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Results for “external validation”

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PubMed2004

Comparison of accuracy between the Partin tables of 1997 and 2001 to predict final pathological stage in clinically localized prostate cancer.

PURPOSE: We validated externally the predictive accuracy of the 2001 Partin tables and compared the 1997 and 2001 versions. MATERIALS AND METHODS: We used ROC derived AUC to test the predictive accuracy of organ confinement (OC), extraprostatic extension (ECE), seminal vesicle invasion (SVI) and lymph node involvement (LNI) of 1997 and 2001 Partin tables derived probabilities. These probabilities were defined by the pretreatment clinical stage, serum prostate specific antigen and biopsy Gleason grade of 2,139 patients treated with radical prostatectomy for clinically localized prostate cancer. RESULTS: OC, ECE, SVI and LNI were noted in 63.5%, 23.1%, 10.5% and 2.9% of cases, respectively. AUC of the 2001 tables was 0.787, 0.766, 0.775 and 0.790, for OC, ECE, SVI and LNI, respectively. These values were virtually the same as the respective 1997 Partin table AUC values, namely 0.784, 0.728, 0.791 and 0.799. CONCLUSIONS: This external validation of the 2001 Partin tables confirms good predictive accuracy of the updated tables. However, predictive accuracy in this external validation data set of 2,139 European men is virtually the same as that of the original 1997 tables. Therefore, a transition from the 1997 tables to the updated 2001 version does not appear warranted unless superior accuracy is demonstrated in other external cohorts.

Adult↗

PubMed2005

Validity and reliability of the Italian version of the Quality-of-Life in Epilepsy Inventory (QOLIE-31).

PURPOSE: To develop an Italian adaptation of the shortened version of the Quality-of-Life in Epilepsy Inventory (QOLIE-31). METHODS: The study population comprised 503 consecutive ambulatory patients with epilepsy from 44 centers. Internal validity was tested by factor analysis, to detect similarities to and differences from the original version, and by multitrait/multi-item analysis, to assess item convergent and discriminant validity. External validity testing included correlation to the SF-36 Inventory, to check the properties of the epilepsy-specific dimensions. Validity testing was completed by analysis of variance (ANOVA) of QOLIE-31 dimension scores against demographic and clinical variables, including age, sex, seizure frequency and number of drugs. RESULTS: The domains showing the highest internal consistency and the best discriminant validity were Medication effect, and Seizure worry. Social functioning had the lower discriminant validity. With reference to the SF-36 scores, the study patients were slightly but constantly below the population values, mostly for General health and Role physical domains. All QOLIE-31 dimensions were sensitive to almost any demographic and clinical variable, except for Medication effects (sensitive to number of drugs) and Energy-fatigue (sensitive to age). CONCLUSIONS: Except for Social functioning, the psychometric properties of the Italian adaptation of the QOLIE-31 Inventory are fairly good and similar to the American version and the Spanish translation. Social functioning scale suffers shortcomings because of life constraints caused by epilepsy (with missing values for regular job and driving license).

Adolescent↗

PubMed2003

Self, friends, and lovers: structural relations among Beck Depression Inventory scores and perceived mate values.

BACKGROUND: We used an economic model based on evolutionary theory to guide an examination of relations among self-reported depressive symptoms and ratings of mate values of self, social, and sexual partners. This model treats assortative mating as a form of social exchange between partners of socially and sexually desirable traits. METHODS: Two studies used variants of the Mate Value Inventory (MVI), a multivariate assessment of attributes desired in social or sexual partners. For study 1, 115 male and 124 female undergraduates provided self reports on four forms of the MVI-11 and on the Beck Depression Inventory (BDI); for study 2, 208 male and 277 female undergraduates provided self reports on seven forms of the MVI-7 and on the BDI-II. RESULTS: Both multisample structural equations models indicated that the parameters were statistically equivalent between female and male subsamples and provided an adequate fit to the data. The models revealed significant relations between the mate values ascribed to the self and those ascribed to short- and long-term partners as well as best friends. Furthermore, greater BDI scores significantly predicted lesser ratings of mate value for the self, and hence indirectly predicted lesser ratings of mate value for all types of partners evaluated. LIMITATIONS: Although the data obtained from the MVI demonstrated good psychometric validity, external validity has not yet been established. CONCLUSIONS: The results are consistent with models predicting: (1) assortative mating by mate value, (2) differential exchange rates of mate value for different types of partners, (3) a negative relation between depressive symptoms and assessment of one's own mate value, and (4) a possibly consequential mismatch of mate values when one partner exhibits or recovers from significant depressive symptoms. The results are inconsistent with models predicting (5) a generalized negativity bias due to depression.

