline patient characteristics and results from the regression analyses were largely comparable. Kaplan-Meier curves of the validation cohort reproduced separated groups of standard (n = 39), intermediate (n = 125), and high-risk (n = 78) patients. This discriminative ability was confirmed by similar values for the hazard ratios across these risk groups. The calibration curve in the validation cohort showed a symmetric underestimation of the predicted survival probabilities. In this external validation study, we demonstrate that the DIPG survival prediction model has acceptable cross-cohort calibration and is able to discriminate patients with short, average, and increased survival. We discuss how this clinico-radiological model may serve a useful role in current clinical practice.

  14. Insight into the structural requirements of proton pump inhibitors based on CoMFA and CoMSIA studies.

    PubMed

    Nayana, M Ravi Shashi; Sekhar, Y Nataraja; Nandyala, Haritha; Muttineni, Ravikumar; Bairy, Santosh Kumar; Singh, Kriti; Mahmood, S K

    2008-10-01

    In the present study, a series of 179 quinoline and quinazoline heterocyclic analogues exhibiting inhibitory activity against Gastric (H+/K+)-ATPase were investigated using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) methods. Both the models exhibited good correlation between the calculated 3D-QSAR fields and the observed biological activity for the respective training set compounds. The most optimal CoMFA and CoMSIA models yielded significant leave-one-out cross-validation coefficient, q(2) of 0.777, 0.744 and conventional cross-validation coefficient, r(2) of 0.927, 0.914 respectively. The predictive ability of generated models was tested on a set of 52 compounds having broad range of activity. CoMFA and CoMSIA yielded predicted activities for test set compounds with r(pred)(2) of 0.893 and 0.917 respectively. These validation tests not only revealed the robustness of the models but also demonstrated that for our models r(pred)(2) based on the mean activity of test set compounds can accurately estimate external predictivity. The factors affecting activity were analyzed carefully according to standard coefficient contour maps of steric, electrostatic, hydrophobic, acceptor and donor fields derived from the CoMFA and CoMSIA. These contour plots identified several key features which explain the wide range of activities. The results obtained from models offer important structural insight into designing novel peptic-ulcer inhibitors prior to their synthesis.

  15. Prediction models for successful external cephalic version: a systematic review.

    PubMed

    Velzel, Joost; de Hundt, Marcella; Mulder, Frederique M; Molkenboer, Jan F M; Van der Post, Joris A M; Mol, Ben W; Kok, Marjolein

    2015-12-01

    To provide an overview of existing prediction models for successful ECV, and to assess their quality, development and performance. We searched MEDLINE, EMBASE and the Cochrane Library to identify all articles reporting on prediction models for successful ECV published from inception to January 2015. We extracted information on study design, sample size, model-building strategies and validation. We evaluated the phases of model development and summarized their performance in terms of discrimination, calibration and clinical usefulness. We collected different predictor variables together with their defined significance, in order to identify important predictor variables for successful ECV. We identified eight articles reporting on seven prediction models. All models were subjected to internal validation. Only one model was also validated in an external cohort. Two prediction models had a low overall risk of bias, of which only one showed promising predictive performance at internal validation. This model also completed the phase of external validation. For none of the models their impact on clinical practice was evaluated. The most important predictor variables for successful ECV described in the selected articles were parity, placental location, breech engagement and the fetal head being palpable. One model was assessed using discrimination and calibration using internal (AUC 0.71) and external validation (AUC 0.64), while two other models were assessed with discrimination and calibration, respectively. We found one prediction model for breech presentation that was validated in an external cohort and had acceptable predictive performance. This model should be used to council women considering ECV. Copyright © 2015. Published by Elsevier Ireland Ltd.

  16. A consensus prognostic gene expression classifier for ER positive breast cancer

    PubMed Central

    Teschendorff, Andrew E; Naderi, Ali; Barbosa-Morais, Nuno L; Pinder, Sarah E; Ellis, Ian O; Aparicio, Sam; Brenton, James D; Caldas, Carlos

    2006-01-01

    Background A consensus prognostic gene expression classifier is still elusive in heterogeneous diseases such as breast cancer. Results Here we perform a combined analysis of three major breast cancer microarray data sets to hone in on a universally valid prognostic molecular classifier in estrogen receptor (ER) positive tumors. Using a recently developed robust measure of prognostic separation, we further validate the prognostic classifier in three external independent cohorts, confirming the validity of our molecular classifier in a total of 877 ER positive samples. Furthermore, we find that molecular classifiers may not outperform classical prognostic indices but that they can be used in hybrid molecular-pathological classification schemes to improve prognostic separation. Conclusion The prognostic molecular classifier presented here is the first to be valid in over 877 ER positive breast cancer samples and across three different microarray platforms. Larger multi-institutional studies will be needed to fully determine the added prognostic value of molecular classifiers when combined with standard prognostic factors. PMID:17076897

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

    Oberije, Cary, E-mail: cary.oberije@maastro.nl; De Ruysscher, Dirk; Universitaire Ziekenhuizen Leuven, KU Leuven

    Purpose: Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can overcome this but are currently lacking. A DSS for stage III NSCLC requires the development and integration of multiple models. The current study takes the first step in this process by developing andmore » validating a model that can provide physicians with a survival probability for an individual NSCLC patient. Methods and Materials: Data from 548 patients with stage III NSCLC were available to enable the development of a prediction model, using stratified Cox regression. Variables were selected by using a bootstrap procedure. Performance of the model was expressed as the c statistic, assessed internally and on 2 external data sets (n=174 and n=130). Results: The final multivariate model, stratified for treatment, consisted of age, gender, World Health Organization performance status, overall treatment time, equivalent radiation dose, number of positive lymph node stations, and gross tumor volume. The bootstrapped c statistic was 0.62. The model could identify risk groups in external data sets. Nomograms were constructed to predict an individual patient's survival probability ( (www.predictcancer.org)). The data set can be downloaded at (https://www.cancerdata.org/10.1016/j.ijrobp.2015.02.048). Conclusions: The prediction model for overall survival of patients with stage III NSCLC highlights the importance of combining patient, clinical, and treatment variables. Nomograms were developed and validated. This tool could be used as a first building block for a decision support system.« less

  18. Physiological responses and external validity of a new setting for taekwondo combat simulation.

    PubMed

    Hausen, Matheus; Soares, Pedro Paulo; Araújo, Marcus Paulo; Porto, Flávia; Franchini, Emerson; Bridge, Craig Alan; Gurgel, Jonas

    2017-01-01

    Combat simulations have served as an alternative framework to study the cardiorespiratory demands of the activity in combat sports, but this setting imposes rule-restrictions that may compromise the competitiveness of the bouts. The aim of this study was to assess the cardiorespiratory responses to a full-contact taekwondo combat simulation using a safe and externally valid competitive setting. Twelve male national level taekwondo athletes visited the laboratory on two separate occasions. On the first visit, anthropometric and running cardiopulmonary exercise assessments were performed. In the following two to seven days, participants performed a full-contact combat simulation, using a specifically designed gas analyser protector. Oxygen uptake ([Formula: see text]), heart rate (HR) and capillary blood lactate measurements ([La-]) were obtained. Time-motion analysis was performed to compare activity profile. The simulation yielded broadly comparable activity profiles to those performed in competition, a mean [Formula: see text] of 36.6 ± 3.9 ml.kg-1.min-1 (73 ± 6% [Formula: see text]) and mean HR of 177 ± 10 beats.min-1 (93 ± 5% HRPEAK). A peak [Formula: see text] of 44.8 ± 5.0 ml.kg-1.min-1 (89 ± 5% [Formula: see text]), a peak heart rate of 190 ± 13 beats.min-1 (98 ± 3% HRmax) and peak [La-] of 12.3 ± 2.9 mmol.L-1 was elicited by the bouts. Regarding time-motion analysis, combat simulation presented a similar exchange time, a shorter preparation time and a longer exchange-preparation ratio. Taekwondo combats capturing the full-contact competitive elements of a bout elicit moderate to high cardiorespiratory demands on the competitors. These data are valuable to assist preparatory strategies within the sport.

  19. Physiological responses and external validity of a new setting for taekwondo combat simulation

    PubMed Central

    2017-01-01

    Combat simulations have served as an alternative framework to study the cardiorespiratory demands of the activity in combat sports, but this setting imposes rule-restrictions that may compromise the competitiveness of the bouts. The aim of this study was to assess the cardiorespiratory responses to a full-contact taekwondo combat simulation using a safe and externally valid competitive setting. Twelve male national level taekwondo athletes visited the laboratory on two separate occasions. On the first visit, anthropometric and running cardiopulmonary exercise assessments were performed. In the following two to seven days, participants performed a full-contact combat simulation, using a specifically designed gas analyser protector. Oxygen uptake (V˙O2), heart rate (HR) and capillary blood lactate measurements ([La-]) were obtained. Time-motion analysis was performed to compare activity profile. The simulation yielded broadly comparable activity profiles to those performed in competition, a mean V˙O2 of 36.6 ± 3.9 ml.kg-1.min-1 (73 ± 6% V˙O2PEAK) and mean HR of 177 ± 10 beats.min-1 (93 ± 5% HRPEAK). A peak V˙O2 of 44.8 ± 5.0 ml.kg-1.min-1 (89 ± 5% V˙O2PEAK), a peak heart rate of 190 ± 13 beats.min-1 (98 ± 3% HRmax) and peak [La-] of 12.3 ± 2.9 mmol.L–1 was elicited by the bouts. Regarding time-motion analysis, combat simulation presented a similar exchange time, a shorter preparation time and a longer exchange-preparation ratio. Taekwondo combats capturing the full-contact competitive elements of a bout elicit moderate to high cardiorespiratory demands on the competitors. These data are valuable to assist preparatory strategies within the sport. PMID:28158252

  20. Validating hospital antibiotic purchasing data as a metric of inpatient antibiotic use.

    PubMed

    Tan, Charlie; Ritchie, Michael; Alldred, Jason; Daneman, Nick

    2016-02-01

    Antibiotic purchasing data are a widely used, but unsubstantiated, measure of antibiotic consumption. To validate this source, we compared purchasing data from hospitals and external medical databases with patient-level dispensing data. Antibiotic purchasing and dispensing data from internal hospital records and purchasing data from IMS Health were obtained for two hospitals between May 2013 and April 2015. Internal purchasing data were validated against dispensing data, and IMS data were compared with both internal metrics. Scatterplots of individual antimicrobial data points were generated; Pearson's correlation and linear regression coefficients were computed. A secondary analysis re-examined these correlations over shorter calendar periods. Internal purchasing data were strongly correlated with dispensing data, with correlation coefficients of 0.90 (95% CI = 0.83-0.95) and 0.98 (95% CI = 0.95-0.99) at hospitals A and B, respectively. Although dispensing data were consistently lower than purchasing data, this was attributed to a single antibiotic at both hospitals. IMS data were favourably correlated with, but underestimated, internal purchasing and dispensing data. This difference was accounted for by eight antibiotics for which direct sales from some manufacturers were not included in the IMS database. The correlation between purchasing and dispensing data was consistent across periods as short as 3 months, but not at monthly intervals. Both internal and external antibiotic purchasing data are strongly correlated with dispensing data. If outliers are accounted for appropriately, internal purchasing data could be used for cost-effective evaluation of antimicrobial stewardship programmes, and external data sets could be used for surveillance and research across geographical regions. © The Author 2015. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. Validating hospital antibiotic purchasing data as a metric of inpatient antibiotic use

    PubMed Central

    Tan, Charlie; Ritchie, Michael; Alldred, Jason; Daneman, Nick

    2016-01-01

    Objectives Antibiotic purchasing data are a widely used, but unsubstantiated, measure of antibiotic consumption. To validate this source, we compared purchasing data from hospitals and external medical databases with patient-level dispensing data. Methods Antibiotic purchasing and dispensing data from internal hospital records and purchasing data from IMS Health were obtained for two hospitals between May 2013 and April 2015. Internal purchasing data were validated against dispensing data, and IMS data were compared with both internal metrics. Scatterplots of individual antimicrobial data points were generated; Pearson's correlation and linear regression coefficients were computed. A secondary analysis re-examined these correlations over shorter calendar periods. Results Internal purchasing data were strongly correlated with dispensing data, with correlation coefficients of 0.90 (95% CI = 0.83–0.95) and 0.98 (95% CI = 0.95–0.99) at hospitals A and B, respectively. Although dispensing data were consistently lower than purchasing data, this was attributed to a single antibiotic at both hospitals. IMS data were favourably correlated with, but underestimated, internal purchasing and dispensing data. This difference was accounted for by eight antibiotics for which direct sales from some manufacturers were not included in the IMS database. The correlation between purchasing and dispensing data was consistent across periods as short as 3 months, but not at monthly intervals. Conclusions Both internal and external antibiotic purchasing data are strongly correlated with dispensing data. If outliers are accounted for appropriately, internal purchasing data could be used for cost-effective evaluation of antimicrobial stewardship programmes, and external data sets could be used for surveillance and research across geographical regions. PMID:26546668

  2. QSAR Analysis of 2-Amino or 2-Methyl-1-Substituted Benzimidazoles Against Pseudomonas aeruginosa

    PubMed Central

    Podunavac-Kuzmanović, Sanja O.; Cvetković, Dragoljub D.; Barna, Dijana J.

    2009-01-01

    A set of benzimidazole derivatives were tested for their inhibitory activities against the Gram-negative bacterium Pseudomonas aeruginosa and minimum inhibitory concentrations were determined for all the compounds. Quantitative structure activity relationship (QSAR) analysis was applied to fourteen of the abovementioned derivatives using a combination of various physicochemical, steric, electronic, and structural molecular descriptors. A multiple linear regression (MLR) procedure was used to model the relationships between molecular descriptors and the antibacterial activity of the benzimidazole derivatives. The stepwise regression method was used to derive the most significant models as a calibration model for predicting the inhibitory activity of this class of molecules. The best QSAR models were further validated by a leave one out technique as well as by the calculation of statistical parameters for the established theoretical models. To confirm the predictive power of the models, an external set of molecules was used. High agreement between experimental and predicted inhibitory values, obtained in the validation procedure, indicated the good quality of the derived QSAR models. PMID:19468332

  3. The Development of Valid Subtypes for Depression in Primary Care Settings

    PubMed Central

    Karasz, Alison

    2009-01-01

    A persistent theme in the debate on the classification of depressive disorders is the distinction between biological and environmental depressions. Despite decades of research, there remains little consensus on how to distinguish between depressive subtypes. This preliminary study describes a method that could be useful, if implemented on a larger scale, in the development of valid subtypes of depression in primary care settings, using explanatory models of depressive illness. Seventeen depressed Hispanic patients at an inner city general practice participated in explanatory model interviews. Participants generated illness narratives, which included details about symptoms, cause, course, impact, health seeking, and anticipated outcome. Two distinct subtypes emerged from the analysis. The internal model subtype was characterized by internal attributions, specifically the notion of an “injured self.” The external model subtype conceptualized depression as a reaction to life situations. Each subtype was associated with a distinct constellation of clinical features and health seeking experiences. Future directions for research using explanatory models to establish depressive subtypes are explored. PMID:18414123

  4. A combined LS-SVM & MLR QSAR workflow for predicting the inhibition of CXCR3 receptor by quinazolinone analogs.

    PubMed

    Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Igglessi-Markopoulou, Olga; Kollias, George

    2010-05-01

    A novel QSAR workflow is constructed that combines MLR with LS-SVM classification techniques for the identification of quinazolinone analogs as "active" or "non-active" CXCR3 antagonists. The accuracy of the LS-SVM classification technique for the training set and test was 100% and 90%, respectively. For the "active" analogs a validated MLR QSAR model estimates accurately their I-IP10 IC(50) inhibition values. The accuracy of the QSAR model (R (2) = 0.80) is illustrated using various evaluation techniques, such as leave-one-out procedure (R(LOO2)) = 0.67) and validation through an external test set (R(pred2) = 0.78). The key conclusion of this study is that the selected molecular descriptors, Highest Occupied Molecular Orbital energy (HOMO), Principal Moment of Inertia along X and Y axes PMIX and PMIZ, Polar Surface Area (PSA), Presence of triple bond (PTrplBnd), and Kier shape descriptor ((1) kappa), demonstrate discriminatory and pharmacophore abilities.

  5. Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches

    NASA Astrophysics Data System (ADS)

    Ragno, Rino; Ballante, Flavio; Pirolli, Adele; Wickersham, Richard B.; Patsilinakos, Alexandros; Hesse, Stéphanie; Perspicace, Enrico; Kirsch, Gilbert

    2015-08-01

    Vascular endothelial growth factor receptor-2, (VEGFR-2), is a key element in angiogenesis, the process by which new blood vessels are formed, and is thus an important pharmaceutical target. Here, 3-D quantitative structure-activity relationship (3-D QSAR) were used to build a quantitative screening and pharmacophore model of the VEGFR-2 receptors for design of inhibitors with improved activities. Most of available experimental data information has been used as training set to derive optimized and fully cross-validated eight mono-probe and a multi-probe quantitative models. Notable is the use of 262 molecules, aligned following both structure-based and ligand-based protocols, as external test set confirming the 3-D QSAR models' predictive capability and their usefulness in design new VEGFR-2 inhibitors. From a survey on literature, this is the first generation of a wide-ranging computational medicinal chemistry application on VEGFR2 inhibitors.

  6. Sources of self-efficacy belief: development and validation of two scales.

    PubMed

    Liu, Ou Lydia; Wilson, Mark

    2010-01-01

    Self-efficacy belief has been an instrumental affective factor in predicting student behavior and achievement in academic settings. Although there is abundant literature on efficacy belief per se, the sources of efficacy belief have not been fully researched. Very few instruments exist to quantify the sources of efficacy-beliefs. To fill this void, we developed two scales for the two main sources of self-efficacy belief: past performance and social persuasion. Pilot test data were collected from 255 middle school students. A self-efficacy measure was also administered to the students as a criterion measure. The Rasch rating scale model was used to analyze the data. Information on item fit, item design, content validity, external validity, internal consistency, and person separation reliability was examined. The two scales displayed satisfactory psychometric properties. Applications and limitations of these two scales are also discussed.

  7. Development and validation of a radiomics nomogram for progression-free survival prediction in stage IV EGFR-mutant non-small cell lung cancer

    NASA Astrophysics Data System (ADS)

    Song, Jiangdian; Zang, Yali; Li, Weimin; Zhong, Wenzhao; Shi, Jingyun; Dong, Di; Fang, Mengjie; Liu, Zaiyi; Tian, Jie

    2017-03-01

    Accurately predict the risk of disease progression and benefit of tyrosine kinase inhibitors (TKIs) therapy for stage IV non-small cell lung cancer (NSCLC) patients with activing epidermal growth factor receptor (EGFR) mutations by current staging methods are challenge. We postulated that integrating a classifier consisted of multiple computed tomography (CT) phenotypic features, and other clinicopathological risk factors into a single model could improve risk stratification and prediction of progression-free survival (PFS) of EGFR TKIs for these patients. Patients confirmed as stage IV EGFR-mutant NSCLC received EGFR TKIs with no resection; pretreatment contrast enhanced CT performed at approximately 2 weeks before the treatment was enrolled. A six-CT-phenotypic-feature-based classifier constructed by the LASSO Cox regression model, and three clinicopathological factors: pathologic N category, performance status (PS) score, and intrapulmonary metastasis status were used to construct a nomogram in a training set of 115 patients. The prognostic and predictive accuracy of this nomogram was then subjected to an external independent validation of 107 patients. PFS between the training and independent validation set is no statistical difference by Mann-Whitney U test (P = 0.2670). PFS of the patients could be predicted with good consistency compared with the actual survival. C-index of the proposed individualized nomogram in the training set (0·707, 95%CI: 0·643, 0·771) and the independent validation set (0·715, 95%CI: 0·650, 0·780) showed the potential of clinical prognosis to predict PFS of stage IV EGFR-mutant NSCLC from EGFR TKIs. The individualized nomogram might facilitate patient counselling and individualise management of patients with this disease.

  8. In silico prediction of Tetrahymena pyriformis toxicity for diverse industrial chemicals with substructure pattern recognition and machine learning methods.

    PubMed

    Cheng, Feixiong; Shen, Jie; Yu, Yue; Li, Weihua; Liu, Guixia; Lee, Philip W; Tang, Yun

    2011-03-01

    There is an increasing need for the rapid safety assessment of chemicals by both industries and regulatory agencies throughout the world. In silico techniques are practical alternatives in the environmental hazard assessment. It is especially true to address the persistence, bioaccumulative and toxicity potentials of organic chemicals. Tetrahymena pyriformis toxicity is often used as a toxic endpoint. In this study, 1571 diverse unique chemicals were collected from the literature and composed of the largest diverse data set for T. pyriformis toxicity. Classification predictive models of T. pyriformis toxicity were developed by substructure pattern recognition and different machine learning methods, including support vector machine (SVM), C4.5 decision tree, k-nearest neighbors and random forest. The results of a 5-fold cross-validation showed that the SVM method performed better than other algorithms. The overall predictive accuracies of the SVM classification model with radial basis functions kernel was 92.2% for the 5-fold cross-validation and 92.6% for the external validation set, respectively. Furthermore, several representative substructure patterns for characterizing T. pyriformis toxicity were also identified via the information gain analysis methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

  9. Validity of the Internal-External Scale in its Relationship with Political Position

    ERIC Educational Resources Information Center

    Silvern, Louise

    1975-01-01

    Previous studies have shown a relationship between left wing political beliefs and externality on Rotter's Scale. By examining the validity of Rotter's Scale in relation to political position, no evidence was found relating political position to locus of control. (DEP)

  10. External validation and comparison of three prediction tools for risk of osteoporotic fractures using data from population based electronic health records: retrospective cohort study

    PubMed Central

    Cohen-Stavi, Chandra; Leventer-Roberts, Maya; Balicer, Ran D

    2017-01-01

    Objective To directly compare the performance and externally validate the three most studied prediction tools for osteoporotic fractures—QFracture, FRAX, and Garvan—using data from electronic health records. Design Retrospective cohort study. Setting Payer provider healthcare organisation in Israel. Participants 1 054 815 members aged 50 to 90 years for comparison between tools and cohorts of different age ranges, corresponding to those in each tools’ development study, for tool specific external validation. Main outcome measure First diagnosis of a major osteoporotic fracture (for QFracture and FRAX tools) and hip fractures (for all three tools) recorded in electronic health records from 2010 to 2014. Observed fracture rates were compared to probabilities predicted retrospectively as of 2010. Results The observed five year hip fracture rate was 2.7% and the rate for major osteoporotic fractures was 7.7%. The areas under the receiver operating curve (AUC) for hip fracture prediction were 82.7% for QFracture, 81.5% for FRAX, and 77.8% for Garvan. For major osteoporotic fractures, AUCs were 71.2% for QFracture and 71.4% for FRAX. All the tools underestimated the fracture risk, but the average observed to predicted ratios and the calibration slopes of FRAX were closest to 1. Tool specific validation analyses yielded hip fracture prediction AUCs of 88.0% for QFracture (among those aged 30-100 years), 81.5% for FRAX (50-90 years), and 71.2% for Garvan (60-95 years). Conclusions Both QFracture and FRAX had high discriminatory power for hip fracture prediction, with QFracture performing slightly better. This performance gap was more pronounced in previous studies, likely because of broader age inclusion criteria for QFracture validations. The simpler FRAX performed almost as well as QFracture for hip fracture prediction, and may have advantages if some of the input data required for QFracture are not available. However, both tools require calibration before implementation. PMID:28104610

  11. Subtyping attention-deficit/hyperactivity disorder using temperament dimensions: toward biologically based nosologic criteria.

    PubMed

    Karalunas, Sarah L; Fair, Damien; Musser, Erica D; Aykes, Kamari; Iyer, Swathi P; Nigg, Joel T

    2014-09-01

    Psychiatric nosology is limited by behavioral and biological heterogeneity within existing disorder categories. The imprecise nature of current nosologic distinctions limits both mechanistic understanding and clinical prediction. We demonstrate an approach consistent with the National Institute of Mental Health Research Domain Criteria initiative to identify superior, neurobiologically valid subgroups with better predictive capacity than existing psychiatric categories for childhood attention-deficit/hyperactivity disorder (ADHD). To refine subtyping of childhood ADHD by using biologically based behavioral dimensions (i.e., temperament), novel classification algorithms, and multiple external validators. A total of 437 clinically well-characterized, community-recruited children, with and without ADHD, participated in an ongoing longitudinal study. Baseline data were used to classify children into subgroups based on temperament dimensions and examine external validators including physiological and magnetic resonance imaging measures. One-year longitudinal follow-up data are reported for a subgroup of the ADHD sample to address stability and clinical prediction. Parent/guardian ratings of children on a measure of temperament were used as input features in novel community detection analyses to identify subgroups within the sample. Groups were validated using 3 widely accepted external validators: peripheral physiological characteristics (cardiac measures of respiratory sinus arrhythmia and pre-ejection period), central nervous system functioning (via resting-state functional connectivity magnetic resonance imaging), and clinical outcomes (at 1-year longitudinal follow-up). The community detection algorithm suggested 3 novel types of ADHD, labeled as mild (normative emotion regulation), surgent (extreme levels of positive approach-motivation), and irritable (extreme levels of negative emotionality, anger, and poor soothability). Types were independent of existing clinical demarcations including DSM-5 presentations or symptom severity. These types showed stability over time and were distinguished by unique patterns of cardiac physiological response, resting-state functional brain connectivity, and clinical outcomes 1 year later. Results suggest that a biologically informed temperament-based typology, developed with a discovery-based community detection algorithm, provides a superior description of heterogeneity in the ADHD population than does any current clinical nosologic criteria. This demonstration sets the stage for more aggressive attempts at a tractable, biologically based nosology.

  12. Impact of External Cue Validity on Driving Performance in Parkinson's Disease

    PubMed Central

    Scally, Karen; Charlton, Judith L.; Iansek, Robert; Bradshaw, John L.; Moss, Simon; Georgiou-Karistianis, Nellie

    2011-01-01

    This study sought to investigate the impact of external cue validity on simulated driving performance in 19 Parkinson's disease (PD) patients and 19 healthy age-matched controls. Braking points and distance between deceleration point and braking point were analysed for red traffic signals preceded either by Valid Cues (correctly predicting signal), Invalid Cues (incorrectly predicting signal), and No Cues. Results showed that PD drivers braked significantly later and travelled significantly further between deceleration and braking points compared with controls for Invalid and No-Cue conditions. No significant group differences were observed for driving performance in response to Valid Cues. The benefit of Valid Cues relative to Invalid Cues and No Cues was significantly greater for PD drivers compared with controls. Trail Making Test (B-A) scores correlated with driving performance for PDs only. These results highlight the importance of external cues and higher cognitive functioning for driving performance in mild to moderate PD. PMID:21789275

  13. Heart rate variability indicates emotional value during pro-social economic laboratory decisions with large external validity.

    PubMed

    Fooken, Jonas

    2017-03-10

    The present study investigates the external validity of emotional value measured in economic laboratory experiments by using a physiological indicator of stress, heart rate variability (HRV). While there is ample evidence supporting the external validity of economic experiments, there is little evidence comparing the magnitude of internal levels of emotional stress during decision making with external stress. The current study addresses this gap by comparing the magnitudes of decision stress experienced in the laboratory with the stress from outside the laboratory. To quantify a large change in HRV, measures observed in the laboratory during decision-making are compared to the difference between HRV during a university exam and other mental activity for the same individuals in and outside of the laboratory. The results outside the laboratory inform about the relevance of laboratory findings in terms of their relative magnitude. Results show that psychologically induced HRV changes observed in the laboratory, particularly in connection with social preferences, correspond to large effects outside. This underscores the external validity of laboratory findings and shows the magnitude of emotional value connected to pro-social economic decisions in the laboratory.

  14. A comprehensive validation toolbox for regional ocean models - Outline, implementation and application to the Baltic Sea

    NASA Astrophysics Data System (ADS)

    Jandt, Simon; Laagemaa, Priidik; Janssen, Frank

    2014-05-01

    The systematic and objective comparison between output from a numerical ocean model and a set of observations, called validation in the context of this presentation, is a beneficial activity at several stages, starting from early steps in model development and ending at the quality control of model based products delivered to customers. Even though the importance of this kind of validation work is widely acknowledged it is often not among the most popular tasks in ocean modelling. In order to ease the validation work a comprehensive toolbox has been developed in the framework of the MyOcean-2 project. The objective of this toolbox is to carry out validation integrating different data sources, e.g. time-series at stations, vertical profiles, surface fields or along track satellite data, with one single program call. The validation toolbox, implemented in MATLAB, features all parts of the validation process - ranging from read-in procedures of datasets to the graphical and numerical output of statistical metrics of the comparison. The basic idea is to have only one well-defined validation schedule for all applications, in which all parts of the validation process are executed. Each part, e.g. read-in procedures, forms a module in which all available functions of this particular part are collected. The interface between the functions, the module and the validation schedule is highly standardized. Functions of a module are set up for certain validation tasks, new functions can be implemented into the appropriate module without affecting the functionality of the toolbox. The functions are assigned for each validation task in user specific settings, which are externally stored in so-called namelists and gather all information of the used datasets as well as paths and metadata. In the framework of the MyOcean-2 project the toolbox is frequently used to validate the forecast products of the Baltic Sea Marine Forecasting Centre. Hereby the performance of any new product version is compared with the previous version. Although, the toolbox is mainly tested for the Baltic Sea yet, it can easily be adapted to different datasets and parameters, regardless of the geographic region. In this presentation the usability of the toolbox is demonstrated along with several results of the validation process.

  15. A QSAR Model for Thyroperoxidase Inhibition and Screening ...

    EPA Pesticide Factsheets

    Thyroid hormones (THs) are critical modulators of a wide range of biological processes from neurodevelopment to metabolism. Well regulated levels of THs are critical during development and even moderate changes in maternal or fetal TH levels produce irreversible neurological deficits in children. The enzyme thyroperoxidase (TPO) plays a key role in the synthesis of THs. Inhibition of TPO by xenobiotics leads to decreased TH synthesis and, depending on the degree of synthesis inhibition, may result in adverse developmental outcomes. Recently, a high-throughput screening assay for TPO inhibition (AUR-TPO) was developed and used to screen the ToxCast Phase I and II chemicals. In the present study, we used the results from the AUR-TPO screening to develop a Quantitative Structure-Activity Relationship (QSAR) model for TPO inhibition in Leadscope®. The training set consisted of 898 discrete organic chemicals: 134 positive and 764 negative for TPO inhibition. A 10 times two-fold 50% cross-validation of the model was performed, yielding a balanced accuracy of 78.7% within its defined applicability domain. More recently, an additional ~800 chemicals from the US EPA Endocrine Disruption Screening Program (EDSP21) were screened using the AUR-TPO assay. This data was used for external validation of the QSAR model, demonstrating a balanced accuracy of 85.7% within its applicability domain. Overall, the cross- and external validations indicate a model with a high predictiv

  16. Independent external validation of predictive models for urinary dysfunction following external beam radiotherapy of the prostate: Issues in model development and reporting.

    PubMed

    Yahya, Noorazrul; Ebert, Martin A; Bulsara, Max; Kennedy, Angel; Joseph, David J; Denham, James W

    2016-08-01

    Most predictive models are not sufficiently validated for prospective use. We performed independent external validation of published predictive models for urinary dysfunctions following radiotherapy of the prostate. Multivariable models developed to predict atomised and generalised urinary symptoms, both acute and late, were considered for validation using a dataset representing 754 participants from the TROG 03.04-RADAR trial. Endpoints and features were harmonised to match the predictive models. The overall performance, calibration and discrimination were assessed. 14 models from four publications were validated. The discrimination of the predictive models in an independent external validation cohort, measured using the area under the receiver operating characteristic (ROC) curve, ranged from 0.473 to 0.695, generally lower than in internal validation. 4 models had ROC >0.6. Shrinkage was required for all predictive models' coefficients ranging from -0.309 (prediction probability was inverse to observed proportion) to 0.823. Predictive models which include baseline symptoms as a feature produced the highest discrimination. Two models produced a predicted probability of 0 and 1 for all patients. Predictive models vary in performance and transferability illustrating the need for improvements in model development and reporting. Several models showed reasonable potential but efforts should be increased to improve performance. Baseline symptoms should always be considered as potential features for predictive models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  17. QSAR models for thiophene and imidazopyridine derivatives inhibitors of the Polo-Like Kinase 1.

    PubMed

    Comelli, Nieves C; Duchowicz, Pablo R; Castro, Eduardo A

    2014-10-01

    The inhibitory activity of 103 thiophene and 33 imidazopyridine derivatives against Polo-Like Kinase 1 (PLK1) expressed as pIC50 (-logIC50) was predicted by QSAR modeling. Multivariate linear regression (MLR) was employed to model the relationship between 0D and 3D molecular descriptors and biological activities of molecules using the replacement method (MR) as variable selection tool. The 136 compounds were separated into several training and test sets. Two splitting approaches, distribution of biological data and structural diversity, and the statistical experimental design procedure D-optimal distance were applied to the dataset. The significance of the training set models was confirmed by statistically higher values of the internal leave one out cross-validated coefficient of determination (Q2) and external predictive coefficient of determination for the test set (Rtest2). The model developed from a training set, obtained with the D-optimal distance protocol and using 3D descriptor space along with activity values, separated chemical features that allowed to distinguish high and low pIC50 values reasonably well. Then, we verified that such model was sufficient to reliably and accurately predict the activity of external diverse structures. The model robustness was properly characterized by means of standard procedures and their applicability domain (AD) was analyzed by leverage method. Copyright © 2014 Elsevier B.V. All rights reserved.

  18. Time from prior chemotherapy enhances prognostic risk grouping in the second-line setting of advanced urothelial carcinoma: a retrospective analysis of pooled, prospective phase 2 trials.

    PubMed

    Sonpavde, Guru; Pond, Gregory R; Fougeray, Ronan; Choueiri, Toni K; Qu, Angela Q; Vaughn, David J; Niegisch, Guenter; Albers, Peter; James, Nicholas D; Wong, Yu-Ning; Ko, Yoo-Joung; Sridhar, Srikala S; Galsky, Matthew D; Petrylak, Daniel P; Vaishampayan, Ulka N; Khan, Awais; Vogelzang, Nicholas J; Beer, Tomasz M; Stadler, Walter M; O'Donnell, Peter H; Sternberg, Cora N; Rosenberg, Jonathan E; Bellmunt, Joaquim

    2013-04-01

    Outcomes for patients in the second-line setting of advanced urothelial carcinoma (UC) are dismal. The recognized prognostic factors in this context are Eastern Cooperative Oncology Group (ECOG) performance status (PS) >0, hemoglobin level (Hb) <10 g/dl, and liver metastasis (LM). The purpose of this retrospective study of prospective trials was to investigate the prognostic value of time from prior chemotherapy (TFPC) independent of known prognostic factors. Data from patients from seven prospective trials with available baseline TFPC, Hb, PS, and LM values were used for retrospective analysis (n=570). External validation was conducted in a second-line phase 3 trial comparing best supportive care (BSC) versus vinflunine plus BSC (n=352). Cox proportional hazards regression was used to evaluate the association of factors, with overall survival (OS) and progression-free survival (PFS) being the respective primary and secondary outcome measures. ECOG-PS >0, LM, Hb <10 g/dl, and shorter TFPC were significant prognostic factors for OS and PFS on multivariable analysis. Patients with zero, one, two, and three to four factors demonstrated median OS of 12.2, 6.7, 5.1, and 3.0 mo, respectively (concordance statistic=0.638). Setting of prior chemotherapy (metastatic disease vs perioperative) and prior platinum agent (cisplatin or carboplatin) were not prognostic factors. External validation demonstrated a significant association of TFPC with PFS on univariable and most multivariable analyses, and with OS on univariable analyses. Limitations of retrospective analyses are applicable. Shorter TFPC enhances prognostic classification independent of ECOG-PS >0, Hb <10 g/dl, and LM in the setting of second-line therapy for advanced UC. These data may facilitate drug development and interpretation of trials. Copyright © 2012 European Association of Urology. Published by Elsevier B.V. All rights reserved.

  19. Validity of the Externalizing Spectrum Inventory in a Criminal Offender Sample: Relations with Disinhibitory Psychopathology, Personality, and Psychopathic Features

    PubMed Central

    Venables, Noah C.; Patrick, Christopher J.

    2013-01-01

    The Externalizing Spectrum Inventory (ESI; Krueger, Markon, Patrick, Benning, & Kramer, 2007) provides a self-report based method for indexing a range of correlated problem behaviors and traits in the domain of deficient impulse control. The ESI organizes lower-order behaviors and traits of this kind around higher-order factors encompassing general disinhibitory proneness, callous-aggression, and substance abuse. The current study used data from a male prisoner sample (N = 235) to evaluate the validity of ESI total and factor scores in relation to external criterion measures consisting of externalizing disorder symptoms (including child and adult antisocial deviance and substance-related problems) assessed via diagnostic interview, personality traits assessed by self-report, and psychopathic features as assessed by both interview and self-report. Results provide evidence for the validity of the ESI measurement model and point to its potential utility as a referent for research on the neurobiological correlates and etiological bases of externalizing proneness. PMID:21787091

  20. Validity of the Externalizing Spectrum Inventory in a criminal offender sample: relations with disinhibitory psychopathology, personality, and psychopathic features.

    PubMed

    Venables, Noah C; Patrick, Christopher J

    2012-03-01

    The Externalizing Spectrum Inventory (ESI; Krueger, Markon, Patrick, Benning, & Kramer, 2007) provides a self-report based method for indexing a range of correlated problem behaviors and traits in the domain of deficient impulse control. The ESI organizes lower order behaviors and traits of this kind around higher order factors encompassing general disinhibitory proneness, callous-aggression, and substance abuse. In the current study, we used data from a male prisoner sample (N = 235) to evaluate the validity of ESI total and factor scores in relation to external criterion measures consisting of externalizing disorder symptoms (including child and adult antisocial deviance and substance-related problems) assessed via diagnostic interviews, personality traits assessed with self-reports, and psychopathic features as assessed with both interviews and self-reports. Results provide evidence for the validity of the ESI measurement model and point to its potential usefulness as a referent for research on the neurobiological correlates and etiological bases of externalizing proneness.

  1. The Amsterdam wrist rules: the multicenter prospective derivation and external validation of a clinical decision rule for the use of radiography in acute wrist trauma.

    PubMed

    Walenkamp, Monique M J; Bentohami, Abdelali; Slaar, Annelie; Beerekamp, M Suzan H; Maas, Mario; Jager, L Cara; Sosef, Nico L; van Velde, Romuald; Ultee, Jan M; Steyerberg, Ewout W; Goslings, J Carel; Schep, Niels W L

    2015-12-18

    Although only 39 % of patients with wrist trauma have sustained a fracture, the majority of patients is routinely referred for radiography. The purpose of this study was to derive and externally validate a clinical decision rule that selects patients with acute wrist trauma in the Emergency Department (ED) for radiography. This multicenter prospective study consisted of three components: (1) derivation of a clinical prediction model for detecting wrist fractures in patients following wrist trauma; (2) external validation of this model; and (3) design of a clinical decision rule. The study was conducted in the EDs of five Dutch hospitals: one academic hospital (derivation cohort) and four regional hospitals (external validation cohort). We included all adult patients with acute wrist trauma. The main outcome was fracture of the wrist (distal radius, distal ulna or carpal bones) diagnosed on conventional X-rays. A total of 882 patients were analyzed; 487 in the derivation cohort and 395 in the validation cohort. We derived a clinical prediction model with eight variables: age; sex, swelling of the wrist; swelling of the anatomical snuffbox, visible deformation; distal radius tender to palpation; pain on radial deviation and painful axial compression of the thumb. The Area Under the Curve at external validation of this model was 0.81 (95 % CI: 0.77-0.85). The sensitivity and specificity of the Amsterdam Wrist Rules (AWR) in the external validation cohort were 98 % (95 % CI: 95-99 %) and 21 % (95 % CI: 15 %-28). The negative predictive value was 90 % (95 % CI: 81-99 %). The Amsterdam Wrist Rules is a clinical prediction rule with a high sensitivity and negative predictive value for fractures of the wrist. Although external validation showed low specificity and 100 % sensitivity could not be achieved, the Amsterdam Wrist Rules can provide physicians in the Emergency Department with a useful screening tool to select patients with acute wrist trauma for radiography. The upcoming implementation study will further reveal the impact of the Amsterdam Wrist Rules on the anticipated reduction of X-rays requested, missed fractures, Emergency Department waiting times and health care costs. This study was registered in the Dutch Trial Registry, reference number NTR2544 on October 1(st), 2010.

