One-stage individual participant data meta-analysis models: estimation of treatment-covariate interactions must avoid ecological bias by separating out within-trial and across-trial information.

ABSTRACT: Stratified medicine utilizes individual-level covariates that are associated with a differential treatment effect, also known as treatment-covariate interactions. When multiple trials are available, meta-analysis is used to help detect true treatment-covariate interactions by combining their data. Meta-regression of trial-level information is prone to low power and ecological bias, and therefore, individual participant data (IPD) meta-analyses are preferable to examine interactions utilizing individual-level information. However, one-stage IPD models are often wrongly specified, such that interactions are based on amalgamating within- and across-trial information. We compare, through simulations and an applied example, fixed-effect and random-effects models for a one-stage IPD meta-analysi

SUBMITTER: Hua H 

PROVIDER: S-EPMC5299543 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature