Clinical trials are an integral component of medical research. Trials require careful design to, for example, maintain the safety of participants, use resources efficiently and allow clinically meaningful conclusions to be drawn. Adaptive clinical trials (i.e. trials that can be altered based on evidence that has accrued) are often more efficient, informative and ethical than standard or non-adaptive trials because they require fewer participants, target more promising treatments, and can stop early with sufficient evidence of effectiveness or harm. The design of adaptive trials requires the pre-specification of adaptions that are permissible throughout the conduct of the trial. Proposed adaptive designs are then usually evaluated through simulation which provides indicative metrics of performance (e.g. statistical power and type-1 error) under different scenarios. Trial simulation requires assumptions about the data generating process to be specified but correctly specifying these in practice can be difficult, particularly for new and emerging diseases. To address this, we propose an approach to design adaptive clinical trials without needing to specify the complete data generating process. To facilitate this, we consider a general Bayesian framework where inference about the treatment effect on a time-to-event outcome can be performed via the partial likelihood. As a consequence, the proposed approach to evaluate trial designs is robust to the specific form of the baseline hazard function. The benefits of this approach are demonstrated through the redesign of a recent clinical trial to evaluate whether a third dose of a vaccine provides improved protection against gastroenteritis in Australian Indigenous infants.

翻译：临床试验是医学研究的核心组成部分。试验需要精心设计，例如保障受试者安全、高效利用资源，并得出具有临床意义的结论。适应性临床试验（即可根据已积累的证据进行调整的试验）通常比标准或非适应性试验更高效、信息更丰富且更符合伦理，因其所需受试者更少、聚焦更有前景的治疗方案，并能在获得疗效或危害的充分证据时提前终止。适应性试验的设计需要预先规定试验过程中允许进行的调整。随后通常通过模拟评估所提出的适应性设计方案，以提供不同场景下的性能指标（如统计功效和I类错误率）。试验模拟需要指定数据生成过程的假设，但在实际中正确指定这些假设往往存在困难，尤其对于新兴疾病。为解决此问题，我们提出一种无需指定完整数据生成过程即可设计适应性临床试验的方法。为此，我们采用通用贝叶斯框架，通过偏似然函数对时间至事件结局的治疗效应进行推断。因此，所提出的试验设计评估方法对基线风险函数的具体形式具有稳健性。我们通过对近期一项评估第三剂疫苗能否为澳大利亚原住民婴儿提供更强胃肠炎保护效果的临床试验进行重新设计，展示了该方法的优势。