  2. Predicting Overall Survival After Stereotactic Ablative Radiation Therapy in Early-Stage Lung Cancer: Development and External Validation of the Amsterdam Prognostic Model

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

    Louie, Alexander V., E-mail: Dr.alexlouie@gmail.com; Department of Radiation Oncology, London Regional Cancer Program, University of Western Ontario, London, Ontario; Department of Epidemiology, Harvard School of Public Health, Harvard University, Boston, Massachusetts

    Purpose: A prognostic model for 5-year overall survival (OS), consisting of recursive partitioning analysis (RPA) and a nomogram, was developed for patients with early-stage non-small cell lung cancer (ES-NSCLC) treated with stereotactic ablative radiation therapy (SABR). Methods and Materials: A primary dataset of 703 ES-NSCLC SABR patients was randomly divided into a training (67%) and an internal validation (33%) dataset. In the former group, 21 unique parameters consisting of patient, treatment, and tumor factors were entered into an RPA model to predict OS. Univariate and multivariate models were constructed for RPA-selected factors to evaluate their relationship with OS. A nomogrammore » for OS was constructed based on factors significant in multivariate modeling and validated with calibration plots. Both the RPA and the nomogram were externally validated in independent surgical (n=193) and SABR (n=543) datasets. Results: RPA identified 2 distinct risk classes based on tumor diameter, age, World Health Organization performance status (PS) and Charlson comorbidity index. This RPA had moderate discrimination in SABR datasets (c-index range: 0.52-0.60) but was of limited value in the surgical validation cohort. The nomogram predicting OS included smoking history in addition to RPA-identified factors. In contrast to RPA, validation of the nomogram performed well in internal validation (r{sup 2}=0.97) and external SABR (r{sup 2}=0.79) and surgical cohorts (r{sup 2}=0.91). Conclusions: The Amsterdam prognostic model is the first externally validated prognostication tool for OS in ES-NSCLC treated with SABR available to individualize patient decision making. The nomogram retained strong performance across surgical and SABR external validation datasets. RPA performance was poor in surgical patients, suggesting that 2 different distinct patient populations are being treated with these 2 effective modalities.« less

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

    PubMed

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

    2017-03-01

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

  4. Sub-millimeter-Wave Equivalent Circuit Model for External Parasitics in Double-Finger HEMT Topologies

    NASA Astrophysics Data System (ADS)

    Karisan, Yasir; Caglayan, Cosan; Sertel, Kubilay

    2018-02-01

    We present a novel distributed equivalent circuit that incorporates a three-way-coupled transmission line to accurately capture the external parasitics of double-finger high electron mobility transistor (HEMT) topologies up to 750 GHz. A six-step systematic parameter extraction procedure is used to determine the equivalent circuit elements for a representative device layout. The accuracy of the proposed approach is validated in the 90-750 GHz band through comparisons between measured data (via non-contact probing) and full-wave simulations, as well as the equivalent circuit response. Subsequently, a semi-distributed active device model is incorporated into the proposed parasitic circuit to demonstrate that the three-way-coupled transmission line model effectively predicts the adverse effect of parasitic components on the sub-mmW performance in an amplifier setting.

  5. BDDCS Class Prediction for New Molecular Entities

    PubMed Central

    Broccatelli, Fabio; Cruciani, Gabriele; Benet, Leslie Z.; Oprea, Tudor I.

    2012-01-01

    The Biopharmaceutics Drug Disposition Classification System (BDDCS) was successfully employed for predicting drug-drug interactions (DDIs) with respect to drug metabolizing enzymes (DMEs), drug transporters and their interplay. The major assumption of BDDCS is that the extent of metabolism (EoM) predicts high versus low intestinal permeability rate, and vice versa, at least when uptake transporters or paracellular transport are not involved. We recently published a collection of over 900 marketed drugs classified for BDDCS. We suggest that a reliable model for predicting BDDCS class, integrated with in vitro assays, could anticipate disposition and potential DDIs of new molecular entities (NMEs). Here we describe a computational procedure for predicting BDDCS class from molecular structures. The model was trained on a set of 300 oral drugs, and validated on an external set of 379 oral drugs, using 17 descriptors calculated or derived from the VolSurf+ software. For each molecule, a probability of BDDCS class membership was given, based on predicted EoM, FDA solubility (FDAS) and their confidence scores. The accuracy in predicting FDAS was 78% in training and 77% in validation, while for EoM prediction the accuracy was 82% in training and 79% in external validation. The actual BDDCS class corresponded to the highest ranked calculated class for 55% of the validation molecules, and it was within the top two ranked more than 92% of the times. The unbalanced stratification of the dataset didn’t affect the prediction, which showed highest accuracy in predicting classes 2 and 3 with respect to the most populated class 1. For class 4 drugs a general lack of predictability was observed. A linear discriminant analysis (LDA) confirmed the degree of accuracy for the prediction of the different BDDCS classes is tied to the structure of the dataset. This model could routinely be used in early drug discovery to prioritize in vitro tests for NMEs (e.g., affinity to transporters, intestinal metabolism, intestinal absorption and plasma protein binding). We further applied the BDDCS prediction model on a large set of medicinal chemistry compounds (over 30,000 chemicals). Based on this application, we suggest that solubility, and not permeability, is the major difference between NMEs and drugs. We anticipate that the forecast of BDDCS categories in early drug discovery may lead to a significant R&D cost reduction. PMID:22224483

  6. A Public-Private Partnership Develops and Externally Validates a 30-Day Hospital Readmission Risk Prediction Model

    PubMed Central

    Choudhry, Shahid A.; Li, Jing; Davis, Darcy; Erdmann, Cole; Sikka, Rishi; Sutariya, Bharat

    2013-01-01

    Introduction: Preventing the occurrence of hospital readmissions is needed to improve quality of care and foster population health across the care continuum. Hospitals are being held accountable for improving transitions of care to avert unnecessary readmissions. Advocate Health Care in Chicago and Cerner (ACC) collaborated to develop all-cause, 30-day hospital readmission risk prediction models to identify patients that need interventional resources. Ideally, prediction models should encompass several qualities: they should have high predictive ability; use reliable and clinically relevant data; use vigorous performance metrics to assess the models; be validated in populations where they are applied; and be scalable in heterogeneous populations. However, a systematic review of prediction models for hospital readmission risk determined that most performed poorly (average C-statistic of 0.66) and efforts to improve their performance are needed for widespread usage. Methods: The ACC team incorporated electronic health record data, utilized a mixed-method approach to evaluate risk factors, and externally validated their prediction models for generalizability. Inclusion and exclusion criteria were applied on the patient cohort and then split for derivation and internal validation. Stepwise logistic regression was performed to develop two predictive models: one for admission and one for discharge. The prediction models were assessed for discrimination ability, calibration, overall performance, and then externally validated. Results: The ACC Admission and Discharge Models demonstrated modest discrimination ability during derivation, internal and external validation post-recalibration (C-statistic of 0.76 and 0.78, respectively), and reasonable model fit during external validation for utility in heterogeneous populations. Conclusions: The ACC Admission and Discharge Models embody the design qualities of ideal prediction models. The ACC plans to continue its partnership to further improve and develop valuable clinical models. PMID:24224068

  7. Estimates of External Validity Bias When Impact Evaluations Select Sites Nonrandomly

    ERIC Educational Resources Information Center

    Bell, Stephen H.; Olsen, Robert B.; Orr, Larry L.; Stuart, Elizabeth A.

    2016-01-01

    Evaluations of educational programs or interventions are typically conducted in nonrandomly selected samples of schools or districts. Recent research has shown that nonrandom site selection can yield biased impact estimates. To estimate the external validity bias from nonrandom site selection, we combine lists of school districts that were…

  8. Design, synthesis and screening studies of potent thiazol-2-amine derivatives as fibroblast growth factor receptor 1 inhibitors.

    PubMed

    Kumar, B V S Suneel; Lakshmi, Narasu; Kumar, M Ravi; Rambabu, Gundla; Manjashetty, Thimmappa H; Arunasree, Kalle M; Sriram, Dharmarajan; Ramkumar, Kavya; Neamati, Nouri; Dayam, Raveendra; Sarma, J A R P

    2014-01-01

    Fibroblast growth factor receptor 1 (FGFR1) a tyrosine kinase receptor, plays important roles in angiogenesis, embryonic development, cell proliferation, cell differentiation, and wound healing. The FGFR isoforms and their receptors (FGFRs) considered as a potential targets and under intense research to design potential anticancer agents. Fibroblast growth factors (FGF's) and its growth factor receptors (FGFR) plays vital role in one of the critical pathway in monitoring angiogenesis. In the current study, quantitative pharmacophore models were generated and validated using known FGFR1 inhibitors. The pharmacophore models were generated using a set of 28 compounds (training). The top pharmacophore model was selected and validated using a set of 126 compounds (test set) and also using external validation. The validated pharmacophore was considered as a virtual screening query to screen a database of 400,000 virtual molecules and pharmacophore model retrieved 2800 hits. The retrieved hits were subsequently filtered based on the fit value. The selected hits were subjected for docking studies to observe the binding modes of the retrieved hits and also to reduce the false positives. One of the potential hits (thiazole-2-amine derivative) was selected based the pharmacophore fit value, dock score, and synthetic feasibility. A few analogues of the thiazole-2-amine derivative were synthesized. These compounds were screened for FGFR1 activity and anti-proliferative studies. The top active compound showed 56.87% inhibition of FGFR1 activity at 50 µM and also showed good cellular activity. Further optimization of thiazole-2-amine derivatives is in progress.

  9. Robust prediction of three-dimensional spinal curve from back surface for non-invasive follow-up of scoliosis

    NASA Astrophysics Data System (ADS)

    Bergeron, Charles; Labelle, Hubert; Ronsky, Janet; Zernicke, Ronald

    2005-04-01

    Spinal curvature progression in scoliosis patients is monitored from X-rays, and this serial exposure to harmful radiation increases the incidence of developing cancer. With the aim of reducing the invasiveness of follow-up, this study seeks to relate the three-dimensional external surface to the internal geometry, having assumed that that the physiological links between these are sufficiently regular across patients. A database was used of 194 quasi-simultaneous acquisitions of two X-rays and a 3D laser scan of the entire trunk. Data was processed to sets of datapoints representing the trunk surface and spinal curve. Functional data analyses were performed using generalized Fourier series using a Haar basis and functional minimum noise fractions. The resulting coefficients became inputs and outputs, respectively, to an array of support vector regression (SVR) machines. SVR parameters were set based on theoretical results, and cross-validation increased confidence in the system's performance. Predicted lateral and frontal views of the spinal curve from the back surface demonstrated average L2-errors of 6.13 and 4.38 millimetres, respectively, across the test set; these compared favourably with measurement error in data. This constitutes a first robust prediction of the 3D spinal curve from external data using learning techniques.

  10. Use of the Monte Carlo Method for OECD Principles-Guided QSAR Modeling of SIRT1 Inhibitors.

    PubMed

    Kumar, Ashwani; Chauhan, Shilpi

    2017-01-01

    SIRT1 inhibitors offer therapeutic potential for the treatment of a number of diseases including cancer and human immunodeficiency virus infection. A diverse series of 45 compounds with reported SIRT1 inhibitory activity has been employed for the development of quantitative structure-activity relationship (QSAR) models using the Monte Carlo optimization method. This method makes use of simplified molecular input line entry system notation of the molecular structure. The QSAR models were built up according to OECD principles. Three subsets of three splits were examined and validated by respective external sets. All the three described models have good statistical quality. The best model has the following statistical characteristics: R 2  = 0.8350, Q 2 test  = 0.7491 for the test set and R 2  = 0.9655, Q 2 ext  = 0.9261 for the validation set. In the mechanistic interpretation, structural attributes responsible for the endpoint increase and decrease are defined. Further, the design of some prospective SIRT1 inhibitors is also presented on the basis of these structural attributes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Thermal-Hydraulic Results for the Boiling Water Reactor Dry Cask Simulator.

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

    Durbin, Samuel; Lindgren, Eric R.

    The thermal performance of commercial nuclear spent fuel dry storage casks is evaluated through detailed numerical analysis. These modeling efforts are completed by the vendor to demonstrate performance and regulatory compliance. The calculations are then independently verified by the Nuclear Regulatory Commission (NRC). Carefully measured data sets generated from testing of full sized casks or smaller cask analogs are widely recognized as vital for validating these models. Recent advances in dry storage cask designs have significantly increased the maximum thermal load allowed in a cask in part by increasing the efficiency of internal conduction pathways and by increasing the internalmore » convection through greater canister helium pressure. These same canistered cask systems rely on ventilation between the canister and the overpack to convect heat away from the canister to the environment for both aboveground and belowground configurations. While several testing programs have been previously conducted, these earlier validation attempts did not capture the effects of elevated helium pressures or accurately portray the external convection of aboveground and belowground canistered dry cask systems. The purpose of this investigation was to produce validation-quality data that can be used to test the validity of the modeling presently used to determine cladding temperatures in modern vertical dry casks. These cladding temperatures are critical to evaluate cladding integrity throughout the storage cycle. To produce these data sets under well-controlled boundary conditions, the dry cask simulator (DCS) was built to study the thermal-hydraulic response of fuel under a variety of heat loads, internal vessel pressures, and external configurations. An existing electrically heated but otherwise prototypic BWR Incoloy-clad test assembly was deployed inside of a representative storage basket and cylindrical pressure vessel that represents a vertical canister system. The symmetric single assembly geometry with well-controlled boundary conditions simplified interpretation of results. Two different arrangements of ducting were used to mimic conditions for aboveground and belowground storage configurations for vertical, dry cask systems with canisters. Transverse and axial temperature profiles were measured throughout the test assembly. The induced air mass flow rate was measured for both the aboveground and belowground configurations. In addition, the impact of cross-wind conditions on the belowground configuration was quantified. Over 40 unique data sets were collected and analyzed for these efforts. Fourteen data sets for the aboveground configuration were recorded for powers and internal pressures ranging from 0.5 to 5.0 kW and 0.3 to 800 kPa absolute, respectively. Similarly, fourteen data sets were logged for the belowground configuration starting at ambient conditions and concluding with thermal-hydraulic steady state. Over thirteen tests were conducted using a custom-built wind machine. The results documented in this report highlight a small, but representative, subset of the available data from this test series. This addition to the dry cask experimental database signifies a substantial addition of first-of-a-kind, high-fidelity transient and steady-state thermal-hydraulic data sets suitable for CFD model validation.« less

  12. Hybrid optimal descriptors as a tool to predict skin sensitization in accordance to OECD principles.

    PubMed

    Toropova, Alla P; Toropov, Andrey A

    2017-06-05

    Skin sensitization (allergic contact dermatitis) is a widespread problem arising from the contact of chemicals with the skin. The detection of molecular features with undesired effect for skin is complex task owing to unclear biochemical mechanisms and unclearness of conditions of action of chemicals to skin. The development of computational methods for estimation of this endpoint in order to reduce animal testing is recommended (Cosmetics Directive EC regulation 1907/2006; EU Regulation, Regulation, 1223/2009). The CORAL software (http://www.insilico.eu/coral) gives good predictive models for the skin sensitization. Simplified molecular input-line entry system (SMILES) together with molecular graph are used to represent the molecular structure for these models. So-called hybrid optimal descriptors are used to establish quantitative structure-activity relationships (QSARs). The aim of this study is the estimation of the predictive potential of the hybrid descriptors. Three different distributions into the training (≈70%), calibration (≈15%), and validation (≈15%) sets are studied. QSAR for these three distributions are built up with using the Monte Carlo technique. The statistical characteristics of these models for external validation set are used as a measure of predictive potential of these models. The best model, according to the above criterion, is characterized by n validation =29, r 2 validation =0.8596, RMSE validation =0.489. Mechanistic interpretation and domain of applicability for these models are defined. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Predicting Mouse Liver Microsomal Stability with “Pruned” Machine Learning Models and Public Data

    PubMed Central

    Perryman, Alexander L.; Stratton, Thomas P.; Ekins, Sean; Freundlich, Joel S.

    2015-01-01

    Purpose Mouse efficacy studies are a critical hurdle to advance translational research of potential therapeutic compounds for many diseases. Although mouse liver microsomal (MLM) stability studies are not a perfect surrogate for in vivo studies of metabolic clearance, they are the initial model system used to assess metabolic stability. Consequently, we explored the development of machine learning models that can enhance the probability of identifying compounds possessing MLM stability. Methods Published assays on MLM half-life values were identified in PubChem, reformatted, and curated to create a training set with 894 unique small molecules. These data were used to construct machine learning models assessed with internal cross-validation, external tests with a published set of antitubercular compounds, and independent validation with an additional diverse set of 571 compounds (PubChem data on percent metabolism). Results “Pruning” out the moderately unstable/moderately stable compounds from the training set produced models with superior predictive power. Bayesian models displayed the best predictive power for identifying compounds with a half-life ≥1 hour. Conclusions Our results suggest the pruning strategy may be of general benefit to improve test set enrichment and provide machine learning models with enhanced predictive value for the MLM stability of small organic molecules. This study represents the most exhaustive study to date of using machine learning approaches with MLM data from public sources. PMID:26415647

  14. Predicting Mouse Liver Microsomal Stability with "Pruned" Machine Learning Models and Public Data.

    PubMed

    Perryman, Alexander L; Stratton, Thomas P; Ekins, Sean; Freundlich, Joel S

    2016-02-01

    Mouse efficacy studies are a critical hurdle to advance translational research of potential therapeutic compounds for many diseases. Although mouse liver microsomal (MLM) stability studies are not a perfect surrogate for in vivo studies of metabolic clearance, they are the initial model system used to assess metabolic stability. Consequently, we explored the development of machine learning models that can enhance the probability of identifying compounds possessing MLM stability. Published assays on MLM half-life values were identified in PubChem, reformatted, and curated to create a training set with 894 unique small molecules. These data were used to construct machine learning models assessed with internal cross-validation, external tests with a published set of antitubercular compounds, and independent validation with an additional diverse set of 571 compounds (PubChem data on percent metabolism). "Pruning" out the moderately unstable / moderately stable compounds from the training set produced models with superior predictive power. Bayesian models displayed the best predictive power for identifying compounds with a half-life ≥1 h. Our results suggest the pruning strategy may be of general benefit to improve test set enrichment and provide machine learning models with enhanced predictive value for the MLM stability of small organic molecules. This study represents the most exhaustive study to date of using machine learning approaches with MLM data from public sources.

  15. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

    PubMed

    Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

    2017-07-01

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in using RF to develop predictive models with large environmental data sets.

  16. A nomogram for predicting complications in patients with solid tumours and seemingly stable febrile neutropenia.

    PubMed

    Fonseca, Paula Jiménez; Carmona-Bayonas, Alberto; García, Ignacio Matos; Marcos, Rosana; Castañón, Eduardo; Antonio, Maite; Font, Carme; Biosca, Mercè; Blasco, Ana; Lozano, Rebeca; Ramchandani, Avinash; Beato, Carmen; de Castro, Eva Martínez; Espinosa, Javier; Martínez-García, Jerónimo; Ghanem, Ismael; Cubero, Jorge Hernando; Manrique, Isabel Aragón; Navalón, Francisco García; Sevillano, Elena; Manzano, Aránzazu; Virizuela, Juan; Garrido, Marcelo; Mondéjar, Rebeca; Arcusa, María Ángeles; Bonilla, Yaiza; Pérez, Quionia; Gallardo, Elena; Del Carmen Soriano, Maria; Cardona, Mercè; Lasheras, Fernando Sánchez; Cruz, Juan Jesús; Ayala, Francisco

    2016-05-24

    We sought to develop and externally validate a nomogram and web-based calculator to individually predict the development of serious complications in seemingly stable adult patients with solid tumours and episodes of febrile neutropenia (FN). The data from the FINITE study (n=1133) and University of Salamanca Hospital (USH) FN registry (n=296) were used to develop and validate this tool. The main eligibility criterion was the presence of apparent clinical stability, defined as events without acute organ dysfunction, abnormal vital signs, or major infections. Discriminatory ability was measured as the concordance index and stratification into risk groups. The rate of infection-related complications in the FINITE and USH series was 13.4% and 18.6%, respectively. The nomogram used the following covariates: Eastern Cooperative Group (ECOG) Performance Status ⩾2, chronic obstructive pulmonary disease, chronic cardiovascular disease, mucositis of grade ⩾2 (National Cancer Institute Common Toxicity Criteria), monocytes <200/mm(3), and stress-induced hyperglycaemia. The nomogram predictions appeared to be well calibrated in both data sets (Hosmer-Lemeshow test, P>0.1). The concordance index was 0.855 and 0.831 in each series. Risk group stratification revealed a significant distinction in the proportion of complications. With a ⩾116-point cutoff, the nomogram yielded the following prognostic indices in the USH registry validation series: 66% sensitivity, 83% specificity, 3.88 positive likelihood ratio, 48% positive predictive value, and 91% negative predictive value. We have developed and externally validated a nomogram and web calculator to predict serious complications that can potentially impact decision-making in patients with seemingly stable FN.

  17. Simulation models in population breast cancer screening: A systematic review.

    PubMed

    Koleva-Kolarova, Rositsa G; Zhan, Zhuozhao; Greuter, Marcel J W; Feenstra, Talitha L; De Bock, Geertruida H

    2015-08-01

    The aim of this review was to critically evaluate published simulation models for breast cancer screening of the general population and provide a direction for future modeling. A systematic literature search was performed to identify simulation models with more than one application. A framework for qualitative assessment which incorporated model type; input parameters; modeling approach, transparency of input data sources/assumptions, sensitivity analyses and risk of bias; validation, and outcomes was developed. Predicted mortality reduction (MR) and cost-effectiveness (CE) were compared to estimates from meta-analyses of randomized control trials (RCTs) and acceptability thresholds. Seven original simulation models were distinguished, all sharing common input parameters. The modeling approach was based on tumor progression (except one model) with internal and cross validation of the resulting models, but without any external validation. Differences in lead times for invasive or non-invasive tumors, and the option for cancers not to progress were not explicitly modeled. The models tended to overestimate the MR (11-24%) due to screening as compared to optimal RCTs 10% (95% CI - 2-21%) MR. Only recently, potential harms due to regular breast cancer screening were reported. Most scenarios resulted in acceptable cost-effectiveness estimates given current thresholds. The selected models have been repeatedly applied in various settings to inform decision making and the critical analysis revealed high risk of bias in their outcomes. Given the importance of the models, there is a need for externally validated models which use systematical evidence for input data to allow for more critical evaluation of breast cancer screening. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. On using summary statistics from an external calibration sample to correct for covariate measurement error.

    PubMed

    Guo, Ying; Little, Roderick J; McConnell, Daniel S

    2012-01-01

    Covariate measurement error is common in epidemiologic studies. Current methods for correcting measurement error with information from external calibration samples are insufficient to provide valid adjusted inferences. We consider the problem of estimating the regression of an outcome Y on covariates X and Z, where Y and Z are observed, X is unobserved, but a variable W that measures X with error is observed. Information about measurement error is provided in an external calibration sample where data on X and W (but not Y and Z) are recorded. We describe a method that uses summary statistics from the calibration sample to create multiple imputations of the missing values of X in the regression sample, so that the regression coefficients of Y on X and Z and associated standard errors can be estimated using simple multiple imputation combining rules, yielding valid statistical inferences under the assumption of a multivariate normal distribution. The proposed method is shown by simulation to provide better inferences than existing methods, namely the naive method, classical calibration, and regression calibration, particularly for correction for bias and achieving nominal confidence levels. We also illustrate our method with an example using linear regression to examine the relation between serum reproductive hormone concentrations and bone mineral density loss in midlife women in the Michigan Bone Health and Metabolism Study. Existing methods fail to adjust appropriately for bias due to measurement error in the regression setting, particularly when measurement error is substantial. The proposed method corrects this deficiency.

  19. Molecular Docking Study on Galantamine Derivatives as Cholinesterase Inhibitors.

    PubMed

    Atanasova, Mariyana; Yordanov, Nikola; Dimitrov, Ivan; Berkov, Strahil; Doytchinova, Irini

    2015-06-01

    A training set of 22 synthetic galantamine derivatives binding to acetylcholinesterase was docked by GOLD and the protocol was optimized in terms of scoring function, rigidity/flexibility of the binding site, presence/absence of a water molecule inside and radius of the binding site. A moderate correlation was found between the affinities of compounds expressed as pIC50 values and their docking scores. The optimized docking protocol was validated by an external test set of 11 natural galantamine derivatives and the correlation coefficient between the docking scores and the pIC50 values was 0.800. The derived relationship was used to analyze the interactions between galantamine derivatives and AChE. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. The headache under-response to treatment (HURT) questionnaire, an outcome measure to guide follow-up in primary care: development, psychometric evaluation and assessment of utility.

    PubMed

    Steiner, T J; Buse, D C; Al Jumah, M; Westergaard, M L; Jensen, R H; Reed, M L; Prilipko, L; Mennini, F S; Láinez, M J A; Ravishankar, K; Sakai, F; Yu, S-Y; Fontebasso, M; Al Khathami, A; MacGregor, E A; Antonaci, F; Tassorelli, C; Lipton, R B

    2018-02-14

    Headache disorders are both common and burdensome but, given the many people affected, provision of health care to all is challenging. Structured headache services based in primary care are the most efficient, equitable and cost-effective solution but place responsibility for managing most patients on health-care providers with limited training in headache care. The development of practical management aids for primary care is therefore a purpose of the Global Campaign against Headache. This manuscript presents an outcome measure, the Headache Under-Response to Treatment (HURT) questionnaire, describing its purpose, development, psychometric evaluation and assessment for clinical utility. The objective was a simple-to-use instrument that would both assess outcome and provide guidance to improving outcome, having utility across the range of headache disorders, across clinical settings and across countries and cultures. After literature review, an expert consensus group drawn from all six world regions formulated HURT through item development and item reduction using item-response theory. Using the American Migraine Prevalence and Prevention Study's general-population respondent panel, two mailed surveys assessed the psychometric properties of HURT, comparing it with other instruments as external validators. Reliability was assessed in patients in two culturally-contrasting clinical settings: headache specialist centres in Europe (n = 159) and primary-care centres in Saudi Arabia (n = 40). Clinical utility was assessed in similar settings (Europe n = 201; Saudi Arabia n = 342). The final instrument, an 8-item self-administered questionnaire, addressed headache frequency, disability, medication use and effect, patients' perceptions of headache "control" and their understanding of their diagnoses. Psychometric evaluation revealed a two-factor model (headache frequency, disability and medication use; and medication efficacy and headache control), with scale properties apparently stable across disorders and correlating well and in the expected directions with external validators. The literature review found few instruments linking assessment to clinical advice or suggested actions: HURT appeared to fill this gap. In European specialist care, it showed utility as an outcome measure across headache disorders. In Saudi Arabian primary care, HURT (translated into Arabic) was reliable and responsive to clinical change. With demonstrated validity and clinical utility across disorders, cultures and settings, HURT is available for clinical and research purposes.

  1. A Psychometric Validation of the Internal and External Motivation to Respond without Prejudice toward People with Disabilities Scale

    ERIC Educational Resources Information Center

    Pruett, Steven R.; Deiches, Jon; Pfaller, Joseph; Moser, Erin; Chan, Fong

    2014-01-01

    Objective: To determine the factorial validity of the Internal and External Motivation to Respond without Prejudice toward People with Disabilities Scale (D-IMS/EMS). Design: A quantitative descriptive design using factor analysis. Participants: 233 rehabilitation counseling and rehabilitation services students. Results: Both exploratory and…

  2. ODD and ADHD Symptoms in Ukrainian Children: External Validators and Comorbidity

    ERIC Educational Resources Information Center

    Drabick, Deborah A. G.; Gadow, Kenneth D.; Carlson, Gabrielle A.; Bromet, Evelyn J.

    2004-01-01

    Objective: To examine potential external validators for oppositional defiant disorder (ODD) and attention-deficient/hyperactive disorder (ADHD) symptoms in a Ukrainian community-based sample of 600 children age 10 to 12 years old and evaluate the nature of co-occurring ODD and ADHD symptoms using mother- and teacher-defined groups. Method: In…

  3. A simple weighted scoring system to guide surgical decision-making in patients with parapneumonic pleural effusion.

    PubMed

    Chang, Che-Chia; Chen, Tzu-Ping; Yeh, Chi-Hsiao; Huang, Pin-Fu; Wang, Yao-Chang; Yin, Shun-Ying

    2016-11-01

    The selection of ideal candidates for surgical intervention among patients with parapneumonic pleural effusion remains challenging. In this retrospective study, we sought to identify the main predictors of surgical treatment and devise a simple scoring system to guide surgical decision-making. Between 2005 and 2014, we identified 276 patients with parapneumonic pleural effusion. Patients in the training set (n=201) were divided into two groups according to their treatment modality (non-surgery vs. surgery). Using multivariable logistic regression analysis, we devised a scoring system to guide surgical decision-making. The score was subsequently validated in an independent set of 75 patients. A white blood cell count >13,500/µL, pleuritic pain, loculations, and split pleura sign were identified as independent predictors of surgical treatment. A weighted score based on these factors was devised, as follows: white blood cell count >13,500/µL (one point), pleuritic pain (one point), loculations (two points), and split pleura sign (three points). A score >4 was associated with a surgical approach with a sensitivity of 93.4%, a specificity of 82.4%, and an area under curve (AUC) of 0.879 (95% confidence interval: 0.828-0.930). In the validation set, a sensitivity of 94.3% and a specificity of 79.6% were found (AUC=0.869). The proposed scoring system reliably identifies patients with parapneumonic pleural effusion who are candidates for surgery. Pending independent external validation, our score may inform the appropriate use of surgical interventions in this clinical setting.

  4. Quality assessment of gasoline using comprehensive two-dimensional gas chromatography combined with unfolded partial least squares: A reliable approach for the detection of gasoline adulteration.

    PubMed

    Parastar, Hadi; Mostafapour, Sara; Azimi, Gholamhasan

    2016-01-01

    Comprehensive two-dimensional gas chromatography and flame ionization detection combined with unfolded-partial least squares is proposed as a simple, fast and reliable method to assess the quality of gasoline and to detect its potential adulterants. The data for the calibration set are first baseline corrected using a two-dimensional asymmetric least squares algorithm. The number of significant partial least squares components to build the model is determined using the minimum value of root-mean square error of leave-one out cross validation, which was 4. In this regard, blends of gasoline with kerosene, white spirit and paint thinner as frequently used adulterants are used to make calibration samples. Appropriate statistical parameters of regression coefficient of 0.996-0.998, root-mean square error of prediction of 0.005-0.010 and relative error of prediction of 1.54-3.82% for the calibration set show the reliability of the developed method. In addition, the developed method is externally validated with three samples in validation set (with a relative error of prediction below 10.0%). Finally, to test the applicability of the proposed strategy for the analysis of real samples, five real gasoline samples collected from gas stations are used for this purpose and the gasoline proportions were in range of 70-85%. Also, the relative standard deviations were below 8.5% for different samples in the prediction set. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Artificial neural network classifier predicts neuroblastoma patients' outcome.

    PubMed

    Cangelosi, Davide; Pelassa, Simone; Morini, Martina; Conte, Massimo; Bosco, Maria Carla; Eva, Alessandra; Sementa, Angela Rita; Varesio, Luigi

    2016-11-08

    More than fifty percent of neuroblastoma (NB) patients with adverse prognosis do not benefit from treatment making the identification of new potential targets mandatory. Hypoxia is a condition of low oxygen tension, occurring in poorly vascularized tissues, which activates specific genes and contributes to the acquisition of the tumor aggressive phenotype. We defined a gene expression signature (NB-hypo), which measures the hypoxic status of the neuroblastoma tumor. We aimed at developing a classifier predicting neuroblastoma patients' outcome based on the assessment of the adverse effects of tumor hypoxia on the progression of the disease. Multi-layer perceptron (MLP) was trained on the expression values of the 62 probe sets constituting NB-hypo signature to develop a predictive model for neuroblastoma patients' outcome. We utilized the expression data of 100 tumors in a leave-one-out analysis to select and construct the classifier and the expression data of the remaining 82 tumors to test the classifier performance in an external dataset. We utilized the Gene set enrichment analysis (GSEA) to evaluate the enrichment of hypoxia related gene sets in patients predicted with "Poor" or "Good" outcome. We utilized the expression of the 62 probe sets of the NB-Hypo signature in 182 neuroblastoma tumors to develop a MLP classifier predicting patients' outcome (NB-hypo classifier). We trained and validated the classifier in a leave-one-out cross-validation analysis on 100 tumor gene expression profiles. We externally tested the resulting NB-hypo classifier on an independent 82 tumors' set. The NB-hypo classifier predicted the patients' outcome with the remarkable accuracy of 87 %. NB-hypo classifier prediction resulted in 2 % classification error when applied to clinically defined low-intermediate risk neuroblastoma patients. The prediction was 100 % accurate in assessing the death of five low/intermediated risk patients. GSEA of tumor gene expression profile demonstrated the hypoxic status of the tumor in patients with poor prognosis. We developed a robust classifier predicting neuroblastoma patients' outcome with a very low error rate and we provided independent evidence that the poor outcome patients had hypoxic tumors, supporting the potential of using hypoxia as target for neuroblastoma treatment.

  6. Development of the SaFETy Score: A Clinical Screening Tool for Predicting Future Firearm Violence Risk

    PubMed Central

    Goldstick, Jason E.; Carter, Patrick M.; Walton, Maureen A.; Dahlberg, Linda L.; Sumner, Steven A.; Zimmerman, Marc A.; Cunningham, Rebecca M.

    2017-01-01

    Background Interpersonal firearm violence among youth is a substantial public health problem, and emergency department (ED) physicians require a clinical screening tool to identify high-risk youth. Objective To derive a clinically feasible risk index for firearm violence. Design 24-month prospective cohort study. Setting Urban, level 1 ED. Participants Substance-using youths, aged 14 to 24 years, seeking ED care for an assault-related injury and a proportionately sampled group of non–assault-injured youth enrolled from September 2009 through December 2011. Measurements Firearm violence (victimization/perpetration) and validated questionnaire items. Results A total of 599 youths were enrolled, and presence/absence of future firearm violence during follow-up could be ascertained in 483 (52.2% were positive). The sample was randomly split into training (75%) and post–score-construction validation (25%) sets. Using elastic-net penalized logistic regression, 118 baseline predictors were jointly analyzed; the most predictive variables fell predominantly into 4 domains: violence victimization, community exposure, peer influences, and fighting. By selection of 1 item from each domain, the 10-point SaFETy (Serious fighting, Friend weapon carrying, community Environment, and firearm Threats) score was derived. SaFETy was associated with firearm violence in the validation set (odds ratio [OR], 1.47 [95% CI, 1.23 to 1.79]); this association remained (OR, 1.44 [CI, 1.20 to 1.76]) after adjustment for reason for ED visit. In 5 risk strata observed in the training data, firearm violence rates in the validation set were 18.2% (2 of 11), 40.0% (18 of 45), 55.8% (24 of 43), 81.3% (13 of 16), and 100.0% (6 of 6), respectively. Limitations The study was conducted in a single ED and involved substance-using youths. SaFETy was not externally validated. Conclusion The SaFETy score is a 4-item score based on clinically feasible questionnaire items and is associated with firearm violence. Although broader validation is required, SaFETy shows potential to guide resource allocation for prevention of firearm violence. Primary Funding Source National Institute on Drug Abuse R01024646. PMID:28395357

  7. Moral identity as moral ideal self: links to adolescent outcomes.

    PubMed

    Hardy, Sam A; Walker, Lawrence J; Olsen, Joseph A; Woodbury, Ryan D; Hickman, Jacob R

    2014-01-01

    The purposes of this study were to conceptualize moral identity as moral ideal self, to develop a measure of this construct, to test for age and gender differences, to examine links between moral ideal self and adolescent outcomes, and to assess purpose and social responsibility as mediators of the relations between moral ideal self and outcomes. Data came from a local school sample (Data Set 1: N = 510 adolescents; 10-18 years of age) and a national online sample (Data Set 2: N = 383 adolescents; 15-18 years of age) of adolescents and their parents. All outcome measures were parent-report (Data Set 1: altruism, moral personality, aggression, and cheating; Data Set 2: environmentalism, school engagement, internalizing, and externalizing), whereas other variables were adolescent-report. The 20-item Moral Ideal Self Scale showed good reliability, factor structure, and validity. Structural equation models demonstrated that, even after accounting for moral identity internalization, in Data Set 1 moral ideal self positively predicted altruism and moral personality and negatively predicted aggression, whereas in Data Set 2 moral ideal self positively predicted environmentalism and negatively predicted internalizing and externalizing symptoms. Further, purpose and social responsibility mediated most relations between moral ideal self and the outcomes in Data Set 2. Moral ideal self was unrelated to age but differentially predicted some outcomes across age. Girls had higher levels of moral ideal self than boys, although moral identity did not differentially predict outcomes between genders. Thus, moral ideal self is a salient element of moral identity and may play a role in morally relevant adolescent outcomes. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  8. Reaction time as an indicator of insufficient effort: Development and validation of an embedded performance validity parameter.

    PubMed

    Stevens, Andreas; Bahlo, Simone; Licha, Christina; Liske, Benjamin; Vossler-Thies, Elisabeth

    2016-11-30

    Subnormal performance in attention tasks may result from various sources including lack of effort. In this report, the derivation and validation of a performance validity parameter for reaction time is described, using a set of malingering-indices ("Slick-criteria"), and 3 independent samples of participants (total n =893). The Slick-criteria yield an estimate of the probability of malingering based on the presence of an external incentive, evidence from neuropsychological testing, from self-report and clinical data. In study (1) a validity parameter is derived using reaction time data of a sample, composed of inpatients with recent severe brain lesions not involved in litigation and of litigants with and without brain lesion. In study (2) the validity parameter is tested in an independent sample of litigants. In study (3) the parameter is applied to an independent sample comprising cooperative and non-cooperative testees. Logistic regression analysis led to a derived validity parameter based on median reaction time and standard deviation. It performed satisfactorily in studies (2) and (3) (study 2 sensitivity=0.94, specificity=1.00; study 3 sensitivity=0.79, specificity=0.87). The findings suggest that median reaction time and standard deviation may be used as indicators of negative response bias. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  9. Proxies and Other External Raters: Methodological Considerations

    PubMed Central

    Snow, A Lynn; Cook, Karon F; Lin, Pay-Shin; Morgan, Robert O; Magaziner, Jay

    2005-01-01

    Objective The purpose of this paper is to introduce researchers to the measurement and subsequent analysis considerations involved when using externally rated data. We will define and describe two categories of externally rated data, recommend methodological approaches for analyzing and interpreting data in these two categories, and explore factors affecting agreement between self-rated and externally rated reports. We conclude with a discussion of needs for future research. Data Sources/Study Setting Data sources for this paper are previous published studies and reviews comparing self-rated with externally rated data. Study Design/Data Collection/Extraction Methods This is a psychometric conceptual paper. Principal Findings We define two types of externally rated data: proxy data and other-rated data. Proxy data refer to those collected from someone who speaks for a patient who cannot, will not, or is unavailable to speak for him or herself, whereas we use the term other-rater data to refer to situations in which the researcher collects ratings from a person other than the patient to gain multiple perspectives on the assessed construct. These two types of data differ in the way the measurement model is defined, the definition of the gold standard against which the measurements are validated, the analysis strategies appropriately used, and how the analyses are interpreted. There are many factors affecting the discrepancies between self- and external ratings, including characteristics of the patient, the proxy, and of the rated construct. Several psychological theories can be helpful in predicting such discrepancies. Conclusions Externally rated data have an important place in health services research, but use of such data requires careful consideration of the nature of the data and how it will be analyzed and interpreted. PMID:16179002

  10. Validation of cross-cultural child mental health and psychosocial research instruments: adapting the Depression Self-Rating Scale and Child PTSD Symptom Scale in Nepal

    PubMed Central

    2011-01-01

    Background The lack of culturally adapted and validated instruments for child mental health and psychosocial support in low and middle-income countries is a barrier to assessing prevalence of mental health problems, evaluating interventions, and determining program cost-effectiveness. Alternative procedures are needed to validate instruments in these settings. Methods Six criteria are proposed to evaluate cross-cultural validity of child mental health instruments: (i) purpose of instrument, (ii) construct measured, (iii) contents of construct, (iv) local idioms employed, (v) structure of response sets, and (vi) comparison with other measurable phenomena. These criteria are applied to transcultural translation and alternative validation for the Depression Self-Rating Scale (DSRS) and Child PTSD Symptom Scale (CPSS) in Nepal, which recently suffered a decade of war including conscription of child soldiers and widespread displacement of youth. Transcultural translation was conducted with Nepali mental health professionals and six focus groups with children (n = 64) aged 11-15 years old. Because of the lack of child mental health professionals in Nepal, a psychosocial counselor performed an alternative validation procedure using psychosocial functioning as a criterion for intervention. The validation sample was 162 children (11-14 years old). The Kiddie-Schedule for Affective Disorders and Schizophrenia (K-SADS) and Global Assessment of Psychosocial Disability (GAPD) were used to derive indication for treatment as the external criterion. Results The instruments displayed moderate to good psychometric properties: DSRS (area under the curve (AUC) = 0.82, sensitivity = 0.71, specificity = 0.81, cutoff score ≥ 14); CPSS (AUC = 0.77, sensitivity = 0.68, specificity = 0.73, cutoff score ≥ 20). The DSRS items with significant discriminant validity were "having energy to complete daily activities" (DSRS.7), "feeling that life is not worth living" (DSRS.10), and "feeling lonely" (DSRS.15). The CPSS items with significant discriminant validity were nightmares (CPSS.2), flashbacks (CPSS.3), traumatic amnesia (CPSS.8), feelings of a foreshortened future (CPSS.12), and easily irritated at small matters (CPSS.14). Conclusions Transcultural translation and alternative validation feasibly can be performed in low clinical resource settings through task-shifting the validation process to trained mental health paraprofessionals using structured interviews. This process is helpful to evaluate cost-effectiveness of psychosocial interventions. PMID:21816045

  11. Insightful practice: a reliable measure for medical revalidation

    PubMed Central

    Guthrie, Bruce; Sullivan, Frank M; Mercer, Stewart W; Russell, Andrew; Bruce, David A

    2012-01-01

    Background Medical revalidation decisions need to be reliable if they are to reassure on the quality and safety of professional practice. This study tested an innovative method in which general practitioners (GPs) were assessed on their reflection and response to a set of externally specified feedback. Setting and participants 60 GPs and 12 GP appraisers in the Tayside region of Scotland, UK. Methods A feedback dataset was specified as (1) GP-specific data collected by GPs themselves (patient and colleague opinion; open book self-evaluated knowledge test; complaints) and (2) Externally collected practice-level data provided to GPs (clinical quality and prescribing safety). GPs' perceptions of whether the feedback covered UK General Medical Council specified attributes of a ‘good doctor’ were examined using a mapping exercise. GPs' professionalism was examined in terms of appraiser assessment of GPs' level of insightful practice, defined as: engagement with, insight into and appropriate action on feedback data. The reliability of assessment of insightful practice and subsequent recommendations on GPs' revalidation by face-to-face and anonymous assessors were investigated using Generalisability G-theory. Main outcome measures Coverage of General Medical Council attributes by specified feedback and reliability of assessor recommendations on doctors' suitability for revalidation. Results Face-to-face assessment proved unreliable. Anonymous global assessment by three appraisers of insightful practice was highly reliable (G=0.85), as were revalidation decisions using four anonymous assessors (G=0.83). Conclusions Unlike face-to-face appraisal, anonymous assessment of insightful practice offers a valid and reliable method to decide GP revalidation. Further validity studies are needed. PMID:22653078

  12. Analysis of internal and external validity criteria for a computerized visual search task: A pilot study.

    PubMed

    Richard's, María M; Introzzi, Isabel; Zamora, Eliana; Vernucci, Santiago

    2017-01-01

    Inhibition is one of the main executive functions, because of its fundamental role in cognitive and social development. Given the importance of reliable and computerized measurements to assessment inhibitory performance, this research intends to analyze the internal and external criteria of validity of a computerized conjunction search task, to evaluate the role of perceptual inhibition. A sample of 41 children (21 females and 20 males), aged between 6 and 11 years old (M = 8.49, SD = 1.47), intentionally selected from a private management school of Mar del Plata (Argentina), middle socio-economic level were assessed. The Conjunction Search Task from the TAC Battery, Coding and Symbol Search tasks from Wechsler Intelligence Scale for Children were used. Overall, results allow us to confirm that the perceptual inhibition task form TAC presents solid rates of internal and external validity that make a valid measurement instrument of this process.

