Assessment of heterogeneity in an individual participant data meta‐analysis of prediction models: An overview and illustration

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 predictio...

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Veröffentlicht in:Statistics in medicine 2019-09, Vol.38 (22), p.4290-4309
Hauptverfasser: Steyerberg, Ewout W., Nieboer, Daan, Debray, Thomas P.A., Houwelingen, Hans C.
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Sprache:eng
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Zusammenfassung: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.
ISSN:0277-6715
1097-0258
DOI:10.1002/sim.8296