In oncology, phase II studies are crucial for clinical development plans as such studies identify potent agents with sufficient activity to continue development in the subsequent phase III trials. Traditionally, phase II studies are single-arm studies, with the primary endpoint being short-term treatment efficacy. However, drug safety is also an important consideration. In the context of such multiple-outcome designs, predictive probability-based Bayesian monitoring strategies have been developed to assess whether a clinical trial will provide enough evidence to continue with a phase III study at the scheduled end of the trial. Herein, we propose a new simple index vector for summarizing 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. The obtained results demonstrate that the proposed method makes appropriate interim go/no-go decisions.

翻译：在肿瘤学领域，二期试验作为临床开发计划的关键环节，旨在识别具有足够活性的有效药物，以便在后续三期试验中继续开发。传统上，二期试验采用单臂设计，主要终点为短期治疗效果。然而，药物安全性同样是重要考量因素。在多结局设计背景下，已开发出基于预测概率的贝叶斯监测策略，用以评估临床试验是否能在预定结束时提供足够证据支持三期试验的推进。本文提出一种新的简洁指标向量，用于总结现有策略无法捕捉的结果。具体而言，针对每个中期监测时间点，我们利用新指标计算贝叶斯预测概率，并据此做出继续/停止决策。最后通过模拟研究评估该设计的操作特性，结果表明所提方法能够做出适当的中期决策。