Work

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

Year: 2019

Type: article

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.

Source: Statistics in Medicine

DOI: 10.1002/sim.8296

Authors: Ewout W. Steyerberg, Daan Nieboer, Thomas P.A. Debray, Hans C. van Houwelingen

Institutions: Leiden University Medical Center, Erasmus MC, University Medical Center Utrecht

Language: English

Topic: Meta-analysis and systematic reviews

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $4,000