ArticleStatistics in medicine2019
Impact of predictor measurement heterogeneity across settings on the performance of prediction models: A measurement error perspective.
Article in Statistics in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 5 of them syntheses that pooled it.
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Who cites it
48 citing papers in PubMed, 5 syntheses or guidelines pooled it.
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- Prediction models for self-harm and suicide: a systematic review and critical appraisal.BMC medicine · 2025Pooled it
- The global prevalence of emotional eating in overweight and obese populations: A systematic review and meta-analysis.British journal of psychology (London, England : 1953) · 2025Pooled it
- Prediction Models for Physical, Cognitive, and Mental Health Impairments After Critical Illness: A Systematic Review and Critical Appraisal.Critical care medicine · 2020Pooled it
- An informatics framework to harmonize electronic health record medication data for managed care analytics and artificial intelligence applications.Journal of managed care & specialty pharmacy · 2026Article
- Development of a noninvasive ultrasound-based model for predicting high-risk esophageal varices in hepatitis-related cirrhosis.Ultrasonography (Seoul, Korea) · 2026Article
- Dynamic Borrowing From Historical Controls via the Synthetic Prior With Covariates in Randomized Clinical Trials.Statistics in medicine · 2026Article
- Digital Monitoring of Pre-Exposure Prophylaxis Users Through Electronic Patient-Reported Outcome Measures and Electronic Patient-Reported Experience Measures: Multicenter Prospective Study on Feasibility, Safety, and Predictive Modeling of Digital Engagement.Journal of medical Internet research · 2026Observational
- Cardiovascular risk stratification without recalibration: A comparative study of the PREVENT and WHO risk scores in a multiethnic Brazilian cohort.American journal of preventive cardiology · 2026Article
- Latent trait or sum score: addressing measurement challenges in the prediction of self-rated symptom outcomes in psychological treatment.Frontiers in psychology · 2026Article
- Commentary: Development and validation of a multivariate predictive model for cancer-related fatigue in esophageal carcinoma: a prospective cohort study integrating biomarkers and psychosocial factors.Frontiers in oncology · 2026Article
- An interpretable XGBoost model for contrast-associated acute kidney injury in patients with acute coronary syndrome: development and geographical external validation.Frontiers in digital health · 2026Article
- Secondary Prevention of AFAIS: Deploying Traditional Regression, Machine Learning, and Deep Learning Models to Validate and Update CHA2DS2-VASc for 90-Day Recurrence.Journal of clinical medicine · 2025Article
- MRDadaptis: self-adaptive parameter configuration enhances minimal residual disease detection in heterogeneous ctDNA samples.Briefings in bioinformatics · 2025Article
- Evaluation of amoxicillin and benzylpenicillin therapy in early-onset neonatal sepsis: a pharmacometric external validation and simulation study.The Journal of antimicrobial chemotherapy · 2025Article
- Predicting prolonged work absence due to musculoskeletal disorders: development, validation, and clinical usefulness of prognostic prediction models.International archives of occupational and environmental health · 2025Article
- Can we predict the future of respiratory failure prediction?Critical care (London, England) · 2025Review
- Data-Driven Approach to Development of a Risk Score for Periprosthetic Joint Infections in Total Joint Arthroplasty Using Electronic Health Records.The Journal of arthroplasty · 2025Article
- Diagnostic prediction model for screening of elevated low-density and non-high-density lipoproteins in young Thai adults between 20 and 40 years of age.BMJ health & care informatics · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is widely acknowledged that the predictive performance of clinical prediction models should be studied in patients that were not part of the data in which the model was derived. Out-of-sample performance can be hampered when predictors are measured differently at derivation and external validation. This may occur, for instance, when predictors are measured using different measurement protocols or when tests are produced by different manufacturers. Although such heterogeneity in predictor measurement between derivation and validation data is common, the impact on the out-of-sample performance is not well studied. Using analytical and simulation approaches, we examined out-of-sample performance of prediction models under various scenarios of heterogeneous predictor measurement. These scenarios were defined and clarified using an established taxonomy of measurement error models. The results of our simulations indicate that predictor measurement heterogeneity can induce miscalibration of prediction and affects discrimination and overall predictive accuracy, to extents that the prediction model may no longer be considered clinically useful. The measurement error taxonomy was found to be helpful in identifying and predicting effects of heterogeneous predictor measurements between settings of prediction model derivation and validation. Our work indicates that homogeneity of measurement strategies across settings is of paramount importance in prediction research.
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