Adolescent↗

PubMed2005

Predicting human serum albumin affinity of interleukin-8 (CXCL8) inhibitors by 3D-QSPR approach.

A novel class of 2-(R)-phenylpropionamides has been recently reported to inhibit in vitro and in vivo interleukin-8 (CXCL8)-induced biological activities. These CXCL8 inhibitors are derivatives of phenylpropionic nonsteroidal antiinflammatory drugs (NSAIDs), high-affinity ligands for site II of human serum albumin (HSA). Up to date, only a limited number of in silico models for the prediction of albumin protein binding are available. A three-dimensional quantitative structure-property relationship (3D-QSPR) approach was used to model the experimental affinity constant (K(i)) to plasma proteins of 37 structurally related molecules, using physicochemical and 3D-pharmacophoric descriptors. Molecular docking studies highlighted that training set molecules preferentially bind site II of HSA. The obtained model shows satisfactory statistical parameters both in fitting and predicting validation. External validation confirmed the statistical significance of the chemometric model, which is a powerful tool for the prediction of HSA binding in virtual libraries of structurally related compounds.

Anti-Inflammatory Agents, Non-Steroidal↗

PubMedDate not supplied

Rating methodological quality: toward improved assessment and investigation.

Assessing methodological quality is considered essential in deciding what investigations to include in research syntheses and in detecting potential sources of bias in meta-analytic results. Quality assessment is also useful in characterizing the strengths and limitations of the research in an area of study. Although numerous instruments to measure research quality have been developed, they have lacked empirically-supported components. In addition, different summary quality scales have yielded different findings when they were used to weight treatment effect estimates for the same body of research. Suggestions for developing improved quality instruments include: distinguishing distinct domains of quality, such as internal validity, external validity, the completeness of the study report, and adherence to ethical practices; focusing on individual aspects, rather than domains of quality; and focusing on empirically-verified criteria. Other ways to facilitate the constructive use of quality assessment are to improve and standardize the reporting of research investigations, so that the quality of studies can be more equitably and thoroughly compared, and to identify optimal methods for incorporating study quality ratings into meta-analyses.

Bias↗

PubMed2003

Risk factors for injury in child and adolescent sport: a systematic review of the literature.

OBJECTIVE: The objective of this systematic review of the literature is to identify risk factors and potential prevention strategies that may modify risk factors for injury in child and adolescent sport. DATA SOURCES: Seven electronic databases were searched to identify potentially relevant articles. A combination of Medical Subject Headings and text words were used (athletic injuries, sports injury, risk factors, adolescent, and child). STUDY SELECTION: This review is based on epidemiological evidence in which the data are original, an exposure and outcome are objectively measured, and an attempt is made to create a comparison group. Forty-five studies were selected for this review. DATA EXTRACTION: The data summarized include study design, study population, exposures, outcomes, and results. Estimates of odds ratios or relative risks were calculated where study data were adequate to do so. The quality of evidence is based on internal validity, external validity, and causal association. DATA SYNTHESIS: There is some evidence that potentially modifiable risk factors including poor endurance, lack of preseason training, and some psychosocial factors are important risk factors for injury in child and adolescent sport. Concerns with study design, internal validity, and generalizability persist. The evidence is consistent, however, with more convincing evidence from adult population studies. The evidence for nonmodifiable risk factors for injury in adolescent sport (ie, age, sex, previous injury) is consistent among studies. CONCLUSIONS: Sport participation and injury rates in child and adolescent sport are high. This review will assist in targeting the relevant groups and designing future research examining risk factors and prevention strategies in child and adolescent sport. Future clinical trials addressing modifiable risk factors to reduce the incidence of sports injury in this population are necessary.

