Premium
Assessment of heterogeneity in an individual participant data meta‐analysis of prediction models: An overview and illustration
Author(s) -
Steyerberg Ewout W.,
Nieboer Daan,
Debray Thomas P.A.,
Houwelingen Hans C.
Publication year - 2019
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.8296
Subject(s) - meta analysis , context (archaeology) , computer science , study heterogeneity , econometrics , medicine , mathematics , paleontology , biology
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.