  13. [Clinical and empirical findings with the OPD-CA].

    PubMed

    Winter, Sibylle; Jelen, Anna; Pressel, Christine; Lenz, Klaus; Lehmkuhl, Ulrike

    2011-01-01

    60 clinical patients (5-17 years) were diagnosed with an interview-manual of OPD-CA (Winter, 2004). For clinical validity a comparison of patients with internal (N=17) and external disorders (N=19) was shown. References for clinical validity resulted from the comparison of the groups, especially for the axes "conflict" and "prerequisites for treatment". Patients with internal disorders showed the conflict desire for care versus autarchy significantly more often than patients with external disorders. On the other hand patients with external disorders displayed the conflict submission versus control significantly more often. Significant differences were also found for the axis "prerequisites for treatment". Patients with internal disorders had better "prerequisites for treatment" in the domains experience of illness and the prerequisites for therapy. For the axes "interpersonal relation", "structure" and "prerequisites for treatment" satisfactory data for validity and reliability were found. The clinical validity points to the usefulness of OPD-CA-manual for psychodynamic diagnostics in childhood and adolescence.

  14. Signatures of subacute potentially catastrophic illness in the intensive care unit: model development and validation

    PubMed Central

    Moss, Travis J.; Lake, Douglas E.; Forrest Calland, J; Enfield, Kyle B; Delos, John B.; Fairchild, Karen D.; Randall Moorman, J.

    2016-01-01

    Objective Patients in intensive care units are susceptible to subacute, potentially catastrophic illnesses such as respiratory failure, sepsis, and hemorrhage that present as severe derangements of vital signs. More subtle physiologic signatures may be present before clinical deterioration, when treatment might be more effective. We performed multivariate statistical analyses of bedside physiologic monitoring data to identify such early, subclinical signatures of incipient life-threatening illness. Design We report a study of model development and validation of a retrospective observational cohort using resampling (TRIPOD Type 1b internal validation), and a study of model validation using separate data (Type 2b internal/external validation). Setting University of Virginia Health System (Charlottesville), a tertiary-care, academic medical center. Patients Critically ill patients consecutively admitted between January 2009 and June 2015 to either the neonatal, surgical/trauma/burn, or medical intensive care units with available physiologic monitoring data. Interventions None. Measurements and Main Results We analyzed 146 patient-years of vital sign and electrocardiography waveform time series from the bedside monitors of 9,232 ICU admissions. Calculations from 30-minute windows of the physiologic monitoring data were made every 15 minutes. Clinicians identified 1,206 episodes of respiratory failure leading to urgent, unplanned intubation, sepsis, or hemorrhage leading to multi-unit transfusions from systematic, individual chart reviews. Multivariate models to predict events up to 24 hours prior had internally-validated C-statistics of 0.61 to 0.88. In adults, physiologic signatures of respiratory failure and hemorrhage were distinct from each other but externally consistent across ICUs. Sepsis, on the other hand, demonstrated less distinct and inconsistent signatures. Physiologic signatures of all neonatal illnesses were similar. Conclusions Subacute, potentially catastrophic illnesses in 3 diverse ICU populations have physiologic signatures that are detectable in the hours preceding clinical detection and intervention. Detection of such signatures can draw attention to patients at highest risk, potentially enabling earlier intervention and better outcomes. PMID:27452809

  15. Psychometric properties of the Norwegian version of the Safety Attitudes Questionnaire (SAQ), Generic version (Short Form 2006).

    PubMed

    Deilkås, Ellen T; Hofoss, Dag

    2008-09-22

    How to protect patients from harm is a question of universal interest. Measuring and improving safety culture in care giving units is an important strategy for promoting a safe environment for patients. The Safety Attitudes Questionnaire (SAQ) is the only instrument that measures safety culture in a way which correlates with patient outcome. We have translated the SAQ to Norwegian and validated the translated version. The psychometric properties of the translated questionnaire are presented in this article. The questionnaire was translated with the back translation technique and tested in 47 clinical units in a Norwegian university hospital. SAQ's (the Generic version (Short Form 2006) the version with the two sets of questions on perceptions of management: on unit management and on hospital management) were distributed to 1911 frontline staff. 762 were distributed during unit meetings and 1149 through the postal system. Cronbach alphas, item-to-own correlations, and test-retest correlations were calculated, and response distribution analysis and confirmatory factor analysis were performed, as well as early validity tests. 1306 staff members completed and returned the questionnaire: a response rate of 68%. Questionnaire acceptability was good. The reliability measures were acceptable. The factor structure of the responses was tested by confirmatory factor analysis. 36 items were ascribed to seven underlying factors: Teamwork Climate, Safety Climate, Stress Recognition, Perceptions of Hospital Management, Perceptions of Unit Management, Working conditions, and Job satisfaction. Goodness-of-Fit Indices showed reasonable, but not indisputable, model fit. External validity indicators - recognizability of results, correlations with "trigger tool"-identified adverse events, with patient satisfaction with hospitalization, patient reports of possible maltreatment, and patient evaluation of organization of hospital work - provided preliminary validation. Based on the data from Akershus University Hospital, we conclude that the Norwegian translation of the SAQ showed satisfactory internal psychometric properties. With data from one hospital only, we cannot draw strong conclusions on its external validity. Further validation studies linking the SAQ-scores to patient outcome data should be performed.

  16. The Main Concept Analysis in Cantonese Aphasic Oral Discourse: External Validation and Monitoring Chronic Aphasia

    ERIC Educational Resources Information Center

    Kong, Anthony Pak-Hin

    2011-01-01

    Purpose: The 1st aim of this study was to further establish the external validity of the main concept (MC) analysis by examining its relationship with the Cantonese Linguistic Communication Measure (CLCM; Kong, 2006; Kong & Law, 2004)--an established quantitative system for narrative production--and the Cantonese version of the Western Aphasia…

  17. External Validity of Childhood Disintegrative Disorder in Comparison with Autistic Disorder

    ERIC Educational Resources Information Center

    Kurita, Hiroshi; Osada, Hirokazu; Miyake, Yuko

    2004-01-01

    To examine the external validity of DSM-IV childhood disintegrative disorder (CDD), 10 children (M = 8.2 yrs) with CDD and 152 gender- and age-matched children with autistic disorder (AD) were compared on 24 variables. The CDD children had a significantly higher rate of epilepsy, significantly less uneven intellectual functioning, and a tendency…

  18. A Clinical Tool for the Prediction of Venous Thromboembolism in Pediatric Trauma Patients.

    PubMed

    Connelly, Christopher R; Laird, Amy; Barton, Jeffrey S; Fischer, Peter E; Krishnaswami, Sanjay; Schreiber, Martin A; Zonies, David H; Watters, Jennifer M

    2016-01-01

    Although rare, the incidence of venous thromboembolism (VTE) in pediatric trauma patients is increasing, and the consequences of VTE in children are significant. Studies have demonstrated increasing VTE risk in older pediatric trauma patients and improved VTE rates with institutional interventions. While national evidence-based guidelines for VTE screening and prevention are in place for adults, none exist for pediatric patients, to our knowledge. To develop a risk prediction calculator for VTE in children admitted to the hospital after traumatic injury to assist efforts in developing screening and prophylaxis guidelines for this population. Retrospective review of 536,423 pediatric patients 0 to 17 years old using the National Trauma Data Bank from January 1, 2007, to December 31, 2012. Five mixed-effects logistic regression models of varying complexity were fit on a training data set. Model validity was determined by comparison of the area under the receiver operating characteristic curve (AUROC) for the training and validation data sets from the original model fit. A clinical tool to predict the risk of VTE based on individual patient clinical characteristics was developed from the optimal model. Diagnosis of VTE during hospital admission. Venous thromboembolism was diagnosed in 1141 of 536,423 children (overall rate, 0.2%). The AUROCs in the training data set were high (range, 0.873-0.946) for each model, with minimal AUROC attenuation in the validation data set. A prediction tool was developed from a model that achieved a balance of high performance (AUROCs, 0.945 and 0.932 in the training and validation data sets, respectively; P = .048) and parsimony. Points are assigned to each variable considered (Glasgow Coma Scale score, age, sex, intensive care unit admission, intubation, transfusion of blood products, central venous catheter placement, presence of pelvic or lower extremity fractures, and major surgery), and the points total is converted to a VTE risk score. The predicted risk of VTE ranged from 0.0% to 14.4%. We developed a simple clinical tool to predict the risk of developing VTE in pediatric trauma patients. It is based on a model created using a large national database and was internally validated. The clinical tool requires external validation but provides an initial step toward the development of the specific VTE protocols for pediatric trauma patients.

  19. Predicting Retention Times of Naturally Occurring Phenolic Compounds in Reversed-Phase Liquid Chromatography: A Quantitative Structure-Retention Relationship (QSRR) Approach

    PubMed Central

    Akbar, Jamshed; Iqbal, Shahid; Batool, Fozia; Karim, Abdul; Chan, Kim Wei

    2012-01-01

    Quantitative structure-retention relationships (QSRRs) have successfully been developed for naturally occurring phenolic compounds in a reversed-phase liquid chromatographic (RPLC) system. A total of 1519 descriptors were calculated from the optimized structures of the molecules using MOPAC2009 and DRAGON softwares. The data set of 39 molecules was divided into training and external validation sets. For feature selection and mapping we used step-wise multiple linear regression (SMLR), unsupervised forward selection followed by step-wise multiple linear regression (UFS-SMLR) and artificial neural networks (ANN). Stable and robust models with significant predictive abilities in terms of validation statistics were obtained with negation of any chance correlation. ANN models were found better than remaining two approaches. HNar, IDM, Mp, GATS2v, DISP and 3D-MoRSE (signals 22, 28 and 32) descriptors based on van der Waals volume, electronegativity, mass and polarizability, at atomic level, were found to have significant effects on the retention times. The possible implications of these descriptors in RPLC have been discussed. All the models are proven to be quite able to predict the retention times of phenolic compounds and have shown remarkable validation, robustness, stability and predictive performance. PMID:23203132

  20. Quantitative prediction of solvation free energy in octanol of organic compounds.

    PubMed

    Delgado, Eduardo J; Jaña, Gonzalo A

    2009-03-01

    The free energy of solvation, DeltaGS0, in octanol of organic compounds is quantitatively predicted from the molecular structure. The model, involving only three molecular descriptors, is obtained by multiple linear regression analysis from a data set of 147 compounds containing diverse organic functions, namely, halogenated and non-halogenated alkanes, alkenes, alkynes, aromatics, alcohols, aldehydes, ketones, amines, ethers and esters; covering a DeltaGS0 range from about -50 to 0 kJ.mol(-1). The model predicts the free energy of solvation with a squared correlation coefficient of 0.93 and a standard deviation, 2.4 kJ.mol(-1), just marginally larger than the generally accepted value of experimental uncertainty. The involved molecular descriptors have definite physical meaning corresponding to the different intermolecular interactions occurring in the bulk liquid phase. The model is validated with an external set of 36 compounds not included in the training set.

  1. Quantitative Prediction of Solvation Free Energy in Octanol of Organic Compounds

    PubMed Central

    Delgado, Eduardo J.; Jaña, Gonzalo A.

    2009-01-01

    The free energy of solvation, ΔGS0, in octanol of organic compunds is quantitatively predicted from the molecular structure. The model, involving only three molecular descriptors, is obtained by multiple linear regression analysis from a data set of 147 compounds containing diverse organic functions, namely, halogenated and non-halogenated alkanes, alkenes, alkynes, aromatics, alcohols, aldehydes, ketones, amines, ethers and esters; covering a ΔGS0 range from about −50 to 0 kJ·mol−1. The model predicts the free energy of solvation with a squared correlation coefficient of 0.93 and a standard deviation, 2.4 kJ·mol−1, just marginally larger than the generally accepted value of experimental uncertainty. The involved molecular descriptors have definite physical meaning corresponding to the different intermolecular interactions occurring in the bulk liquid phase. The model is validated with an external set of 36 compounds not included in the training set. PMID:19399236

  2. In-Silico Screening of Ligand Based Pharmacophore, Database Mining and Molecular Docking on 2, 5-Diaminopyrimidines Azapurines as Potential Inhibitors of Glycogen Synthase Kinase-3β.

    PubMed

    Mishra, Pooja; Kesar, Seema; Paliwal, Sarvesh K; Chauhan, Monika; Madan, Kirtika

    2018-05-29

    Glycogen synthase kinase-3β plays a significant role in the regulation of various pathological pathways relating to central nervous system (CNS). Dysregulation of Glycogen synthase kinase 3 (GSK-3) activity gives a rise to numerous neuroinflammation and neurodegenerative related disorders that affect the whole central nervous system. By the sequential application of in-silico tools, efforts have been attempted to design the novel GSK-3β inhibitors. Owing to the potential role of GSK-3β in nervous disorders, we have attempted to develop the quantitative four featured pharmacophore model comprising two hydrogen bond acceptors (HBA), one ring aromatic (RA), and one hydrophobe (HY), which were further affirmed by cost-function analysis, rm2 matrices, internal and external test set validation and Güner-Henry (GH) scoring analysis. Validated pharmacophoric model was used for virtual screening and out of 345 compounds, two potential virtual hits were finalized that were on the basis of fit value, estimated activity and Lipinski's violation. The chosen compounds were subjected to dock within the active site of GSK-3β Result: Four essential features, i.e., two hydrogen bond acceptors(HBA), one ring aromatic(RA), and one hydrophobe(HY), were subjected to build the pharmacophoric model and showed good correlation coefficient, RMSD and cost difference values of 0.91, 0.94 and 42.9 respectively and further model was validated employing cost-function analysis, rm2-matrices, internal and external test set prediction with r2 value of 0.77 and 0.84. Docked conformations showed potential interactions in between the features of the identified hits (NCI 4296, NCI 3034) and the amino acids present in the active site. In line with the overhead discussion, and through our stepwise computational approaches, we have identified novel, structurally diverse glycogen synthase kinase inhibitors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  3. Risk score for first-screening of prevalent undiagnosed chronic kidney disease in Peru: the CRONICAS-CKD risk score.

    PubMed

    Carrillo-Larco, Rodrigo M; Miranda, J Jaime; Gilman, Robert H; Medina-Lezama, Josefina; Chirinos-Pacheco, Julio A; Muñoz-Retamozo, Paola V; Smeeth, Liam; Checkley, William; Bernabe-Ortiz, Antonio

    2017-11-29

    Chronic Kidney Disease (CKD) represents a great burden for the patient and the health system, particularly if diagnosed at late stages. Consequently, tools to identify patients at high risk of having CKD are needed, particularly in limited-resources settings where laboratory facilities are scarce. This study aimed to develop a risk score for prevalent undiagnosed CKD using data from four settings in Peru: a complete risk score including all associated risk factors and another excluding laboratory-based variables. Cross-sectional study. We used two population-based studies: one for developing and internal validation (CRONICAS), and another (PREVENCION) for external validation. Risk factors included clinical- and laboratory-based variables, among others: sex, age, hypertension and obesity; and lipid profile, anemia and glucose metabolism. The outcome was undiagnosed CKD: eGFR < 60 ml/min/1.73m 2 . We tested the performance of the risk scores using the area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, positive/negative predictive values and positive/negative likelihood ratios. Participants in both studies averaged 57.7 years old, and over 50% were females. Age, hypertension and anemia were strongly associated with undiagnosed CKD. In the external validation, at a cut-off point of 2, the complete and laboratory-free risk scores performed similarly well with a ROC area of 76.2% and 76.0%, respectively (P = 0.784). The best assessment parameter of these risk scores was their negative predictive value: 99.1% and 99.0% for the complete and laboratory-free, respectively. The developed risk scores showed a moderate performance as a screening test. People with a score of ≥ 2 points should undergo further testing to rule out CKD. Using the laboratory-free risk score is a practical approach in developing countries where laboratories are not readily available and undiagnosed CKD has significant morbidity and mortality.

  4. CoMFA and CoMSIA 3D-QSAR studies on S(6)-(4-nitrobenzyl)mercaptopurine riboside (NBMPR) analogs as inhibitors of human equilibrative nucleoside transporter 1 (hENT1).

    PubMed

    Gupte, Amol; Buolamwini, John K

    2009-01-15

    3D-QSAR (CoMFA and CoMSIA) studies were performed on human equlibrative nucleoside transporter (hENT1) inhibitors displaying K(i) values ranging from 10,000 to 0.7nM. Both CoMFA and CoMSIA analysis gave reliable models with q2 values >0.50 and r2 values >0.92. The models have been validated for their stability and robustness using group validation and bootstrapping techniques and for their predictive abilities using an external test set of nine compounds. The high predictive r2 values of the test set (0.72 for CoMFA model and 0.74 for CoMSIA model) reveals that the models can prove to be a useful tool for activity prediction of newly designed nucleoside transporter inhibitors. The CoMFA and CoMSIA contour maps identify features important for exhibiting good binding affinities at the transporter, and can thus serve as a useful guide for the design of potential equilibrative nucleoside transporter inhibitors.

  5. Development of a QSAR Model for Thyroperoxidase Inhbition ...

    EPA Pesticide Factsheets

    hyroid hormones (THs) are involved in multiple biological processes and are critical modulators of fetal development. Even moderate changes in maternal or fetal TH levels can produce irreversible neurological deficits in children, such as lower IQ. The enzyme thyroperoxidase (TPO) plays a key role in the synthesis of THs, and inhibition of TPO by xenobiotics results in decreased TH synthesis. Recently, a high-throughput screening assay for TPO inhibition (AUR-TPO) was developed and used to test the ToxCast Phase I and II chemicals. In the present study, we used the results from AUR-TPO to develop a Quantitative Structure-Activity Relationship (QSAR) model for TPO inhibition. The training set consisted of 898 discrete organic chemicals: 134 inhibitors and 764 non-inhibitors. A five times two-fold cross-validation of the model was performed, yielding a balanced accuracy of 78.7%. More recently, an additional ~800 chemicals were tested in the AUR-TPO assay. These data were used for a blinded external validation of the QSAR model, demonstrating a balanced accuracy of 85.7%. Overall, the cross- and external validation indicate a robust model with high predictive performance. Next, we used the QSAR model to predict 72,526 REACH pre-registered substances. The model could predict 49.5% (35,925) of the substances in its applicability domain and of these, 8,863 (24.7%) were predicted to be TPO inhibitors. Predictions from this screening can be used in a tiered approach to

  6. Deep Learning to Classify Radiology Free-Text Reports.

    PubMed

    Chen, Matthew C; Ball, Robyn L; Yang, Lingyao; Moradzadeh, Nathaniel; Chapman, Brian E; Larson, David B; Langlotz, Curtis P; Amrhein, Timothy J; Lungren, Matthew P

    2018-03-01

    Purpose To evaluate the performance of a deep learning convolutional neural network (CNN) model compared with a traditional natural language processing (NLP) model in extracting pulmonary embolism (PE) findings from thoracic computed tomography (CT) reports from two institutions. Materials and Methods Contrast material-enhanced CT examinations of the chest performed between January 1, 1998, and January 1, 2016, were selected. Annotations by two human radiologists were made for three categories: the presence, chronicity, and location of PE. Classification of performance of a CNN model with an unsupervised learning algorithm for obtaining vector representations of words was compared with the open-source application PeFinder. Sensitivity, specificity, accuracy, and F1 scores for both the CNN model and PeFinder in the internal and external validation sets were determined. Results The CNN model demonstrated an accuracy of 99% and an area under the curve value of 0.97. For internal validation report data, the CNN model had a statistically significant larger F1 score (0.938) than did PeFinder (0.867) when classifying findings as either PE positive or PE negative, but no significant difference in sensitivity, specificity, or accuracy was found. For external validation report data, no statistical difference between the performance of the CNN model and PeFinder was found. Conclusion A deep learning CNN model can classify radiology free-text reports with accuracy equivalent to or beyond that of an existing traditional NLP model. © RSNA, 2017 Online supplemental material is available for this article.

  7. External validation of type 2 diabetes computer simulation models: definitions, approaches, implications and room for improvement-a protocol for a systematic review.

    PubMed

    Ogurtsova, Katherine; Heise, Thomas L; Linnenkamp, Ute; Dintsios, Charalabos-Markos; Lhachimi, Stefan K; Icks, Andrea

    2017-12-29

    Type 2 diabetes mellitus (T2DM), a highly prevalent chronic disease, puts a large burden on individual health and health care systems. Computer simulation models, used to evaluate the clinical and economic effectiveness of various interventions to handle T2DM, have become a well-established tool in diabetes research. Despite the broad consensus about the general importance of validation, especially external validation, as a crucial instrument of assessing and controlling for the quality of these models, there are no systematic reviews comparing such validation of diabetes models. As a result, the main objectives of this systematic review are to identify and appraise the different approaches used for the external validation of existing models covering the development and progression of T2DM. We will perform adapted searches by applying respective search strategies to identify suitable studies from 14 electronic databases. Retrieved study records will be included or excluded based on predefined eligibility criteria as defined in this protocol. Among others, a publication filter will exclude studies published before 1995. We will run abstract and full text screenings and then extract data from all selected studies by filling in a predefined data extraction spreadsheet. We will undertake a descriptive, narrative synthesis of findings to address the study objectives. We will pay special attention to aspects of quality of these models in regard to the external validation based upon ISPOR and ADA recommendations as well as Mount Hood Challenge reports. All critical stages within the screening, data extraction and synthesis processes will be conducted by at least two authors. This protocol adheres to PRISMA and PRISMA-P standards. The proposed systematic review will provide a broad overview of the current practice in the external validation of models with respect to T2DM incidence and progression in humans built on simulation techniques. PROSPERO CRD42017069983 .

  8. Validation of Patient-Reported Outcomes Measurement Information System Short Forms for Use in Childhood-Onset Systemic Lupus Erythematosus.

    PubMed

    Jones, Jordan T; Carle, Adam C; Wootton, Janet; Liberio, Brianna; Lee, Jiha; Schanberg, Laura E; Ying, Jun; Morgan DeWitt, Esi; Brunner, Hermine I

    2017-01-01

    To validate the pediatric Patient-Reported Outcomes Measurement Information System short forms (PROMIS-SFs) in childhood-onset systemic lupus erythematosus (SLE) in a clinical setting. At 3 study visits, childhood-onset SLE patients completed the PROMIS-SFs (anger, anxiety, depressive symptoms, fatigue, physical function-mobility, physical function-upper extremity, pain interference, and peer relationships) using the PROMIS assessment center, and health-related quality of life (HRQoL) legacy measures (Pediatric Quality of Life Inventory, Childhood Health Assessment Questionnaire, Simple Measure of Impact of Lupus Erythematosus in Youngsters [SMILEY], and visual analog scales [VAS] of pain and well-being). Physicians rated childhood-onset SLE activity on a VAS and completed the Systemic Lupus Erythematosus Disease Activity Index 2000. Using a global rating scale of change (GRC) between study visits, physicians rated change of childhood-onset SLE activity (GRC-MD1: better/same/worse) and change of patient overall health (GRC-MD2: better/same/worse). Questionnaire scores were compared in support of validity and responsiveness to change (external standards: GRC-MD1, GRC-MD2). In this population-based cohort (n = 100) with a mean age of 15.8 years (range 10-20 years), the PROMIS-SFs were completed in less than 5 minutes in a clinical setting. The PROMIS-SF scores correlated at least moderately (Pearson's r ≥ 0.5) with those of legacy HRQoL measures, except for the SMILEY. Measures of childhood-onset SLE activity did not correlate with the PROMIS-SFs. Responsiveness to change of the PROMIS-SFs was supported by path, mixed-model, and correlation analyses. To assess HRQoL in childhood-onset SLE, the PROMIS-SFs demonstrated feasibility, internal consistency, construct validity, and responsiveness to change in a clinical setting. © 2016, American College of Rheumatology.

  9. Assessing the accuracy and stability of variable selection ...

    EPA Pesticide Factsheets

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used, or stepwise procedures are employed which iteratively add/remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating dataset consists of the good/poor condition of n=1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p=212) of landscape features from the StreamCat dataset. Two types of RF models are compared: a full variable set model with all 212 predictors, and a reduced variable set model selected using a backwards elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors, and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substanti

  10. Design and internal validation of an obstetric early warning score: secondary analysis of the Intensive Care National Audit and Research Centre Case Mix Programme database.

    PubMed

    Carle, C; Alexander, P; Columb, M; Johal, J

    2013-04-01

    We designed and internally validated an aggregate weighted early warning scoring system specific to the obstetric population that has the potential for use in the ward environment. Direct obstetric admissions from the Intensive Care National Audit and Research Centre's Case Mix Programme Database were randomly allocated to model development (n = 2240) or validation (n = 2200) sets. Physiological variables collected during the first 24 h of critical care admission were analysed. Logistic regression analysis for mortality in the model development set was initially used to create a statistically based early warning score. The statistical score was then modified to create a clinically acceptable early warning score. Important features of this clinical obstetric early warning score are that the variables are weighted according to their statistical importance, a surrogate for the FI O2 /Pa O2 relationship is included, conscious level is assessed using a simplified alert/not alert variable, and the score, trigger thresholds and response are consistent with the new non-obstetric National Early Warning Score system. The statistical and clinical early warning scores were internally validated using the validation set. The area under the receiver operating characteristic curve was 0.995 (95% CI 0.992-0.998) for the statistical score and 0.957 (95% CI 0.923-0.991) for the clinical score. Pre-existing empirically designed early warning scores were also validated in the same way for comparison. The area under the receiver operating characteristic curve was 0.955 (95% CI 0.922-0.988) for Swanton et al.'s Modified Early Obstetric Warning System, 0.937 (95% CI 0.884-0.991) for the obstetric early warning score suggested in the 2003-2005 Report on Confidential Enquiries into Maternal Deaths in the UK, and 0.973 (95% CI 0.957-0.989) for the non-obstetric National Early Warning Score. This highlights that the new clinical obstetric early warning score has an excellent ability to discriminate survivors from non-survivors in this critical care data set. Further work is needed to validate our new clinical early warning score externally in the obstetric ward environment. Anaesthesia © 2013 The Association of Anaesthetists of Great Britain and Ireland.

  11. Initial Evidence for the Reliability and Validity of the Student Risk Screening Scale for Internalizing and Externalizing Behaviors at the Elementary Level

    ERIC Educational Resources Information Center

    Lane, Kathleen Lynne; Oakes, Wendy P.; Harris, Pamela J.; Menzies, Holly Mariah; Cox, Meredith; Lambert, Warren

    2012-01-01

    We report findings of an exploratory validation study of a revised instrument: the Student Risk Screening Scale-Internalizing and Externalizing (SRSS-IE). The SRSS-IE was modified to include seven additional items reflecting characteristics of internalizing behaviors, with proposed items generated from the current literature base, review of…

  12. Internal and External Validity of Scores on the Balanced Inventory of Desirable Responding and the Paulhus Deception Scales

    ERIC Educational Resources Information Center

    Lanyon, Richard I.; Carle, Adam C.

    2007-01-01

    The internal and external validity of scores on the two-scale Balanced Inventory of Desirable Responding (BIDR) and its recent revision, the Paulhus Deception Scales (PDS), developed to measure two facets of social desirability, were studied with three groups of forensic clients and two groups of college undergraduates (total N = 519). The two…

  13. Implementing the undergraduate mini-CEX: a tailored approach at Southampton University.

    PubMed

    Hill, Faith; Kendall, Kathleen; Galbraith, Kevin; Crossley, Jim

    2009-04-01

    The mini-clinical evaluation exercise (mini-CEX) is widely used in the UK to assess clinical competence, but there is little evidence regarding its implementation in the undergraduate setting. This study aimed to estimate the validity and reliability of the undergraduate mini-CEX and discuss the challenges involved in its implementation. A total of 3499 mini-CEX forms were completed. Validity was assessed by estimating associations between mini-CEX score and a number of external variables, examining the internal structure of the instrument, checking competency domain response rates and profiles against expectations, and by qualitative evaluation of stakeholder interviews. Reliability was evaluated by overall reliability coefficient (R), estimation of the standard error of measurement (SEM), and from stakeholders' perceptions. Variance component analysis examined the contribution of relevant factors to students' scores. Validity was threatened by various confounding variables, including: examiner status; case complexity; attachment specialty; patient gender, and case focus. Factor analysis suggested that competency domains reflect a single latent variable. Maximum reliability can be achieved by aggregating scores over 15 encounters (R = 0.73; 95% confidence interval [CI] +/- 0.28 based on a 6-point assessment scale). Examiner stringency contributed 29% of score variation and student attachment aptitude 13%. Stakeholder interviews revealed staff development needs but the majority perceived the mini-CEX as more reliable and valid than the previous long case. The mini-CEX has good overall utility for assessing aspects of the clinical encounter in an undergraduate setting. Strengths include fidelity, wide sampling, perceived validity, and formative observation and feedback. Reliability is limited by variable examiner stringency, and validity by confounding variables, but these should be viewed within the context of overall assessment strategies.

  14. Translation and validation of the German version of the Bournemouth Questionnaire for Neck Pain.

    PubMed

    Soklic, Marina; Peterson, Cynthia; Humphreys, B Kim

    2012-01-25

    Clinical outcome measures are important tools to monitor patient improvement during treatment as well as to document changes for research purposes. The short-form Bournemouth questionnaire for neck pain patients (BQN) was developed from the biopsychosocial model and measures pain, disability, cognitive and affective domains. It has been shown to be a valid and reliable outcome measure in English, French and Dutch and more sensitive to change compared to other questionnaires. The purpose of this study was to translate and validate a German version of the Bournemouth questionnaire for neck pain patients. German translation and back translation into English of the BQN was done independently by four persons and overseen by an expert committee. Face validity of the German BQN was tested on 30 neck pain patients in a single chiropractic practice. Test-retest reliability was evaluated on 31 medical students and chiropractors before and after a lecture. The German BQN was then assessed on 102 first time neck pain patients at two chiropractic practices for internal consistency, external construct validity, external longitudinal construct validity and sensitivity to change compared to the German versions of the Neck Disability Index (NDI) and the Neck Pain and Disability Scale (NPAD). Face validity testing lead to minor changes to the German BQN. The Intraclass Correlation Coefficient for the test-retest reliability was 0.99. The internal consistency was strong for all 7 items of the BQN with Cronbach α's of .79 and .80 for the pre and post-treatment total scores. External construct validity and external longitudinal construct validity using Pearson's correlation coefficient showed statistically significant correlations for all 7 scales of the BQN with the other questionnaires. The German BQN showed greater responsiveness compared to the other questionnaires for all scales. The German BQN is a valid and reliable outcome measure that has been successfully translated and culturally adapted. It is shorter, easier to use, and more responsive to change than the NDI and NPAD.

  15. Precision assessment of model-based RSA for a total knee prosthesis in a biplanar set-up.

    PubMed

    Trozzi, C; Kaptein, B L; Garling, E H; Shelyakova, T; Russo, A; Bragonzoni, L; Martelli, S

    2008-10-01

    Model-based Roentgen Stereophotogrammetric Analysis (RSA) was recently developed for the measurement of prosthesis micromotion. Its main advantage is that markers do not need to be attached to the implants as traditional marker-based RSA requires. Model-based RSA has only been tested in uniplanar radiographic set-ups. A biplanar set-up would theoretically facilitate the pose estimation algorithm, since radiographic projections would show more different shape features of the implants than in uniplanar images. We tested the precision of model-based RSA and compared it with that of the traditional marker-based method in a biplanar set-up. Micromotions of both tibial and femoral components were measured with both the techniques from double examinations of patients participating in a clinical study. The results showed that in the biplanar set-up model-based RSA presents a homogeneous distribution of precision for all the translation directions, but an inhomogeneous error for rotations, especially internal-external rotation presented higher errors than rotations about the transverse and sagittal axes. Model-based RSA was less precise than the marker-based method, although the differences were not significant for the translations and rotations of the tibial component, with the exception of the internal-external rotations. For both prosthesis components the precisions of model-based RSA were below 0.2 mm for all the translations, and below 0.3 degrees for rotations about transverse and sagittal axes. These values are still acceptable for clinical studies aimed at evaluating total knee prosthesis micromotion. In a biplanar set-up model-based RSA is a valid alternative to traditional marker-based RSA where marking of the prosthesis is an enormous disadvantage.

  16. A Severe Sepsis Mortality Prediction Model and Score for Use with Administrative Data

    PubMed Central

    Ford, Dee W.; Goodwin, Andrew J.; Simpson, Annie N.; Johnson, Emily; Nadig, Nandita; Simpson, Kit N.

    2016-01-01

    Objective Administrative data is used for research, quality improvement, and health policy in severe sepsis. However, there is not a sepsis-specific tool applicable to administrative data with which to adjust for illness severity. Our objective was to develop, internally validate, and externally validate a severe sepsis mortality prediction model and associated mortality prediction score. Design Retrospective cohort study using 2012 administrative data from five US states. Three cohorts of patients with severe sepsis were created: 1) ICD-9-CM codes for severe sepsis/septic shock, 2) ‘Martin’ approach, and 3) ‘Angus’ approach. The model was developed and internally validated in ICD-9-CM cohort and externally validated in other cohorts. Integer point values for each predictor variable were generated to create a sepsis severity score. Setting Acute care, non-federal hospitals in NY, MD, FL, MI, and WA Subjects Patients in one of three severe sepsis cohorts: 1) explicitly coded (n=108,448), 2) Martin cohort (n=139,094), and 3) Angus cohort (n=523,637) Interventions None Measurements and Main Results Maximum likelihood estimation logistic regression to develop a predictive model for in-hospital mortality. Model calibration and discrimination assessed via Hosmer-Lemeshow goodness-of-fit (GOF) and C-statistics respectively. Primary cohort subset into risk deciles and observed versus predicted mortality plotted. GOF demonstrated p>0.05 for each cohort demonstrating sound calibration. C-statistic ranged from low of 0.709 (sepsis severity score) to high of 0.838 (Angus cohort) suggesting good to excellent model discrimination. Comparison of observed versus expected mortality was robust although accuracy decreased in highest risk decile. Conclusions Our sepsis severity model and score is a tool that provides reliable risk adjustment for administrative data. PMID:26496452

  17. A nomogram for predicting complications in patients with solid tumours and seemingly stable febrile neutropenia

    PubMed Central

    Fonseca, Paula Jiménez; Carmona-Bayonas, Alberto; García, Ignacio Matos; Marcos, Rosana; Castañón, Eduardo; Antonio, Maite; Font, Carme; Biosca, Mercè; Blasco, Ana; Lozano, Rebeca; Ramchandani, Avinash; Beato, Carmen; de Castro, Eva Martínez; Espinosa, Javier; Martínez-García, Jerónimo; Ghanem, Ismael; Cubero, Jorge Hernando; Manrique, Isabel Aragón; Navalón, Francisco García; Sevillano, Elena; Manzano, Aránzazu; Virizuela, Juan; Garrido, Marcelo; Mondéjar, Rebeca; Arcusa, María Ángeles; Bonilla, Yaiza; Pérez, Quionia; Gallardo, Elena; del Carmen Soriano, Maria; Cardona, Mercè; Lasheras, Fernando Sánchez; Cruz, Juan Jesús; Ayala, Francisco

    2016-01-01

    Background: We sought to develop and externally validate a nomogram and web-based calculator to individually predict the development of serious complications in seemingly stable adult patients with solid tumours and episodes of febrile neutropenia (FN). Patients and methods: The data from the FINITE study (n=1133) and University of Salamanca Hospital (USH) FN registry (n=296) were used to develop and validate this tool. The main eligibility criterion was the presence of apparent clinical stability, defined as events without acute organ dysfunction, abnormal vital signs, or major infections. Discriminatory ability was measured as the concordance index and stratification into risk groups. Results: The rate of infection-related complications in the FINITE and USH series was 13.4% and 18.6%, respectively. The nomogram used the following covariates: Eastern Cooperative Group (ECOG) Performance Status ⩾2, chronic obstructive pulmonary disease, chronic cardiovascular disease, mucositis of grade ⩾2 (National Cancer Institute Common Toxicity Criteria), monocytes <200/mm3, and stress-induced hyperglycaemia. The nomogram predictions appeared to be well calibrated in both data sets (Hosmer–Lemeshow test, P>0.1). The concordance index was 0.855 and 0.831 in each series. Risk group stratification revealed a significant distinction in the proportion of complications. With a ⩾116-point cutoff, the nomogram yielded the following prognostic indices in the USH registry validation series: 66% sensitivity, 83% specificity, 3.88 positive likelihood ratio, 48% positive predictive value, and 91% negative predictive value. Conclusions: We have developed and externally validated a nomogram and web calculator to predict serious complications that can potentially impact decision-making in patients with seemingly stable FN. PMID:27187687

  18. Prognostic nomogram and score to predict overall survival in locally advanced untreated pancreatic cancer (PROLAP)

    PubMed Central

    Vernerey, Dewi; Huguet, Florence; Vienot, Angélique; Goldstein, David; Paget-Bailly, Sophie; Van Laethem, Jean-Luc; Glimelius, Bengt; Artru, Pascal; Moore, Malcolm J; André, Thierry; Mineur, Laurent; Chibaudel, Benoist; Benetkiewicz, Magdalena; Louvet, Christophe; Hammel, Pascal; Bonnetain, Franck

    2016-01-01

    Background: The management of locally advanced pancreatic cancer (LAPC) patients remains controversial. Better discrimination for overall survival (OS) at diagnosis is needed. We address this issue by developing and validating a prognostic nomogram and a score for OS in LAPC (PROLAP). Methods: Analyses were derived from 442 LAPC patients enrolled in the LAP07 trial. The prognostic ability of 30 baseline parameters was evaluated using univariate and multivariate Cox regression analyses. Performance assessment and internal validation of the final model were done with Harrell's C-index, calibration plot and bootstrap sample procedures. On the basis of the final model, a prognostic nomogram and a score were developed, and externally validated in 106 consecutive LAPC patients treated in Besançon Hospital, France. Results: Age, pain, tumour size, albumin and CA 19-9 were independent prognostic factors for OS. The final model had good calibration, acceptable discrimination (C-index=0.60) and robust internal validity. The PROLAP score has the potential to delineate three different prognosis groups with median OS of 15.4, 11.7 and 8.5 months (log-rank P<0.0001). The score ability to discriminate OS was externally confirmed in 63 (59%) patients with complete clinical data derived from a data set of 106 consecutive LAPC patients; median OS of 18.3, 14.1 and 7.6 months for the three groups (log-rank P<0.0001). Conclusions: The PROLAP nomogram and score can accurately predict OS before initiation of induction chemotherapy in LAPC-untreated patients. They may help to optimise clinical trials design and might offer the opportunity to define risk-adapted strategies for LAPC management in the future. PMID:27404456

  19. Carbon nuclear magnetic resonance spectroscopic fingerprinting of commercial gasoline: pattern-recognition analyses for screening quality control purposes.

    PubMed

    Flumignan, Danilo Luiz; Boralle, Nivaldo; Oliveira, José Eduardo de

    2010-06-30

    In this work, the combination of carbon nuclear magnetic resonance ((13)C NMR) fingerprinting with pattern-recognition analyses provides an original and alternative approach to screening commercial gasoline quality. Soft Independent Modelling of Class Analogy (SIMCA) was performed on spectroscopic fingerprints to classify representative commercial gasoline samples, which were selected by Hierarchical Cluster Analyses (HCA) over several months in retails services of gas stations, into previously quality-defined classes. Following optimized (13)C NMR-SIMCA algorithm, sensitivity values were obtained in the training set (99.0%), with leave-one-out cross-validation, and external prediction set (92.0%). Governmental laboratories could employ this method as a rapid screening analysis to discourage adulteration practices. Copyright 2010 Elsevier B.V. All rights reserved.