Accident Prevention↗

PubMed2006

Development of an emergency department work score to predict ambulance diversion.

OBJECTIVES: The authors sought to develop and validate an emergency department (ED) work score that could be used in real time to quantify crowding and staff workload in an ED. This work score could be used by public health officials to direct ambulance traffic based on an objective measure of ED status and to track ED conditions over time. In addition, the authors sought to determine which portion of ED care was most responsible for crowding. METHODS: The setting was a tertiary teaching hospital with an emergency medicine residency. A number of ED parameters were measured throughout 2003 and then matched to times that an ED was on diversion status. Odd months of the year were used to develop the standard and even months to validate the standard. A marginal logistic regression analysis was used to develop the standard. The decision to divert ambulances was used as the criterion for ED crowding. RESULTS: The logistic regression demonstrated excellent correlation between the work score and diversion status. At the point of maximum inflection of the receiver operating characteristic curve, the work score predicted diversion status with 86% sensitivity and 80% specificity. CONCLUSIONS: An ED work score was successfully developed and internally validated. External validation should be performed before widespread use.

Ambulances↗

PubMed2001

Management of acute exacerbations of COPD: a summary and appraisal of published evidence.

STUDY OBJECTIVES: To critically review the available data on the diagnostic evaluation, risk stratification, and therapeutic management of patients with acute exacerbations of COPD. DESIGN, SETTING, AND PARTICIPANTS: English-language articles were identified from the following databases: MEDLINE (from 1966 to week 5, 2000), EMBASE (from 1974 to week 18, 2000), HealthStar (from 1975 to June 2000), and the Cochrane Controlled Trials Register (2000, issue 1). The best available evidence on each subtopic then was selected for analysis. Randomized trials, sometimes buttressed by cohort studies, were used to evaluate therapeutic interventions. Cohort studies were used to evaluate diagnostic tests and risk stratification. Study design and results were summarized in evidence tables. Individual studies were rated as to their internal validity, external validity, and quality of study design. Statistical analyses of combined data were not performed. MEASUREMENT AND RESULTS: Limited data exist regarding the utility of most diagnostic tests. However, chest radiography and arterial blood gas sampling appear to be useful, while short-term spirometry measurements do not. In terms of the risk of relapse and the risk of death after hospitalization for an acute exacerbation, there are identifiable clinical variables that are associated with these outcomes. Therapies for which there is evidence of efficacy include bronchodilators, corticosteroids, and noninvasive positive-pressure ventilation. There is also support for the use of antibiotics in patients with more severe exacerbations. Based on limited data, mucolytics and chest physiotherapy do not appear to be of benefit, and oxygen supplementation appears to increase the risk of respiratory failure in an identifiable subgroup of patients. CONCLUSIONS: Although suggestions for appropriate management can be made based on available evidence, the supporting literature is spotty. Further high-quality research is needed and will require an improved, generally acceptable, and transportable definition of the syndrome "acute exacerbation of COPD" and improved methods for observing and measuring outcomes.

Acute Disease↗

PubMed2001

Management of acute exacerbations of chronic obstructive pulmonary disease: a summary and appraisal of published evidence.

PURPOSE: To review critically the available data on diagnostic evaluation, risk stratification, and therapeutic management of patients with acute exacerbations of chronic obstructive pulmonary disease (COPD). DATA SOURCES: English-language articles were identified by searching MEDLINE (1966 to 2000, week 5), EMBASE (1974 to 2000, week 18), HealthStar (1975 to June 2000), and the Cochrane Controlled Trials Register (2000, Issue 1). STUDY SELECTION: The best available evidence on each subtopic was selected for analysis. Randomized trials, sometimes buttressed by cohort studies, were used to evaluate therapeutic interventions. Cohort studies were used to evaluate diagnostic tests and risk stratification. DATA EXTRACTION: Study design and results were summarized in evidence tables. Individual studies were rated by internal validity, external validity, and quality of design. Statistical analyses of combined data were not performed. DATA SYNTHESIS: Data on the utility of most diagnostic tests are limited. However, chest radiography and arterial blood gas sampling seem useful while acute spirometry does not. Identifiable clinical variables are associated with risk for relapse and risk for death after hospitalization for an acute exacerbation. Evidence of efficacy was found for bronchodilators, corticosteroids, and noninvasive positive-pressure ventilation. There is also support for the use of antibiotics in patients with more severe exacerbations. On the basis of limited data, mucolytics and chest physiotherapy do not seem to be of benefit, and oxygen supplementation seems to increase the risk for respiratory failure only in an identifiable subgroup of patients. CONCLUSIONS: Although suggestions for appropriate management can be made on the basis of available evidence, the supporting literature is scarce and further high-quality research is necessary. Such research will require an improved, generally acceptable, and transportable definition of acute exacerbation of COPD, as well as improved methods for observing and measuring outcomes.

Acute Disease↗

PubMed1993

Defining and classifying skin tears: need for a common language.

Very little has been written about skin tears. A common taxonomy and definition for each type of skin tear can organize teaching, practice, and research in the field. In 1990, Payne and Martin published the results of a descriptive clinical nursing research study on the epidemiology and management of skin tears in older adults. The Payne-Martin Classification System for Skin Tears, definitions, and characteristics of skin tears were presented. The purpose of this article is to critique their classification system and definitions. Criteria for evaluating taxonomies, internal validity, external validity, and utility, are used for the critique. A revision based upon continuing research and work with the classification system is presented. Further testing and modification will refine the classification and advance the science of wound care.

Humans↗

PubMedDate not supplied

Prediction of anti-HIV-1 activity of a series of tetrapyrrole molecules.

Anti-HIV-1 activities of 20 tetrapyrroles (hematoporphyrin derivatives, meso-tetraphenylporphyrins, a chlorin, and a phthalocyanine) were predicted based on their molecular structures using artificial neural networks. The molecular structures were optimized by HyperChem program using MM+ molecular mechanics and conformational search for the global minimum conformer. Eighty-seven theoretical descriptors were calculated for characterization of molecular structures. The network architecture was optimized, and suitable descriptors were selected applying a novel variable selection method. The 3DNET program was used for the calculation of descriptors and for neural network computations. The reliability of models was tested by randomization of biological activity data, leave-one-out, leave-n-out cross-validation, and external validation process. The predictive ability of the artificial neural network was compared to other model building methods, like multiple linear regressions and partial least squares projection to latent structures. For prediction of anti-HIV-1 activity, the artificial neural network gave the best results at cross-validation processes and at external validation as well. We built four nonlinear models with good predictive ability in all validation steps, which can be applied to predict the anti-HIV-1 activity of tetrapyrrole-type compounds in a much better way than with any other three-dimensional quantitative structure-activity relationship methods published to date.

Algorithms↗

PubMed2026

Diagnostic performance of machine learning models for malignant and non-malignant pleural effusion: Systematic review and meta-analysis.

BACKGROUND: Accurately distinguishing malignant pleural effusion (MPE) from non-malignant pleural effusion is clinically important, but the generalisability and methodological quality of machine-learning (ML) models remain uncertain. METHODS: We searched eight databases to 23 April 2026. Diagnostic performance was pooled using random-effects and Reitsma bivariate models, and study quality was assessed using PROBAST+AI. RESULTS: Forty-two studies were included; 17 contributed to the AUC meta-analysis and 14 to the bivariate analysis. The pooled AUC was 0.90 (95 % CI 0.85-0.94; 95 % prediction interval 0.62-0.98), with sensitivity of 0.80 (95 % CI 0.77-0.83) and specificity of 0.87 (95 % CI 0.79-0.92). Only nine studies reported external, temporal or independent validation. Externally validated studies had a lower pooled AUC than studies without external validation (0.83 vs 0.92), with lower specificity observed in the two externally validated studies contributing sensitivity and specificity data. All 42 development assessments had high overall quality concerns, and all 42 model evaluations were judged at high risk of bias. CONCLUSIONS: ML models showed good apparent accuracy for distinguishing MPE from non-MPE, but the evidence was limited by substantial heterogeneity, high risk of bias and scarce external validation. The pooled estimates reflect the average performance of different selected models rather than the expected accuracy of a single clinical test. ML models should be regarded as adjuncts to existing diagnostic pathways until they are confirmed by rigorous multicentre prospective external validation and clinical-impact studies.

Humans↗

PubMed1996

Psychometric analysis of an advance directive.

OBJECTIVES: Reliability and validity are as necessary for predrafted advance directive forms as they are for all clinical assessment instruments. Performance of predrafted advance directive forms with both lay persons and clinicians is relevant. Evidence relating to test- retest reliability, content validity, and criterion-related validity of one form, the Medical Directive, has been documented for outpatients. The authors investigated construct validity and external validity among outpatients, physicians, and the general public. METHODS: Four hundred ninety-five outpatients, 513 physicians, and 102 members of the general public were surveyed with the Medical Directive. Preference for 11 specific treatments in four to six illness scenarios were recorded. Mokken modeling of responses was used to produce a psychometric scale of receptiveness-to-treatment and desirability of treatments. The Kuder Richardson-20 statistic, Friedman's procedure for analysis of variance, and the Kruskall-Wallis test were used, respectively, to measure inter-item reliability, the relation with scenarios, and the relation between physicians' general goals for care and their scaled preferences. RESULTS: All model diagnostic tests indicated a close-fitting scale for all three respondent groups. Kuder Richardson-20 for outpatients (.98), physicians (.97), and the public (.93) demonstrated high inter-item reliability. Treatment desirabilities were related to invasiveness. Receptiveness-to-treatment was related to prognoses and disabilities of described illness scenarios among each group and to physicians' goals for care. CONCLUSIONS: The Medical Directive has construct validity in relations among specific treatment preferences and between treatment preferences, illness scenarios, and goals for care. External validity is supported by study of separate outpatient, physician, and general public populations. The treatment items constitute a highly reliable scale that can be used in further empirical research regarding life-sustaining treatment.

Adult↗

PubMed2006

Development and validation of Transfusion Risk Understanding Scoring Tool (TRUST) to stratify cardiac surgery patients according to their blood transfusion needs.

BACKGROUND: Allogeneic blood transfusion is associated with transfusion reactions, infection transmission, and postoperative morbidity and mortality. The objective of this study was to develop and validate an accurate and simple clinical index to stratify cardiac surgery patients according to their blood transfusion needs. METHODS AND RESULTS: Data on consecutive adult patients who underwent cardiac surgery at Toronto General Hospital (n = 11,113) and Sunnybrook and Women's College Health Sciences Center (n = 5316) between May 1999 and June 2004 were collected for the development, validation, and external validation of the index. Primary outcome was the exposure to blood transfusion in the operative and first postoperative days. Multivariable logistic regression modeling techniques were used to determine the relationship between each independent variable and the exposure to allogeneic blood transfusion. Score assignment for each predictor variable was based on its regression coefficient. The predicted probabilities at each total score were compared to the observed proportions of patients exposed to blood transfusion. The clinical tool consists of eight preoperative variables: preoperative hemoglobin, weight, female sex, age, nonelective procedure, preoperative creatinine, previous cardiac surgical procedure, and nonisolated procedure. CONCLUSIONS: Based on the standards of measurement in clinical research, a valid clinical tool was developed for predicting the need for blood transfusion in patients undergoing cardiac surgery. The clinical tool was internally and externally validated, and the results suggest that it should perform well at other institutions.

Aged↗

PubMed2026

Non-small cell lung cancer and tumor-educated platelets: screening of biomarkers and construction of a prognostic model.

BACKGROUND: Lung cancer is a leading cause of cancer-related mortality worldwide, emphasizing the urgent need for effective early detection strategies. Traditional Chinese medicine (TCM) provides a unique perspective on tumor pathogenesis, focusing on concepts such as "long-term stasis leading to accumulation". Tumor-educated platelets (TEPs) offer potential as biomarkers due to their ability to reflect cancer heterogeneity and facilitate less invasive diagnostic approaches. This study aims to identify TEP-related prognostic biomarkers for non-small cell lung cancer (NSCLC) and to construct and validate a multigene prognostic model by integrating platelet transcriptomic data with tumor tissue datasets. METHODS: We performed comprehensive analysis of gene expression datasets obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories to characterize transcriptomic differences among lung cancer specimens, normal tissue samples, and TEPs. Using R software, we identified Differentially expressed genes (DEGs) and subsequently applied a multi-stage analytical pipeline to TEP-associated DEGs, incorporating univariate Cox proportional hazards regression, least absolute shrinkage and selection operator (LASSO) regression, multivariate Cox regression, and stepwise regression modeling to pinpoint genes with prognostic significance. These prognostically relevant genes served as the foundation for developing a risk stratification model. We computed individual risk scores across both training and validation cohorts, enabling patient stratification into high- and low-risk categories. Model robustness was assessed through internal cross-validation and external validation procedures, while predictive performance was quantified using risk calibration metrics and receiver operating characteristic (ROC) curve analysis. RESULTS: Through systematic bioinformatics screening, we identified a four-gene prognostic signature comprising NELL2, C4orf48, PRAM1, and KLHL35, which served as the foundation for developing our risk stratification algorithm. Rigorous internal cross-validation and external cohort validation substantiated the moderate predictive performance of this signature. Comprehensive clinicopathological correlation analysis revealed that elevated risk indices, advanced pathological staging (stage III-IV), increased primary tumor dimensions, regional lymph node metastasis, and distant organ dissemination each demonstrated statistically significant associations with diminished overall survival (OS) outcomes in lung cancer patients. The clinical nomogram exhibited acceptable calibration, with calibration plots showing reasonable concordance between predicted and observed survival probabilities across all time points. Discriminative capacity assessment via time-dependent ROC analysis yielded area under the curve (AUC) values consistently surpassing 0.6, confirming moderate prognostic discrimination. Furthermore, decision curve analysis (DCA) demonstrated that our integrated multi-gene model conferred potential net clinical benefit compared to individual prognostic variables across the full spectrum of clinically relevant threshold probabilities (0-1 range), thereby establishing its potential utility for risk-informed clinical decision-making. CONCLUSIONS: This study identified NELL2, C4orf48, PRAM1, and KLHL35 as candidate TEP-related prognostic biomarkers for non-small cell lung cancer (NSCLC). The developed prognostic model shows preliminary potential for patient stratification, but its clinical application, particularly as a platelet-based liquid biopsy tool, requires further validation in independent TEP-based cohorts.

Tumor-educated platelets (TEPs)↗

PubMed1999

Real world designs in economic evaluation. Bridging the gap between clinical research and policy-making.

This paper identifies the information that economic evaluation should provide to adequately inform policy-makers. First, policy-makers need cost-effectiveness information that is both internally and externally valid. The latter aspect is often ignored and refers to the relevance of the results of economic trials to the specific decision-making context of the policy-maker. Second, policy-makers, like purchasers of care, may want assessments of the overall budget and health impacts of adopting an intervention in a disease or treatment area. This requires more of an aggregate analysis than the current approaches to economic evaluation (which are typically individual-orientated). There are 3 main conceptual approaches to economic evaluation: the use of randomised controlled trials (RCTs), observational studies and modelling. The RCT can be considered as the gold standard in economic evaluation because of its high internal validity, but results should be interpreted with caution because of its low external validity. There a number of options to enhance external validity; of these, additional modelling and observational data seem to be the most promising. To address issues at the system level, disease modelling or public health modelling is suggested. A 3-step approach, comprising successive assessment of internal validity, external validity (real world relevance) and net impact at the system level, can enhance the informative value of economic analyses. For example, this approach has been used to assess the informative value to decision-makers of an RCT in benign prostatic hyperplasia. The analysis emphasised the feasibility and importance of additional modelling beyond the results from an RCT-based economic analysis and provided important information of relevance for policy-making. Because of the need to increase the real world relevance of pharmacoeconomic analyses, there is potentially a large role for modelling in economic evaluation; however, in order to enhance its credibility, more attention should be paid to validity aspects.

