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Assessment of heterogeneity in an individual participant data meta-analysis of prediction models: An overview and
Ewout W Steyerberg1,2, Daan Nieboer2, Thomas P A Debray3,4
1Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
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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