In oncology, phase II studies are crucial for clinical development plans, as they identify potent agents with sufficient activity to continue development in the subsequent phase III trials. Traditionally, phase II studies are single-arm studies, with an endpoint of treatment efficacy in the short-term. However, drug safety is also an important consideration. Thus, in the context of such multiple outcome design, predictive probabilities-based Bayesian monitoring strategies have been developed to assess if a clinical trial will show a conclusive result at the planned end of the study. In this paper, we propose a new simple index vector for summarizing the results that cannot be captured by existing strategies. Specifically, for each interim monitoring time point, we calculate the Bayesian predictive probability using our new index, and use it to assign a go/no-go decision. Finally, simulation studies are performed to evaluate the operating characteristics of the design. This analysis demonstrates that the proposed method makes appropriate interim go/no-go decisions.

翻译：在肿瘤学中，二期试验对于临床开发计划至关重要，因其能够识别具有足够活性的有效药物，以推进至后续三期试验。传统上，二期试验为单臂设计，以短期治疗疗效作为终点。然而，药物安全性同样是需要重点考量的因素。因此，在多重结局设计的背景下，已开发出基于预测概率的贝叶斯监测策略，用于评估临床试验是否能在计划终点时得出决定性结论。本文提出一种新的简洁指标向量，以概括现有策略无法捕捉的结果。具体而言，在每次中期监测时间点，我们利用新指标计算贝叶斯预测概率，并据此做出继续/终止决策。最后，通过模拟研究评估该设计的操作特征。分析表明，所提方法能够做出合理的中期继续/终止决策。