Inference on subgroups identified based on a heterogeneous treatment effect in a post hoc analysis of a clinical trial.

ABSTRACT: Due to the many benefits of understanding treatment effect heterogeneity in a clinical trial, an exploratory post hoc subgroup analysis is often performed to find subpopulations of patients with conditional average treatment effect that suggests better treatment efficacy than in the overall population. A naive re-substitution approach uses all available data to identify a subgroup and then proceeds with estimation and inference using the same data set. This approach generally leads to an overly optimistic estimate of conditional average treatment effect. In this article, in a post hoc analysis, we estimate the target optimal subgroup through maximizing a utility function, from candidates systematically identified with a penalized regression. We then compare two resampling-based bias-correc

SUBMITTER: Zhao B 

PROVIDER: S-EPMC10338703 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature