Estimating interactions and subgroup-specific treatment effects in meta-analysis without aggregation bias: A within-trial framework.

ABSTRACT: Estimation of within-trial interactions in meta-analysis is crucial for reliable assessment of how treatment effects vary across participant subgroups. However, current methods have various limitations. Patients, clinicians and policy-makers need reliable estimates of treatment effects within specific covariate subgroups, on relative and absolute scales, in order to target treatments appropriately-which estimation of an interaction effect does not in itself provide. Also, the focus has been on covariates with only two subgroups, and may exclude relevant data if only a single subgroup is reported. Therefore, in this article we further develop the "within-trial" framework by providing practical methods to (1) estimate within-trial interactions across two or more subgroups; (2) estimate subgr

SUBMITTER: Godolphin PJ 

PROVIDER: S-EPMC10087172 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature