Benefit–Risk Evaluation of Multi-Stage Adaptive Designs

Abstract

Under a group sequential design, the conditional power at an interim analysis represents the probability of success in the future given the past data. Because an adequate overall power is not a guarantee of an adequate conditional power, many authors in the literature have proposed multi-stage adaptive designs allowing sample size adjustment. In this paper, we evaluate the consequences of various such adaptive designs. This is achieved through the use of not only a conventional efficiency criterion of expected sample size, but also an effectiveness criterion from a benefit–risk analysis which takes into consideration some constraints associated with the drug development process. We show that with a proper choice of an adaptive design the conditional power can be maintained at a desirable level, which improves the efficiency, and more importantly, effectiveness of a clinical trial.