title: A framework for developing, implementing, and evaluating clinical prediction models in an individual participant data meta-analysis.
abstract: The use of individual participant data (IPD) from multiple studies is an increasingly popular approach when developing a multivariable risk prediction model. Corresponding datasets, however, typically differ in important aspects, such as baseline risk. This has driven the adoption of meta-analytical approaches for appropriately dealing with heterogeneity between study populations. Although these approaches provide an averaged prediction model across all studies, little guidance exists about how to apply or validate this model to new individuals or study populations outside the derivation data. We consider several approaches to develop a multivariable logistic regression model from an IPD meta-analysis (IPD-MA) with potential between-study heterogeneity. We also propose strategies for choosing a valid model intercept for when the model is to be validated or applied to new individuals or study populations. These strategies can be implemented by the IPD-MA developers or future model validators. Finally, we show how model generalizability can be evaluated when external validation data are lacking using internal-external cross-validation and extend our framework to count and time-to-event data. In an empirical evaluation, our results show how stratified estimation allows study-specific model intercepts, which can then inform the intercept to be used when applying the model in practice, even to a population not represented by included studies. In summary, our framework allows the development (through stratified estimation), implementation in new individuals (through focused intercept choice), and evaluation (through internal-external validation) of a single, integrated prediction model from an IPD-MA in order to achieve improved model performance and generalizability.
authors: Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. T.Debray@umcutrecht.nl
authors: Thomas P A
authors: TP
authors: Debray
authors: Karel G M
authors: KG
authors: Moons
authors: Ikhlaaq
authors: I
authors: Ahmed
authors: Hendrik
authors: H
authors: Koffijberg
authors: Richard David
authors: RD
authors: Riley
mesh_terms: D002986:Clinical Trials as Topic / Q000379:methods*; D003627:Data Interpretation, Statistical; D005544:Forecasting / Q000379:methods; D006801:Humans; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D020246:Venous Thrombosis / Q000175:diagnosis
keywords: individual participant data (IPD); internal-external validation; logistic regression; meta-analysis; multivariable; prediction research; risk prediction models