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Efficacy and toxicity monitoring via Bayesian predictive probabilities in phase Ⅱ clinical trials

机译：Ⅱ期临床试验中贝叶斯预测概率的疗效和毒性监测

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摘要

Bayesian monitoring strategies based on predictive probabilities are widely used in phase II clinical trials that involve a single efficacy binary variable. The essential idea is to control the predictive probability that the trial will show a conclusive result at the scheduled end of the study, given the information at the interim stage and the prior beliefs. In this paper, we present an extension of this approach to incorporate toxicity considerations in single-arm phase II trials. We consider two binary endpoints representing response and toxicity of the experimental treatment and define the result as successful at the conclusion of the study if the posterior probability of an high efficacy and that of a small toxicity are both sufficiently large. At any interim look, the Multinomial-Dirichlet distribution provides the predictive probability of each possible combination of future efficacy and toxicity outcomes. It is exploited to obtain the predictive probability that the trial will yield a positive outcome, if it continues to the planned end. Different possible interim situations are considered to investigate the behaviour of the proposed predictive rules and the differences with the monitoring strategies based on posterior probabilities are highlighted. Simulation studies are also performed to evaluate the frequentist operating characteristics of the proposed design and to calibrate the design parameters.
机译：基于预测概率的贝叶斯监测策略广泛应用于II期临床试验，其涉及单一效能的二元变量。在临时阶段和先前信仰的情况下，基本思想是控制试验将在研究的预定结束时显示在研究的结论结果。在本文中，我们展示了这种方法的延伸，以掺入单臂期II试验中的毒性考虑。我们考虑代表实验治疗的响应和毒性的两个二进制端点，并将结果定义在研究的结论中，如果高效的后验概率和小毒性的概率都足够大。在任何临时外观下，多项式 - Dirichlet分布提供了每个可能的未来疗效和毒性结果组合的预测概率。如果它继续计划结束，则利用试验将产生积极结果的预测概率。不同可能的临时情况被认为是调查拟议的预测规则的行为，并突出了基于后验概率的监测策略的差异。还进行了仿真研究以评估所提出的设计的频繁操作特性并校准设计参数。

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