  20. 3D Simulation of External Flooding Events for the RISMC Pathway

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

    Prescott, Steven; Mandelli, Diego; Sampath, Ramprasad

    2015-09-01

    Incorporating 3D simulations as part of the Risk-Informed Safety Margins Characterization (RISMIC) Toolkit allows analysts to obtain a more complete picture of complex system behavior for events including external plant hazards. External events such as flooding have become more important recently – however these can be analyzed with existing and validated simulated physics toolkits. In this report, we describe these approaches specific to flooding-based analysis using an approach called Smoothed Particle Hydrodynamics. The theory, validation, and example applications of the 3D flooding simulation are described. Integrating these 3D simulation methods into computational risk analysis provides a spatial/visual aspect to themore » design, improves the realism of results, and can prove visual understanding to validate the analysis of flooding.« less

  1. German Translation and Validation of the Cognitive Style Questionnaire Short Form (CSQ-SF-D)

    PubMed Central

    Huys, Quentin J. M.; Renz, Daniel; Petzschner, Frederike; Berwian, Isabel; Stoppel, Christian; Haker, Helene

    2016-01-01

    Background The Cognitive Style Questionnaire is a valuable tool for the assessment of hopeless cognitive styles in depression research, with predictive power in longitudinal studies. However, it is very burdensome to administer. Even the short form is still long, and neither this nor the original version exist in validated German translations. Methods The questionnaire was translated from English to German, back-translated and commented on by clinicians. The reliability, factor structure and external validity of an online form of the questionnaire were examined on 214 participants. External validity was measured on a subset of 90 subjects. Results The resulting CSQ-SF-D had good to excellent reliability, both across items and subscales, and similar external validity to the original English version. The internality subscale appeared less robust than other subscales. A detailed analysis of individual item performance suggests that stable results could be achieved with a very short form (CSQ-VSF-D) including only 27 of the 72 items. Conclusions The CSQ-SF-D is a validated and freely distributed translation of the CSQ-SF into German. This should make efficient assessment of cognitive style in German samples more accessible to researchers. PMID:26934499

  2. German Translation and Validation of the Cognitive Style Questionnaire Short Form (CSQ-SF-D).

    PubMed

    Huys, Quentin J M; Renz, Daniel; Petzschner, Frederike; Berwian, Isabel; Stoppel, Christian; Haker, Helene

    2016-01-01

    The Cognitive Style Questionnaire is a valuable tool for the assessment of hopeless cognitive styles in depression research, with predictive power in longitudinal studies. However, it is very burdensome to administer. Even the short form is still long, and neither this nor the original version exist in validated German translations. The questionnaire was translated from English to German, back-translated and commented on by clinicians. The reliability, factor structure and external validity of an online form of the questionnaire were examined on 214 participants. External validity was measured on a subset of 90 subjects. The resulting CSQ-SF-D had good to excellent reliability, both across items and subscales, and similar external validity to the original English version. The internality subscale appeared less robust than other subscales. A detailed analysis of individual item performance suggests that stable results could be achieved with a very short form (CSQ-VSF-D) including only 27 of the 72 items. The CSQ-SF-D is a validated and freely distributed translation of the CSQ-SF into German. This should make efficient assessment of cognitive style in German samples more accessible to researchers.

  3. Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries.

    PubMed

    Jochems, Arthur; Deist, Timo M; El Naqa, Issam; Kessler, Marc; Mayo, Chuck; Reeves, Jackson; Jolly, Shruti; Matuszak, Martha; Ten Haken, Randall; van Soest, Johan; Oberije, Cary; Faivre-Finn, Corinne; Price, Gareth; de Ruysscher, Dirk; Lambin, Philippe; Dekker, Andre

    2017-10-01

    Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with chemoradiation or radiation therapy are of limited quality. In this work, we developed a predictive model of survival at 2 years. The model is based on a large volume of historical patient data and serves as a proof of concept to demonstrate the distributed learning approach. Clinical data from 698 lung cancer patients, treated with curative intent with chemoradiation or radiation therapy alone, were collected and stored at 2 different cancer institutes (559 patients at Maastro clinic (Netherlands) and 139 at Michigan university [United States]). The model was further validated on 196 patients originating from The Christie (United Kingdon). A Bayesian network model was adapted for distributed learning (the animation can be viewed at https://www.youtube.com/watch?v=ZDJFOxpwqEA). Two-year posttreatment survival was chosen as the endpoint. The Maastro clinic cohort data are publicly available at https://www.cancerdata.org/publication/developing-and-validating-survival-prediction-model-nsclc-patients-through-distributed, and the developed models can be found at www.predictcancer.org. Variables included in the final model were T and N category, age, performance status, and total tumor dose. The model has an area under the curve (AUC) of 0.66 on the external validation set and an AUC of 0.62 on a 5-fold cross validation. A model based on the T and N category performed with an AUC of 0.47 on the validation set, significantly worse than our model (P<.001). Learning the model in a centralized or distributed fashion yields a minor difference on the probabilities of the conditional probability tables (0.6%); the discriminative performance of the models on the validation set is similar (P=.26). Distributed learning from federated databases allows learning of predictive models on data originating from multiple institutions while avoiding many of the data-sharing barriers. We believe that distributed learning is the future of sharing data in health care. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  4. Patterns of Cognitive Strengths and Weaknesses: Identification Rates, Agreement, and Validity for Learning Disabilities Identification

    PubMed Central

    Miciak, Jeremy; Fletcher, Jack M.; Stuebing, Karla; Vaughn, Sharon; Tolar, Tammy D.

    2014-01-01

    Purpose Few empirical investigations have evaluated LD identification methods based on a pattern of cognitive strengths and weaknesses (PSW). This study investigated the reliability and validity of two proposed PSW methods: the concordance/discordance method (C/DM) and cross battery assessment (XBA) method. Methods Cognitive assessment data for 139 adolescents demonstrating inadequate response to intervention was utilized to empirically classify participants as meeting or not meeting PSW LD identification criteria using the two approaches, permitting an analysis of: (1) LD identification rates; (2) agreement between methods; and (3) external validity. Results LD identification rates varied between the two methods depending upon the cut point for low achievement, with low agreement for LD identification decisions. Comparisons of groups that met and did not meet LD identification criteria on external academic variables were largely null, raising questions of external validity. Conclusions This study found low agreement and little evidence of validity for LD identification decisions based on PSW methods. An alternative may be to use multiple measures of academic achievement to guide intervention. PMID:24274155

  5. Setting limits on Effective Field Theories: the case of Dark Matter

    NASA Astrophysics Data System (ADS)

    Pobbe, Federico; Wulzer, Andrea; Zanetti, Marco

    2017-08-01

    The usage of Effective Field Theories (EFT) for LHC new physics searches is receiving increasing attention. It is thus important to clarify all the aspects related with the applicability of the EFT formalism in the LHC environment, where the large available energy can produce reactions that overcome the maximal range of validity, i.e. the cutoff, of the theory. We show that this does not forbid to set rigorous limits on the EFT parameter space through a modified version of the ordinary binned likelihood hypothesis test, which we design and validate. Our limit-setting strategy can be carried on in its full-fledged form by the LHC experimental collaborations, or performed externally to the collaborations, through the Simplified Likelihood approach, by relying on certain approximations. We apply it to the recent CMS mono-jet analysis and derive limits on a Dark Matter (DM) EFT model. DM is selected as a case study because the limited reach on the DM production EFT Wilson coefficient and the structure of the theory suggests that the cutoff might be dangerously low, well within the LHC reach. However our strategy can also be applied, if needed, to EFT's parametrising the indirect effects of heavy new physics in the Electroweak and Higgs sectors.

  6. Evaluation of physical activity interventions in youth via the Reach, Efficacy/Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework: A systematic review of randomised and non-randomised trials.

    PubMed

    McGoey, Tara; Root, Zach; Bruner, Mark W; Law, Barbi

    2015-07-01

    An identified limitation of existing reviews of physical activity interventions in school-aged youth is the lack of reporting on issues related to the translatability of the research into health promotion practice. This review used the Reach, Efficacy/Effectiveness, Adoption, Implementation and Maintenance framework to determine the extent to which intervention studies promoting physical activity in youth report on factors that inform generalizability across settings and populations. A systematic search for controlled interventions conducted within the last ten years identified 50 studies that met the selection criteria. Based on Reach, Efficacy/Effectiveness, Adoption, Implementation and Maintenance criteria, most of these studies focused on statistically significant findings and internal validity rather than on issues of external validity. Due to this lack of information, it is difficult to determine whether or not reportedly successful interventions are feasible and sustainable in an uncontrolled, real-world setting. Areas requiring further research include costs associated with recruitment and implementation, adoption rate, and representativeness of participants and settings. This review adds data to support recommendations that interventions promoting physical activity in youth should include assessment of adoption and implementation issues. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures

    NASA Astrophysics Data System (ADS)

    Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany

    2016-07-01

    Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.

  8. 6 DOF articulated-arm robot and mobile platform: Dynamic modelling as Multibody System and its validation via Experimental Modal Analysis.

    NASA Astrophysics Data System (ADS)

    Toledo Fuentes, A.; Kipfmueller, M.; José Prieto, M. A.

    2017-10-01

    Mobile manipulators are becoming a key instrument to increase the flexibility in industrial processes. Some of their requirements include handling of objects with different weights and sizes and their “fast” transportation, without jeopardizing production workers and machines. The compensation of forces affecting the system dynamic is therefore needed to avoid unwanted oscillations and tilting by sudden accelerations and decelerations. One general solution may be the implementation of external positioning elements to active stabilize the system. To accomplish the approach, the dynamic behavior of a robotic arm and a mobile platform was investigated to develop the stabilization mechanism using multibody simulations. The methodology used was divided into two phases for each subsystem: their natural frequencies and modal shapes were obtained using experimental modal analyses. Then, based on these experimental results, multibody simulation models (MBS) were set up and its dynamical parameters adjusted. Their modal shapes together with their obtained natural frequencies allowed a quantitative and qualitative analysis. In summary, the MBS models were successfully validated with the real subsystems, with a maximal percentage error of 15%. These models will serve as the basis for future steps in the design of the external actuators and its control strategy using a co-simulation tool.

  9. Multiple QSAR models, pharmacophore pattern and molecular docking analysis for anticancer activity of α, β-unsaturated carbonyl-based compounds, oxime and oxime ether analogues

    NASA Astrophysics Data System (ADS)

    Masand, Vijay H.; El-Sayed, Nahed N. E.; Bambole, Mukesh U.; Quazi, Syed A.

    2018-04-01

    Multiple discrete quantitative structure-activity relationships (QSARs) models were constructed for the anticancer activity of α, β-unsaturated carbonyl-based compounds, oxime and oxime ether analogues with a variety of substituents like sbnd Br, sbnd OH, -OMe, etc. at different positions. A big pool of descriptors was considered for QSAR model building. Genetic algorithm (GA), available in QSARINS-Chem, was executed to choose optimum number and set of descriptors to create the multi-linear regression equations for a dataset of sixty-nine compounds. The newly developed five parametric models were subjected to exhaustive internal and external validation along with Y-scrambling using QSARINS-Chem, according to the OECD principles for QSAR model validation. The models were built using easily interpretable descriptors and accepted after confirming statistically robustness with high external predictive ability. The five parametric models were found to have R2 = 0.80 to 0.86, R2ex = 0.75 to 0.84, and CCCex = 0.85 to 0.90. The models indicate that frequency of nitrogen and oxygen atoms separated by five bonds from each other and internal electronic environment of the molecule have correlation with the anticancer activity.

  10. Technical Note: A respiratory monitoring and processing system based on computer vision: prototype and proof of principle

    PubMed Central

    Atallah, Vincent; Escarmant, Patrick; Vinh‐Hung, Vincent

    2016-01-01

    Monitoring and controlling respiratory motion is a challenge for the accuracy and safety of therapeutic irradiation of thoracic tumors. Various commercial systems based on the monitoring of internal or external surrogates have been developed but remain costly. In this article we describe and validate Madibreast, an in‐house‐made respiratory monitoring and processing device based on optical tracking of external markers. We designed an optical apparatus to ensure real‐time submillimetric image resolution at 4 m. Using OpenCv libraries, we optically tracked high‐contrast markers set on patients' breasts. Validation of spatial and time accuracy was performed on a mechanical phantom and on human breast. Madibreast was able to track motion of markers up to a 5 cm/s speed, at a frame rate of 30 fps, with submillimetric accuracy on mechanical phantom and human breasts. Latency was below 100 ms. Concomitant monitoring of three different locations on the breast showed discrepancies in axial motion up to 4 mm for deep‐breathing patterns. This low‐cost, computer‐vision system for real‐time motion monitoring of the irradiation of breast cancer patients showed submillimetric accuracy and acceptable latency. It allowed the authors to highlight differences in surface motion that may be correlated to tumor motion. PACS number(s): 87.55.km PMID:27685116

  11. Technical Note: A respiratory monitoring and processing system based on computer vision: prototype and proof of principle.

    PubMed

    Leduc, Nicolas; Atallah, Vincent; Escarmant, Patrick; Vinh-Hung, Vincent

    2016-09-08

    Monitoring and controlling respiratory motion is a challenge for the accuracy and safety of therapeutic irradiation of thoracic tumors. Various commercial systems based on the monitoring of internal or external surrogates have been developed but remain costly. In this article we describe and validate Madibreast, an in-house-made respiratory monitoring and processing device based on optical tracking of external markers. We designed an optical apparatus to ensure real-time submillimetric image resolution at 4 m. Using OpenCv libraries, we optically tracked high-contrast markers set on patients' breasts. Validation of spatial and time accuracy was performed on a mechanical phantom and on human breast. Madibreast was able to track motion of markers up to a 5 cm/s speed, at a frame rate of 30 fps, with submillimetric accuracy on mechanical phantom and human breasts. Latency was below 100 ms. Concomitant monitoring of three different locations on the breast showed discrepancies in axial motion up to 4 mm for deep-breathing patterns. This low-cost, computer-vision system for real-time motion monitoring of the irradiation of breast cancer patients showed submillimetric accuracy and acceptable latency. It allowed the authors to highlight differences in surface motion that may be correlated to tumor motion.v. © 2016 The Authors.

  12. Multiple receptor conformation docking and dock pose clustering as tool for CoMFA and CoMSIA analysis - a case study on HIV-1 protease inhibitors.

    PubMed

    Sivan, Sree Kanth; Manga, Vijjulatha

    2012-02-01

    Multiple receptors conformation docking (MRCD) and clustering of dock poses allows seamless incorporation of receptor binding conformation of the molecules on wide range of ligands with varied structural scaffold. The accuracy of the approach was tested on a set of 120 cyclic urea molecules having HIV-1 protease inhibitory activity using 12 high resolution X-ray crystal structures and one NMR resolved conformation of HIV-1 protease extracted from protein data bank. A cross validation was performed on 25 non-cyclic urea HIV-1 protease inhibitor having varied structures. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were generated using 60 molecules in the training set by applying leave one out cross validation method, r (loo) (2) values of 0.598 and 0.674 for CoMFA and CoMSIA respectively and non-cross validated regression coefficient r(2) values of 0.983 and 0.985 were obtained for CoMFA and CoMSIA respectively. The predictive ability of these models was determined using a test set of 60 cyclic urea molecules that gave predictive correlation (r (pred) (2) ) of 0.684 and 0.64 respectively for CoMFA and CoMSIA indicating good internal predictive ability. Based on this information 25 non-cyclic urea molecules were taken as a test set to check the external predictive ability of these models. This gave remarkable out come with r (pred) (2) of 0.61 and 0.53 for CoMFA and CoMSIA respectively. The results invariably show that this method is useful for performing 3D QSAR analysis on molecules having different structural motifs.

  13. Development of Short-Form Versions of the Screener and Opioid Assessment for Patients with Pain-Revised (SOAPP-R): A Proof-of-Principle Study.

    PubMed

    Finkelman, Matthew D; Smits, Niels; Kulich, Ronald J; Zacharoff, Kevin L; Magnuson, Britta E; Chang, Hong; Dong, Jinghui; Butler, Stephen F

    2017-07-01

    The Screener and Opioid Assessment for Patients with Pain-Revised (SOAPP-R) is a 24-item questionnaire designed to assess risk of aberrant medication-related behaviors in chronic pain patients. The introduction of short forms of the SOAPP-R may save time and increase utilization by practitioners. To develop and evaluate candidate SOAPP-R short forms. Retrospective study. Pain centers. Four hundred and twenty-eight patients with chronic noncancer pain. Subjects had previously been administered the full-length version of the SOAPP-R and been categorized as positive or negative for aberrant medication-related behaviors via the Aberrant Drug Behavior Index (ADBI). Short forms of the SOAPP-R were developed using lasso logistic regression. Sensitivity, specificity, and area under the curve (AUC) of all forms were calculated with respect to the ADBI using the complete data set, training-test analysis, and 10-fold cross-validation. The coefficient alpha of each form was also calculated. An external set of 12 pain practitioners reviewed the forms for content. In the complete data set analysis, a form of 12 items exhibited sensitivity, specificity, and AUC greater than or equal to those of the full-length SOAPP-R (which were 0.74, 0.67, and 0.76, respectively). The short form had a coefficient alpha of 0.76. In the training-test analysis and 10-fold cross-validation, it exhibited an AUC value within 0.01 of that of the full-length SOAPP-R. The majority of external practitioners reported a preference for this short form. The 12-item version of the SOAPP-R has potential as a short risk screener and should be tested prospectively. © 2016 American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  14. Initial Evidence for the Reliability and Validity of the Student Risk Screening Scale for Internalizing and Externalizing Behaviors at the Middle School Level

    ERIC Educational Resources Information Center

    Lane, Kathleen Lynne; Oakes, Wendy Peia; Carter, Erik W.; Lambert, Warren E.; Jenkins, Abbie B.

    2013-01-01

    We reported findings of an exploratory validation study of a revised universal screening instrument: the Student Risk Screening Scale--Internalizing and Externalizing (SRSS-IE) for use with middle school students. Tested initially for use with elementary-age students, the SRSS-IE was adapted to include seven additional items reflecting…

  15. A Validation of the Student Risk Screening Scale for Internalizing and Externalizing Behaviors: Patterns in Rural and Urban Elementary Schools

    ERIC Educational Resources Information Center

    Lane, Kathleen Lynne; Menzies, Holly M.; Oakes, Wendy P.; Lambert, Warren; Cox, Meredith; Hankins, Katy

    2012-01-01

    We report findings of two studies, one conducted in a rural school district (N = 982) and a second conducted in an urban district (N = 1,079), offering additional evidence of the reliability and validity of a revised instrument, the Student Risk Screening Scale-Internalizing and Externalizing (SRSS-IE), to accurately detect internalizing and…

  16. Validity, Responsibility, and Aporia

    ERIC Educational Resources Information Center

    Koro-Ljungberg, Mirka

    2010-01-01

    In this article, the author problematizes external, objectified, oversimplified, and mechanical approaches to validity in qualitative research, which endorse simplistic and reductionist views of knowledge and data. Instead of promoting one generalizable definition or operational criteria for validity, the author's "deconstructive validity work"…

  17. Geographic Information Systems to Assess External Validity in Randomized Trials.

    PubMed

    Savoca, Margaret R; Ludwig, David A; Jones, Stedman T; Jason Clodfelter, K; Sloop, Joseph B; Bollhalter, Linda Y; Bertoni, Alain G

    2017-08-01

    To support claims that RCTs can reduce health disparities (i.e., are translational), it is imperative that methodologies exist to evaluate the tenability of external validity in RCTs when probabilistic sampling of participants is not employed. Typically, attempts at establishing post hoc external validity are limited to a few comparisons across convenience variables, which must be available in both sample and population. A Type 2 diabetes RCT was used as an example of a method that uses a geographic information system to assess external validity in the absence of a priori probabilistic community-wide diabetes risk sampling strategy. A geographic information system, 2009-2013 county death certificate records, and 2013-2014 electronic medical records were used to identify community-wide diabetes prevalence. Color-coded diabetes density maps provided visual representation of these densities. Chi-square goodness of fit statistic/analysis tested the degree to which distribution of RCT participants varied across density classes compared to what would be expected, given simple random sampling of the county population. Analyses were conducted in 2016. Diabetes prevalence areas as represented by death certificate and electronic medical records were distributed similarly. The simple random sample model was not a good fit for death certificate record (chi-square, 17.63; p=0.0001) and electronic medical record data (chi-square, 28.92; p<0.0001). Generally, RCT participants were oversampled in high-diabetes density areas. Location is a highly reliable "principal variable" associated with health disparities. It serves as a directly measurable proxy for high-risk underserved communities, thus offering an effective and practical approach for examining external validity of RCTs. Copyright © 2017 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

  18. Predicting survival of men with recurrent prostate cancer after radical prostatectomy.

    PubMed

    Dell'Oglio, Paolo; Suardi, Nazareno; Boorjian, Stephen A; Fossati, Nicola; Gandaglia, Giorgio; Tian, Zhe; Moschini, Marco; Capitanio, Umberto; Karakiewicz, Pierre I; Montorsi, Francesco; Karnes, R Jeffrey; Briganti, Alberto

    2016-02-01

    To develop and externally validate a novel nomogram aimed at predicting cancer-specific mortality (CSM) after biochemical recurrence (BCR) among prostate cancer (PCa) patients treated with radical prostatectomy (RP) with or without adjuvant external beam radiotherapy (aRT) and/or hormonal therapy (aHT). The development cohort included 689 consecutive PCa patients treated with RP between 1987 and 2011 with subsequent BCR, defined as two subsequent prostate-specific antigen values >0.2 ng/ml. Multivariable competing-risks regression analyses tested the predictors of CSM after BCR for the purpose of 5-year CSM nomogram development. Validation (2000 bootstrap resamples) was internally tested. External validation was performed into a population of 6734 PCa patients with BCR after treatment with RP at the Mayo Clinic from 1987 to 2011. The predictive accuracy (PA) was quantified using the receiver operating characteristic-derived area under the curve and the calibration plot method. The 5-year CSM-free survival rate was 83.6% (confidence interval [CI]: 79.6-87.2). In multivariable analyses, pathologic stage T3b or more (hazard ratio [HR]: 7.42; p = 0.008), pathologic Gleason score 8-10 (HR: 2.19; p = 0.003), lymph node invasion (HR: 3.57; p = 0.001), time to BCR (HR: 0.99; p = 0.03) and age at BCR (HR: 1.04; p = 0.04), were each significantly associated with the risk of CSM after BCR. The bootstrap-corrected PA was 87.4% (bootstrap 95% CI: 82.0-91.7%). External validation of our nomogram showed a good PA at 83.2%. We developed and externally validated the first nomogram predicting 5-year CSM applicable to contemporary patients with BCR after RP with or without adjuvant treatment. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities*

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

    Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov; Cross, Kevin P.

    Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describemore » the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ► We characterize a new in silico model to predict mutagenicity of drug impurities. ► The model predicts Salmonella mutagenicity and will be useful for safety assessment. ► We examine toxicity fingerprints and toxicophores of this Ames assay model. ► We compare these attributes to those found in drug impurities known to FDA/CDER. ► We validate the model and find it has a desired predictive performance.« less

  20. An observational examination of the literature in diagnostic anatomic pathology.

    PubMed

    Foucar, Elliott; Wick, Mark R

    2005-05-01

    Original research published in the medical literature confronts the reader with three very basic and closely linked questions--are the authors' conclusions true in the contextual setting in which the work was performed (internally valid); if so, are the conclusions also applicable in other practice settings (externally valid); and, if the conclusions of the study are bona fide, do they represent an important contribution to medical practice or are they true-but-insignificant? Most publications attempt to convince readers that the researchers' conclusions are both internally valid and important, and occasionally papers also directly address external validity. Developing standardized methods to facilitate the prospective determination of research importance would be useful to both journals and their readers, but has proven difficult. In contrast, the evidence-based medicine (EBM) movement has had more success with understanding and codifying factors thought to promote research validity. Of the many variables that can influence research validity, research design is the one that has received the most attention. The present paper reviews the contributions of EBM to understanding research validity, looking for areas where EBM's body of knowledge is applicable to the anatomic pathology (AP) literature. As part of this project, the authors performed a pilot observational analysis of a representative sample of the current pertinent literature on diagnostic tissue pathology. The results of that review showed that most of the latter publications employ one of the four categories of "observational" research design that have been delineated by the EBM movement, and that the most common of these observational designs is a "cross-sectional" comparison. Pathologists do not presently use the "experimental" research designs so admired by advocates of EBM. Slightly > 50% of AP observational studies employed statistical evaluations to support their final conclusions. Comparison of the current AP literature with a selected group of papers published in 1977 shows a discernible change over that period that has affected not just technological procedures, but also research design and use of statistics. Although we feel that advocates of EBM deserve credit for bringing attention to the close link between research design and research validity, much of the EBM effort has centered on refining "experimental" methodology, and the complexities of observational research have often been treated in an inappropriately dismissive manner. For advocates of EBM, an observational study is what you are relegated to as a second choice when you are unable to do an experimental study. The latter viewpoint may be true for evaluating new chemotherapeutic agents, but is unacceptable to pathologists, whose research advances are currently completely dependent on well-conducted observational research. Rather than succumb to randomization envy and accept EBM's assertion that observational research is second best, the challenge to AP is to develop and adhere to standards for observational research that will allow our patients to benefit from the full potential of this time tested approach to developing valid insights into disease.

  1. Translational research: bridging the gap between long-term weight loss maintenance research and practice.

    PubMed

    Akers, Jeremy D; Estabrooks, Paul A; Davy, Brenda M

    2010-10-01

    The number of US adults classified as overweight or obese has dramatically increased in the past 25 years, resulting in a significant body of research addressing weight loss and weight loss maintenance. However, little is known about the potential of weight loss maintenance interventions to be translated into actual practice settings. Thus, the purpose of this article is to determine the translation potential of published weight loss maintenance intervention studies by determining the extent to which they report information across the reach, efficacy/effectiveness, adoption, implementation, and maintenance (RE-AIM) framework. A secondary purpose is to provide recommendations for research based on these findings. To identify relevant research articles, a literature search was conducted using four databases; 19 weight loss maintenance intervention studies were identified for inclusion. Each article was evaluated using the RE-AIM Coding Sheet for Publications to determine the extent to which dimensions related to internal and external validity were reported. Approximately half of the articles provided information addressing three RE-AIM dimensions, yet only a quarter provided information addressing adoption and maintenance. Significant gaps were identified in understanding external validity, and metrics that could facilitate the translation of these interventions from research to practice are presented. Based upon this review, it is unknown how effective weight loss maintenance interventions could be in real-world situations, such as clinical or community practice settings. Future studies should be planned to address how weight loss maintenance intervention programs will be adopted and maintained, with special attention to costs for participants and for program implementation. Copyright © 2010 American Dietetic Association. Published by Elsevier Inc. All rights reserved.

  2. Towards personalized therapy for multiple sclerosis: prediction of individual treatment response.

    PubMed

    Kalincik, Tomas; Manouchehrinia, Ali; Sobisek, Lukas; Jokubaitis, Vilija; Spelman, Tim; Horakova, Dana; Havrdova, Eva; Trojano, Maria; Izquierdo, Guillermo; Lugaresi, Alessandra; Girard, Marc; Prat, Alexandre; Duquette, Pierre; Grammond, Pierre; Sola, Patrizia; Hupperts, Raymond; Grand'Maison, Francois; Pucci, Eugenio; Boz, Cavit; Alroughani, Raed; Van Pesch, Vincent; Lechner-Scott, Jeannette; Terzi, Murat; Bergamaschi, Roberto; Iuliano, Gerardo; Granella, Franco; Spitaleri, Daniele; Shaygannejad, Vahid; Oreja-Guevara, Celia; Slee, Mark; Ampapa, Radek; Verheul, Freek; McCombe, Pamela; Olascoaga, Javier; Amato, Maria Pia; Vucic, Steve; Hodgkinson, Suzanne; Ramo-Tello, Cristina; Flechter, Shlomo; Cristiano, Edgardo; Rozsa, Csilla; Moore, Fraser; Luis Sanchez-Menoyo, Jose; Laura Saladino, Maria; Barnett, Michael; Hillert, Jan; Butzkueven, Helmut

    2017-09-01

    Timely initiation of effective therapy is crucial for preventing disability in multiple sclerosis; however, treatment response varies greatly among patients. Comprehensive predictive models of individual treatment response are lacking. Our aims were: (i) to develop predictive algorithms for individual treatment response using demographic, clinical and paraclinical predictors in patients with multiple sclerosis; and (ii) to evaluate accuracy, and internal and external validity of these algorithms. This study evaluated 27 demographic, clinical and paraclinical predictors of individual response to seven disease-modifying therapies in MSBase, a large global cohort study. Treatment response was analysed separately for disability progression, disability regression, relapse frequency, conversion to secondary progressive disease, change in the cumulative disease burden, and the probability of treatment discontinuation. Multivariable survival and generalized linear models were used, together with the principal component analysis to reduce model dimensionality and prevent overparameterization. Accuracy of the individual prediction was tested and its internal validity was evaluated in a separate, non-overlapping cohort. External validity was evaluated in a geographically distinct cohort, the Swedish Multiple Sclerosis Registry. In the training cohort (n = 8513), the most prominent modifiers of treatment response comprised age, disease duration, disease course, previous relapse activity, disability, predominant relapse phenotype and previous therapy. Importantly, the magnitude and direction of the associations varied among therapies and disease outcomes. Higher probability of disability progression during treatment with injectable therapies was predominantly associated with a greater disability at treatment start and the previous therapy. For fingolimod, natalizumab or mitoxantrone, it was mainly associated with lower pretreatment relapse activity. The probability of disability regression was predominantly associated with pre-baseline disability, therapy and relapse activity. Relapse incidence was associated with pretreatment relapse activity, age and relapsing disease course, with the strength of these associations varying among therapies. Accuracy and internal validity (n = 1196) of the resulting predictive models was high (>80%) for relapse incidence during the first year and for disability outcomes, moderate for relapse incidence in Years 2-4 and for the change in the cumulative disease burden, and low for conversion to secondary progressive disease and treatment discontinuation. External validation showed similar results, demonstrating high external validity for disability and relapse outcomes, moderate external validity for cumulative disease burden and low external validity for conversion to secondary progressive disease and treatment discontinuation. We conclude that demographic, clinical and paraclinical information helps predict individual response to disease-modifying therapies at the time of their commencement. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  3. Psychological therapy for inpatients receiving acute mental health care: A systematic review and meta-analysis of controlled trials.

    PubMed

    Paterson, Charlotte; Karatzias, Thanos; Dickson, Adele; Harper, Sean; Dougall, Nadine; Hutton, Paul

    2018-04-16

    The effectiveness of psychological therapies for those receiving acute adult mental health inpatient care remains unclear, partly because of the difficulty in conducting randomized controlled trials (RCTs) in this setting. The aim of this meta-analysis was to synthesize evidence from all controlled trials of psychological therapy carried out with this group, to estimate its effects on a number of important outcomes and examine whether the presence of randomization and rater blinding moderated these estimates. A systematic review and meta-analysis of all controlled trials of psychological therapy delivered in acute inpatient settings was conducted, with a focus on psychotic symptoms, readmissions or emotional distress (anxiety and depression). Studies were identified through ASSIA, EMBASE, CINAHL, Cochrane, MEDLINE, and PsycINFO using a combination of the key terms 'inpatient', 'psychological therapy', and 'acute'. No restriction was placed on diagnosis. The moderating effect of the use of assessor-blind RCT methodology was examined via subgroup and sensitivity analyses. Overall, psychological therapy was associated with small-to-moderate improvements in psychotic symptoms at end of therapy but the effect was smaller and not significant at follow-up. Psychological therapy was also associated with reduced readmissions, depression, and anxiety. The use of single-blind randomized controlled trial methodology was associated with significantly reduced benefits on psychotic symptoms and was also associated with reduced benefits on readmission and depression; however, these reductions were not statistically significant. The provision of psychological therapy to acute psychiatric inpatients is associated with improvements; however, the use of single-blind RCT methodology was associated with reduced therapy-attributable improvements. Whether this is a consequence of increased internal validity or reduced external validity is unclear. Trials with both high internal and external validity are now required to establish what type, format, and intensity of brief psychological therapy is required to achieve sustained benefits. Clinical implications: This review provides the first meta-analytical synthesis of brief psychological therapy delivered in acute psychiatric inpatient settings. This review suggests that brief psychological therapy may be associated with reduced emotional distress and readmissions. The evidence in this review is of limited quality. The type, format, and intensity of brief psychological therapy required to achieve sustained benefits are yet to be established. © 2018 The British Psychological Society.

  4. A comparative evaluation of risk-adjustment models for benchmarking amputation-free survival after lower extremity bypass.

    PubMed

    Simons, Jessica P; Goodney, Philip P; Flahive, Julie; Hoel, Andrew W; Hallett, John W; Kraiss, Larry W; Schanzer, Andres

    2016-04-01

    Providing patients and payers with publicly reported risk-adjusted quality metrics for the purpose of benchmarking physicians and institutions has become a national priority. Several prediction models have been developed to estimate outcomes after lower extremity revascularization for critical limb ischemia, but the optimal model to use in contemporary practice has not been defined. We sought to identify the highest-performing risk-adjustment model for amputation-free survival (AFS) at 1 year after lower extremity bypass (LEB). We used the national Society for Vascular Surgery Vascular Quality Initiative (VQI) database (2003-2012) to assess the performance of three previously validated risk-adjustment models for AFS. The Bypass versus Angioplasty in Severe Ischaemia of the Leg (BASIL), Finland National Vascular (FINNVASC) registry, and the modified Project of Ex-vivo vein graft Engineering via Transfection III (PREVENT III [mPIII]) risk scores were applied to the VQI cohort. A novel model for 1-year AFS was also derived using the VQI data set and externally validated using the PIII data set. The relative discrimination (Harrell c-index) and calibration (Hosmer-May goodness-of-fit test) of each model were compared. Among 7754 patients in the VQI who underwent LEB for critical limb ischemia, the AFS was 74% at 1 year. Each of the previously published models for AFS demonstrated similar discriminative performance: c-indices for BASIL, FINNVASC, mPIII were 0.66, 0.60, and 0.64, respectively. The novel VQI-derived model had improved discriminative ability with a c-index of 0.71 and appropriate generalizability on external validation with a c-index of 0.68. The model was well calibrated in both the VQI and PIII data sets (goodness of fit P = not significant). Currently available prediction models for AFS after LEB perform modestly when applied to national contemporary VQI data. Moreover, the performance of each model was inferior to that of the novel VQI-derived model. Because the importance of risk-adjusted outcome reporting continues to increase, national registries such as VQI should begin using this novel model for benchmarking quality of care. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

  5. Design and Optimization of a Chemometric-Assisted Spectrophotometric Determination of Telmisartan and Hydrochlorothiazide in Pharmaceutical Dosage Form

    PubMed Central

    Lakshmi, KS; Lakshmi, S

    2010-01-01

    Two chemometric methods were developed for the simultaneous determination of telmisartan and hydrochlorothiazide. The chemometric methods applied were principal component regression (PCR) and partial least square (PLS-1). These approaches were successfully applied to quantify the two drugs in the mixture using the information included in the UV absorption spectra of appropriate solutions in the range of 200-350 nm with the intervals Δλ = 1 nm. The calibration of PCR and PLS-1 models was evaluated by internal validation (prediction of compounds in its own designed training set of calibration) and by external validation over laboratory prepared mixtures and pharmaceutical preparations. The PCR and PLS-1 methods require neither any separation step, nor any prior graphical treatment of the overlapping spectra of the two drugs in a mixture. The results of PCR and PLS-1 methods were compared with each other and a good agreement was found. PMID:21331198

  6. Design and optimization of a chemometric-assisted spectrophotometric determination of telmisartan and hydrochlorothiazide in pharmaceutical dosage form.

    PubMed

    Lakshmi, Ks; Lakshmi, S

    2010-01-01

    Two chemometric methods were developed for the simultaneous determination of telmisartan and hydrochlorothiazide. The chemometric methods applied were principal component regression (PCR) and partial least square (PLS-1). These approaches were successfully applied to quantify the two drugs in the mixture using the information included in the UV absorption spectra of appropriate solutions in the range of 200-350 nm with the intervals Δλ = 1 nm. The calibration of PCR and PLS-1 models was evaluated by internal validation (prediction of compounds in its own designed training set of calibration) and by external validation over laboratory prepared mixtures and pharmaceutical preparations. The PCR and PLS-1 methods require neither any separation step, nor any prior graphical treatment of the overlapping spectra of the two drugs in a mixture. The results of PCR and PLS-1 methods were compared with each other and a good agreement was found.

  7. A review of how to conduct a surgical survey using a questionnaire.

    PubMed

    Hing, C B; Smith, T O; Hooper, L; Song, F; Donell, S T

    2011-08-01

    Health surveys using questionnaires facilitate the acquisition of information on the knowledge, behaviour, attitudes, perceptions and clinical history of a selected population. Their internal and external validities are threatened by poor design and low response rates. Numerous studies have investigated survey design and administration but care should be taken when generalising findings in different clinical and cultural settings. The current evidence-base suggests that no single mode of survey administration, such as postal, electronic or telephone, is superior to another. Whilst there is no evidence of an ideal response rate relationship to survey validity, response rates can be enhanced by including monetary incentives, providing a time cue, and repeat contact with non-responders. Unlike other modes of experimental data collection, few guidelines currently exist for survey and questionnaire design and response rate should not be considered a direct measure of a survey's quality. Copyright © 2010 Elsevier B.V. All rights reserved.

  8. Observation of early childhood physical aggression: a psychometric study of the system for coding early physical aggression.

    PubMed

    Mesman, Judi; Alink, Lenneke R A; van Zeijl, Jantien; Stolk, Mirjam N; Bakermans-Kranenburg, Marian J; van Ijzendoorn, Marinus H; Juffer, Femmie; Koot, Hans M

    2008-01-01

    We investigated the reliability and (convergent and discriminant) validity of an observational measure of physical aggression in toddlers and preschoolers, originally developed by Keenan and Shaw [1994]. The observation instrument is based on a developmental definition of aggression. Physical aggression was observed twice in a laboratory setting, the first time when children were 1-3 years old, and again 1 year later. Observed physical aggression was significantly related to concurrent mother-rated physical aggression for 2- to 4-year-olds, but not to maternal ratings of nonaggressive externalizing problems, indicating the measure's discriminant validity. However, we did not find significant 1-year stability of observed physical aggression in any of the age groups, whereas mother-rated physical aggression was significantly stable for all ages. The observational measure shows promise, but may have assessed state rather than trait aggression in our study. Copyright 2008 Wiley-Liss, Inc.

  9. Linear and nonlinear models for predicting fish bioconcentration factors for pesticides.

    PubMed

    Yuan, Jintao; Xie, Chun; Zhang, Ting; Sun, Jinfang; Yuan, Xuejie; Yu, Shuling; Zhang, Yingbiao; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu

    2016-08-01

    This work is devoted to the applications of the multiple linear regression (MLR), multilayer perceptron neural network (MLP NN) and projection pursuit regression (PPR) to quantitative structure-property relationship analysis of bioconcentration factors (BCFs) of pesticides tested on Bluegill (Lepomis macrochirus). Molecular descriptors of a total of 107 pesticides were calculated with the DRAGON Software and selected by inverse enhanced replacement method. Based on the selected DRAGON descriptors, a linear model was built by MLR, nonlinear models were developed using MLP NN and PPR. The robustness of the obtained models was assessed by cross-validation and external validation using test set. Outliers were also examined and deleted to improve predictive power. Comparative results revealed that PPR achieved the most accurate predictions. This study offers useful models and information for BCF prediction, risk assessment, and pesticide formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Classification and virtual screening of androgen receptor antagonists.

    PubMed

    Li, Jiazhong; Gramatica, Paola

    2010-05-24

    Computational tools, such as quantitative structure-activity relationship (QSAR), are highly useful as screening support for prioritization of substances of very high concern (SVHC). From the practical point of view, QSAR models should be effective to pick out more active rather than inactive compounds, expressed as sensitivity in classification works. This research investigates the classification of a big data set of endocrine-disrupting chemicals (EDCs)-androgen receptor (AR) antagonists, mainly aiming to improve the external sensitivity and to screen for potential AR binders. The kNN, lazy IB1, and ADTree methods and the consensus approach were used to build different models, which improve the sensitivity on external chemicals from 57.1% (literature) to 76.4%. Additionally, the models' predictive abilities were further validated on a blind collected data set (sensitivity: 85.7%). Then the proposed classifiers were used: (i) to distinguish a set of AR binders into antagonists and agonists; (ii) to screen a combined estrogen receptor binder database to find out possible chemicals that can bind to both AR and ER; and (iii) to virtually screen our in-house environmental chemical database. The in silico screening results suggest: (i) that some compounds can affect the normal endocrine system through a complex mechanism binding both to ER and AR; (ii) new EDCs, which are nonER binders, but can in silico bind to AR, are recognized; and (iii) about 20% of compounds in a big data set of environmental chemicals are predicted as new AR antagonists. The priority should be given to them to experimentally test the binding activities with AR.

  11. The 7 up 7 down inventory: a 14-item measure of manic and depressive tendencies carved from the General Behavior Inventory.

    PubMed

    Youngstrom, Eric A; Murray, Greg; Johnson, Sheri L; Findling, Robert L

    2013-12-01

    The aim of this study was to develop and validate manic and depressive scales carved from the full-length General Behavior Inventory (GBI). The brief version was designed to be applicable for youths and adults and to improve separation between mania and depression dimensions. Data came from 9 studies (2 youth clinical samples, aggregate N = 738, and 7 nonclinical adult samples, aggregate N = 1,756). Items with high factor loadings on the 2 extracted dimensions of mania and depression were identified from both data sets, and final item selection was based on internal reliability criteria. Confirmatory factor analyses described the 2-factor model's fit. Criterion validity was compared between mania and depression scales, and with the full-length GBI scales. For both mania and depression factors, 7 items produced a psychometrically adequate measure applicable across both aggregate samples. Internal reliability of the Mania scale was .81 (youth) and .83 (adult) and for Depression was .93 (youth) and .95 (adult). By design, the brief scales were less strongly correlated with each other than were the original GBI scales. Construct validity of the new instrument was supported in observed discriminant and convergent relationships with external correlates and discrimination of diagnostic groups. The new brief GBI, the 7 Up 7 Down Inventory, demonstrates sound psychometric properties across a wide age range, showing expected relationships with external correlates. The new instrument provides a clearer separation of manic and depressive tendencies than the original. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

  12. In silico modeling to predict drug-induced phospholipidosis

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

    Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov

    2013-06-01

    Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structure–activity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the constructionmore » and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 80–81% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ≥ 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: • New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. • The training set data in the models is derived from the FDA's phospholipidosis database. • We find excellent predictivity values of the models based on external validation. • The models can support drug screening and regulatory decision-making on DIPL.« less

  13. Risk assessment tools to identify women with increased risk of osteoporotic fracture: complexity or simplicity? A systematic review.

