Sample-Size Optimal Bayesian Procedure for Sequential Pharmaceutical Trials

摘要

Consider a pharmaceutical trial where the consequences of different decisions areexpressed on a financial sale. The efficacy of the new drug under consideration has a prior distribution obtained from the underlying biological process, animal experiments, clinical experience, and so forth. In an important paper, Berry and Ho (1988) show how these components are used to establish an optimal (Bayes) sequential procedure, assuming a known constant size at each decision point. We show in this article how it is also possible to optimize with respect to the sample-size rule. This last component of the design, which is missing from most sequential procedures, has the potential to yield considerably larger expected net gains.