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.

翻译：临床假设的先验概率尚未被系统性地应用于临床试验设计，原因在于担心较差的先验可能导致错误的决策。为解决这一顾虑，本文阐述了一种保守的贝叶斯试验设计方法，要求主要试验结果的运行特征强于先验。该方法与当前贝叶斯设计方法互补，通过定义与离散设计先验相称的样本量，防止先验-数据冲突。该方法具备伦理性，要求设计符合达到预设临床均衡失衡水平的要求。文中讨论了实际案例，展示了针对二分类或时间至事件终点的试验设计。研究表明，适度增加II期研究样本量，可为药物开发中的"通过/不通过"决策提供高水平的总体证据。群体序贯确证性设计所提供的阴性证据水平可忽略不计，这突显了在疗效边界之外补充非约束性无效性标准的重要性。