Cost-Benefit Analysis↗

PubMed2025

A Digital Tool for Clinical Evidence-Driven Guideline Development by Studying Properties of Trial Eligible and Ineligible Populations: Development and Usability Study.

BACKGROUND: Clinical guideline development preferentially relies on evidence from randomized controlled trials (RCTs). RCTs are gold-standard methods to evaluate the efficacy of treatments with the highest internal validity but limited external validity, in the sense that their findings may not always be applicable to or generalizable to clinical populations or population characteristics. The external validity of RCTs for the clinical population is constrained by the lack of tailored epidemiological data analysis designed for this purpose due to data governance, consistency of disease or condition definitions, and reduplicated effort in analysis code. OBJECTIVE: This study aims to develop a digital tool that characterizes the overall population and differences between clinical trial eligible and ineligible populations from the clinical populations of a disease or condition regarding demography (eg, age, gender, ethnicity), comorbidity, coprescription, hospitalization, and mortality. Currently, the process is complex, onerous, and time-consuming, whereas a real-time tool may be used to rapidly inform a guideline developer's judgment about the applicability of evidence. METHODS: The National Institute for Health and Care Excellence-particularly the gout guideline development group-and the Scottish Intercollegiate Guidelines Network guideline developers were consulted to gather their requirements and evidential data needs when developing guidelines. An R Shiny (R Foundation for Statistical Computing) tool was designed and developed using electronic primary health care data linked with hospitalization and mortality data built upon an optimized data architecture. Disclosure control mechanisms were built into the tool to ensure data confidentiality. The tool was deployed within a Trusted Research Environment, allowing only trusted preapproved researchers to conduct analysis. RESULTS: The tool supports 128 chronic health conditions as index conditions and 161 conditions as comorbidities (33 in addition to the 128 index conditions). It enables 2 types of analyses via the graphic interface: overall population and stratified by user-defined eligibility criteria. The analyses produce an overview of statistical tables (eg, age, gender) of the index condition population and, within the overview groupings, produce details on, for example, electronic frailty index, comorbidities, and coprescriptions. The disclosure control mechanism is integral to the tool, limiting tabular counts to meet local governance needs. An exemplary result for gout as an index condition is presented to demonstrate the tool's functionality. Guideline developers from the National Institute for Health and Care Excellence and the Scottish Intercollegiate Guidelines Network provided positive feedback on the tool. CONCLUSIONS: The tool is a proof-of-concept, and the user feedback has demonstrated that this is a step toward computer-interpretable guideline development. Using the digital tool can potentially improve evidence-driven guideline development through the availability of real-world data in real time.

Humans↗

PubMedDate not supplied

Validated QSAR prediction of OH tropospheric degradation of VOCs: splitting into training-test sets and consensus modeling.

The rate constant for hydroxyl radical tropospheric degradation of 460 heterogeneous organic compounds is predicted by QSAR modeling. The applied Multiple Linear Regression is based on a variety of theoretical molecular descriptors, selected by the Genetic Algorithms-Variable Subset Selection (GA-VSS) procedure. The models were validated for predictivity by both internal and external validation. For the external validation two splitting approaches, D-optimal Experimental Design and Kohonen Artificial Neural Networks (K-ANN), were applied to the original data set to compare the two methodologies. We emphasize that external validation is the only way to establish a reliable QSAR model for predictive purposes. Predicted data by consensus modeling from different models are also proposed.

Journal Article↗