ArticleStatistics in medicine2019
Assessment of heterogeneity in an individual participant data meta-analysis of prediction models: An overview and illustration.
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 41 papers, 7 of them syntheses that pooled it.
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Who cites it
41 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Estimating individualized treatment effects using an individual participant data meta-analysis.BMC medical research methodology · 2024Pooled it
- Pooled it
- Individual participant data meta-analysis with mixed-effects transformation models.Biostatistics (Oxford, England) · 2022Pooled it
- Systematic review and meta-analysis of mortality risk prediction models in adult cardiac surgery.Interactive cardiovascular and thoracic surgery · 2021Pooled it
- Developing more generalizable prediction models from pooled studies and large clustered data sets.Statistics in medicine · 2021Pooled it
- Accuracy of pancreatic stone protein for the diagnosis of infection in hospitalized adults: a systematic review and individual patient level meta-analysis.Critical care (London, England) · 2021Pooled it
- Effect of mannose-binding lectin gene polymorphisms on the risk of rheumatoid arthritis: Evidence from a meta-analysis.International journal of rheumatic diseases · 2021Pooled it
- Improving early prediction for adverse dengue outcomes using data from the IDAMS prospective multicentre study.Nature communications · 2026Observational
- Updating the International Early Warning Score with frailty and comparing to gestalt for prediction of 3-day critical illness and mortality in emergency department patients.Internal and emergency medicine · 2026Article
- External validation of a US claims-based frailty indicator and development of a population-specific model for the German healthcare system.GeroScience · 2026Article
- Clustered flexible calibration plots for binary outcomes using random effects modeling.Research synthesis methods · 2026Article
- Does the Addition of Vaginal Oestrogen to Anticholinergic Medication Improve Overactive Bladder Symptoms? A Systematic Review and Meta-Analysis.International urogynecology journal · 2026Review
- Hip Morphology-Based Osteoarthritis Risk Prediction Models: Development and External Validation Using Individual Participant Data From the World COACH Consortium.Arthritis care & research · 2026Article
- Multimorbidity measurement strategies for predicting hospital visits.BMC health services research · 2025Article
- A personalized prediction of longitudinal growth using People-Like-Me methods.Computers in biology and medicine · 2025Article
- Beyond Conventional Meta-Analysis: A Meta-Learning Model to Predict Cohort-Level Mortality After Transcatheter Aortic Valve Replacement (TAVR).Journal of cardiovascular development and disease · 2025Review
- Multiple imputation for systematically missing effect modifiers in individual participant data meta-analysis.Statistical methods in medical research · 2025Article
- Heterogeneity in mortality risk prediction: a study of vulnerable adults in the Canadian longitudinal study on aging.Aging clinical and experimental research · 2025Article
- Pitfalls of single-study external validation illustrated with a model predicting functional outcome after aneurysmal subarachnoid hemorrhage.BMC medical research methodology · 2024Article
- Development and Validation of a Prediction Model for 1-Year Mortality in Patients With a Hematologic Malignancy Admitted to the ICU.Critical care explorations · 2024Article
Corrections and comments
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Clinical prediction models aim to provide estimates of absolute risk for a diagnostic or prognostic endpoint. Such models may be derived from data from various studies in the context of a meta-analysis. We describe and propose approaches for assessing heterogeneity in predictor effects and predictions arising from models based on data from different sources. These methods are illustrated in a case study with patients suffering from traumatic brain injury, where we aim to predict 6-month mortality based on individual patient data using meta-analytic techniques (15 studies, n = 11 022 patients). The insights into various aspects of heterogeneity are important to develop better models and understand problems with the transportability of absolute risk predictions.
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