    PubMed

    Rubin, Katrine Hass; Friis-Holmberg, Teresa; Hermann, Anne Pernille; Abrahamsen, Bo; Brixen, Kim

    2013-08-01

    A huge number of risk assessment tools have been developed. Far from all have been validated in external studies, more of them have absence of methodological and transparent evidence, and few are integrated in national guidelines. Therefore, we performed a systematic review to provide an overview of existing valid and reliable risk assessment tools for prediction of osteoporotic fractures. Additionally, we aimed to determine if the performance of each tool was sufficient for practical use, and last, to examine whether the complexity of the tools influenced their discriminative power. We searched PubMed, Embase, and Cochrane databases for papers and evaluated these with respect to methodological quality using the Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS) checklist. A total of 48 tools were identified; 20 had been externally validated, however, only six tools had been tested more than once in a population-based setting with acceptable methodological quality. None of the tools performed consistently better than the others and simple tools (i.e., the Osteoporosis Self-assessment Tool [OST], Osteoporosis Risk Assessment Instrument [ORAI], and Garvan Fracture Risk Calculator [Garvan]) often did as well or better than more complex tools (i.e., Simple Calculated Risk Estimation Score [SCORE], WHO Fracture Risk Assessment Tool [FRAX], and Qfracture). No studies determined the effectiveness of tools in selecting patients for therapy and thus improving fracture outcomes. High-quality studies in randomized design with population-based cohorts with different case mixes are needed. Copyright © 2013 American Society for Bone and Mineral Research.

  14. Quantitative structure-activity relationship study of P2X7 receptor inhibitors using combination of principal component analysis and artificial intelligence methods.

    PubMed

    Ahmadi, Mehdi; Shahlaei, Mohsen

    2015-01-01

    P2X7 antagonist activity for a set of 49 molecules of the P2X7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. The activity of these compounds was estimated by means of combination of principal component analysis (PCA), as a well-known data reduction method, genetic algorithm (GA), as a variable selection technique, and artificial neural network (ANN), as a non-linear modeling method. First, a linear regression, combined with PCA, (principal component regression) was operated to model the structure-activity relationships, and afterwards a combination of PCA and ANN algorithm was employed to accurately predict the biological activity of the P2X7 antagonist. PCA preserves as much of the information as possible contained in the original data set. Seven most important PC's to the studied activity were selected as the inputs of ANN box by an efficient variable selection method, GA. The best computational neural network model was a fully-connected, feed-forward model with 7-7-1 architecture. The developed ANN model was fully evaluated by different validation techniques, including internal and external validation, and chemical applicability domain. All validations showed that the constructed quantitative structure-activity relationship model suggested is robust and satisfactory.

  15. Quantitative structure–activity relationship study of P2X7 receptor inhibitors using combination of principal component analysis and artificial intelligence methods

    PubMed Central

    Ahmadi, Mehdi; Shahlaei, Mohsen

    2015-01-01

    P2X7 antagonist activity for a set of 49 molecules of the P2X7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. The activity of these compounds was estimated by means of combination of principal component analysis (PCA), as a well-known data reduction method, genetic algorithm (GA), as a variable selection technique, and artificial neural network (ANN), as a non-linear modeling method. First, a linear regression, combined with PCA, (principal component regression) was operated to model the structure–activity relationships, and afterwards a combination of PCA and ANN algorithm was employed to accurately predict the biological activity of the P2X7 antagonist. PCA preserves as much of the information as possible contained in the original data set. Seven most important PC's to the studied activity were selected as the inputs of ANN box by an efficient variable selection method, GA. The best computational neural network model was a fully-connected, feed-forward model with 7−7−1 architecture. The developed ANN model was fully evaluated by different validation techniques, including internal and external validation, and chemical applicability domain. All validations showed that the constructed quantitative structure–activity relationship model suggested is robust and satisfactory. PMID:26600858

  16. Results for the Aboveground Configuration of the Boiling Water Reactor Dry Cask Simulator

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

    Durbin, Samuel G.; Lindgren, Eric R.

    The thermal performance of commercial nuclear spent fuel dry storage casks is evaluated through detailed numerical analysis. These modeling efforts are completed by the vendor to demonstrate performance and regulatory compliance. The calculations are then independently verified by the Nuclear Regulatory Commission (NRC). Carefully measured data sets generated from testing of full-sized casks or smaller cask analogs are widely recognized as vital for validating these models. Recent advances in dry storage cask designs have significantly increased the maximum thermal load allowed in a cask, in part by increasing the efficiency of internal conduction pathways, and also by increasing the internalmore » convection through greater canister helium pressure. These same canistered cask systems rely on ventilation between the canister and the overpack to convect heat away from the canister to the environment for both above- and below-ground configurations. While several testing programs have been previously conducted, these earlier validation attempts did not capture the effects of elevated helium pressures or accurately portray the external convection of above-ground and below-ground canistered dry cask systems. The purpose of the current investigation was to produce data sets that can be used to test the validity of the assumptions associated with the calculations used to determine steady-state cladding temperatures in modern dry casks that utilize elevated helium pressure in the sealed canister in an above-ground configuration.« less

  17. Early prediction of intensive care unit-acquired weakness using easily available parameters: a prospective observational study.

    PubMed

    Wieske, Luuk; Witteveen, Esther; Verhamme, Camiel; Dettling-Ihnenfeldt, Daniela S; van der Schaaf, Marike; Schultz, Marcus J; van Schaik, Ivo N; Horn, Janneke

    2014-01-01

    An early diagnosis of Intensive Care Unit-acquired weakness (ICU-AW) using muscle strength assessment is not possible in most critically ill patients. We hypothesized that development of ICU-AW can be predicted reliably two days after ICU admission, using patient characteristics, early available clinical parameters, laboratory results and use of medication as parameters. Newly admitted ICU patients mechanically ventilated ≥2 days were included in this prospective observational cohort study. Manual muscle strength was measured according to the Medical Research Council (MRC) scale, when patients were awake and attentive. ICU-AW was defined as an average MRC score <4. A prediction model was developed by selecting predictors from an a-priori defined set of candidate predictors, based on known risk factors. Discriminative performance of the prediction model was evaluated, validated internally and compared to the APACHE IV and SOFA score. Of 212 included patients, 103 developed ICU-AW. Highest lactate levels, treatment with any aminoglycoside in the first two days after admission and age were selected as predictors. The area under the receiver operating characteristic curve of the prediction model was 0.71 after internal validation. The new prediction model improved discrimination compared to the APACHE IV and the SOFA score. The new early prediction model for ICU-AW using a set of 3 easily available parameters has fair discriminative performance. This model needs external validation.

  18. Prognostic models for complete recovery in ischemic stroke: a systematic review and meta-analysis.

    PubMed

    Jampathong, Nampet; Laopaiboon, Malinee; Rattanakanokchai, Siwanon; Pattanittum, Porjai

    2018-03-09

    Prognostic models have been increasingly developed to predict complete recovery in ischemic stroke. However, questions arise about the performance characteristics of these models. The aim of this study was to systematically review and synthesize performance of existing prognostic models for complete recovery in ischemic stroke. We searched journal publications indexed in PUBMED, SCOPUS, CENTRAL, ISI Web of Science and OVID MEDLINE from inception until 4 December, 2017, for studies designed to develop and/or validate prognostic models for predicting complete recovery in ischemic stroke patients. Two reviewers independently examined titles and abstracts, and assessed whether each study met the pre-defined inclusion criteria and also independently extracted information about model development and performance. We evaluated validation of the models by medians of the area under the receiver operating characteristic curve (AUC) or c-statistic and calibration performance. We used a random-effects meta-analysis to pool AUC values. We included 10 studies with 23 models developed from elderly patients with a moderately severe ischemic stroke, mainly in three high income countries. Sample sizes for each study ranged from 75 to 4441. Logistic regression was the only analytical strategy used to develop the models. The number of various predictors varied from one to 11. Internal validation was performed in 12 models with a median AUC of 0.80 (95% CI 0.73 to 0.84). One model reported good calibration. Nine models reported external validation with a median AUC of 0.80 (95% CI 0.76 to 0.82). Four models showed good discrimination and calibration on external validation. The pooled AUC of the two validation models of the same developed model was 0.78 (95% CI 0.71 to 0.85). The performance of the 23 models found in the systematic review varied from fair to good in terms of internal and external validation. Further models should be developed with internal and external validation in low and middle income countries.

  19. Development and Validation of Participation and Positive Psychologic Function Measures for Stroke Survivors

    PubMed Central

    Bode, Rita K.; Heinemann, Allen W.; Butt, Zeeshan; Stallings, Jena; Taylor, Caitlin; Rowe, Morgan; Roth, Elliot J.

    2013-01-01

    Bode RK, Heinemann AW, Butt Z, Stallings J, Taylor C, Rowe M, Roth EJ. Development and validation of participation and positive psychologic function measures for stroke survivors. Objective To evaluate the reliability and validity of Neurologic Quality of Life (NeuroQOL) item banks that assess quality-of-life (QOL) domains not typically included in poststroke measures. Design Secondary analysis of item responses to selected NeuroQOL domains. Setting Community. Participants Community-dwelling stroke survivors (n=111) who were at least 12 months poststroke. Interventions Not applicable. Main Outcome Measures Five measures developed for 3 NeuroQoL domains: ability to participate in social activities, satisfaction with participation in social activities, and positive psychologic function. Results A single bank was developed for the positive psychologic function domain, but 2 banks each were developed for the ability-to-participate and satisfaction-with-participation domains. The resulting item banks showed good psychometric properties and external construct validity with correlations with the legacy instruments, ranging from .53 to .71. Using these measures, stroke survivors in this sample reported an overall high level of QOL. Conclusions The NeuroQoL-derived measures are promising and valid methods for assessing aspects of QOL not typically measured in this population. PMID:20801251

  20. PROMIS measures of pain, fatigue, negative affect, physical function, and social function demonstrated clinical validity across a range of chronic conditions.

    PubMed

    Cook, Karon F; Jensen, Sally E; Schalet, Benjamin D; Beaumont, Jennifer L; Amtmann, Dagmar; Czajkowski, Susan; Dewalt, Darren A; Fries, James F; Pilkonis, Paul A; Reeve, Bryce B; Stone, Arthur A; Weinfurt, Kevin P; Cella, David

    2016-05-01

    To present an overview of a series of studies in which the clinical validity of the National Institutes of Health's Patient Reported Outcome Measurement Information System (NIH; PROMIS) measures was evaluated, by domain, across six clinical populations. Approximately 1,500 individuals at baseline and 1,300 at follow-up completed PROMIS measures. The analyses reported in this issue were conducted post hoc, pooling data across six previous studies, and accommodating the different designs of the six, within-condition, parent studies. Changes in T-scores, standardized response means, and effect sizes were calculated in each study. When a parent study design allowed, known groups validity was calculated using a linear mixed model. The results provide substantial support for the clinical validity of nine PROMIS measures in a range of chronic conditions. The cross-condition focus of the analyses provided a unique and multifaceted perspective on how PROMIS measures function in "real-world" clinical settings and provides external anchors that can support comparative effectiveness research. The current body of clinical validity evidence for the nine PROMIS measures indicates the success of NIH PROMIS in developing measures that are effective across a range of chronic conditions. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Analysis of near infrared spectra for age-grading of wild populations of Anopheles gambiae.

    PubMed

    Krajacich, Benjamin J; Meyers, Jacob I; Alout, Haoues; Dabiré, Roch K; Dowell, Floyd E; Foy, Brian D

    2017-11-07

    Understanding the age-structure of mosquito populations, especially malaria vectors such as Anopheles gambiae, is important for assessing the risk of infectious mosquitoes, and how vector control interventions may impact this risk. The use of near-infrared spectroscopy (NIRS) for age-grading has been demonstrated previously on laboratory and semi-field mosquitoes, but to date has not been utilized on wild-caught mosquitoes whose age is externally validated via parity status or parasite infection stage. In this study, we developed regression and classification models using NIRS on datasets of wild An. gambiae (s.l.) reared from larvae collected from the field in Burkina Faso, and two laboratory strains. We compared the accuracy of these models for predicting the ages of wild-caught mosquitoes that had been scored for their parity status as well as for positivity for Plasmodium sporozoites. Regression models utilizing variable selection increased predictive accuracy over the more common full-spectrum partial least squares (PLS) approach for cross-validation of the datasets, validation, and independent test sets. Models produced from datasets that included the greatest range of mosquito samples (i.e. different sampling locations and times) had the highest predictive accuracy on independent testing sets, though overall accuracy on these samples was low. For classification, we found that intramodel accuracy ranged between 73.5-97.0% for grouping of mosquitoes into "early" and "late" age classes, with the highest prediction accuracy found in laboratory colonized mosquitoes. However, this accuracy was decreased on test sets, with the highest classification of an independent set of wild-caught larvae reared to set ages being 69.6%. Variation in NIRS data, likely from dietary, genetic, and other factors limits the accuracy of this technique with wild-caught mosquitoes. Alternative algorithms may help improve prediction accuracy, but care should be taken to either maximize variety in models or minimize confounders.

  2. Psychopathy in Bulgaria: The cross-cultural generalizability of the Hare Psychopathy Checklist

    PubMed Central

    Wilson, Michael J.; Abramowitz, Carolyn; Vasilev, Georgi; Bozgunov, Kiril; Vassileva, Jasmin

    2014-01-01

    The generalizability of the psychopathy construct to Eastern European cultures has not been well-studied, and no prior studies have evaluated psychopathy in non-offender samples from this population. The current validation study examines the factor structure, internal consistency, and external validity of the Bulgarian translation of the Hare Psychopathy Checklist: Screening Version. Two hundred sixty-two Bulgarian adults from the general community were assessed, of which 185 had a history of substance dependence. Confirmatory factor analysis indicated good fit for the two-, three-, and four-factor models of psychopathy. Zero-order and partial correlation analyses were conducted between the two factors of psychopathy and criterion measures of antisocial behavior, internalizing and externalizing psychopathology, personality traits, addictive disorders and demographic characteristics. Relationships to external variables provided evidence for the convergent and discriminant validity of the psychopathy construct in a Bulgarian community sample. PMID:25313268

  3. AlzhCPI: A knowledge base for predicting chemical-protein interactions towards Alzheimer's disease.

    PubMed

    Fang, Jiansong; Wang, Ling; Li, Yecheng; Lian, Wenwen; Pang, Xiaocong; Wang, Hong; Yuan, Dongsheng; Wang, Qi; Liu, Ai-Lin; Du, Guan-Hua

    2017-01-01

    Alzheimer's disease (AD) is a complicated progressive neurodegeneration disorder. To confront AD, scientists are searching for multi-target-directed ligands (MTDLs) to delay disease progression. The in silico prediction of chemical-protein interactions (CPI) can accelerate target identification and drug discovery. Previously, we developed 100 binary classifiers to predict the CPI for 25 key targets against AD using the multi-target quantitative structure-activity relationship (mt-QSAR) method. In this investigation, we aimed to apply the mt-QSAR method to enlarge the model library to predict CPI towards AD. Another 104 binary classifiers were further constructed to predict the CPI for 26 preclinical AD targets based on the naive Bayesian (NB) and recursive partitioning (RP) algorithms. The internal 5-fold cross-validation and external test set validation were applied to evaluate the performance of the training sets and test set, respectively. The area under the receiver operating characteristic curve (ROC) for the test sets ranged from 0.629 to 1.0, with an average of 0.903. In addition, we developed a web server named AlzhCPI to integrate the comprehensive information of approximately 204 binary classifiers, which has potential applications in network pharmacology and drug repositioning. AlzhCPI is available online at http://rcidm.org/AlzhCPI/index.html. To illustrate the applicability of AlzhCPI, the developed system was employed for the systems pharmacology-based investigation of shichangpu against AD to enhance the understanding of the mechanisms of action of shichangpu from a holistic perspective.

  4. Atom-type-based AI topological descriptors: application in structure-boiling point correlations of oxo organic compounds.

    PubMed

    Ren, Biye

    2003-01-01

    Structure-boiling point relationships are studied for a series of oxo organic compounds by means of multiple linear regression (MLR) analysis. Excellent MLR models based on the recently introduced Xu index and the atom-type-based AI indices are obtained for the two subsets containing respectively 77 ethers and 107 carbonyl compounds and a combined set of 184 oxo compounds. The best models are tested using the leave-one-out cross-validation and an external test set, respectively. The MLR model produces a correlation coefficient of r = 0.9977 and a standard error of s = 3.99 degrees C for the training set of 184 compounds, and r(cv) = 0.9974 and s(cv) = 4.16 degrees C for the cross-validation set, and r(pred) = 0.9949 and s(pred) = 4.38 degrees C for the prediction set of 21 compounds. For the two subsets containing respectively 77 ethers and 107 carbonyl compounds, the quality of the models is further improved. The standard errors are reduced to 3.30 and 3.02 degrees C, respectively. Furthermore, the results obtained from this study indicate that the boiling points of the studied oxo compound dominantly depend on molecular size and also depend on individual atom types, especially oxygen heteroatoms in molecules due to strong polar interactions between molecules. These excellent structure-boiling point models not only provide profound insights into the role of structural features in a molecule but also illustrate the usefulness of these indices in QSPR/QSAR modeling of complex compounds.

  5. Clinical audit project in undergraduate medical education curriculum: an assessment validation study

    PubMed Central

    Steketee, Carole; Mak, Donna

    2016-01-01

    Objectives To evaluate the merit of the Clinical Audit Project (CAP) in an assessment program for undergraduate medical education using a systematic assessment validation framework. Methods A cross-sectional assessment validation study at one medical school in Western Australia, with retrospective qualitative analysis of the design, development, implementation and outcomes of the CAP, and quantitative analysis of assessment data from four cohorts of medical students (2011- 2014). Results The CAP is fit for purpose with clear external and internal alignment to expected medical graduate outcomes.  Substantive validity in students’ and examiners’ response processes is ensured through relevant methodological and cognitive processes. Multiple validity features are built-in to the design, planning and implementation process of the CAP.  There is evidence of high internal consistency reliability of CAP scores (Cronbach’s alpha > 0.8) and inter-examiner consistency reliability (intra-class correlation>0.7). Aggregation of CAP scores is psychometrically sound, with high internal consistency indicating one common underlying construct.  Significant but moderate correlations between CAP scores and scores from other assessment modalities indicate validity of extrapolation and alignment between the CAP and the overall target outcomes of medical graduates.  Standard setting, score equating and fair decision rules justify consequential validity of CAP scores interpretation and use. Conclusions This study provides evidence demonstrating that the CAP is a meaningful and valid component in the assessment program. This systematic framework of validation can be adopted for all levels of assessment in medical education, from individual assessment modality, to the validation of an assessment program as a whole.  PMID:27716612

  6. Clinical audit project in undergraduate medical education curriculum: an assessment validation study.

    PubMed

    Tor, Elina; Steketee, Carole; Mak, Donna

    2016-09-24

    To evaluate the merit of the Clinical Audit Project (CAP) in an assessment program for undergraduate medical education using a systematic assessment validation framework. A cross-sectional assessment validation study at one medical school in Western Australia, with retrospective qualitative analysis of the design, development, implementation and outcomes of the CAP, and quantitative analysis of assessment data from four cohorts of medical students (2011- 2014). The CAP is fit for purpose with clear external and internal alignment to expected medical graduate outcomes.  Substantive validity in students' and examiners' response processes is ensured through relevant methodological and cognitive processes. Multiple validity features are built-in to the design, planning and implementation process of the CAP.  There is evidence of high internal consistency reliability of CAP scores (Cronbach's alpha > 0.8) and inter-examiner consistency reliability (intra-class correlation>0.7). Aggregation of CAP scores is psychometrically sound, with high internal consistency indicating one common underlying construct.  Significant but moderate correlations between CAP scores and scores from other assessment modalities indicate validity of extrapolation and alignment between the CAP and the overall target outcomes of medical graduates.  Standard setting, score equating and fair decision rules justify consequential validity of CAP scores interpretation and use. This study provides evidence demonstrating that the CAP is a meaningful and valid component in the assessment program. This systematic framework of validation can be adopted for all levels of assessment in medical education, from individual assessment modality, to the validation of an assessment program as a whole.

  7. Combined HQSAR, topomer CoMFA, homology modeling and docking studies on triazole derivatives as SGLT2 inhibitors.

    PubMed

    Yu, Shuling; Yuan, Jintao; Zhang, Yi; Gao, Shufang; Gan, Ying; Han, Meng; Chen, Yuewen; Zhou, Qiaoqiao; Shi, Jiahua

    2017-06-01

    Sodium-glucose cotransporter 2 (SGLT2) is a promising target for diabetes therapy. We aimed to develop computational approaches to identify structural features for more potential SGLT2 inhibitors. In this work, 46 triazole derivatives as SGLT2 inhibitors were studied using a combination of several approaches, including hologram quantitative structure-activity relationships (HQSAR), topomer comparative molecular field analysis (CoMFA), homology modeling, and molecular docking. HQSAR and topomer CoMFA were used to construct models. Molecular docking was conducted to investigate the interaction of triazole derivatives and homology modeling of SGLT2, as well as to validate the results of the HQSAR and topomer CoMFA models. The most effective HQSAR and topomer CoMFA models exhibited noncross-validated correlation coefficients of 0.928 and 0.891 for the training set, respectively. External predictions were made successfully on a test set and then compared with previously reported models. The graphical results of HQSAR and topomer CoMFA were proven to be consistent with the binding mode of the inhibitors and SGLT2 from molecular docking. The models and docking provided important insights into the design of potent inhibitors for SGLT2.

  8. Key elements of high-quality practice organisation in primary health care: a systematic review.

    PubMed

    Crossland, Lisa; Janamian, Tina; Jackson, Claire L

    2014-08-04

    To identify elements that are integral to high-quality practice and determine considerations relating to high-quality practice organisation in primary care. A narrative systematic review of published and grey literature. Electronic databases (PubMed, CINAHL, the Cochrane Library, Embase, Emerald Insight, PsycInfo, the Primary Health Care Research and Information Service website, Google Scholar) were searched in November 2013 and used to identify articles published in English from 2002 to 2013. Reference lists of included articles were searched for relevant unpublished articles and reports. Data were configured at the study level to allow for the inclusion of findings from a broad range of study types. Ten elements were most often included in the existing organisational assessment tools. A further three elements were identified from an inductive thematic analysis of descriptive articles, and were noted as important considerations in effective quality improvement in primary care settings. Although there are some validated tools available to primary care that identify and build quality, most are single-strategy approaches developed outside health care settings. There are currently no validated organisational improvement tools, designed specifically for primary health care, which combine all elements of practice improvement and whose use does not require extensive external facilitation.

  9. Quantitative structure-property relationship analysis for the retention index of fragrance-like compounds on a polar stationary phase.

    PubMed

    Rojas, Cristian; Duchowicz, Pablo R; Tripaldi, Piercosimo; Pis Diez, Reinaldo

    2015-11-27

    A quantitative structure-property relationship (QSPR) was developed for modeling the retention index of 1184 flavor and fragrance compounds measured using a Carbowax 20M glass capillary gas chromatography column. The 4885 molecular descriptors were calculated using Dragon software, and then were simultaneously analyzed through multivariable linear regression analysis using the replacement method (RM) variable subset selection technique. We proceeded in three steps, the first one by considering all descriptor blocks, the second one by excluding conformational descriptor blocks, and the last one by analyzing only 3D-descriptor families. The models were validated through an external test set of compounds. Cross-validation methods such as leave-one-out and leave-many-out were applied, together with Y-randomization and applicability domain analysis. The developed model was used to estimate the I of a set of 22 molecules. The results clearly suggest that 3D-descriptors do not offer relevant information for modeling the retention index, while a topological index such as the Randić-like index from reciprocal squared distance matrix has a high relevance for this purpose. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Evaluation of multivariate calibration models with different pre-processing and processing algorithms for a novel resolution and quantitation of spectrally overlapped quaternary mixture in syrup

    NASA Astrophysics Data System (ADS)

    Moustafa, Azza A.; Hegazy, Maha A.; Mohamed, Dalia; Ali, Omnia

    2016-02-01

    A novel approach for the resolution and quantitation of severely overlapped quaternary mixture of carbinoxamine maleate (CAR), pholcodine (PHL), ephedrine hydrochloride (EPH) and sunset yellow (SUN) in syrup was demonstrated utilizing different spectrophotometric assisted multivariate calibration methods. The applied methods have used different processing and pre-processing algorithms. The proposed methods were partial least squares (PLS), concentration residuals augmented classical least squares (CRACLS), and a novel method; continuous wavelet transforms coupled with partial least squares (CWT-PLS). These methods were applied to a training set in the concentration ranges of 40-100 μg/mL, 40-160 μg/mL, 100-500 μg/mL and 8-24 μg/mL for the four components, respectively. The utilized methods have not required any preliminary separation step or chemical pretreatment. The validity of the methods was evaluated by an external validation set. The selectivity of the developed methods was demonstrated by analyzing the drugs in their combined pharmaceutical formulation without any interference from additives. The obtained results were statistically compared with the official and reported methods where no significant difference was observed regarding both accuracy and precision.

  11. QSPR models of n-octanol/water partition coefficients and aqueous solubility of halogenated methyl-phenyl ethers by DFT method.

    PubMed

    Zeng, Xiao-Lan; Wang, Hong-Jun; Wang, Yan

    2012-02-01

    The possible molecular geometries of 134 halogenated methyl-phenyl ethers were optimized at B3LYP/6-31G(*) level with Gaussian 98 program. The calculated structural parameters were taken as theoretical descriptors to establish two new novel QSPR models for predicting aqueous solubility (-lgS(w,l)) and n-octanol/water partition coefficient (lgK(ow)) of halogenated methyl-phenyl ethers. The two models achieved in this work both contain three variables: energy of the lowest unoccupied molecular orbital (E(LUMO)), most positive atomic partial charge in molecule (q(+)), and quadrupole moment (Q(yy) or Q(zz)), of which R values are 0.992 and 0.970 respectively, their standard errors of estimate in modeling (SD) are 0.132 and 0.178, respectively. The results of leave-one-out (LOO) cross-validation for training set and validation with external test sets both show that the models obtained exhibited optimum stability and good predictive power. We suggests that two QSPR models derived here can be used to predict S(w,l) and K(ow) accurately for non-tested halogenated methyl-phenyl ethers congeners. Copyright © 2011 Elsevier Ltd. All rights reserved.

  12. External Correlates of the MMPI-2 Content Component Scales in Mental Health Inpatients

    ERIC Educational Resources Information Center

    Green, Bradley A.; Handel, Richard W.; Archer, Robert P.

    2006-01-01

    External correlates of the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) Content Component Scales were identified using an inpatient sample of 544 adults. The Brief Psychiatric Rating Scale (BPRS) and Symptom Checklist 90-Revised (SCL-90-R) produced correlates of the Content Component Scales, demonstrating external validity with…

  13. Choosing a Control Group in Effectiveness Trials of Behavioral Drug Abuse Treatments

    PubMed Central

    Brigham, Gregory S.; Feaster, Daniel J.; Wakim, Paul G.; Dempsey, Catherine L.

    2009-01-01

    Effectiveness trials are an important step in the scientific process of developing and evaluating behavioral treatments. The focus on effectiveness research presents a different set of requirements on the research design when compared with efficacy studies. The choice of a control condition has many implications for a clinical trial's internal and external validity. The purpose of this manuscript is to provide a discussion of the issues involved in choosing a control group for effectiveness trials of behavioral interventions in substance abuse treatment. The authors provide a description of four trial designs and a discussion of the advantages and disadvantages of each. PMID:19553062

  14. [The balanced scorecard used as a management tool in a clinical laboratory: internal business processes indicators].

    PubMed

    Salinas La Casta, Maria; Flores Pardo, Emilio; Uris Selles, Joaquín

    2009-01-01

    to propose a set of indicators as a management tool for a clinical laboratory, by using the balanced scorecard internal business processes perspective. indicators proposed are obtained from different sources; external proficiency testing of the Valencia Community Government, by means of internal surveys and laboratory information system registers. One year testing process proportion indicators results are showed. internal management indicators are proposed (process, appropriateness and proficiency testing). The process indicators results show gradual improvement since its establishment. after one years of using a conceptually solid Balanced Scorecard Internal business processes perspective indicators, the obtained results validate the usefulness as a laboratory management tool.

  15. ADHD bifactor model based on parent and teacher ratings of Malaysian children.

    PubMed

    Gomez, Rapson

    2014-04-01

    The study used confirmatory factor analysis to ascertain support for the bifactor model of the Attention Deficit/Hyperactivity Disorder (ADHD) symptoms, based on parent and teacher ratings for a group of Malaysian children. Malaysian parents and teachers completed ratings of ADHD and Opposition Defiant Disorder (ODD) symptoms for 934 children. For both sets of ratings, the findings indicating good fit for the bifactor model, and the factors in this model showed differential associations with ODD, thereby supporting the internal and external validity of this model. The theoretical and clinical implications of the findings are discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

  16. A critical analysis of climatic influences on indoor radon concentrations: Implications for seasonal correction.

    PubMed

    Groves-Kirkby, Christopher J; Crockett, Robin G M; Denman, Antony R; Phillips, Paul S

    2015-10-01

    Although statistically-derived national Seasonal Correction Factors (SCFs) are conventionally used to convert sub-year radon concentration measurements to an annual mean, it has recently been suggested that external temperature could be used to derive local SCFs for short-term domestic measurements. To validate this approach, hitherto unanalysed radon and temperature data from an environmentally-stable location were analysed. Radon concentration and internal temperature were measured over periods totalling 1025 days during an overall period of 1762 days, the greatest continuous sampling period being 334 days, with corresponding meteorological data collected at a weather station 10 km distant. Mean daily, monthly and annual radon concentrations and internal temperatures were calculated. SCFs derived using monthly mean radon concentration, external temperature and internal-external temperature-difference were cross-correlated with each other and with published UK domestic SCF sets. Relatively good correlation exists between SCFs derived from radon concentration and internal-external temperature difference but correlation with external temperature, was markedly poorer. SCFs derived from external temperature correlate very well with published SCF tabulations, confirming that the complexity of deriving SCFs from temperature data may be outweighed by the convenience of using either of the existing domestic SCF tabulations. Mean monthly radon data fitted to a 12-month sinusoid showed reasonable correlation with many of the annual climatic parameter profiles, exceptions being atmospheric pressure, rainfall and internal temperature. Introducing an additional 6-month sinusoid enhanced correlation with these three parameters, the other correlations remaining essentially unchanged. Radon latency of the order of months in moisture-related parameters suggests that the principal driver for radon is total atmospheric moisture content rather than relative humidity. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. The effects of an adopted narrow gait on the external adduction moment at the knee joint during level walking: evidence of asymmetry.

    PubMed

    Street, Brian D; Gage, William

    2013-04-01

    The external knee adduction moment is an accurate estimation of the load distribution of the knee and is a valid predictor for the presence, severity and progression rate of medial compartment knee osteoarthritis. Gait modification strategies have been shown to be an effective means of reducing the external adduction moment. The purpose of this study was to test narrow gait as a mechanism to reduce the external adduction moment and investigate if limb dominance affects this pattern. Fifteen healthy male participants (mean age: 23.8 (SD=3.1) years, mean height: 1.8 (SD=0.1) m, and mean body mass: 82.9 (SD=16.1 kg) took part in this study. Five walking trials were performed for each of the three different gait conditions: normal gait, toe-out gait, and narrow gait. Adoption of the narrow gait strategy significantly reduced the early stance phase external knee adduction moment compared to normal and toe-out gait (p<.002). However, it was observed that this reduction only occurred in the non-dominant limb. Gait modification can reduce the external knee adduction moment. However, asymmetrical patterns between the dominant and non-dominant limbs, specifically during gait modification, may attenuate the effectiveness of this intervention. The mechanism of limb dominance and the specific roles of each limb during gait may account for an asymmetrical pattern in the moment arm and center of mass displacement during stance. This new insight into how limb-dominance effects gait modification strategies will be useful in the clinical setting when identifying appropriate patients, when indicating a gait modification strategy and in future research methodology. Copyright © 2013 Elsevier B.V. All rights reserved.

  18. Alternative Fistula Risk Score for Pancreatoduodenectomy (a-FRS): Design and International External Validation.

    PubMed

    Mungroop, Timothy H; van Rijssen, L Bengt; van Klaveren, David; Smits, F Jasmijn; van Woerden, Victor; Linnemann, Ralph J; de Pastena, Matteo; Klompmaker, Sjors; Marchegiani, Giovanni; Ecker, Brett L; van Dieren, Susan; Bonsing, Bert; Busch, Olivier R; van Dam, Ronald M; Erdmann, Joris; van Eijck, Casper H; Gerhards, Michael F; van Goor, Harry; van der Harst, Erwin; de Hingh, Ignace H; de Jong, Koert P; Kazemier, Geert; Luyer, Misha; Shamali, Awad; Barbaro, Salvatore; Armstrong, Thomas; Takhar, Arjun; Hamady, Zaed; Klaase, Joost; Lips, Daan J; Molenaar, I Quintus; Nieuwenhuijs, Vincent B; Rupert, Coen; van Santvoort, Hjalmar C; Scheepers, Joris J; van der Schelling, George P; Bassi, Claudio; Vollmer, Charles M; Steyerberg, Ewout W; Abu Hilal, Mohammed; Groot Koerkamp, Bas; Besselink, Marc G

    2017-12-12

    The aim of this study was to develop an alternative fistula risk score (a-FRS) for postoperative pancreatic fistula (POPF) after pancreatoduodenectomy, without blood loss as a predictor. Blood loss, one of the predictors of the original-FRS, was not a significant factor during 2 recent external validations. The a-FRS was developed in 2 databases: the Dutch Pancreatic Cancer Audit (18 centers) and the University Hospital Southampton NHS. Primary outcome was grade B/C POPF according to the 2005 International Study Group on Pancreatic Surgery (ISGPS) definition. The score was externally validated in 2 independent databases (University Hospital of Verona and University Hospital of Pennsylvania), using both 2005 and 2016 ISGPS definitions. The a-FRS was also compared with the original-FRS. For model design, 1924 patients were included of whom 12% developed POPF. Three predictors were strongly associated with POPF: soft pancreatic texture [odds ratio (OR) 2.58, 95% confidence interval (95% CI) 1.80-3.69], small pancreatic duct diameter (per mm increase, OR: 0.68, 95% CI: 0.61-0.76), and high body mass index (BMI) (per kg/m increase, OR: 1.07, 95% CI: 1.04-1.11). Discrimination was adequate with an area under curve (AUC) of 0.75 (95% CI: 0.71-0.78) after internal validation, and 0.78 (0.74-0.82) after external validation. The predictive capacity of a-FRS was comparable with the original-FRS, both for the 2005 definition (AUC 0.78 vs 0.75, P = 0.03), and 2016 definition (AUC 0.72 vs 0.70, P = 0.05). The a-FRS predicts POPF after pancreatoduodenectomy based on 3 easily available variables (pancreatic texture, duct diameter, BMI) without blood loss and pathology, and was successfully validated for both the 2005 and 2016 POPF definition.

  19. Patient-Reported Outcomes After Radiation Therapy in Men With Prostate Cancer: A Systematic Review of Prognostic Tool Accuracy and Validity

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

    O'Callaghan, Michael E., E-mail: elspeth.raymond@health.sa.gov.au; Freemasons Foundation Centre for Men's Health, University of Adelaide; Urology Unit, Repatriation General Hospital, SA Health, Flinders Centre for Innovation in Cancer

    Purpose: To identify, through a systematic review, all validated tools used for the prediction of patient-reported outcome measures (PROMs) in patients being treated with radiation therapy for prostate cancer, and provide a comparative summary of accuracy and generalizability. Methods and Materials: PubMed and EMBASE were searched from July 2007. Title/abstract screening, full text review, and critical appraisal were undertaken by 2 reviewers, whereas data extraction was performed by a single reviewer. Eligible articles had to provide a summary measure of accuracy and undertake internal or external validation. Tools were recommended for clinical implementation if they had been externally validated and foundmore » to have accuracy ≥70%. Results: The search strategy identified 3839 potential studies, of which 236 progressed to full text review and 22 were included. From these studies, 50 tools predicted gastrointestinal/rectal symptoms, 29 tools predicted genitourinary symptoms, 4 tools predicted erectile dysfunction, and no tools predicted quality of life. For patients treated with external beam radiation therapy, 3 tools could be recommended for the prediction of rectal toxicity, gastrointestinal toxicity, and erectile dysfunction. For patients treated with brachytherapy, 2 tools could be recommended for the prediction of urinary retention and erectile dysfunction. Conclusions: A large number of tools for the prediction of PROMs in prostate cancer patients treated with radiation therapy have been developed. Only a small minority are accurate and have been shown to be generalizable through external validation. This review provides an accessible catalogue of tools that are ready for clinical implementation as well as which should be prioritized for validation.« less

  20. Personalized Prediction of Psychosis: External validation of the NAPLS2 Psychosis Risk Calculator with the EDIPPP project

    PubMed Central

    Carrión, Ricardo E.; Cornblatt, Barbara A.; Burton, Cynthia Z.; Tso, Ivy F; Auther, Andrea; Adelsheim, Steven; Calkins, Roderick; Carter, Cameron S.; Niendam, Tara; Taylor, Stephan F.; McFarlane, William R.

    2016-01-01

    Objective In the current issue, Cannon and colleagues, as part of the second phase of the North American Prodrome Longitudinal Study (NAPLS2), report on a risk calculator for the individualized prediction of developing a psychotic disorder in a 2-year period. The present study represents an external validation of the NAPLS2 psychosis risk calculator using an independent sample of subjects at clinical high risk for psychosis collected as part of the Early Detection, Intervention, and Prevention of Psychosis Program (EDIPPP). Methods 176 subjects with follow-up (from the total EDIPPP sample of 210) rated as clinical high-risk (CHR) based on the Structured Interview for Prodromal Syndromes were used to construct a new prediction model with the 6 significant predictor variables in the NAPLS2 psychosis risk calculator (unusual thoughts, suspiciousness, Symbol Coding, verbal learning, social functioning decline, baseline age, and family history). Discrimination performance was assessed with the area under the receiver operating curve (AUC). The NAPLS2 risk calculator was then used to generate a psychosis risk estimate for each case in the external validation sample. Results The external validation model showed good discrimination, with an AUC of 79% (95% CI 0.644–0.937). In addition, the personalized risk generated by the NAPLS calculator provided a solid estimation of the actual conversion outcome in the validation sample. Conclusions In the companion papers in this issue, two independent samples of CHR subjects converge to validate the NAPLS2 psychosis risk calculator. This prediction calculator represents a meaningful step towards early intervention and personalized treatment of psychotic disorders. PMID:27363511

  1. Validation of a new mortality risk prediction model for people 65 years and older in northwest Russia: The Crystal risk score.

    PubMed

    Turusheva, Anna; Frolova, Elena; Bert, Vaes; Hegendoerfer, Eralda; Degryse, Jean-Marie

    2017-07-01

    Prediction models help to make decisions about further management in clinical practice. This study aims to develop a mortality risk score based on previously identified risk predictors and to perform internal and external validations. In a population-based prospective cohort study of 611 community-dwelling individuals aged 65+ in St. Petersburg (Russia), all-cause mortality risks over 2.5 years follow-up were determined based on the results obtained from anthropometry, medical history, physical performance tests, spirometry and laboratory tests. C-statistic, risk reclassification analysis, integrated discrimination improvement analysis, decision curves analysis, internal validation and external validation were performed. Older adults were at higher risk for mortality [HR (95%CI)=4.54 (3.73-5.52)] when two or more of the following components were present: poor physical performance, low muscle mass, poor lung function, and anemia. If anemia was combined with high C-reactive protein (CRP) and high B-type natriuretic peptide (BNP) was added the HR (95%CI) was slightly higher (5.81 (4.73-7.14)) even after adjusting for age, sex and comorbidities. Our models were validated in an external population of adults 80+. The extended model had a better predictive capacity for cardiovascular mortality [HR (95%CI)=5.05 (2.23-11.44)] compared to the baseline model [HR (95%CI)=2.17 (1.18-4.00)] in the external population. We developed and validated a new risk prediction score that may be used to identify older adults at higher risk for mortality in Russia. Additional studies need to determine which targeted interventions improve the outcomes of these at-risk individuals. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Molecular electronegativity distance vector model for the prediction of bioconcentration factors in fish.

    PubMed

    Liu, Shu-Shen; Qin, Li-Tang; Liu, Hai-Ling; Yin, Da-Qiang

    2008-02-01

    Molecular electronegativity distance vector (MEDV) derived directly from the molecular topological structures was used to describe the structures of 122 nonionic organic compounds (NOCs) and a quantitative relationship between the MEDV descriptors and the bioconcentration factors (BCF) of NOCs in fish was developed using the variable selection and modeling based on prediction (VSMP). It was found that some main structural factors influencing the BCFs of NOCs are the substructures expressed by four atomic types of nos. 2, 3, 5, and 13, i.e., atom groups -CH(2)- or =CH-, -CH< or =C<, -NH(2), and -Cl or -Br where the former two groups exist in the molecular skeleton of NOC and the latter three groups are related closely to the substituting groups on a benzene ring. The best 5-variable model, with the correlation coefficient (r(2)) of 0.9500 and the leave-one-out cross-validation correlation coefficient (q(2)) of 0.9428, was built by multiple linear regressions, which shows a good estimation ability and stability. A predictive power for the external samples was tested by the model from the training set of 80 NOCs and the predictive correlation coefficient (u(2)) for the 42 external samples in the test set was 0.9028.

  3. Shuttle to space station transfer of the materials exposure facility

    NASA Technical Reports Server (NTRS)

    Shannon, David T., Jr.; Klich, Phillip J.

    1995-01-01

    The Materials Exposure Facility (MEF) is being proposed by LaRC as the first long-term space materials exposure facility with real-time interaction with materials experiments in actual conditions of orbital space flight. The MEF is proposed as a Space Station external payload dedicated to technology advancement in spacecraft materials and coatings research. This paper will define a set of potential logistics for removing the MEF from the Shuttle cargo bay and the process required for transferring the MEF to a specific external payload site on Space Station Freedom (SSF). The SSF UF-2 configuration is used for this study. The kinematics and ability to successfully perform the appropriate MEF maneuvers required were verified. During completion of this work, the Space Station was redesigned and the International Space Station Alpha (ISSA) configuration evolved. The transfer procedure for SSF was valid for ISSA; however, a verification of kinematics and clearances was essential. Also, SSF and ISSA robotic interfaces with the Orbiter were different.

  4. Kinetics and mass-transfer phenomena in anaerobic granular sludge.

    PubMed

    Gonzalez-Gil, G; Seghezzo, L; Lettinga, G; Kleerebezem, R

    2001-04-20

    The kinetic properties of acetate-degrading methanogenic granular sludge of different mean diameters were assessed at different up-flow velocities (V(up)). Using this approach, the influence of internal and external mass transfer could be estimated. First, the apparent Monod constant (K(S)) for each data set was calculated by means of a curve-fitting procedure. The experimental results revealed that variations in the V(up) did not affect the apparent K(S)-value, indicating that external mass-transport resistance normally can be neglected. With regard to the granule size, a clear increase in K(S) was found at increasing granule diameters. The experimental data were further used to validate a dynamic mathematical biofilm model. The biofilm model was able to describe reaction-diffusion kinetics in anaerobic granules, using a single value for the effective diffusion coefficient in the granules. This suggests that biogas formation did not influence the diffusion-rates in the granular biomass. Copyright 2001 John Wiley & Sons, Inc.

  5. Generating Models of Infinite-State Communication Protocols Using Regular Inference with Abstraction

    NASA Astrophysics Data System (ADS)

    Aarts, Fides; Jonsson, Bengt; Uijen, Johan

    In order to facilitate model-based verification and validation, effort is underway to develop techniques for generating models of communication system components from observations of their external behavior. Most previous such work has employed regular inference techniques which generate modest-size finite-state models. They typically suppress parameters of messages, although these have a significant impact on control flow in many communication protocols. We present a framework, which adapts regular inference to include data parameters in messages and states for generating components with large or infinite message alphabets. A main idea is to adapt the framework of predicate abstraction, successfully used in formal verification. Since we are in a black-box setting, the abstraction must be supplied externally, using information about how the component manages data parameters. We have implemented our techniques by connecting the LearnLib tool for regular inference with the protocol simulator ns-2, and generated a model of the SIP component as implemented in ns-2.

  6. Validity of self-assessment in a quality improvement collaborative in Ecuador.

    PubMed

    Hermida, Jorge; Broughton, Edward I; Miller Franco, Lynne

    2011-12-01

    Health care quality improvement (QI) efforts commonly use self-assessment to measure compliance with quality standards. This study investigates the validity of self-assessment of quality indicators. Cross sectional. A maternal and newborn care improvement collaborative intervention conducted in health facilities in Ecuador in 2005. Four external evaluators were trained in abstracting medical records to calculate six indicators reflecting compliance with treatment standards. About 30 medical records per month were examined at 12 participating health facilities for a total of 1875 records. The same records had already been reviewed by QI teams at these facilities (self-assessment). Overall compliance, agreement (using the Kappa statistic), sensitivity and specificity were analyzed. We also examined patterns of disagreement and the effect of facility characteristics on levels of agreement. External evaluators reported compliance of 69-90%, while self-assessors reported 71-92%, with raw agreement of 71-95% and Kappa statistics ranging from fair to almost perfect agreement. Considering external evaluators as the gold standard, sensitivity of self-assessment ranged from 90 to 99% and specificity from 48 to 86%. Simpler indicators had fewer disagreements. When disagreements occurred between self-assessment and external valuators, the former tended to report more positive findings in five of six indicators, but this tendency was not of a magnitude to change program actions. Team leadership, understanding of the tools and facility size had no overall impact on the level of agreement. When compared with external evaluation (gold standard), self-assessment was found to be sufficiently valid for tracking QI team performance. Sensitivity was generally higher than specificity. Simplifying indicators may improve validity.

  7. Differential sensitivity of the Response Bias Scale (RBS) and MMPI-2 validity scales to memory complaints.

    PubMed

    Gervais, Roger O; Ben-Porath, Yossef S; Wygant, Dustin B; Green, Paul

    2008-12-01

    The MMPI-2 Response Bias Scale (RBS) is designed to detect response bias in forensic neuropsychological and disability assessment settings. Validation studies have demonstrated that the scale is sensitive to cognitive response bias as determined by failure on the Word Memory Test (WMT) and other symptom validity tests. Exaggerated memory complaints are a common feature of cognitive response bias. The present study was undertaken to determine the extent to which the RBS is sensitive to memory complaints and how it compares in this regard to other MMPI-2 validity scales and indices. This archival study used MMPI-2 and Memory Complaints Inventory (MCI) data from 1550 consecutive non-head-injury disability-related referrals to the first author's private practice. ANOVA results indicated significant increases in memory complaints across increasing RBS score ranges with large effect sizes. Regression analyses indicated that the RBS was a better predictor of the mean memory complaints score than the F, F(B), and F(P) validity scales and the FBS. There was no correlation between the RBS and the CVLT, an objective measure of verbal memory. These findings suggest that elevated scores on the RBS are associated with over-reporting of memory problems, which provides further external validation of the RBS as a sensitive measure of cognitive response bias. Interpretive guidelines for the RBS are provided.

  8. Fun and Games: The Validity of Games for the Study of Conflict

    ERIC Educational Resources Information Center

    Schlenker, Barry R.; Bonoma, Thomas V.

    1978-01-01

    Examines claimed advantages and criticisms of the use of games in the study of social conflict, differentiating the advantages and criticisms into questions of internal validity, external validity, and ecological validity. Available from: Sage Publications, Inc., 275 South Beverly Drive, Beverly Hills, California 90212. (JG)

  9. Homework Stress: Construct Validation of a Measure

    ERIC Educational Resources Information Center

    Katz, Idit; Buzukashvili, Tamara; Feingold, Liat

    2012-01-01

    This article presents 2 studies aimed at validating a measure of stress experienced by children and parents around the issue of homework, applying Benson's program of validation (Benson, 1998). Study 1 provides external validity of the measure by supporting hypothesized relations between stress around homework and students' and parents' positive…

  10. Impact of correlation of predictors on discrimination of risk models in development and external populations.

    PubMed

    Kundu, Suman; Mazumdar, Madhu; Ferket, Bart

    2017-04-19

    The area under the ROC curve (AUC) of risk models is known to be influenced by differences in case-mix and effect size of predictors. The impact of heterogeneity in correlation among predictors has however been under investigated. We sought to evaluate how correlation among predictors affects the AUC in development and external populations. We simulated hypothetical populations using two different methods based on means, standard deviations, and correlation of two continuous predictors. In the first approach, the distribution and correlation of predictors were assumed for the total population. In the second approach, these parameters were modeled conditional on disease status. In both approaches, multivariable logistic regression models were fitted to predict disease risk in individuals. Each risk model developed in a population was validated in the remaining populations to investigate external validity. For both approaches, we observed that the magnitude of the AUC in the development and external populations depends on the correlation among predictors. Lower AUCs were estimated in scenarios of both strong positive and negative correlation, depending on the direction of predictor effects and the simulation method. However, when adjusted effect sizes of predictors were specified in the opposite directions, increasingly negative correlation consistently improved the AUC. AUCs in external validation populations were higher or lower than in the derivation cohort, even in the presence of similar predictor effects. Discrimination of risk prediction models should be assessed in various external populations with different correlation structures to make better inferences about model generalizability.

  11. Guidelines for Reporting Case Studies on Extracorporeal Treatments in Poisonings: Methodology

    PubMed Central

    Lavergne, Valéry; Ouellet, Georges; Bouchard, Josée; Galvao, Tais; Kielstein, Jan T; Roberts, Darren M; Kanji, Salmaan; Mowry, James B; Calello, Diane P; Hoffman, Robert S; Gosselin, Sophie; Nolin, Thomas D; Goldfarb, David S; Burdmann, Emmanuel A; Dargan, Paul I; Decker, Brian Scott; Hoegberg, Lotte C; Maclaren, Robert; Megarbane, Bruno; Sowinski, Kevin M; Yates, Christopher; Mactier, Robert; Wiegand, Timothy; Ghannoum, Marc

    2014-01-01

    A literature review performed by the EXtracorporeal TReatments In Poisoning (EXTRIP) workgroup highlighted deficiencies in the existing literature, especially the reporting of case studies. Although general reporting guidelines exist for case studies, there are none in the specific field of extracorporeal treatments in toxicology. Our goal was to construct and propose a checklist that systematically outlines the minimum essential items to be reported in a case study of poisoned patients undergoing extracorporeal treatments. Through a modified two-round Delphi technique, panelists (mostly chosen from the EXTRIP workgroup) were asked to vote on the pertinence of a set of items to identify those considered minimally essential for reporting complete and accurate case reports. Furthermore, independent raters validated the clarity of each selected items between each round of voting. All case reports containing data on extracorporeal treatments in poisoning published in Medline in 2011 were reviewed during the external validation rounds. Twenty-one panelists (20 from the EXTRIP workgroup and an invited expert on pharmacology reporting guidelines) participated in the modified Delphi technique. This group included journal editors and experts in nephrology, clinical toxicology, critical care medicine, emergency medicine, and clinical pharmacology. Three independent raters participated in the validation rounds. Panelists voted on a total of 144 items in the first round and 137 items in the second round, with response rates of 96.3% and 98.3%, respectively. Twenty case reports were evaluated at each validation round and the independent raters' response rate was 99.6% and 98.8% per validation round. The final checklist consists of 114 items considered essential for case study reporting. This methodology of alternate voting and external validation rounds was useful in developing the first reporting guideline for case studies in the field of extracorporeal treatments in poisoning. We believe that this guideline will improve the completeness and transparency of published case reports and that the systematic aggregation of information from case reports may provide early signals of effectiveness and/or harm, thereby improving healthcare decision-making. PMID:24890576

  12. Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures.

    PubMed

    Hegazy, Maha A; Lotfy, Hayam M; Mowaka, Shereen; Mohamed, Ekram Hany

    2016-07-05

    Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Estimation of the chemical-induced eye injury using a Weight-of-Evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part II: corrosion potential.

    PubMed

    Verma, Rajeshwar P; Matthews, Edwin J

    2015-03-01

    This is part II of an in silico investigation of chemical-induced eye injury that was conducted at FDA's CFSAN. Serious eye damage caused by chemical (eye corrosion) is assessed using the rabbit Draize test, and this endpoint is an essential part of hazard identification and labeling of industrial and consumer products to ensure occupational and consumer safety. There is an urgent need to develop an alternative to the Draize test because EU's 7th amendment to the Cosmetic Directive (EC, 2003; 76/768/EEC) and recast Regulation now bans animal testing on all cosmetic product ingredients and EU's REACH Program limits animal testing for chemicals in commerce. Although in silico methods have been reported for eye irritation (reversible damage), QSARs specific for eye corrosion (irreversible damage) have not been published. This report describes the development of 21 ANN c-QSAR models (QSAR-21) for assessing eye corrosion potential of chemicals using a large and diverse CFSAN data set of 504 chemicals, ADMET Predictor's three sensitivity analyses and ANNE classification functionalities with 20% test set selection from seven different methods. QSAR-21 models were internally and externally validated and exhibited high predictive performance: average statistics for the training, verification, and external test sets of these models were 96/96/94% sensitivity and 91/91/90% specificity. Copyright © 2014 Elsevier Inc. All rights reserved.

  14. Near infrared spectroscopy for prediction of antioxidant compounds in the honey.

    PubMed

    Escuredo, Olga; Seijo, M Carmen; Salvador, Javier; González-Martín, M Inmaculada

    2013-12-15

    The selection of antioxidant variables in honey is first time considered applying the near infrared (NIR) spectroscopic technique. A total of 60 honey samples were used to develop the calibration models using the modified partial least squares (MPLS) regression method and 15 samples were used for external validation. Calibration models on honey matrix for the estimation of phenols, flavonoids, vitamin C, antioxidant capacity (DPPH), oxidation index and copper using near infrared (NIR) spectroscopy has been satisfactorily obtained. These models were optimised by cross-validation, and the best model was evaluated according to multiple correlation coefficient (RSQ), standard error of cross-validation (SECV), ratio performance deviation (RPD) and root mean standard error (RMSE) in the prediction set. The result of these statistics suggested that the equations developed could be used for rapid determination of antioxidant compounds in honey. This work shows that near infrared spectroscopy can be considered as rapid tool for the nondestructive measurement of antioxidant constitutes as phenols, flavonoids, vitamin C and copper and also the antioxidant capacity in the honey. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Adapting Social Neuroscience Measures for Schizophrenia Clinical Trials, Part 3: Fathoming External Validity

    PubMed Central

    Olbert, Charles M.

    2013-01-01

    It is unknown whether measures adapted from social neuroscience linked to specific neural systems will demonstrate relationships to external variables. Four paradigms adapted from social neuroscience were administered to 173 clinically stable outpatients with schizophrenia to determine their relationships to functionally meaningful variables and to investigate their incremental validity beyond standard measures of social and nonsocial cognition. The 4 paradigms included 2 that assess perception of nonverbal social and action cues (basic biological motion and emotion in biological motion) and 2 that involve higher level inferences about self and others’ mental states (self- referential memory and empathic accuracy). Overall, social neuroscience paradigms showed significant relationships to functional capacity but weak relationships to community functioning; the paradigms also showed weak correlations to clinical symptoms. Evidence for incremental validity beyond standard measures of social and nonsocial cognition was mixed with additional predictive power shown for functional capacity but not community functioning. Of the newly adapted paradigms, the empathic accuracy task had the broadest external validity. These results underscore the difficulty of translating developments from neuroscience into clinically useful tasks with functional significance. PMID:24072806

  16. Adapting social neuroscience measures for schizophrenia clinical trials, part 3: fathoming external validity.

    PubMed

    Olbert, Charles M; Penn, David L; Kern, Robert S; Lee, Junghee; Horan, William P; Reise, Steven P; Ochsner, Kevin N; Marder, Stephen R; Green, Michael F

    2013-11-01

    It is unknown whether measures adapted from social neuroscience linked to specific neural systems will demonstrate relationships to external variables. Four paradigms adapted from social neuroscience were administered to 173 clinically stable outpatients with schizophrenia to determine their relationships to functionally meaningful variables and to investigate their incremental validity beyond standard measures of social and nonsocial cognition. The 4 paradigms included 2 that assess perception of nonverbal social and action cues (basic biological motion and emotion in biological motion) and 2 that involve higher level inferences about self and others' mental states (self-referential memory and empathic accuracy). Overall, social neuroscience paradigms showed significant relationships to functional capacity but weak relationships to community functioning; the paradigms also showed weak correlations to clinical symptoms. Evidence for incremental validity beyond standard measures of social and nonsocial cognition was mixed with additional predictive power shown for functional capacity but not community functioning. Of the newly adapted paradigms, the empathic accuracy task had the broadest external validity. These results underscore the difficulty of translating developments from neuroscience into clinically useful tasks with functional significance.

  17. Effect of simulated forward airspeed on small-scale-model externally blown flap noise

    NASA Technical Reports Server (NTRS)

    Goodykoontz, J. H.; Dorsch, R. G.; Olsen, W. A.

    1976-01-01

    Noise tests were conducted on a small-scale model of an externally blown flap lift augmentation system. The nozzle/wing model was subjected to external flow that simulated takeoff and landing flight velocities by placing it in a 33-centimeter-diameter free jet. The results showed that external flow attenuated the noise associated with the various configurations tested. The amount of attenuation depended on flap setting. More attenuation occurred with a trailing-flap setting of 20 deg than with one of 60 deg. Noise varied with relative velocity as a function of the trailing-flap setting and the angle from the nozzle inlet.

  18. Regional climate simulations with COSMO-CLM over MENA-CORDEX domain

    NASA Astrophysics Data System (ADS)

    Galluccio, Salvatore; Bucchignani, Edoardo; Mercogliano, Paola; Montesarchio, Myriam

    2014-05-01

    In the frame of WCRP Coordinated Regional Downscaling Experiment (CORDEX), a set of common Regional Climate Downscaling (RCD) domains has been defined, as a prerequisite for the development of model evaluation and climate projection frameworks. CORDEX domains encompass the majority of land areas of the world. In this work, climate simulations have been performed over MENA-CORDEX domain, which includes North-Africa, southern Europe and the whole Arabian peninsula. The non-hydrostatic regional climate model COSMO-CLM has been used. At CMCC, regional climate modelling is a part of an integrated simulation system and it has been used in different European and African projects to provide qualitative and quantitative evaluation of the hydrogeological and public health risks. A series of simulations has been conducted over the MENA-CORDEX area at spatial resolution of 0.44°. A sensitivity analysis was conducted to adjust the model configuration to better reproduce the observed climate data. The numerical simulations were driven by ERA-Interim reanalysis (horizontal resolution of 0.703°) for the period 1979-1984; the first year, was considered as a spin up period. The validation was performed by using several data sets: CRU data set was used to validate temperature, precipitation and cloud cover; MERRA data set was used to validate temperature and precipitation and GPCP for precipitation. The model sensitivity to the external parameters was tested considering two different configurations for the surface albedo. In the first one, albedo is only function of soil-type whereas in the second configuration it is prescribed by two external fields for dry and saturated soil based on MODIS data. Moreover, we tested two aerosol distributions as well, namely the default Tanre aerosol distribution and aerosol maps according to Tegen (NASA/GISS). We found, as expected, a significant sensitivity, in particular on the African region. We also varied tuning and physical parameters, such as the scaling factor for the thickness of the laminar boundary layer for heat, which defines the layer with non-turbulent characteristics, mean entrainment rate for shallow convection, cloud ice threshold for autoconversion, radiation and clouds. We choose such parameters following several literature works, which showed that these parameters mostly affect the fields simulated by the model. However, it is known that the sensitivity of a RCM with respect to parameter variations depends, in general, on the model domain, the temporal and spatial scales and the model variables considered. We made a first set of simulations varying one parameter at a time, using Taylor's diagrams, as well as seasonal cycles and bias maps to take tracking changes in the model performance. Successively, we run a second set of simulations in which we varied two or three parameters at a time to get an optimal configuration. The selected configuration is being used to carry out simulations on a 30-years past period, starting from 1979, for three horizontal resolutions, namely 0.44°, 0.22° and 0.11°.

  19. International Technology Transfer of a GCLP-Compliant HIV-1 Neutralizing Antibody Assay for Human Clinical Trials

    PubMed Central

    Todd, Christopher A.; Greene, Kelli M.; Montefiori, David C.; Sarzotti-Kelsoe, Marcella

    2012-01-01

    The Collaboration for AIDS Vaccine Discovery/Comprehensive Antibody – Vaccine Immune Monitoring Consortium (CAVD/CA-VIMC) assisted an international network of laboratories in transferring a validated assay used to judge HIV-1 vaccine immunogenicity in compliance with Good Clinical Laboratory Practice (GCLP) with the goal of adding quality to the conduct of endpoint assays for Human Immunodeficiency Virus I (HIV-1) vaccine human clinical trials. Eight Regional Laboratories in the international setting (Regional Laboratories), many located in regions where the HIV-1 epidemic is most prominent, were selected to implement the standardized, GCLP-compliant Neutralizing Antibody Assay for HIV-1 in TZM-bl Cells (TZM-bl NAb Assay). Each laboratory was required to undergo initial training and implementation of the immunologic assay on-site and then perform partial assay re-validation, competency testing, and undergo formal external audits for GCLP compliance. Furthermore, using a newly established external proficiency testing program for the TZM-bl NAb Assay has allowed the Regional Laboratories to assess the comparability of assay results at their site with the results of neutralizing antibody assays performed around the world. As a result, several of the CAVD/CA-VIMC Regional Laboratories are now in the process of conducting or planning to conduct the GCLP-compliant TZM-bl NAb Assay as an indicator of vaccine immunogenicity for ongoing human clinical trials. PMID:22303476

  20. International technology transfer of a GCLP-compliant HIV-1 neutralizing antibody assay for human clinical trials.

    PubMed

    Ozaki, Daniel A; Gao, Hongmei; Todd, Christopher A; Greene, Kelli M; Montefiori, David C; Sarzotti-Kelsoe, Marcella

    2012-01-01

    The Collaboration for AIDS Vaccine Discovery/Comprehensive Antibody-Vaccine Immune Monitoring Consortium (CAVD/CA-VIMC) assisted an international network of laboratories in transferring a validated assay used to judge HIV-1 vaccine immunogenicity in compliance with Good Clinical Laboratory Practice (GCLP) with the goal of adding quality to the conduct of endpoint assays for Human Immunodeficiency Virus I (HIV-1) vaccine human clinical trials. Eight Regional Laboratories in the international setting (Regional Laboratories), many located in regions where the HIV-1 epidemic is most prominent, were selected to implement the standardized, GCLP-compliant Neutralizing Antibody Assay for HIV-1 in TZM-bl Cells (TZM-bl NAb Assay). Each laboratory was required to undergo initial training and implementation of the immunologic assay on-site and then perform partial assay re-validation, competency testing, and undergo formal external audits for GCLP compliance. Furthermore, using a newly established external proficiency testing program for the TZM-bl NAb Assay has allowed the Regional Laboratories to assess the comparability of assay results at their site with the results of neutralizing antibody assays performed around the world. As a result, several of the CAVD/CA-VIMC Regional Laboratories are now in the process of conducting or planning to conduct the GCLP-compliant TZM-bl NAb Assay as an indicator of vaccine immunogenicity for ongoing human clinical trials.

  1. Generalizing disease management program results: how to get from here to there.

    PubMed

    Linden, Ariel; Adams, John L; Roberts, Nancy

    2004-07-01

    For a disease management (DM) program, the ability to generalize results from the intervention group to the population, to other populations, or to other diseases is as important as demonstrating internal validity. This article provides an overview of the threats to external validity of DM programs, and offers methods to improve the capability for generalizing results obtained through the program. The external validity of DM programs must be evaluated even before program selection and implementation are begun with a prospective new client. Any fundamental differences in characteristics between individuals in an established DM program and in a new population/environment may limit the ability to generalize.

  2. Modelling the distributions and spatial coincidence of bluetongue vectors Culicoides imicola and the Culicoides obsoletus group throughout the Iberian peninsula.

    PubMed

    Calvete, C; Estrada, R; Miranda, M A; Borrás, D; Calvo, J H; Lucientes, J

    2008-06-01

    Data obtained by a Spanish national surveillance programme in 2005 were used to develop climatic models for predictions of the distribution of the bluetongue virus (BTV) vectors Culicoides imicola Kieffer (Diptera: Ceratopogonidae) and the Culicoides obsoletus group Meigen throughout the Iberian peninsula. Models were generated using logistic regression to predict the probability of species occurrence at an 8-km spatial resolution. Predictor variables included the annual mean values and seasonalities of a remotely sensed normalized difference vegetation index (NDVI), a sun index, interpolated precipitation and temperature. Using an information-theoretic paradigm based on Akaike's criterion, a set of best models accounting for 95% of model selection certainty were selected and used to generate an average predictive model for each vector. The predictive performances (i.e. the discrimination capacity and calibration) of the average models were evaluated by both internal and external validation. External validation was achieved by comparing average model predictions with surveillance programme data obtained in 2004 and 2006. The discriminatory capacity of both models was found to be reasonably high. The estimated areas under the receiver operating characteristic (ROC) curve (AUC) were 0.78 and 0.70 for the C. imicola and C. obsoletus group models, respectively, in external validation, and 0.81 and 0.75, respectively, in internal validation. The predictions of both models were in close agreement with the observed distribution patterns of both vectors. Both models, however, showed a systematic bias in their predicted probability of occurrence: observed occurrence was systematically overestimated for C. imicola and underestimated for the C. obsoletus group. Average models were used to determine the areas of spatial coincidence of the two vectors. Although their spatial distributions were highly complementary, areas of spatial coincidence were identified, mainly in Portugal and in the southwest of peninsular Spain. In a hypothetical scenario in which both Culicoides members had similar vectorial capacity for a BTV strain, these areas should be considered of special epidemiological concern because any epizootic event could be intensified by consecutive vector activity developed for both species during the year; consequently, the probability of BTV spreading to remaining areas occupied by both vectors might also be higher.

  3. In silico target prediction for elucidating the mode of action of herbicides including prospective validation.

    PubMed

    Chiddarwar, Rucha K; Rohrer, Sebastian G; Wolf, Antje; Tresch, Stefan; Wollenhaupt, Sabrina; Bender, Andreas

    2017-01-01

    The rapid emergence of pesticide resistance has given rise to a demand for herbicides with new mode of action (MoA). In the agrochemical sector, with the availability of experimental high throughput screening (HTS) data, it is now possible to utilize in silico target prediction methods in the early discovery phase to suggest the MoA of a compound via data mining of bioactivity data. While having been established in the pharmaceutical context, in the agrochemical area this approach poses rather different challenges, as we have found in this work, partially due to different chemistry, but even more so due to different (usually smaller) amounts of data, and different ways of conducting HTS. With the aim to apply computational methods for facilitating herbicide target identification, 48,000 bioactivity data against 16 herbicide targets were processed to train Laplacian modified Naïve Bayesian (NB) classification models. The herbicide target prediction model ("HerbiMod") is an ensemble of 16 binary classification models which are evaluated by internal, external and prospective validation sets. In addition to the experimental inactives, 10,000 random agrochemical inactives were included in the training process, which showed to improve the overall balanced accuracy of our models up to 40%. For all the models, performance in terms of balanced accuracy of≥80% was achieved in five-fold cross validation. Ranking target predictions was addressed by means of z-scores which improved predictivity over using raw scores alone. An external testset of 247 compounds from ChEMBL and a prospective testset of 394 compounds from BASF SE tested against five well studied herbicide targets (ACC, ALS, HPPD, PDS and PROTOX) were used for further validation. Only 4% of the compounds in the external testset lied in the applicability domain and extrapolation (and correct prediction) was hence impossible, which on one hand was surprising, and on the other hand illustrated the utilization of using applicability domains in the first place. However, performance better than 60% in balanced accuracy was achieved on the prospective testset, where all the compounds fell within the applicability domain, and which hence underlines the possibility of using target prediction also in the area of agrochemicals. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Cumulative impact of common genetic variants and other risk factors on colorectal cancer risk in 42,103 individuals

    PubMed Central

    Dunlop, Malcolm G.; Tenesa, Albert; Farrington, Susan M.; Ballereau, Stephane; Brewster, David H.; Pharoah, Paul DP.; Schafmayer, Clemens; Hampe, Jochen; Völzke, Henry; Chang-Claude, Jenny; Hoffmeister, Michael; Brenner, Hermann; von Holst, Susanna; Picelli, Simone; Lindblom, Annika; Jenkins, Mark A.; Hopper, John L.; Casey, Graham; Duggan, David; Newcomb, Polly; Abulí, Anna; Bessa, Xavier; Ruiz-Ponte, Clara; Castellví-Bel, Sergi; Niittymäki, Iina; Tuupanen, Sari; Karhu, Auli; Aaltonen, Lauri; Zanke, Brent W.; Hudson, Thomas J.; Gallinger, Steven; Barclay, Ella; Martin, Lynn; Gorman, Maggie; Carvajal-Carmona, Luis; Walther, Axel; Kerr, David; Lubbe, Steven; Broderick, Peter; Chandler, Ian; Pittman, Alan; Penegar, Steven; Campbell, Harry; Tomlinson, Ian; Houlston, Richard S.

    2016-01-01

    Objective Colorectal cancer (CRC) has a substantial heritable component. Common genetic variation has been shown to contribute to CRC risk. In a large, multi-population study, we set out to assess the feasibility of CRC risk prediction using common genetic variant data, combined with other risk factors. We built a risk prediction model and applied it to the Scottish population using available data. Design Nine populations of European descent were studied to develop and validate colorectal cancer risk prediction models. Binary logistic regression was used to assess the combined effect of age, gender, family history (FH) and genotypes at 10 susceptibility loci that individually only modestly influence colorectal cancer risk. Risk models were generated from case-control data incorporating genotypes alone (n=39,266), and in combination with gender, age and family history (n=11,324). Model discriminatory performance was assessed using 10-fold internal cross-validation and externally using 4,187 independent samples. 10-year absolute risk was estimated by modelling genotype and FH with age- and gender-specific population risks. Results Median number of risk alleles was greater in cases than controls (10 vs 9, p<2.2×10−16), confirmed in external validation sets (Sweden p=1.2×10−6, Finland p=2×10−5). Mean per-allele increase in risk was 9% (OR 1.09; 95% CI 1.05–1.13). Discriminative performance was poor across the risk spectrum (area under curve (AUC) for genotypes alone - 0.57; AUC for genotype/age/gender/FH - 0.59). However, modelling genotype data, FH, age and gender with Scottish population data shows the practicalities of identifying a subgroup with >5% predicted 10-year absolute risk. Conclusion We show that genotype data provides additional information that complements age, gender and FH as risk factors. However, individualized genetic risk prediction is not currently feasible. Nonetheless, the modelling exercise suggests public health potential, since it is possible to stratify the population into CRC risk categories, thereby informing targeted prevention and surveillance. PMID:22490517

  5. Risk assessment and HbA1c measurement in Norwegian community pharmacies to identify people with undiagnosed type 2 diabetes - A feasibility study.

    PubMed

    Risøy, Aslaug Johanne; Kjome, Reidun Lisbet Skeide; Sandberg, Sverre; Sølvik, Una Ørvim

    2018-01-01

    Determine the feasibility of using a diabetes risk assessment tool followed by HbA1c-measurement in a community-pharmacy setting in Norway. In this longitudinal study two pharmacists in each of three community pharmacies were trained to perform risk assessments, HbA1c-measurements and counselling. Pharmacy customers who were > 18 years old and could understand and speak Norwegian or English were recruited in the pharmacies during a two-months-period. Information about the service was presented in local newspapers, social media, leaflets and posters at the pharmacy. Customers wishing to participate contacted the pharmacy staff. Participants completed a validated diabetes risk test and a background questionnaire including a validated instrument for self-rated health. A HbA1c measurement was performed for individuals with a moderate to high risk of developing diabetes. If HbA1c ≥ 6.5% they were recommended to visit their general practitioner for follow-up. The pharmacies performed internal and external quality control of the HbA1c instrument. Of the 211 included participants 97 (46%) were > 50 years old. HbA1c was measured for the 47 participants (22%) with high risk. Thirty-two (15%) had HbA1c values < 5.7%, twelve (5.4%) had values between 5.7%-6.4%, and three (1.4%) had an HbA1c ≥ 6.5%. Two participants with HbA1 ≥ 6.5% were diagnosed with diabetes by their general practitioner. The third was lost to follow-up. Results from internal and external quality control for HbA1c were within set limits. The pharmacists were able to perform the risk assessment and measurement of HbA1c, and pharmacy customers were willing to participate. The HbA1c measurements fulfilled the requirements for analytical quality. Thus, it is feasible to implement this service in community pharmacies in Norway. In a large-scale study the inclusion criteria should be increased to 45 years in accordance with the population the risk test has been validated for.

  6. Risk assessment and HbA1c measurement in Norwegian community pharmacies to identify people with undiagnosed type 2 diabetes – A feasibility study

    PubMed Central

    Kjome, Reidun Lisbet Skeide; Sandberg, Sverre; Sølvik, Una Ørvim

    2018-01-01

    Objectives Determine the feasibility of using a diabetes risk assessment tool followed by HbA1c-measurement in a community-pharmacy setting in Norway. Methods In this longitudinal study two pharmacists in each of three community pharmacies were trained to perform risk assessments, HbA1c-measurements and counselling. Pharmacy customers who were > 18 years old and could understand and speak Norwegian or English were recruited in the pharmacies during a two-months-period. Information about the service was presented in local newspapers, social media, leaflets and posters at the pharmacy. Customers wishing to participate contacted the pharmacy staff. Participants completed a validated diabetes risk test and a background questionnaire including a validated instrument for self-rated health. A HbA1c measurement was performed for individuals with a moderate to high risk of developing diabetes. If HbA1c ≥ 6.5% they were recommended to visit their general practitioner for follow-up. The pharmacies performed internal and external quality control of the HbA1c instrument. Results Of the 211 included participants 97 (46%) were > 50 years old. HbA1c was measured for the 47 participants (22%) with high risk. Thirty-two (15%) had HbA1c values < 5.7%, twelve (5.4%) had values between 5.7%—6.4%, and three (1.4%) had an HbA1c ≥ 6.5%. Two participants with HbA1 ≥ 6.5% were diagnosed with diabetes by their general practitioner. The third was lost to follow-up. Results from internal and external quality control for HbA1c were within set limits. Conclusion The pharmacists were able to perform the risk assessment and measurement of HbA1c, and pharmacy customers were willing to participate. The HbA1c measurements fulfilled the requirements for analytical quality. Thus, it is feasible to implement this service in community pharmacies in Norway. In a large-scale study the inclusion criteria should be increased to 45 years in accordance with the population the risk test has been validated for. PMID:29474501

  7. Considerations Underlying the Use of Mixed Group Validation

    ERIC Educational Resources Information Center

    Jewsbury, Paul A.; Bowden, Stephen C.

    2013-01-01

    Mixed Group Validation (MGV) is an approach for estimating the diagnostic accuracy of tests. MGV is a promising alternative to the more commonly used Known Groups Validation (KGV) approach for estimating diagnostic accuracy. The advantage of MGV lies in the fact that the approach does not require a perfect external validity criterion or gold…

  8. Predicting Blunt Cerebrovascular Injury in Pediatric Trauma: Validation of the “Utah Score”

    PubMed Central

    Ravindra, Vijay M.; Bollo, Robert J.; Sivakumar, Walavan; Akbari, Hassan; Naftel, Robert P.; Limbrick, David D.; Jea, Andrew; Gannon, Stephen; Shannon, Chevis; Birkas, Yekaterina; Yang, George L.; Prather, Colin T.; Kestle, John R.

    2017-01-01

    Abstract Risk factors for blunt cerebrovascular injury (BCVI) may differ between children and adults, suggesting that children at low risk for BCVI after trauma receive unnecessary computed tomography angiography (CTA) and high-dose radiation. We previously developed a score for predicting pediatric BCVI based on retrospective cohort analysis. Our objective is to externally validate this prediction score with a retrospective multi-institutional cohort. We included patients who underwent CTA for traumatic cranial injury at four pediatric Level I trauma centers. Each patient in the validation cohort was scored using the “Utah Score” and classified as high or low risk. Before analysis, we defined a misclassification rate <25% as validating the Utah Score. Six hundred forty-five patients (mean age 8.6 ± 5.4 years; 63.4% males) underwent screening for BCVI via CTA. The validation cohort was 411 patients from three sites compared with the training cohort of 234 patients. Twenty-two BCVIs (5.4%) were identified in the validation cohort. The Utah Score was significantly associated with BCVIs in the validation cohort (odds ratio 8.1 [3.3, 19.8], p < 0.001) and discriminated well in the validation cohort (area under the curve 72%). When the Utah Score was applied to the validation cohort, the sensitivity was 59%, specificity was 85%, positive predictive value was 18%, and negative predictive value was 97%. The Utah Score misclassified 16.6% of patients in the validation cohort. The Utah Score for predicting BCVI in pediatric trauma patients was validated with a low misclassification rate using a large, independent, multicenter cohort. Its implementation in the clinical setting may reduce the use of CTA in low-risk patients. PMID:27297774

  9. A confidence metric for using neurobiological feedback in actor-critic reinforcement learning based brain-machine interfaces

    PubMed Central

    Prins, Noeline W.; Sanchez, Justin C.; Prasad, Abhishek

    2014-01-01

    Brain-Machine Interfaces (BMIs) can be used to restore function in people living with paralysis. Current BMIs require extensive calibration that increase the set-up times and external inputs for decoder training that may be difficult to produce in paralyzed individuals. Both these factors have presented challenges in transitioning the technology from research environments to activities of daily living (ADL). For BMIs to be seamlessly used in ADL, these issues should be handled with minimal external input thus reducing the need for a technician/caregiver to calibrate the system. Reinforcement Learning (RL) based BMIs are a good tool to be used when there is no external training signal and can provide an adaptive modality to train BMI decoders. However, RL based BMIs are sensitive to the feedback provided to adapt the BMI. In actor-critic BMIs, this feedback is provided by the critic and the overall system performance is limited by the critic accuracy. In this work, we developed an adaptive BMI that could handle inaccuracies in the critic feedback in an effort to produce more accurate RL based BMIs. We developed a confidence measure, which indicated how appropriate the feedback is for updating the decoding parameters of the actor. The results show that with the new update formulation, the critic accuracy is no longer a limiting factor for the overall performance. We tested and validated the system onthree different data sets: synthetic data generated by an Izhikevich neural spiking model, synthetic data with a Gaussian noise distribution, and data collected from a non-human primate engaged in a reaching task. All results indicated that the system with the critic confidence built in always outperformed the system without the critic confidence. Results of this study suggest the potential application of the technique in developing an autonomous BMI that does not need an external signal for training or extensive calibration. PMID:24904257

  10. Evaluation of physical activity interventions in children via the reach, efficacy/effectiveness, adoption, implementation, and maintenance (RE-AIM) framework: A systematic review of randomized and non-randomized trials.

    PubMed

    McGoey, Tara; Root, Zach; Bruner, Mark W; Law, Barbi

    2016-01-01

    Existing reviews of physical activity (PA) interventions designed to increase PA behavior exclusively in children (ages 5 to 11years) focus primarily on the efficacy (e.g., internal validity) of the interventions without addressing the applicability of the results in terms of generalizability and translatability (e.g., external validity). This review used the RE-AIM (Reach, Efficacy/Effectiveness, Adoption, Implementation, Maintenance) framework to measure the degree to which randomized and non-randomized PA interventions in children report on internal and external validity factors. A systematic search for controlled interventions conducted within the past 12years identified 78 studies that met the inclusion criteria. Based on the RE-AIM criteria, most of the studies focused on elements of internal validity (e.g., sample size, intervention location and efficacy/effectiveness) with minimal reporting of external validity indicators (e.g., representativeness of participants, start-up costs, protocol fidelity and sustainability). Results of this RE-AIM review emphasize the need for future PA interventions in children to report on real-world challenges and limitations, and to highlight considerations for translating evidence-based results into health promotion practice. Copyright © 2015 Elsevier Inc. All rights reserved.

  11. Validation of a short-term memory test for the recognition of people and faces.

    PubMed

    Leyk, D; Sievert, A; Heiss, A; Gorges, W; Ridder, D; Alexander, T; Wunderlich, M; Ruther, T

    2008-08-01

    Memorising and processing faces is a short-term memory dependent task of utmost importance in the security domain, in which constant and high performance is a must. Especially in access or passport control-related tasks, the timely identification of performance decrements is essential, margins of error are narrow and inadequate performance may have grave consequences. However, conventional short-term memory tests frequently use abstract settings with little relevance to working situations. They may thus be unable to capture task-specific decrements. The aim of the study was to devise and validate a new test, better reflecting job specifics and employing appropriate stimuli. After 1.5 s (short) or 4.5 s (long) presentation, a set of seven portraits of faces had to be memorised for comparison with two control stimuli. Stimulus appearance followed 2 s (first item) and 8 s (second item) after set presentation. Twenty eight subjects (12 male, 16 female) were tested at seven different times of day, 3 h apart. Recognition rates were above 60% even for the least favourable condition. Recognition was significantly better in the 'long' condition (+10%) and for the first item (+18%). Recognition time showed significant differences (10%) between items. Minor effects of learning were found for response latencies only. Based on occupationally relevant metrics, the test displayed internal and external validity, consistency and suitability for further use in test/retest scenarios. In public security, especially where access to restricted areas is monitored, margins of error are narrow and operator performance must remain high and level. Appropriate schedules for personnel, based on valid test results, are required. However, task-specific data and performance tests, permitting the description of task specific decrements, are not available. Commonly used tests may be unsuitable due to undue abstraction and insufficient reference to real-world conditions. Thus, tests are required that account for task-specific conditions and neurophysiological characteristics.

