Elastic priors to dynamically borrow information from historical data in clinical trials.

ABSTRACT: Use of historical data and real-world evidence holds great potential to improve the efficiency of clinical trials. One major challenge is to effectively borrow information from historical data while maintaining a reasonable type I error and minimal bias. We propose the elastic prior approach to address this challenge. Unlike existing approaches, this approach proactively controls the behavior of information borrowing and type I errors by incorporating a well-known concept of clinically significant difference through an elastic function, defined as a monotonic function of a congruence measure between historical data and trial data. The elastic function is constructed to satisfy a set of prespecified criteria such that the resulting prior will strongly borrow information when historical and

SUBMITTER: Jiang L 

PROVIDER: S-EPMC11840877 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature