Assessment of heterogeneity in an individual participant data meta-analysis of prediction models: An overview and illustration
Steyerberg EW, Nieboer D, Debray TPA, van Houwelingen HC
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 = 11022 patients). The insights into various aspects of heterogeneity are important to develop better models and understand problems with the transportability of absolute risk predictions.
Cite as: Steyerberg EW, Nieboer D, Debray TPA, van Houwelingen HC. Assessment of heterogeneity in an individual participant data meta-analysis of prediction models: An overview and illustration. Stat Med 2019, volume 0. DOI: 10.1002/sim.8296.