Principled type I error rate inflation in two-arm clinical trial designs with external control information borrowing

Abstract

External information borrowing is often considered in order to improve a clinical trial's efficiency. The Bayesian approach borrows such external information by specifying an informative prior distribution. A potential issue with this procedure is that external and current information may conflict, but such inconsistency may not be predictable a priori. Robust prior choices are typically proposed to limit extreme worsening of operating characteristics (OCs) in these situations. However, trade-offs are still present and in general strict control of type I error (TIE) rate prevents any power gains. In this context, principled justifications for TIE rate inflation can be of interest. We investigate two-arm trials, with a focus on external/historical control information borrowing. We illustrate OCs trade-offs and propose an interpretable approach for external information borrowing. The approach analytically links observed prior-data conflict with allowances for TIE rate inflation and power loss. The approach does not rely on a robust prior specification, but can instead be interpreted as an adaptive choice of Bayes - or, equivalently, frequentist - test decision thresholds under the available informative prior. In addition, it can be used to evaluate any dynamic borrowing approach from a frequentist testing standpoint, and to guarantee robustness with respect to misspecification of the data generating process (i.e., design prior) in Bayesian evaluations. A development for both Normal and binomial outcomes is provided.