  12. From Research to Clinical Settings: Validation of the Affect in Play Scale – Preschool Brief Version in a Sample of Preschool and School Aged Italian Children

    PubMed Central

    Di Riso, Daniela; Salcuni, Silvia; Lis, Adriana; Delvecchio, Elisa

    2017-01-01

    Affect in Play Scale-Preschool (APS-P) is one of the few standardized tools to measure pretend play. APS-P is an effective measure of symbolic play, able to detect both cognitive and affective dimensions which classically designated play in children, but often are evaluated separately and are scarcely integrated. The scale uses 5 min standardized play task with a set of toys. Recently the scale was extended from 6 to 10 years old and validated in Italy preschool and school-aged children. Some of the main limitations of this measure are that it requires videotaping, verbatim transcripts, and an extensive scoring training, which could compromise its clinical utility. For these reasons, a Brief version of the measure was developed by the original authors. This paper will focus on an APS-P Brief Version and its Extended Version through ages (6–10 years), which consists “in vivo” coding. This study aimed to evaluate construct and external validity of this APS-P Brief Version and its Extended Version in a sample of 538 Italian children aged 4-to-10 years. Confirmatory factor analysis yielded a two correlated factor structure including an affective and a cognitive factor. APS-P-BR and its Extended Version factor scores strongly related to APS-P Extended Version factor scores. Significant relationships were found with a divergent thinking task. Results suggest that the APS-P-BR and its Extended Version is an encouraging brief measure assessing pretend play using toys. It would easily substitute the APS-P and its Extended Version in clinical and research settings, reducing time and difficulties in scoring procedures and maintaining the same strengths. PMID:28553243

  13. Pyrolysis of reinforced polymer composites: Parameterizing a model for multiple compositions

    NASA Astrophysics Data System (ADS)

    Martin, Geraldine E.

    A single set of material properties was developed to describe the pyrolysis of fiberglass reinforced polyester composites at multiple composition ratios. Milligram-scale testing was performed on the unsaturated polyester (UP) resin using thermogravimetric analysis (TGA) coupled with differential scanning calorimetry (DSC) to establish and characterize an effective semi-global reaction mechanism, of three consecutive first-order reactions. Radiation-driven gasification experiments were conducted on UP resin and the fiberglass composites at compositions ranging from 41 to 54 wt% resin at external heat fluxes from 30 to 70 kW m -2. The back surface temperature was recorded with an infrared camera and used as the target for inverse analysis to determine the thermal conductivity of the systematically isolated constituent species. Manual iterations were performed in a comprehensive pyrolysis model, ThermaKin. The complete set of properties was validated for the ability to reproduce the mass loss rate during gasification testing.

  14. Applying Theory across Settings, Behaviors and Populations: Translational Challenges and Opportunities

    PubMed Central

    Mermelstein, Robin J.; Revenson, Tracey A.

    2013-01-01

    Basic social psychological theories have much to contribute to our understanding of health problems and health-related behaviors and may provide potential avenues for intervention development. However, for these theories to have broader reach and applicability to the field of health psychology, more work needs to be done in integrating contexts into these theories and addressing more specifically their application across settings, behaviors, and populations. We argue that integration of these theories into a broader multi-disciplinary and multi-level ecological framework is needed to enhance their translation into real-world applications. To enhance this translation, we make several recommendations, including breaking down silos between disciplinary perspectives and enhancing bidirectional communication and translation; analyzing boundary conditions of theories; expanding research approaches to move outside the laboratory and maintain a focus on external validity; and conducting efficacy testing of theories with meaningful, relevant endpoints. PMID:23646843

  15. Update: Advancement of Contact Dynamics Modeling for Human Spaceflight Simulation Applications

    NASA Technical Reports Server (NTRS)

    Brain, Thomas A.; Kovel, Erik B.; MacLean, John R.; Quiocho, Leslie J.

    2017-01-01

    Pong is a new software tool developed at the NASA Johnson Space Center that advances interference-based geometric contact dynamics based on 3D graphics models. The Pong software consists of three parts: a set of scripts to extract geometric data from 3D graphics models, a contact dynamics engine that provides collision detection and force calculations based on the extracted geometric data, and a set of scripts for visualizing the dynamics response with the 3D graphics models. The contact dynamics engine can be linked with an external multibody dynamics engine to provide an integrated multibody contact dynamics simulation. This paper provides a detailed overview of Pong including the overall approach and modeling capabilities, which encompasses force generation from contact primitives and friction to computational performance. Two specific Pong-based examples of International Space Station applications are discussed, and the related verification and validation using this new tool are also addressed.

  16. Applying theory across settings, behaviors, and populations: translational challenges and opportunities.

    PubMed

    Mermelstein, Robin J; Revenson, Tracey A

    2013-05-01

    Basic social psychological theories have much to contribute to our understanding of health problems and health-related behaviors and may provide potential avenues for intervention development. However, for these theories to have broader reach and applicability to the field of health psychology, more work needs to be done in integrating contexts into these theories and addressing more specifically their application across settings, behaviors, and populations. We argue that integration of these theories into a broader multidisciplinary and multilevel ecological framework is needed to enhance their translation into real-world applications. To enhance this translation, we make several recommendations, including breaking down silos between disciplinary perspectives and enhancing bidirectional communication and translation; analyzing boundary conditions of theories; expanding research approaches to move outside the laboratory and maintain a focus on external validity; and conducting efficacy testing of theories with meaningful, relevant endpoints. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  17. The Research Doesn't Always Apply: Practical Solutions to Evidence-Based Training-Load Monitoring in Elite Team Sports.

    PubMed

    Burgess, Darren J

    2017-04-01

    Research describing load-monitoring techniques for team sport is plentiful. Much of this research is conducted retrospectively and typically involves recreational or semielite teams. Load-monitoring research conducted on professional team sports is largely observational. Challenges exist for the practitioner in implementing peer-reviewed research into the applied setting. These challenges include match scheduling, player adherence, manager/coach buy-in, sport traditions, and staff availability. External-load monitoring often attracts questions surrounding technology reliability and validity, while internal-load monitoring makes some assumptions about player adherence, as well as having some uncertainty around the impact these measures have on player performance This commentary outlines examples of load-monitoring research, discusses the issues associated with the application of this research in an elite team-sport setting, and suggests practical adjustments to the existing research where necessary.

  18. Effective Recruitment of Schools for Randomized Clinical Trials: Role of School Nurses.

    PubMed

    Petosa, R L; Smith, L

    2017-01-01

    In school settings, nurses lead efforts to improve the student health and well-being to support academic success. Nurses are guided by evidenced-based practice and data to inform care decisions. The randomized controlled trial (RCT) is considered the gold standard of scientific rigor for clinical trials. RCTs are critical to the development of evidence-based health promotion programs in schools. The purpose of this article is to present practical solutions to implementing principles of randomization to RCT trials conducted in school settings. Randomization is a powerful sampling method used to build internal and external validity. The school's daily organization and educational mission provide several barriers to randomization. Based on the authors' experience in conducting school-based RCTs, they offer a host of practical solutions to working with schools to successfully implement randomization procedures. Nurses play a critical role in implementing RCTs in schools to promote rigorous science in support of evidence-based practice.

  19. Signal analysis of accelerometry data using gravity-based modeling

    NASA Astrophysics Data System (ADS)

    Davey, Neil P.; James, Daniel A.; Anderson, Megan E.

    2004-03-01

    Triaxial accelerometers have been used to measure human movement parameters in swimming. Interpretation of data is difficult due to interference sources including interaction of external bodies. In this investigation the authors developed a model to simulate the physical movement of the lower back. Theoretical accelerometery outputs were derived thus giving an ideal, or noiseless dataset. An experimental data collection apparatus was developed by adapting a system to the aquatic environment for investigation of swimming. Model data was compared against recorded data and showed strong correlation. Comparison of recorded and modeled data can be used to identify changes in body movement, this is especially useful when cyclic patterns are present in the activity. Strong correlations between data sets allowed development of signal processing algorithms for swimming stroke analysis using first the pure noiseless data set which were then applied to performance data. Video analysis was also used to validate study results and has shown potential to provide acceptable results.

  20. External Heat Transfer Coefficient Measurements on a Surrogate Indirect Inertial Confinement Fusion Target

    DOE PAGES

    Miles, Robin; Havstad, Mark; LeBlanc, Mary; ...

    2015-09-15

    External heat transfer coefficients were measured around a surrogate Indirect inertial confinement fusion (ICF) based on the Laser Inertial Fusion Energy (LIFE) design target to validate thermal models of the LIFE target during flight through a fusion chamber. Results indicate that heat transfer coefficients for this target 25-50 W/m 2∙K are consistent with theoretically derived heat transfer coefficients and valid for use in calculation of target heating during flight through a fusion chamber.

  1. Combining the role of convenience and consideration set size in explaining fish consumption in Norway.

    PubMed

    Rortveit, Asbjorn Warvik; Olsen, Svein Ottar

    2009-04-01

    The purpose of this study is to explore how convenience orientation, perceived product inconvenience and consideration set size are related to attitudes towards fish and fish consumption. The authors present a structural equation model (SEM) based on the integration of two previous studies. The results of a SEM analysis using Lisrel 8.72 on data from a Norwegian consumer survey (n=1630) suggest that convenience orientation and perceived product inconvenience have a negative effect on both consideration set size and consumption frequency. Attitude towards fish has the greatest impact on consumption frequency. The results also indicate that perceived product inconvenience is a key variable since it has a significant impact on attitude, and on consideration set size and consumption frequency. Further, the analyses confirm earlier findings suggesting that the effect of convenience orientation on consumption is partially mediated through perceived product inconvenience. The study also confirms earlier findings suggesting that the consideration set size affects consumption frequency. Practical implications drawn from this research are that the seafood industry would benefit from developing and positioning products that change beliefs about fish as an inconvenient product. Future research for other food categories should be done to enhance the external validity.

  2. Screening experiments of ecstasy street samples using near infrared spectroscopy.

    PubMed

    Sondermann, N; Kovar, K A

    1999-12-20

    Twelve different sets of confiscated ecstasy samples were analysed applying both near infrared spectroscopy in reflectance mode (1100-2500 nm) and high-performance liquid chromatography (HPLC). The sets showed a large variance in composition. A calibration data set was generated based on the theory of factorial designs. It contained 221 N-methyl-3,4-methylenedioxyamphetamine (MDMA) samples, 167 N-ethyl-3,4-methylenedioxyamphetamine (MDE), 111 amphetamine and 106 samples without a controlled substance, which will be called placebo samples thereafter. From this data set, PLS-1 models were calculated and were successfully applied for validation of various external laboratory test sets. The transferability of these results to confiscated tablets is demonstrated here. It is shown that differentiation into placebo, amphetamine and ecstasy samples is possible. Analysis of intact tablets is practicable. However, more reliable results are obtained from pulverised samples. This is due to ill-defined production procedures. The use of mathematically pretreated spectra improves the prediction quality of all the PLS-1 models studied. It is possible to improve discrimination between MDE and MDMA with the help of a second model based on raw spectra. Alternative strategies are briefly discussed.

  3. Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations.

    PubMed

    Wang, Dong-Yu; Done, Susan J; Mc Cready, David R; Leong, Wey L

    2014-07-04

    Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts. An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147). The original training cohort reached a statistically significant difference (p < 0.05) in disease-free survivals between the three CMTC groups after an additional two years of follow-up (median = 55 months). The prognostic value of the triad classification was reproduced in the second independent internal cohort and the new external validation cohort. CMTC achieved even higher prognostic significance when all available patients were analyzed (n = 4,851). Oncogenic pathways Myc, E2F1, Ras and β-catenin were again implicated in the high-risk groups. Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments.

  4. Iterative random vs. Kennard-Stone sampling for IR spectrum-based classification task using PLS2-DA

    NASA Astrophysics Data System (ADS)

    Lee, Loong Chuen; Liong, Choong-Yeun; Jemain, Abdul Aziz

    2018-04-01

    External testing (ET) is preferred over auto-prediction (AP) or k-fold-cross-validation in estimating more realistic predictive ability of a statistical model. With IR spectra, Kennard-stone (KS) sampling algorithm is often used to split the data into training and test sets, i.e. respectively for model construction and for model testing. On the other hand, iterative random sampling (IRS) has not been the favored choice though it is theoretically more likely to produce reliable estimation. The aim of this preliminary work is to compare performances of KS and IRS in sampling a representative training set from an attenuated total reflectance - Fourier transform infrared spectral dataset (of four varieties of blue gel pen inks) for PLS2-DA modeling. The `best' performance achievable from the dataset is estimated with AP on the full dataset (APF, error). Both IRS (n = 200) and KS were used to split the dataset in the ratio of 7:3. The classic decision rule (i.e. maximum value-based) is employed for new sample prediction via partial least squares - discriminant analysis (PLS2-DA). Error rate of each model was estimated repeatedly via: (a) AP on full data (APF, error); (b) AP on training set (APS, error); and (c) ET on the respective test set (ETS, error). A good PLS2-DA model is expected to produce APS, error and EVS, error that is similar to the APF, error. Bearing that in mind, the similarities between (a) APS, error vs. APF, error; (b) ETS, error vs. APF, error and; (c) APS, error vs. ETS, error were evaluated using correlation tests (i.e. Pearson and Spearman's rank test), using series of PLS2-DA models computed from KS-set and IRS-set, respectively. Overall, models constructed from IRS-set exhibits more similarities between the internal and external error rates than the respective KS-set, i.e. less risk of overfitting. In conclusion, IRS is more reliable than KS in sampling representative training set.

  5. External Validation of the Simple Clinical Score and the HOTEL Score, Two Scores for Predicting Short-Term Mortality after Admission to an Acute Medical Unit

    PubMed Central

    Stræde, Mia; Brabrand, Mikkel

    2014-01-01

    Background Clinical scores can be of aid to predict early mortality after admission to a medical admission unit. A developed scoring system needs to be externally validated to minimise the risk of the discriminatory power and calibration to be falsely elevated. We performed the present study with the objective of validating the Simple Clinical Score (SCS) and the HOTEL score, two existing risk stratification systems that predict mortality for medical patients based solely on clinical information, but not only vital signs. Methods Pre-planned prospective observational cohort study. Setting Danish 460-bed regional teaching hospital. Findings We included 3046 consecutive patients from 2 October 2008 until 19 February 2009. 26 (0.9%) died within one calendar day and 196 (6.4%) died within 30 days. We calculated SCS for 1080 patients. We found an AUROC of 0.960 (95% confidence interval [CI], 0.932 to 0.988) for 24-hours mortality and 0.826 (95% CI, 0.774–0.879) for 30-day mortality, and goodness-of-fit test, χ2 = 2.68 (10 degrees of freedom), P = 0.998 and χ2 = 4.00, P = 0.947, respectively. We included 1470 patients when calculating the HOTEL score. Discriminatory power (AUROC) was 0.931 (95% CI, 0.901–0.962) for 24-hours mortality and goodness-of-fit test, χ2 = 5.56 (10 degrees of freedom), P = 0.234. Conclusion We find that both the SCS and HOTEL scores showed an excellent to outstanding ability in identifying patients at high risk of dying with good or acceptable precision. PMID:25144186

  6. Lung cancer in symptomatic patients presenting in primary care: a systematic review of risk prediction tools

    PubMed Central

    Schmidt-Hansen, Mia; Berendse, Sabine; Hamilton, Willie; Baldwin, David R

    2017-01-01

    Background Lung cancer is the leading cause of cancer deaths. Around 70% of patients first presenting to specialist care have advanced disease, at which point current treatments have little effect on survival. The issue for primary care is how to recognise patients earlier and investigate appropriately. This requires an assessment of the risk of lung cancer. Aim The aim of this study was to systematically review the existing risk prediction tools for patients presenting in primary care with symptoms that may indicate lung cancer Design and setting Systematic review of primary care data. Method Medline, PreMedline, Embase, the Cochrane Library, Web of Science, and ISI Proceedings (1980 to March 2016) were searched. The final list of included studies was agreed between two of the authors, who also appraised and summarised them. Results Seven studies with between 1482 and 2 406 127 patients were included. The tools were all based on UK primary care data, but differed in complexity of development, number/type of variables examined/included, and outcome time frame. There were four multivariable tools with internal validation area under the curves between 0.88 and 0.92. The tools all had a number of limitations, and none have been externally validated, or had their clinical and cost impact examined. Conclusion There is insufficient evidence for the recommendation of any one of the available risk prediction tools. However, some multivariable tools showed promising discrimination. What is needed to guide clinical practice is both external validation of the existing tools and a comparative study, so that the best tools can be incorporated into clinical decision tools used in primary care. PMID:28483820

  7. Simulation studies for the evaluation of health information technologies: experiences and results.

    PubMed

    Ammenwerth, Elske; Hackl, Werner O; Binzer, Kristine; Christoffersen, Tue E H; Jensen, Sanne; Lawton, Kitta; Skjoet, Peter; Nohr, Christian

    It is essential for new health information technologies (IT) to undergo rigorous evaluations to ensure they are effective and safe for use in real-world situations. However, evaluation of new health IT is challenging, as field studies are often not feasible when the technology being evaluated is not sufficiently mature. Laboratory-based evaluations have also been shown to have insufficient external validity. Simulation studies seem to be a way to bridge this gap. The aim of this study was to evaluate, using a simulation methodology, the impact of a new prototype of an electronic medication management system on the appropriateness of prescriptions and drug-related activities, including laboratory test ordering or medication changes. This article presents the results of a controlled simulation study with 50 simulation runs, including ten doctors and five simulation patients, and discusses experiences and lessons learnt while conducting the study. Although the new electronic medication management system showed tendencies to improve medication safety when compared with the standard system, this tendency was not significant. Altogether, five distinct situations were identified where the new medication management system did help to improve medication safety. This simulation study provided a good compromise between internal validity and external validity. However, several challenges need to be addressed when undertaking simulation evaluations including: preparation of adequate test cases; training of participants before using unfamiliar applications; consideration of time, effort and costs of conducting the simulation; technical maturity of the evaluated system; and allowing adequate preparation of simulation scenarios and simulation setting. Simulation studies are an interesting but time-consuming approach, which can be used to evaluate newly developed health IT systems, particularly those systems that are not yet sufficiently mature to undergo field evaluation studies.

  8. Integrated tokamak modeling: when physics informs engineering and research planning

    NASA Astrophysics Data System (ADS)

    Poli, Francesca

    2017-10-01

    Simulations that integrate virtually all the relevant engineering and physics aspects of a real tokamak experiment are a power tool for experimental interpretation, model validation and planning for both present and future devices. This tutorial will guide through the building blocks of an ``integrated'' tokamak simulation, such as magnetic flux diffusion, thermal, momentum and particle transport, external heating and current drive sources, wall particle sources and sinks. Emphasis is given to the connection and interplay between external actuators and plasma response, between the slow time scales of the current diffusion and the fast time scales of transport, and how reduced and high-fidelity models can contribute to simulate a whole device. To illustrate the potential and limitations of integrated tokamak modeling for discharge prediction, a helium plasma scenario for the ITER pre-nuclear phase is taken as an example. This scenario presents challenges because it requires core-edge integration and advanced models for interaction between waves and fast-ions, which are subject to a limited experimental database for validation and guidance. Starting from a scenario obtained by re-scaling parameters from the demonstration inductive ``ITER baseline'', it is shown how self-consistent simulations that encompass both core and edge plasma regions, as well as high-fidelity heating and current drive source models are needed to set constraints on the density, magnetic field and heating scheme. This tutorial aims at demonstrating how integrated modeling, when used with adequate level of criticism, can not only support design of operational scenarios, but also help to asses the limitations and gaps in the available models, thus indicating where improved modeling tools are required and how present experiments can help their validation and inform research planning. Work supported by DOE under DE-AC02-09CH1146.

  9. Development of a relationship between external measurements and reinforcement stress

    NASA Astrophysics Data System (ADS)

    Brault, Andre; Hoult, Neil A.; Lees, Janet M.

    2015-03-01

    As many countries around the world face an aging infrastructure crisis, there is an increasing need to develop more accurate monitoring and assessment techniques for reinforced concrete structures. One of the challenges associated with assessing existing infrastructure is correlating externally measured parameters such as crack widths and surface strains with reinforcement stresses as this is dependent on a number of variables. The current research investigates how the use of distributed fiber optic sensors to measure reinforcement strain can be correlated with digital image correlation measurements of crack widths to relate external crack width measurements to reinforcement stresses. An initial set of experiments was undertaken involving a series of small-scale beam specimens tested in three-point bending with variable reinforcement properties. Relationships between crack widths and internal reinforcement strains were observed including that both the diameter and number of bars affected the measured maximum strain and crack width. A model that uses measured crack width to estimate reinforcement strain was presented and compared to the experimental results. The model was found to provide accurate estimates of load carrying capacity for a given crack width, however, the model was potentially less accurate when crack widths were used to estimate the experimental reinforcement strains. The need for more experimental data to validate the conclusions of this research was also highlighted.

  10. Development and testing of the KERNset: an instrument to assess the quality of telephone triage in out-of-hours primary care services.

    PubMed

    Smits, Marleen; Keizer, Ellen; Ram, Paul; Giesen, Paul

    2017-12-02

    Telephone triage is a core but vulnerable part of the care process at out-of-hours general practitioner (GP) cooperatives. In the Netherlands, different instruments have been used for assessing the quality of telephone triage. These instruments focussed mainly on communicational aspects, and less on the medical quality of triage decisions. Our aim was to develop and test a minimum set of items to assess the quality of telephone triage. A national survey among all GP cooperatives in the Netherlands was performed to examine the most important aspects of telephone triage. Next, corresponding items from existing instruments were searched on these topics. Subsequently, an expert panel judged these items on importance, completeness and formulation. The concept KERNset consisted of 24 items about the telephone conversation: 13 medical, ten communicational and one regarding both types. It was pilot tested on measurement characteristics, reliability, validity and variation between triagists. In this pilot study, 114 anonymous calls from four GP cooperatives spread across the Netherlands were judged by three out of eight raters, both internal and external raters. Cronbach's alpha was .94 for the medical items and .75 for the communicational items. Inter-rater reliability: complete agreement between the external raters was 45% and reasonable agreement 73% (difference of maximally one point on the five-point scale). Intra-rater reliability: complete agreement within raters was 55% and reasonable agreement 84%. There were hardly any differences between internal and external raters, but there were differences in strictness between individual raters. The construct validity was confirmed by the high correlation between the general impression of the call and the items of the KERNset. Of the differences within items 19% could be explained by differences between triage nurses, which means the KERNset is able to demonstrate differences between triage nurses. The KERNset can be used to assess the quality of telephone triage. The validity is good and differences between calls and between triage nurses can be measured. A more intensive training for raters could improve the reliability.

  11. Validation of a predictive model for identifying febrile young infants with altered urinalysis at low risk of invasive bacterial infection.

    PubMed

    Velasco, R; Gómez, B; Hernández-Bou, S; Olaciregui, I; de la Torre, M; González, A; Rivas, A; Durán, I; Rubio, A

    2017-02-01

    In 2015, a predictive model for invasive bacterial infection (IBI) in febrile young infants with altered urine dipstick was published. The aim of this study was to externally validate a previously published set of low risk criteria for invasive bacterial infection in febrile young infants with altered urine dipstick. Retrospective multicenter study including nine Spanish hospitals. Febrile infants ≤90 days old with altered urinalysis (presence of leukocyturia and/or nitrituria) were included. According to our predictive model, an infant is classified as low-risk for IBI when meeting all the following: appearing well at arrival to the emergency department, being >21 days old, having a procalcitonin value <0.5 ng/mL and a C-reactive protein value <20 mg/L. IBI was considered as secondary to urinary tract infection if the same pathogen was isolated in the urine culture and in the blood or cerebrospinal fluid culture. A total of 391 patients with altered urine dipstick were included. Thirty (7.7 %) of them developed an IBI, with 26 (86.7 %) of them secondary to UTI. Prevalence of IBI was 2/104 (1.9 %; CI 95% 0.5-6.7) among low-risk patients vs 28/287 (9.7 %; CI 95% 6.8-13.7) among high-risk patients (p < 0.05). Sensitivity of the model was 93.3 % (CI 95% 78.7-98.2) and negative predictive value was 98.1 % (93.3-99.4). Although our predictive model was shown to be less accurate in the validation cohort, it still showed a good discriminatory ability to detect IBI. Larger prospective external validation studies, taking into account fever duration as well as the role of ED observation, should be undertaken before its implementation into clinical practice.

  12. Predicting stress urinary incontinence during pregnancy: combination of pelvic floor ultrasound parameters and clinical factors.

    PubMed

    Chen, Ling; Luo, Dan; Yu, Xiajuan; Jin, Mei; Cai, Wenzhi

    2018-05-12

    The aim of this study was to develop and validate a predictive tool that combining pelvic floor ultrasound parameters and clinical factors for stress urinary incontinence during pregnancy. A total of 535 women in first or second trimester were included for an interview and transperineal ultrasound assessment from two hospitals. Imaging data sets were analyzed offline to assess for bladder neck vertical position, urethra angles (α, β, and γ angles), hiatal area and bladder neck funneling. All significant continuous variables at univariable analysis were analyzed by receiver-operating characteristics. Three multivariable logistic models were built on clinical factor, and combined with ultrasound parameters. The final predictive model with best performance and fewest variables was selected to establish a nomogram. Internal and external validation of the nomogram were performed by both discrimination represented by C-index and calibration measured by Hosmer-Lemeshow test. A decision curve analysis was conducted to determine the clinical utility of the nomogram. After excluding 14 women with invalid data, 521 women were analyzed. β angle, γ angle and hiatal area had limited predictive value for stress urinary incontinence during pregnancy, with area under curves of 0.558-0.648. The final predictive model included body mass index gain since pregnancy, constipation, previous delivery mode, β angle at rest, and bladder neck funneling. The nomogram based on the final model showed good discrimination with a C-index of 0.789 and satisfactory calibration (P=0.828), both of which were supported by external validation. Decision curve analysis showed that the nomogram was clinical useful. The nomogram incorporating both the pelvic floor ultrasound parameters and clinical factors has been validated to show good discrimination and calibration, and could be an important tool for stress urinary incontinence risk prediction at an early stage of pregnancy. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  13. The Introduction of Standardized External Testing in Ukraine: Challenges and Successes

    ERIC Educational Resources Information Center

    Kovalchuk, Serhiy; Koroliuk, Svitlana

    2012-01-01

    Standardized external testing (SET) began to be implemented in Ukraine in 2008 as an instrument for combating corruption in higher education and ensuring fair university admission. This article examines the conditions and processes that led to the introduction of SET, overviews its implementation over three years (2008-10), analyzes SET and…

  14. Prognostic value of purinergic P2X7 receptor expression in patients with hepatocellular carcinoma after curative resection.

    PubMed

    Liu, Haiou; Liu, Weisi; Liu, Zheng; Liu, Yidong; Zhang, Weijuan; Xu, Le; Xu, Jiejie

    2015-07-01

    The family of type 2 purinergic (P2) receptors, especially P2X7, is responsible for the direct tumor-killing functions of extracellular adenosine triphosphate (ATP), but the precise role of P2X7 in the progression of hepatocellular carcinoma (HCC) remains elusive. This study aims to evaluate prognostic value of P2X7 expression in HCC patients after surgical resection. Expression of P2X7 was assessed by immunohistochemistry in tissue microarrays containing paired tumor and peritumoral liver tissues from 273 patients with HCC who had undergone hepatectomy between 2006 and 2007. Prognostic value of P2X7 expression and clinical outcomes were evaluated. Peritumoral P2X7 expression was significantly higher than intratumoral P2X7 expression. No significant prognostic difference was observed for overall survival for intratumoral P2X7 density, whereas peritumoral P2X7 density indicates unfavorable overall survival in training set and BCLC stage 0-A subset. Besides, peritumoral P2X7 density, which correlated with tumor size, venous invasion, and BCLC stage, was identified as an independent poor prognosticator for overall survival and recurrence-free survival. The association was further validated in validation set. Peritumoral P2X7 is a potential unfavorable prognosticator for overall survival and recurrence free survival in HCC patients after surgical resection. Further external validation and functional analysis should be pursued to evaluate its potential prognostic value and therapeutic significance for HCC patients.

  15. The establishment and external validation of NIR qualitative analysis model for waste polyester-cotton blend fabrics.

    PubMed

    Li, Feng; Li, Wen-Xia; Zhao, Guo-Liang; Tang, Shi-Jun; Li, Xue-Jiao; Wu, Hong-Mei

    2014-10-01

    A series of 354 polyester-cotton blend fabrics were studied by the near-infrared spectra (NIRS) technology, and a NIR qualitative analysis model for different spectral characteristics was established by partial least squares (PLS) method combined with qualitative identification coefficient. There were two types of spectrum for dying polyester-cotton blend fabrics: normal spectrum and slash spectrum. The slash spectrum loses its spectral characteristics, which are effected by the samples' dyes, pigments, matting agents and other chemical additives. It was in low recognition rate when the model was established by the total sample set, so the samples were divided into two types of sets: normal spectrum sample set and slash spectrum sample set, and two NIR qualitative analysis models were established respectively. After the of models were established the model's spectral region, pretreatment methods and factors were optimized based on the validation results, and the robustness and reliability of the model can be improved lately. The results showed that the model recognition rate was improved greatly when they were established respectively, the recognition rate reached up to 99% when the two models were verified by the internal validation. RC (relation coefficient of calibration) values of the normal spectrum model and slash spectrum model were 0.991 and 0.991 respectively, RP (relation coefficient of prediction) values of them were 0.983 and 0.984 respectively, SEC (standard error of calibration) values of them were 0.887 and 0.453 respectively, SEP (standard error of prediction) values of them were 1.131 and 0.573 respectively. A series of 150 bounds samples reached used to verify the normal spectrum model and slash spectrum model and the recognition rate reached up to 91.33% and 88.00% respectively. It showed that the NIR qualitative analysis model can be used for identification in the recycle site for the polyester-cotton blend fabrics.

  16. Development and validation of a medical chart review checklist for symptom management performance of oncologists in the routine care of patients with advanced cancer.

    PubMed

    Blum, David; Rosa, Daniel; deWolf-Linder, Susanne; Hayoz, Stefanie; Ribi, Karin; Koeberle, Dieter; Strasser, Florian

    2014-12-01

    Oncologists perform a range of pharmacological and nonpharmacological interventions to manage the symptoms of outpatients with advanced cancer. The aim of this study was to develop and test a symptom management performance checklist (SyMPeC) to review medical charts. First, the content of the checklist was determined by consensus of an interprofessional team. The SyMPeC was tested using the data set of the SAKK 96/06 E-MOSAIC (Electronical Monitoring of Symptoms and Syndromes Associated with Cancer) trial, which included six consecutive visits from 247 patients. In a test data set (half of the data) of medical charts, two people extracted and quantified the definitions of the parameters (content validity). To assess the inter-rater reliability, three independent researchers used the SyMPeC on a random sample (10% of the test data set), and Fleiss's kappa was calculated. To test external validity, the interventions retrieved by the SyMPeC chart review were compared with nurse-led assessment of patient-perceived oncologists' palliative interventions. Five categories of symptoms were included: pain, fatigue, anorexia/nausea, dyspnea, and depression/anxiety. Interventions were categorized as symptom specific or symptom unspecific. In the test data set of 123 patients, 402 unspecific and 299 symptom-specific pharmacological interventions were detected. Nonpharmacological interventions (n = 242) were mostly symptom unspecific. Fleiss's kappa for symptom and intervention detections was K = 0.7 and K = 0.86, respectively. In 1003 of 1167 visits (86%), there was a match between SyMPeC and nurse-led assessment. Seventy-nine percent (195 of 247) of patients had no or one mismatch. Chart review by SyMPeC seems reliable to detect symptom management interventions by oncologists in outpatient clinics. Nonpharmacological interventions were less symptom specific. A template for documentation is needed for standardization. Copyright © 2014 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

  17. Reduced serum club cell protein as a pulmonary damage marker for chronic fine particulate matter exposure in Chinese population.

    PubMed

    Wang, Yanhua; Duan, Huawei; Meng, Tao; Shen, Meili; Ji, Qianpeng; Xing, Jie; Wang, Qingrong; Wang, Ting; Niu, Yong; Yu, Tao; Liu, Zhong; Jia, Hongbing; Zhan, Yuliang; Chen, Wen; Zhang, Zhihu; Su, Wenge; Dai, Yufei; Zhang, Xuchun; Zheng, Yuxin

    2018-03-01

    Exposure to fine particulate matter (PM 2.5 ) pollution is associated with increased morbidity and mortality from respiratory diseases. However, few population-based studies have been conducted to assess the alterations in circulating pulmonary proteins due to long-term PM 2.5 exposure. We designed a two-stage study. In the first stage (training set), we assessed the associations between PM 2.5 exposure and levels of pulmonary damage markers (CC16, SP-A and SP-D) and lung function in a coke oven emission (COE) cohort with 558 coke plant workers and 210 controls. In the second stage (validation set), significant initial findings were validated by an independent diesel engine exhaust (DEE) cohort with 50 DEE exposed workers and 50 controls. Serum CC16 levels decreased in a dose response manner in association with both external and internal PM 2.5 exposures in the two cohorts. In the training set, serum CC16 levels decreased with increasing duration of occupational PM 2.5 exposure history. An interquartile range (IQR) (122.0μg/m 3 ) increase in PM 2.5 was associated with a 5.76% decrease in serum CC16 levels, whereas an IQR (1.06μmol/mol creatinine) increase in urinary 1-hydroxypyrene (1-OHP) concentration was associated with a 5.36% decrease in serum CC16 levels in the COE cohort. In the validation set, the concentration of serum CC16 in the PM 2.5 exposed group was 22.42% lower than that of the controls and an IQR (1.24μmol/mol creatinine) increase in urinary 1-OHP concentration was associated with a 12.24% decrease in serum CC16 levels in the DEE cohort. Serum CC16 levels may be a sensitive marker for pulmonary damage in populations with high PM 2.5 exposure. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. No need for external orthogonality in subsystem density-functional theory.

    PubMed

    Unsleber, Jan P; Neugebauer, Johannes; Jacob, Christoph R

    2016-08-03

    Recent reports on the necessity of using externally orthogonal orbitals in subsystem density-functional theory (SDFT) [Annu. Rep. Comput. Chem., 8, 2012, 53; J. Phys. Chem. A, 118, 2014, 9182] are re-investigated. We show that in the basis-set limit, supermolecular Kohn-Sham-DFT (KS-DFT) densities can exactly be represented as a sum of subsystem densities, even if the subsystem orbitals are not externally orthogonal. This is illustrated using both an analytical example and in basis-set free numerical calculations for an atomic test case. We further show that even with finite basis sets, SDFT calculations using accurate reconstructed potentials can closely approach the supermolecular KS-DFT density, and that the deviations between SDFT and KS-DFT decrease as the basis-set limit is approached. Our results demonstrate that formally, there is no need to enforce external orthogonality in SDFT, even though this might be a useful strategy when developing projection-based DFT embedding schemes.

  19. Using beta binomials to estimate classification uncertainty for ensemble models.

    PubMed

    Clark, Robert D; Liang, Wenkel; Lee, Adam C; Lawless, Michael S; Fraczkiewicz, Robert; Waldman, Marvin

    2014-01-01

    Quantitative structure-activity (QSAR) models have enormous potential for reducing drug discovery and development costs as well as the need for animal testing. Great strides have been made in estimating their overall reliability, but to fully realize that potential, researchers and regulators need to know how confident they can be in individual predictions. Submodels in an ensemble model which have been trained on different subsets of a shared training pool represent multiple samples of the model space, and the degree of agreement among them contains information on the reliability of ensemble predictions. For artificial neural network ensembles (ANNEs) using two different methods for determining ensemble classification - one using vote tallies and the other averaging individual network outputs - we have found that the distribution of predictions across positive vote tallies can be reasonably well-modeled as a beta binomial distribution, as can the distribution of errors. Together, these two distributions can be used to estimate the probability that a given predictive classification will be in error. Large data sets comprised of logP, Ames mutagenicity, and CYP2D6 inhibition data are used to illustrate and validate the method. The distributions of predictions and errors for the training pool accurately predicted the distribution of predictions and errors for large external validation sets, even when the number of positive and negative examples in the training pool were not balanced. Moreover, the likelihood of a given compound being prospectively misclassified as a function of the degree of consensus between networks in the ensemble could in most cases be estimated accurately from the fitted beta binomial distributions for the training pool. Confidence in an individual predictive classification by an ensemble model can be accurately assessed by examining the distributions of predictions and errors as a function of the degree of agreement among the constituent submodels. Further, ensemble uncertainty estimation can often be improved by adjusting the voting or classification threshold based on the parameters of the error distribution. Finally, the profiles for models whose predictive uncertainty estimates are not reliable provide clues to that effect without the need for comparison to an external test set.

  20. Sherlock Holmes and child psychopathology assessment approaches: the case of the false-positive.

    PubMed

    Jensen, P S; Watanabe, H

    1999-02-01

    To explore the relative value of various methods of assessing childhood psychopathology, the authors compared 4 groups of children: those who met criteria for one or more DSM diagnoses and scored high on parent symptom checklists, those who met psychopathology criteria on either one of these two assessment approaches alone, and those who met no psychopathology assessment criterion. Parents of 201 children completed the Child Behavior Checklist (CBCL), after which children and parents were administered the Diagnostic Interview Schedule for Children (version 2.1). Children and parents also completed other survey measures and symptom report inventories. The 4 groups of children were compared against "external validators" to examine the merits of "false-positive" and "false-negative" cases. True-positive cases (those that met DSM criteria and scored high on the CBCL) differed significantly from the true-negative cases on most external validators. "False-positive" and "false-negative" cases had intermediate levels of most risk factors and external validators. "False-positive" cases were not normal per se because they scored significantly above the true-negative group on a number of risk factors and external validators. A similar but less marked pattern was noted for "false-negatives." Findings call into question whether cases with high symptom checklist scores despite no formal diagnoses should be considered "false-positive." Pending the availability of robust markers for mental illness, researchers and clinicians must resist the tendency to reify diagnostic categories or to engage in arcane debates about the superiority of one assessment approach over another.

  1. Validation of the DECAF score to predict hospital mortality in acute exacerbations of COPD

    PubMed Central

    Echevarria, C; Steer, J; Heslop-Marshall, K; Stenton, SC; Hickey, PM; Hughes, R; Wijesinghe, M; Harrison, RN; Steen, N; Simpson, AJ; Gibson, GJ; Bourke, SC

    2016-01-01

    Background Hospitalisation due to acute exacerbations of COPD (AECOPD) is common, and subsequent mortality high. The DECAF score was derived for accurate prediction of mortality and risk stratification to inform patient care. We aimed to validate the DECAF score, internally and externally, and to compare its performance to other predictive tools. Methods The study took place in the two hospitals within the derivation study (internal validation) and in four additional hospitals (external validation) between January 2012 and May 2014. Consecutive admissions were identified by screening admissions and searching coding records. Admission clinical data, including DECAF indices, and mortality were recorded. The prognostic value of DECAF and other scores were assessed by the area under the receiver operator characteristic (AUROC) curve. Results In the internal and external validation cohorts, 880 and 845 patients were recruited. Mean age was 73.1 (SD 10.3) years, 54.3% were female, and mean (SD) FEV1 45.5 (18.3) per cent predicted. Overall mortality was 7.7%. The DECAF AUROC curve for inhospital mortality was 0.83 (95% CI 0.78 to 0.87) in the internal cohort and 0.82 (95% CI 0.77 to 0.87) in the external cohort, and was superior to other prognostic scores for inhospital or 30-day mortality. Conclusions DECAF is a robust predictor of mortality, using indices routinely available on admission. Its generalisability is supported by consistent strong performance; it can identify low-risk patients (DECAF 0–1) potentially suitable for Hospital at Home or early supported discharge services, and high-risk patients (DECAF 3–6) for escalation planning or appropriate early palliation. Trial registration number UKCRN ID 14214. PMID:26769015

  2. Evaluating diagnosis-based case-mix measures: how well do they apply to the VA population?

    PubMed

    Rosen, A K; Loveland, S; Anderson, J J; Rothendler, J A; Hankin, C S; Rakovski, C C; Moskowitz, M A; Berlowitz, D R

    2001-07-01

    Diagnosis-based case-mix measures are increasingly used for provider profiling, resource allocation, and capitation rate setting. Measures developed in one setting may not adequately capture the disease burden in other settings. To examine the feasibility of adapting two such measures, Adjusted Clinical Groups (ACGs) and Diagnostic Cost Groups (DCGs), to the Department of Veterans Affairs (VA) population. A 60% random sample of veterans who used health care services during FY 1997 was obtained from VA inpatient and outpatient administrative databases. A split-sample technique was used to obtain a 40% sample (n = 1,046,803) for development and a 20% sample (n = 524,461) for validation. Concurrent ACG and DCG risk adjustment models, using 1997 diagnoses and demographics to predict FY 1997 utilization (ambulatory provider encounters, and service days-the sum of a patient's inpatient and outpatient visit days), were fitted and cross-validated. Patients were classified into groupings that indicated a population with multiple psychiatric and medical diseases. Model R-squares explained between 6% and 32% of the variation in service utilization. Although reparameterized models did better in predicting utilization than models with external weights, none of the models was adequate in characterizing the entire population. For predicting service days, DCGs were superior to ACGs in most categories, whereas ACGs did better at discriminating among veterans who had the lowest utilization. Although "off-the-shelf" case-mix measures perform moderately well when applied to another setting, modifications may be required to accurately characterize a population's disease burden with respect to the resource needs of all patients.

  3. Data-constrained models of quiet and storm-time geosynchronous magnetic field based on observations in the near geospace

    NASA Astrophysics Data System (ADS)

    Andreeva, V. A.; Tsyganenko, N. A.

    2017-12-01

    The geosynchronous orbit is unique in that its nightside segment skims along the boundary, separating the inner magnetosphere with a predominantly dipolar configuration from the magnetotail, where the Earth's magnetic field becomes small relative to the contribution from external sources. The ability to accurately reconstruct the magnetospheric configuration at GEO is important to understand the behavior of plasma and energetic particles, which critically affect space weather in the area densely populated by a host of satellites. To that end, we have developed a dynamical empirical model of the geosynchronous magnetic field with forecasting capability, based on a multi-year set of data taken by THEMIS, Polar, Cluster, Geotail, and Van Allen missions. The model's mathematical structure is devised using a new approach [Andreeva and Tsyganenko, 2016, doi:10.1002/2015JA022242], in which the toroidal/poloidal components of the field are represented using the radial and azimuthal basis functions. The model describes the field as a function of solar-magnetic coordinates, geodipole tilt angle, solar wind pressure, and a set of dynamic variables, quantifying the magnetosphere's response to external driving/loading and internal relaxation/dissipation during the disturbance recovery. The response variables are introduced following the approach by Tsyganenko and Sitnov [2005, doi:10.1029/2004JA010798], in which the electric current dynamics was described as a result of competition between the external energy input and the subsequent internal losses of the injected energy. The model's applicability range extends from quiet to moderately disturbed conditions, with peak Sym-H values -150 nT. The obtained results have been validated using independent GOES magnetometer data, taken during the maximum of the 23rd solar cycle and its declining phase.

  4. Nomogram predicting response after chemoradiotherapy in rectal cancer using sequential PETCT imaging: a multicentric prospective study with external validation.

    PubMed

    van Stiphout, Ruud G P M; Valentini, Vincenzo; Buijsen, Jeroen; Lammering, Guido; Meldolesi, Elisa; van Soest, Johan; Leccisotti, Lucia; Giordano, Alessandro; Gambacorta, Maria A; Dekker, Andre; Lambin, Philippe

    2014-11-01

    To develop and externally validate a predictive model for pathologic complete response (pCR) for locally advanced rectal cancer (LARC) based on clinical features and early sequential (18)F-FDG PETCT imaging. Prospective data (i.a. THUNDER trial) were used to train (N=112, MAASTRO Clinic) and validate (N=78, Università Cattolica del S. Cuore) the model for pCR (ypT0N0). All patients received long-course chemoradiotherapy (CRT) and surgery. Clinical parameters were age, gender, clinical tumour (cT) stage and clinical nodal (cN) stage. PET parameters were SUVmax, SUVmean, metabolic tumour volume (MTV) and maximal tumour diameter, for which response indices between pre-treatment and intermediate scan were calculated. Using multivariate logistic regression, three probability groups for pCR were defined. The pCR rates were 21.4% (training) and 23.1% (validation). The selected predictive features for pCR were cT-stage, cN-stage, response index of SUVmean and maximal tumour diameter during treatment. The models' performances (AUC) were 0.78 (training) and 0.70 (validation). The high probability group for pCR resulted in 100% correct predictions for training and 67% for validation. The model is available on the website www.predictcancer.org. The developed predictive model for pCR is accurate and externally validated. This model may assist in treatment decisions during CRT to select complete responders for a wait-and-see policy, good responders for extra RT boost and bad responders for additional chemotherapy. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  5. Robustness and Uncertainty: Applications for Policy in Climate and Hydrological Modeling

    NASA Astrophysics Data System (ADS)

    Fields, A. L., III

    2015-12-01

    Policymakers must often decide how to proceed when presented with conflicting simulation data from hydrological, climatological, and geological models. While laboratory sciences often appeal to the reproducibility of results to argue for the validity of their conclusions, simulations cannot use this strategy for a number of pragmatic and methodological reasons. However, robustness of predictions and causal structures can serve the same function for simulations as reproducibility does for laboratory experiments and field observations in either adjudicating between conflicting results or showing that there is insufficient justification to externally validate the results. Additionally, an interpretation of the argument from robustness is presented that involves appealing to the convergence of many well-built and diverse models rather than the more common version which involves appealing to the probability that one of a set of models is likely to be true. This interpretation strengthens the case for taking robustness as an additional requirement for the validation of simulation results and ultimately supports the idea that computer simulations can provide information about the world that is just as trustworthy as data from more traditional laboratory studies and field observations. Understanding the importance of robust results for the validation of simulation data is especially important for policymakers making decisions on the basis of potentially conflicting models. Applications will span climate, hydrological, and hydroclimatological models.

  6. Computer-aided design of liposomal drugs: In silico prediction and experimental validation of drug candidates for liposomal remote loading.

    PubMed

    Cern, Ahuva; Barenholz, Yechezkel; Tropsha, Alexander; Goldblum, Amiram

    2014-01-10

    Previously we have developed and statistically validated Quantitative Structure Property Relationship (QSPR) models that correlate drugs' structural, physical and chemical properties as well as experimental conditions with the relative efficiency of remote loading of drugs into liposomes (Cern et al., J. Control. Release 160 (2012) 147-157). Herein, these models have been used to virtually screen a large drug database to identify novel candidate molecules for liposomal drug delivery. Computational hits were considered for experimental validation based on their predicted remote loading efficiency as well as additional considerations such as availability, recommended dose and relevance to the disease. Three compounds were selected for experimental testing which were confirmed to be correctly classified by our previously reported QSPR models developed with Iterative Stochastic Elimination (ISE) and k-Nearest Neighbors (kNN) approaches. In addition, 10 new molecules with known liposome remote loading efficiency that were not used by us in QSPR model development were identified in the published literature and employed as an additional model validation set. The external accuracy of the models was found to be as high as 82% or 92%, depending on the model. This study presents the first successful application of QSPR models for the computer-model-driven design of liposomal drugs. © 2013.

  7. Computer-aided design of liposomal drugs: in silico prediction and experimental validation of drug candidates for liposomal remote loading

    PubMed Central

    Cern, Ahuva; Barenholz, Yechezkel; Tropsha, Alexander; Goldblum, Amiram

    2014-01-01

    Previously we have developed and statistically validated Quantitative Structure Property Relationship (QSPR) models that correlate drugs’ structural, physical and chemical properties as well as experimental conditions with the relative efficiency of remote loading of drugs into liposomes (Cern et al, Journal of Controlled Release, 160(2012) 14–157). Herein, these models have been used to virtually screen a large drug database to identify novel candidate molecules for liposomal drug delivery. Computational hits were considered for experimental validation based on their predicted remote loading efficiency as well as additional considerations such as availability, recommended dose and relevance to the disease. Three compounds were selected for experimental testing which were confirmed to be correctly classified by our previously reported QSPR models developed with Iterative Stochastic Elimination (ISE) and k-nearest neighbors (kNN) approaches. In addition, 10 new molecules with known liposome remote loading efficiency that were not used in QSPR model development were identified in the published literature and employed as an additional model validation set. The external accuracy of the models was found to be as high as 82% or 92%, depending on the model. This study presents the first successful application of QSPR models for the computer-model-driven design of liposomal drugs. PMID:24184343

  8. Validation of External Corrosion Growth-Rate Using Polarization Resistance and Soil Properties

    DOT National Transportation Integrated Search

    2010-08-01

    The research project evaluated the use of the Linear Polarization Resistance (LPR) and the Electric Resistance (ER) technologies in estimating the external corrosion growth rates of buried steel pipelines. This was achieved by performing laboratory a...

  9. Cole-Cole broadening in dielectric relaxation and strange kinetics.

    PubMed

    Puzenko, Alexander; Ishai, Paul Ben; Feldman, Yuri

    2010-07-16

    We present a fresh appraisal of the Cole-Cole (CC) description of dielectric relaxation. While the approach is phenomenological, it demonstrates a fundamental connection between the parameters of the CC dispersion. Based on the fractal nature of the time set representing the interaction of the relaxing dipole with its encompassing matrix, and the Kirkwood-Froehlich correlation factor, a new 3D phase space linking together the kinetic and structural properties is proposed. The evolution of the relaxation process is represented in this phase space by a trajectory, which is determined by the variation of external macroscopic parameters. As an example, the validity of the approach is demonstrated on two porous silica glasses exhibiting a CC relaxation process.

  10. Construct Validity of the Psychopathic Personality Inventory Two-Factor Model With Offenders

    PubMed Central

    Patrick, Christopher J.; Poythress, Norman G.; Edens, John F.; Lilienfeld, Scott O.; Benning, Stephen D.

    2008-01-01

    Much of the research on psychopathy has treated it as a unitary construct operationalized by total scores on one (or more) measures. More recent studies on the Psychopathic Personality Inventory (PPI) suggest the existence of two distinct facets of psychopathy with unique external correlates. Here, the authors report reanalyses of two offender data sets that included scores on the PPI along with various theoretically relevant criterion variables. Consistent with hypotheses, the two PPI factors showed convergent and discriminant relations with criterion measures, many of which would otherwise have been obscured when relying on PPI total scores. These results highlight the importance of examining facets of psychopathy as well as total scores. PMID:16768596

  11. All Together Now: Measuring Staff Cohesion in Special Education Classrooms

    PubMed Central

    Kratz, Hilary E.; Locke, Jill; Piotrowski, Zinnia; Ouellette, Rachel R.; Xie, Ming; Stahmer, Aubyn C.; Mandell, David S.

    2015-01-01

    This study sought to validate a new measure, the Classroom Cohesion Survey (CCS), designed to examine the relationship between teachers and classroom assistants in autism support classrooms. Teachers, classroom assistants, and external observers showed good inter-rater agreement on the CCS and good internal consistency for all scales. Simple factor structures were found for both teacher- and classroom assistant–rated scales, with one-factor solutions for both scales. Paired t tests revealed that on average, classroom assistants rated classroom cohesion stronger than teachers. The CCS may be an effective tool for measuring cohesion between classroom staff and may have an important impact on various clinical and implementation outcomes in school settings. PMID:26213443

  12. How Sharp is a Unicorn's Horn?

    ERIC Educational Resources Information Center

    Johnston, Peter H.; Allignton, Richard L.

    1983-01-01

    Criticizes a study of the reliability and validity of curriculum-based reading inventories by L. S. Fuchs, D. Fuchs, and S. L. Deno and raises questions regarding the study's internal and external validity. (AEA)

  13. Rapid and non-invasive analysis of deoxynivalenol in durum and common wheat by Fourier-Transform Near Infrared (FT-NIR) spectroscopy.

    PubMed

    De Girolamo, A; Lippolis, V; Nordkvist, E; Visconti, A

    2009-06-01

    Fourier transform near-infrared spectroscopy (FT-NIR) was used for rapid and non-invasive analysis of deoxynivalenol (DON) in durum and common wheat. The relevance of using ground wheat samples with a homogeneous particle size distribution to minimize measurement variations and avoid DON segregation among particles of different sizes was established. Calibration models for durum wheat, common wheat and durum + common wheat samples, with particle size <500 microm, were obtained by using partial least squares (PLS) regression with an external validation technique. Values of root mean square error of prediction (RMSEP, 306-379 microg kg(-1)) were comparable and not too far from values of root mean square error of cross-validation (RMSECV, 470-555 microg kg(-1)). Coefficients of determination (r(2)) indicated an "approximate to good" level of prediction of the DON content by FT-NIR spectroscopy in the PLS calibration models (r(2) = 0.71-0.83), and a "good" discrimination between low and high DON contents in the PLS validation models (r(2) = 0.58-0.63). A "limited to good" practical utility of the models was ascertained by range error ratio (RER) values higher than 6. A qualitative model, based on 197 calibration samples, was developed to discriminate between blank and naturally contaminated wheat samples by setting a cut-off at 300 microg kg(-1) DON to separate the two classes. The model correctly classified 69% of the 65 validation samples with most misclassified samples (16 of 20) showing DON contamination levels quite close to the cut-off level. These findings suggest that FT-NIR analysis is suitable for the determination of DON in unprocessed wheat at levels far below the maximum permitted limits set by the European Commission.

  14. Measuring Long-Distance Romantic Relationships: A Validity Study

    ERIC Educational Resources Information Center

    Pistole, M. Carole; Roberts, Amber

    2011-01-01

    This study investigated aspects of construct validity for the scores of a new long-distance romantic relationship measure. A single-factor structure of the long-distance romantic relationship index emerged, with convergent and discriminant evidence of external validity, high internal consistency reliability, and applied utility of the scores.…

  15. The Impact of Overreporting on MMPI-2-RF Substantive Scale Score Validity

    ERIC Educational Resources Information Center

    Burchett, Danielle L.; Ben-Porath, Yossef S.

    2010-01-01

    This study examined the impact of overreporting on the validity of Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF) substantive scale scores by comparing correlations with relevant external criteria (i.e., validity coefficients) of individuals who completed the instrument under instructions to (a) feign psychopathology…

  16. Easy and low-cost identification of metabolic syndrome in patients treated with second-generation antipsychotics: artificial neural network and logistic regression models.

    PubMed

    Lin, Chao-Cheng; Bai, Ya-Mei; Chen, Jen-Yeu; Hwang, Tzung-Jeng; Chen, Tzu-Ting; Chiu, Hung-Wen; Li, Yu-Chuan

    2010-03-01

    Metabolic syndrome (MetS) is an important side effect of second-generation antipsychotics (SGAs). However, many SGA-treated patients with MetS remain undetected. In this study, we trained and validated artificial neural network (ANN) and multiple logistic regression models without biochemical parameters to rapidly identify MetS in patients with SGA treatment. A total of 383 patients with a diagnosis of schizophrenia or schizoaffective disorder (DSM-IV criteria) with SGA treatment for more than 6 months were investigated to determine whether they met the MetS criteria according to the International Diabetes Federation. The data for these patients were collected between March 2005 and September 2005. The input variables of ANN and logistic regression were limited to demographic and anthropometric data only. All models were trained by randomly selecting two-thirds of the patient data and were internally validated with the remaining one-third of the data. The models were then externally validated with data from 69 patients from another hospital, collected between March 2008 and June 2008. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of all models. Both the final ANN and logistic regression models had high accuracy (88.3% vs 83.6%), sensitivity (93.1% vs 86.2%), and specificity (86.9% vs 83.8%) to identify MetS in the internal validation set. The mean +/- SD AUC was high for both the ANN and logistic regression models (0.934 +/- 0.033 vs 0.922 +/- 0.035, P = .63). During external validation, high AUC was still obtained for both models. Waist circumference and diastolic blood pressure were the common variables that were left in the final ANN and logistic regression models. Our study developed accurate ANN and logistic regression models to detect MetS in patients with SGA treatment. The models are likely to provide a noninvasive tool for large-scale screening of MetS in this group of patients. (c) 2010 Physicians Postgraduate Press, Inc.

  17. Validation of a dynamic linked segment model to calculate joint moments in lifting.

    PubMed

    de Looze, M P; Kingma, I; Bussmann, J B; Toussaint, H M

    1992-08-01

    A two-dimensional dynamic linked segment model was constructed and applied to a lifting activity. Reactive forces and moments were calculated by an instantaneous approach involving the application of Newtonian mechanics to individual adjacent rigid segments in succession. The analysis started once at the feet and once at a hands/load segment. The model was validated by comparing predicted external forces and moments at the feet or at a hands/load segment to actual values, which were simultaneously measured (ground reaction force at the feet) or assumed to be zero (external moments at feet and hands/load and external forces, beside gravitation, at hands/load). In addition, results of both procedures, in terms of joint moments, including the moment at the intervertebral disc between the fifth lumbar and first sacral vertebra (L5-S1), were compared. A correlation of r = 0.88 between calculated and measured vertical ground reaction forces was found. The calculated external forces and moments at the hands showed only minor deviations from the expected zero level. The moments at L5-S1, calculated starting from feet compared to starting from hands/load, yielded a coefficient of correlation of r = 0.99. However, moments calculated from hands/load were 3.6% (averaged values) and 10.9% (peak values) higher. This difference is assumed to be due mainly to erroneous estimations of the positions of centres of gravity and joint rotation centres. The estimation of the location of L5-S1 rotation axis can affect the results significantly. Despite the numerous studies estimating the load on the low back during lifting on the basis of linked segment models, only a few attempts to validate these models have been made. This study is concerned with the validity of the presented linked segment model. The results support the model's validity. Effects of several sources of error threatening the validity are discussed. Copyright © 1992. Published by Elsevier Ltd.

  18. Construction and validation of a Tamil logMAR chart.

    PubMed

    Varadharajan, Srinivasa; Srinivasan, Krithica; Kumaresan, Brindha

    2009-09-01

    To design, construct and validate a new Tamil logMAR visual acuity chart based on current recommendations. Ten Tamil letters of equal legibility were identified experimentally and were used in the chart. Two charts, one internally illuminated and one externally illuminated, were constructed for testing at 4 m distance. The repeatability of the two charts was tested. For validation, the two charts were compared with a standard English logMAR chart (ETDRS). When compared to the ETDRS chart, a difference of 0.06 +/- 0.07 and 0.07 +/- 0.07 logMAR was found for the internally and externally illuminated charts respectively. Limits of agreement between the internally illuminated Tamil logMAR chart and ETDRS chart were found to be (-0.08, 0.19), and (-0.07, 0.20) for the externally illuminated chart. The test - retest results showed a difference of 0.02 +/- 0.04 and 0.02 +/- 0.06 logMAR for the internally and externally illuminated charts respectively. Limits of agreement for repeated measurements for the internally illuminated Tamil logMAR chart were found to be (-0.06, 0.10), and (-0.10, 0.14) for the externally illuminated chart. The newly constructed Tamil logMAR charts have good repeatability. The difference in visual acuity scores between the newly constructed Tamil logMAR chart and the standard English logMAR chart was within acceptable limits. This new chart can be used for measuring visual acuity in the literate Tamil population.

  19. If We Don’t, Who Will? The Employment of the United States Army to Combat Potential Pandemic Outbreaks in West Africa

    DTIC Science & Technology

    2015-06-12

    27 viii Threats to Validity and Biases ...draw conclusions and make recommendations for future research. Threats to Validity and Biases There are a several issues that pose a threat to...validity and bias to the research. Threats to validity affect the accuracy of the research and soundness of the conclusion. Threats to external validity

  20. Modeling complex treatment strategies: construction and validation of a discrete event simulation model for glaucoma.

    PubMed

    van Gestel, Aukje; Severens, Johan L; Webers, Carroll A B; Beckers, Henny J M; Jansonius, Nomdo M; Schouten, Jan S A G

    2010-01-01

    Discrete event simulation (DES) modeling has several advantages over simpler modeling techniques in health economics, such as increased flexibility and the ability to model complex systems. Nevertheless, these benefits may come at the cost of reduced transparency, which may compromise the model's face validity and credibility. We aimed to produce a transparent report on the construction and validation of a DES model using a recently developed model of ocular hypertension and glaucoma. Current evidence of associations between prognostic factors and disease progression in ocular hypertension and glaucoma was translated into DES model elements. The model was extended to simulate treatment decisions and effects. Utility and costs were linked to disease status and treatment, and clinical and health economic outcomes were defined. The model was validated at several levels. The soundness of design and the plausibility of input estimates were evaluated in interdisciplinary meetings (face validity). Individual patients were traced throughout the simulation under a multitude of model settings to debug the model, and the model was run with a variety of extreme scenarios to compare the outcomes with prior expectations (internal validity). Finally, several intermediate (clinical) outcomes of the model were compared with those observed in experimental or observational studies (external validity) and the feasibility of evaluating hypothetical treatment strategies was tested. The model performed well in all validity tests. Analyses of hypothetical treatment strategies took about 30 minutes per cohort and lead to plausible health-economic outcomes. There is added value of DES models in complex treatment strategies such as glaucoma. Achieving transparency in model structure and outcomes may require some effort in reporting and validating the model, but it is feasible.

  1. Issues in cross-cultural validity: example from the adaptation, reliability, and validity testing of a Turkish version of the Stanford Health Assessment Questionnaire.

    PubMed

    Küçükdeveci, Ayse A; Sahin, Hülya; Ataman, Sebnem; Griffiths, Bridget; Tennant, Alan

    2004-02-15

    Guidelines have been established for cross-cultural adaptation of outcome measures. However, invariance across cultures must also be demonstrated through analysis of Differential Item Functioning (DIF). This is tested in the context of a Turkish adaptation of the Health Assessment Questionnaire (HAQ). Internal construct validity of the adapted HAQ is assessed by Rasch analysis; reliability, by internal consistency and the intraclass correlation coefficient; external construct validity, by association with impairments and American College of Rheumatology functional stages. Cross-cultural validity is tested through DIF by comparison with data from the UK version of the HAQ. The adapted version of the HAQ demonstrated good internal construct validity through fit of the data to the Rasch model (mean item fit 0.205; SD 0.998). Reliability was excellent (alpha = 0.97) and external construct validity was confirmed by expected associations. DIF for culture was found in only 1 item. Cross-cultural validity was found to be sufficient for use in international studies between the UK and Turkey. Future adaptation of instruments should include analysis of DIF at the field testing stage in the adaptation process.

  2. The first Latin-American risk stratification system for cardiac surgery: can be used as a graphic pocket-card score.

    PubMed

    Carosella, Victorio C; Navia, Jose L; Al-Ruzzeh, Sharif; Grancelli, Hugo; Rodriguez, Walter; Cardenas, Cesar; Bilbao, Jorge; Nojek, Carlos

    2009-08-01

    This study aims to develop the first Latin-American risk model that can be used as a simple, pocket-card graphic score at bedside. The risk model was developed on 2903 patients who underwent cardiac surgery at the Spanish Hospital of Buenos Aires, Argentina, between June 1994 and December 1999. Internal validation was performed on 708 patients between January 2000 and June 2001 at the same center. External validation was performed on 1087 patients between February 2000 and January 2007 at three other centers in Argentina. In the development dataset the area under receiver operating characteristics (ROC) curve was 0.73 and the Hosmer-Lemeshow (HL) test was P=0.88. In the internal validation ROC curve was 0.77. In the external validation ROC curve was 0.81, but imperfect calibration was detected because the observed in-hospital mortality (3.96%) was significantly lower than the development dataset (8.20%) (P<0.0001). Recalibration was done in 2007, showing excellent level of agreement between the observed and predicted mortality rates on all patients (P=0.92). This is the first risk model for cardiac surgery developed in a population of Latin-America with both internal and external validation. A simple graphic pocket-card score allows an easy bedside application with acceptable statistic precision.

  3. Psychometric Evaluation of the MMPI-2/MMPI-2-RF Restructured Clinical Scales in an Israeli Sample.

    PubMed

    Shkalim, Eleanor

    2015-10-01

    The current study cross-culturally evaluated the psychometric properties of the Minnesota Multiphasic Personality Inventory-2 (MMPI-2)/MMPI-2-Restructured Form Restructured Clinical (RC) Scales in psychiatric settings in Israel with a sample of 100 men and 133 women. Participants were administered the MMPI-2 and were rated by their therapists on a 188-item Patient Description Form. Results indicated that in most instances the RC Scales demonstrated equivalent or better internal consistencies and improved intercorrelation patterns relative to their clinical counterparts. Furthermore, external analyses revealed comparable or improved convergent validity (with the exceptions of Antisocial Behavior [RC4] and Ideas of Persecution [RC6] among men), and mostly greater discriminant validity. Overall, the findings indicate that consistent with previous findings, the RC Scales generally exhibit comparable to improved psychometric properties over the Clinical Scales. Implications of the results, limitations, and recommendations for future research are discussed. © The Author(s) 2014.

  4. Explanatory Versus Pragmatic Trials: An Essential Concept in Study Design and Interpretation.

    PubMed

    Merali, Zamir; Wilson, Jefferson R

    2017-11-01

    Randomized clinical trials often represent the highest level of clinical evidence available to evaluate the efficacy of an intervention in clinical medicine. Although the process of randomization serves to maximize internal validity, the external validity, or generalizability, of such studies depends on several factors determined at the design phase of the trial including eligibility criteria, study setting, and outcomes of interest. In general, explanatory trials are optimized to demonstrate the efficacy of an intervention in a highly selected patient group; however, findings from these studies may not be generalizable to the larger clinical problem. In contrast, pragmatic trials attempt to understand the real-world benefit of an intervention by incorporating design elements that allow for greater generalizability and clinical applicability of study results. In this article we describe the explanatory-pragmatic continuum for clinical trials in greater detail. Further, a well-accepted tool for grading trials on this continuum is described, and applied, to 2 recently published trials pertaining to the surgical management of lumbar degenerative spondylolisthesis.

  5. Pharmacoepidemiology resources in Ireland-an introduction to pharmacy claims data.

    PubMed

    Sinnott, Sarah-Jo; Bennett, Kathleen; Cahir, Caitriona

    2017-11-01

    Administrative health data, such as pharmacy claims data, present a valuable resource for conducting pharmacoepidemiological and health services research. Often, data are available for whole populations allowing population level analyses. Moreover, their routine collection ensures that the data reflect health care utilisation in the real-world setting compared to data collected in clinical trials. The Irish Health Service Executive-Primary Care Reimbursement Service (HSE-PCRS) community pharmacy claims database is described. The availability of demographic variables and drug-related information is discussed. The strengths and limitations associated using this database for conducting research are presented, in particular, internal and external validity. Examples of recently conducted research using the HSE-PCRS pharmacy claims database are used to illustrate the breadth of its use. The HSE-PCRS national pharmacy claims database is a large, high-quality, valid and accurate data source for measuring drug exposure in specific populations in Ireland. The main limitation is the lack of generalisability for those aged <70 years and the lack of information on indication or outcome.

  6. Pharmacophore modeling, virtual screening and molecular docking of ATPase inhibitors of HSP70.

    PubMed

    Sangeetha, K; Sasikala, R P; Meena, K S

    2017-10-01

    Heat shock protein 70 is an effective anticancer target as it influences many signaling pathways. Hence the study investigated the important pharmacophore feature required for ATPase inhibitors of HSP70 by generating a ligand based pharmacophore model followed by virtual based screening and subsequent validation by molecular docking in Discovery studio V4.0. The most extrapolative pharmacophore model (hypotheses 8) consisted of four hydrogen bond acceptors. Further validation by external test set prediction identified 200 hits from Mini Maybridge, Drug Diverse, SCPDB compounds and Phytochemicals. Consequently, the screened compounds were refined by rule of five, ADMET and molecular docking to retain the best competitive hits. Finally Phytochemical compounds Muricatetrocin B, Diacetylphiladelphicalactone C, Eleutheroside B and 5-(3-{[1-(benzylsulfonyl)piperidin-4-yl]amino}phenyl)- 4-bromo-3-(carboxymethoxy)thiophene-2-carboxylic acid were obtained as leads to inhibit the ATPase activity of HSP70 in our findings and thus can be proposed for further in vitro and in vivo evaluation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Liquefied Petroleum Gas Monitoring System Based on Polystyrene Coated Long Period Grating

    PubMed Central

    Zotti, Aldobenedetto; Palumbo, Giovanna; Zuppolini, Simona; Consales, Marco; Cutolo, Antonello; Borriello, Anna; Zarrelli, Mauro; Iadicicco, Agostino

    2018-01-01

    In this work, we report the in-field demonstration of a liquefied petroleum gas monitoring system based on optical fiber technology. Long-period grating coated with a thin layer of atactic polystyrene (aPS) was employed as a gas sensor, and an array comprising two different fiber Bragg gratings was set for the monitoring of environmental conditions such as temperature and humidity. A custom package was developed for the sensors, ensuring their suitable installation and operation in harsh conditions. The developed system was installed in a real railway location scenario (i.e., a southern Italian operative railway tunnel), and tests were performed to validate the system performances in operational mode. Daytime normal working operations of the railway line and controlled gas expositions, at very low concentrations, were the searched realistic conditions for an out-of-lab validation of the developed system. Encouraging results were obtained with a precise indication of the gas concentration and external conditioning of the sensor. PMID:29734731

  8. Quasi-experiments to establish causal effects of HIV care and treatment and to improve the cascade of care

    PubMed Central

    Bor, Jacob; Geldsetzer, Pascal; Venkataramani, Atheendar; Bärnighausen, Till

    2015-01-01

    Purpose of review Randomized, population-representative trials of clinical interventions are rare. Quasi-experiments have been used successfully to generate causal evidence on the cascade of HIV care in a broad range of real-world settings. Recent findings Quasi-experiments exploit exogenous, or quasi-random, variation occurring naturally in the world or because of an administrative rule or policy change to estimate causal effects. Well designed quasi-experiments have greater internal validity than typical observational research designs. At the same time, quasi-experiments may also have potential for greater external validity than experiments and can be implemented when randomized clinical trials are infeasible or unethical. Quasi-experimental studies have established the causal effects of HIV testing and initiation of antiretroviral therapy on health, economic outcomes and sexual behaviors, as well as indirect effects on other community members. Recent quasi-experiments have evaluated specific interventions to improve patient performance in the cascade of care, providing causal evidence to optimize clinical management of HIV. Summary Quasi-experiments have generated important data on the real-world impacts of HIV testing and treatment and on interventions to improve the cascade of care. With the growth in large-scale clinical and administrative data, quasi-experiments enable rigorous evaluation of policies implemented in real-world settings. PMID:26371463

  9. Quasi-experiments to establish causal effects of HIV care and treatment and to improve the cascade of care.

    PubMed

    Bor, Jacob; Geldsetzer, Pascal; Venkataramani, Atheendar; Bärnighausen, Till

    2015-11-01

    Randomized, population-representative trials of clinical interventions are rare. Quasi-experiments have been used successfully to generate causal evidence on the cascade of HIV care in a broad range of real-world settings. Quasi-experiments exploit exogenous, or quasi-random, variation occurring naturally in the world or because of an administrative rule or policy change to estimate causal effects. Well designed quasi-experiments have greater internal validity than typical observational research designs. At the same time, quasi-experiments may also have potential for greater external validity than experiments and can be implemented when randomized clinical trials are infeasible or unethical. Quasi-experimental studies have established the causal effects of HIV testing and initiation of antiretroviral therapy on health, economic outcomes and sexual behaviors, as well as indirect effects on other community members. Recent quasi-experiments have evaluated specific interventions to improve patient performance in the cascade of care, providing causal evidence to optimize clinical management of HIV. Quasi-experiments have generated important data on the real-world impacts of HIV testing and treatment and on interventions to improve the cascade of care. With the growth in large-scale clinical and administrative data, quasi-experiments enable rigorous evaluation of policies implemented in real-world settings.

  10. 78 FR 1162 - Cardiovascular Devices; Reclassification of External Cardiac Compressor

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-08

    ... safety and electromagnetic compatibility; For devices containing software, software verification... electromagnetic compatibility; For devices containing software, software verification, validation, and hazard... electrical components, appropriate analysis and testing must validate electrical safety and electromagnetic...

  11. Preference on cash-choice task predicts externalizing outcomes in 17-year-olds.

    PubMed

    Sparks, Jordan C; Isen, Joshua D; Iacono, William G

    2014-03-01

    Delay-discounting, the tendency to prefer a smaller-sooner reward to a larger-later reward, has been associated with a range of externalizing behaviors. Laboratory delay-discounting tasks have emerged as a useful measure to index impulsivity and a proclivity towards externalizing pyschopathology. While many studies demonstrate the existence of a latent externalizing factor that is heritable, there have been few genetic studies of delay-discounting. Further, the increased vulnerability for risky behavior in adolescence makes adolescent samples an attractive target for future research, and expeditious, ecologically-valid delay-discounting measures are helpful in this regard. The primary goal of this study was to help validate the utility of a "cash-choice" measure for use in a sample of older adolescents. We used a sample of 17-year-old twins (n = 791) from the Minnesota Twin Family Enrichment study. Individuals who chose the smaller-sooner reward were more likely to have used a range of addictive substances, engaged in sexual intercourse, and earned lower GPAs. Best fitting biometric models from univariate analyses supported the heritability of cash-choice and externalizing, but bivariate modeling results indicated that the correlation between cash-choice and externalizing was determined largely by shared environmental influences, thus failing to support cash-choice as a possible endophenotype for externalizing in this age group. Our findings lend further support to the utility of cash-choice as a measure of individual differences in decision making and suggest that, by late adolescence, this task indexes shared environmental risk for externalizing behavior.

  12. Predicting drug-induced liver injury in human with Naïve Bayes classifier approach.

    PubMed

    Zhang, Hui; Ding, Lan; Zou, Yi; Hu, Shui-Qing; Huang, Hai-Guo; Kong, Wei-Bao; Zhang, Ji

    2016-10-01

    Drug-induced liver injury (DILI) is one of the major safety concerns in drug development. Although various toxicological studies assessing DILI risk have been developed, these methods were not sufficient in predicting DILI in humans. Thus, developing new tools and approaches to better predict DILI risk in humans has become an important and urgent task. In this study, we aimed to develop a computational model for assessment of the DILI risk with using a larger scale human dataset and Naïve Bayes classifier. The established Naïve Bayes prediction model was evaluated by 5-fold cross validation and an external test set. For the training set, the overall prediction accuracy of the 5-fold cross validation was 94.0 %. The sensitivity, specificity, positive predictive value and negative predictive value were 97.1, 89.2, 93.5 and 95.1 %, respectively. The test set with the concordance of 72.6 %, sensitivity of 72.5 %, specificity of 72.7 %, positive predictive value of 80.4 %, negative predictive value of 63.2 %. Furthermore, some important molecular descriptors related to DILI risk and some toxic/non-toxic fragments were identified. Thus, we hope the prediction model established here would be employed for the assessment of human DILI risk, and the obtained molecular descriptors and substructures should be taken into consideration in the design of new candidate compounds to help medicinal chemists rationally select the chemicals with the best prospects to be effective and safe.

  13. Adaptation of the ESPA29 Parental Socialization Styles Scale to the Basque language: evidence of validity.

    PubMed

    López-Jáuregui, Alicia; Oliden, Paula Elosua

    2009-11-01

    The aim of this study is to adapt the ESPA29 scale of parental socialization styles in adolescence to the Basque language. The study of its psychometric properties is based on the search for evidence of internal and external validity. The first focuses on the assessment of the dimensionality of the scale by means of exploratory factor analysis. The relationship between the dimensions of parental socialization styles and gender and age guarantee the external validity of the scale. The study of the equivalence of the adapted and original versions is based on the comparisons of the reliability coefficients and on factor congruence. The results allow us to conclude the equivalence of the two scales.

  14. The predictive utility of neuropsychological symptom validity testing as it relates to psychological presentation.

    PubMed

    Zakzanis, Konstantine K; Gammada, Emnet; Jeffay, Eliyas

    2012-01-01

    The present study examined the relationship between multiple neuropsychological symptom validity tests (SVTs) and psychological presentation. More formally, we set out to determine if performance on neuropsychological SVTs was related to psychological symptom credibility and which specific neuropsychological SVTs were most associated with noncredible psychological presentation. Archival records from 106 litigating examinees were utilized in this study. Our results illustrate that neuropsychological SVTs are modestly related to psychological symptom credibility and that specific neuropsychological SVTs are variably associated to this end. We conclude that when multiple, but not independent, neuropsychological SVTs are employed within the context of a neuropsychological examination, they do have clinical utility as it relates to credibility of psychological presentation and these constructs do share variance reciprocally in clinically meaningful ways. When independently employed, however, the observed relationship is modest at best. Hence, to place clinical opinion on firmer scientific grounds within the context of a neuropsychological examination, multiple cognitive SVTs, in hand with psychological test instruments that include validity indexes, are essential to derive opinion that is based on science rather than faith in the instance of litigation when an incentive to manifest disability for the sake of an external reward holds probable.

  15. Selecting the optimum number of partial least squares components for the calibration of attenuated total reflectance-mid-infrared spectra of undesigned kerosene samples.

    PubMed

    Gómez-Carracedo, M P; Andrade, J M; Rutledge, D N; Faber, N M

    2007-03-07

    Selecting the correct dimensionality is critical for obtaining partial least squares (PLS) regression models with good predictive ability. Although calibration and validation sets are best established using experimental designs, industrial laboratories cannot afford such an approach. Typically, samples are collected in an (formally) undesigned way, spread over time and their measurements are included in routine measurement processes. This makes it hard to evaluate PLS model dimensionality. In this paper, classical criteria (leave-one-out cross-validation and adjusted Wold's criterion) are compared to recently proposed alternatives (smoothed PLS-PoLiSh and a randomization test) to seek out the optimum dimensionality of PLS models. Kerosene (jet fuel) samples were measured by attenuated total reflectance-mid-IR spectrometry and their spectra where used to predict eight important properties determined using reference methods that are time-consuming and prone to analytical errors. The alternative methods were shown to give reliable dimensionality predictions when compared to external validation. By contrast, the simpler methods seemed to be largely affected by the largest changes in the modeling capabilities of the first components.

  16. Mapping the Moral Domain

    PubMed Central

    Graham, Jesse; Nosek, Brian A.; Haidt, Jonathan; Iyer, Ravi; Koleva, Spassena; Ditto, Peter H.

    2010-01-01

    The moral domain is broader than the empathy and justice concerns assessed by existing measures of moral competence, and it is not just a subset of the values assessed by value inventories. To fill the need for reliable and theoretically-grounded measurement of the full range of moral concerns, we developed the Moral Foundations Questionnaire (MFQ) based on a theoretical model of five universally available (but variably developed) sets of moral intuitions: Harm/care, Fairness/reciprocity, Ingroup/loyalty, Authority/respect, and Purity/sanctity. We present evidence for the internal and external validity of the scale and the model, and in doing so present new findings about morality: 1. Comparative model fitting of confirmatory factor analyses provides empirical justification for a five-factor structure of moral concerns. 2. Convergent/discriminant validity evidence suggests that moral concerns predict personality features and social group attitudes not previously considered morally relevant. 3. We establish pragmatic validity of the measure in providing new knowledge and research opportunities concerning demographic and cultural differences in moral intuitions. These analyses provide evidence for the usefulness of Moral Foundations Theory in simultaneously increasing the scope and sharpening the resolution of psychological views of morality. PMID:21244182

  17. Big Data in Designing Clinical Trials: Opportunities and Challenges

    PubMed Central

    Mayo, Charles S.; Matuszak, Martha M.; Schipper, Matthew J.; Jolly, Shruti; Hayman, James A.; Ten Haken, Randall K.

    2017-01-01

    Emergence of big data analytics resource systems (BDARSs) as a part of routine practice in Radiation Oncology is on the horizon. Gradually, individual researchers, vendors, and professional societies are leading initiatives to create and demonstrate use of automated systems. What are the implications for design of clinical trials, as these systems emerge? Gold standard, randomized controlled trials (RCTs) have high internal validity for the patients and settings fitting constraints of the trial, but also have limitations including: reproducibility, generalizability to routine practice, infrequent external validation, selection bias, characterization of confounding factors, ethics, and use for rare events. BDARS present opportunities to augment and extend RCTs. Preliminary modeling using single- and muti-institutional BDARS may lead to better design and less cost. Standardizations in data elements, clinical processes, and nomenclatures used to decrease variability and increase veracity needed for automation and multi-institutional data pooling in BDARS also support ability to add clinical validation phases to clinical trial design and increase participation. However, volume and variety in BDARS present other technical, policy, and conceptual challenges including applicable statistical concepts, cloud-based technologies. In this summary, we will examine both the opportunities and the challenges for use of big data in design of clinical trials. PMID:28913177

  18. Big Data in Designing Clinical Trials: Opportunities and Challenges.

    PubMed

    Mayo, Charles S; Matuszak, Martha M; Schipper, Matthew J; Jolly, Shruti; Hayman, James A; Ten Haken, Randall K

    2017-01-01

    Emergence of big data analytics resource systems (BDARSs) as a part of routine practice in Radiation Oncology is on the horizon. Gradually, individual researchers, vendors, and professional societies are leading initiatives to create and demonstrate use of automated systems. What are the implications for design of clinical trials, as these systems emerge? Gold standard, randomized controlled trials (RCTs) have high internal validity for the patients and settings fitting constraints of the trial, but also have limitations including: reproducibility, generalizability to routine practice, infrequent external validation, selection bias, characterization of confounding factors, ethics, and use for rare events. BDARS present opportunities to augment and extend RCTs. Preliminary modeling using single- and muti-institutional BDARS may lead to better design and less cost. Standardizations in data elements, clinical processes, and nomenclatures used to decrease variability and increase veracity needed for automation and multi-institutional data pooling in BDARS also support ability to add clinical validation phases to clinical trial design and increase participation. However, volume and variety in BDARS present other technical, policy, and conceptual challenges including applicable statistical concepts, cloud-based technologies. In this summary, we will examine both the opportunities and the challenges for use of big data in design of clinical trials.

  19. Generating a taxonomy of spatially cued attention for visual discrimination: Effects of judgment precision and set size on attention

    PubMed Central

    Hetley, Richard; Dosher, Barbara Anne; Lu, Zhong-Lin

    2014-01-01

    Attention precues improve the performance of perceptual tasks in many but not all circumstances. These spatial attention effects may depend upon display set size or workload, and have been variously attributed to external noise filtering, stimulus enhancement, contrast gain, or response gain, or to uncertainty or other decision effects. In this study, we document systematically different effects of spatial attention in low- and high-precision judgments, with and without external noise, and in different set sizes in order to contribute to the development of a taxonomy of spatial attention. An elaborated perceptual template model (ePTM) provides an integrated account of a complex set of effects of spatial attention with just two attention factors: a set-size dependent exclusion or filtering of external noise and a narrowing of the perceptual template to focus on the signal stimulus. These results are related to the previous literature by classifying the judgment precision and presence of external noise masks in those experiments, suggesting a taxonomy of spatially cued attention in discrimination accuracy. PMID:24939234

  20. Generating a taxonomy of spatially cued attention for visual discrimination: effects of judgment precision and set size on attention.

    PubMed

    Hetley, Richard; Dosher, Barbara Anne; Lu, Zhong-Lin

    2014-11-01

    Attention precues improve the performance of perceptual tasks in many but not all circumstances. These spatial attention effects may depend upon display set size or workload, and have been variously attributed to external noise filtering, stimulus enhancement, contrast gain, or response gain, or to uncertainty or other decision effects. In this study, we document systematically different effects of spatial attention in low- and high-precision judgments, with and without external noise, and in different set sizes in order to contribute to the development of a taxonomy of spatial attention. An elaborated perceptual template model (ePTM) provides an integrated account of a complex set of effects of spatial attention with just two attention factors: a set-size dependent exclusion or filtering of external noise and a narrowing of the perceptual template to focus on the signal stimulus. These results are related to the previous literature by classifying the judgment precision and presence of external noise masks in those experiments, suggesting a taxonomy of spatially cued attention in discrimination accuracy.

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