FWER control in adaptive designs with group-wise futility

Music City Center 

In adaptive design clinical trials, controlling type 1 error is critical to ensuring the validity of statistical inferences. Traditional methods for type 1 error control, such as the Bonferroni and Holmes procedures, have been widely used to adjust for multiple comparisons. However, these methods often lead to conservative results, limiting statistical power and increasing the risk of Type II errors. Additionally, they do not adequately account for the dynamic nature of adaptive trials, where interim analyses and information updating are integral to the study design. This paper introduces a type 1 error control approach designed specifically for adaptive trials with multiple correlated comparisons. Our method uses an iterative approach to identify an optimal level of significance at which to test the individual hypotheses. This balances the family wise error rate while maintaining a desired level of statistical power. We compared the efficiency of our technique with more traditional methods, as well as more recent simulation-based approaches, through simulation studies. We further integrate our approach with Go/No-go decision making with multiple endpoints.

Multiplicity adjustment

group sequential design

correlated endpoints 

Biopharmaceutical Section