Abstract–Platform trials are increasingly popular in clinical research since these trials can evaluate multiple treatments in targeted subgroups of patients within a single trial infrastructure. In this article, we describe the development and implementation of a new clinical trial design OPTIM-ARTS (Open Platform Trial Investigating Multiple Compounds—Adaptive Randomized Design with Treatment Selection)—with application to a phase II study of an anti-PD-1 antibody in combination with other novel targeted therapies and immuno-agents in metastatic melanoma. The design consists of two main parts—the open platform (selection) phase, in which different treatments are initially assessed for efficacy in a randomized fashion, and the expansion phase, which will allow for a formal examination of efficacy with the selected promising treatment(s). The sample size for the expansion phase is chosen adaptively, using Bayesian shrinkage estimation, to mitigate selection bias due to potential random highs, and to ensure high predictive probability of obtaining significant final results. We performed calibration of the proposed design in a platform trial setting with four treatment arms and compared it with more standard designs. We found that our design is flexible and efficient, and it could be useful in an open platform trial setting with multiple investigational compounds.

摘要-平台试验在临床研究中越来越受欢迎，因为这些试验可以在单个试验基础设施内评估目标患者亚组的多种治疗方法。在本文中，我们描述了一种新的临床试验设计 OPTIM-ARTS（研究多种化合物的开放平台试验——具有治疗选择的自适应随机设计）的开发和实施——并应用于抗 PD-1 抗体的 II 期研究与转移性黑色素瘤的其他新型靶向疗法和免疫剂相结合。该设计由两个主要部分组成——开放平台（选择）阶段，其中最初以随机方式评估不同治疗的疗效，以及扩展阶段，这将允许对所选有希望的治疗的疗效进行正式检查。 s)。使用贝叶斯收缩估计自适应地选择扩展阶段的样本大小，以减轻由于潜在随机高点导致的选择偏差，并确保获得重要最终结果的高预测概率。我们在具有四个治疗臂的平台试验环境中对提议的设计进行了校准，并将其与更多标准设计进行了比较。我们发现我们的设计灵活高效，并且在具有多种研究化合物的开放平台试验环境中很有用。我们在具有四个治疗臂的平台试验环境中对提议的设计进行了校准，并将其与更多标准设计进行了比较。我们发现我们的设计灵活高效，并且在具有多种研究化合物的开放平台试验环境中很有用。我们在具有四个治疗臂的平台试验环境中对提议的设计进行了校准，并将其与更多标准设计进行了比较。我们发现我们的设计灵活高效，并且在具有多种研究化合物的开放平台试验环境中很有用。