Multivariate Bayesian Dynamic Borrowing for Repeated Measures Data With Application to External Control Arms in Open-Label Extension Studies.

ABSTRACT: Borrowing analyses are increasingly important in clinical trials. We develop a method for using robust mixture priors in multivariate dynamic borrowing. The method was motivated by a desire to produce causally valid, long-term treatment effect estimates of a continuous endpoint from a single active-arm open-label extension study following a randomized clinical trial by dynamically incorporating prior beliefs from a long-term external control arm. The proposed method is a generally applicable Bayesian dynamic borrowing analysis for estimates of multivariate summary metrics based on a multivariate normal likelihood function for various parameter models, some of which we describe. There are important connections to estimation incorporating a prior belief for a hypothetical estimand strategy,

SUBMITTER: Hartley BF 

PROVIDER: S-EPMC12504158 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature