  Prior probabilities of clinical hypotheses are not systematically used for
clinical trial design yet, due to a concern that poor priors may lead to poor
decisions. To address this concern, a conservative approach to Bayesian trial
design is illustrated here, requiring that the operational characteristics of
the primary trial outcome are stronger than the prior. This approach is
complementary to current Bayesian design methods, in that it insures against
prior-data conflict by defining a sample size commensurate to a discrete design
prior. This approach is ethical, in that it requires designs appropriate to
achieving pre-specified levels of clinical equipoise imbalance. Practical
examples are discussed, illustrating design of trials with binary or time to
event endpoints. Moderate increases in phase II study sample size are shown to
deliver strong levels of overall evidence for go/no-go clinical development
decisions. Levels of negative evidence provided by group sequential
confirmatory designs are found negligible, highlighting the importance of
complementing efficacy boundaries with non-binding futility criteria.

Methodology;Applications