Statistical inference for heterogeneous treatment effect with right-censored data from synthesizing randomized clinical trials and real-world data.

ABSTRACT: The heterogeneous treatment effect plays a crucial role in precision medicine. There is evidence that real-world data, even subject to biases, can be employed as supplementary evidence for randomized clinical trials to improve the statistical efficiency of the heterogeneous treatment effect estimation. In this paper, for survival data with right censoring, we consider estimating the heterogeneous treatment effect, defined as the difference of the treatment-specific conditional restricted mean survival times given covariates, by synthesizing evidence from randomized clinical trials and the real-world data with possible biases. We define an omnibus bias function to characterize the effect of biases caused by unmeasured confounders, censoring, and outcome heterogeneity, and further, identify

SUBMITTER: Mao G 

PROVIDER: S-EPMC12505326 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature