EXTENDING A BAYESIAN DECISION-THEORETIC APPROACH TO VALUE-BASED SEQUENTIAL CLINICAL TRIAL DESIGN

摘要

Recent work has illustrated how Bayesian approaches to discrete simulation optimization can be applied to clinical trial design. These approaches balance the expected cost of running the trial with the expected economic benefits of adopting one of the treatments, based on the information which accumulates during the trial. Some work in this space has presented a model of a fully sequential trial, but with simplifying assumptions; other work has incorporated some special features of pragmatic clinical trials into a one-stage (that is, non-sequential) framework. This paper shows how simulation optimization ideas can be used to model fully sequential sampling for trials which contain these features.