Abstract：
Adaptive designs, such as group sequential designs (and the ones with additional adaptive features) or adaptive platform trials, have been quintessential efficient design strategies in trials of unmet medical needs, especially for generating evidence from global regions. Such designs allow interim decision making and making adjustment to study design when necessary, meanwhile maintaining study integrity and operating characteristics. However, driven by the heightened competitive landscape and the desire to bring effective treatment to patients faster, innovation in the already functional designs is still germane to further propel drug development to a more efficient path. One way to achieve this is by leveraging external real-world data (RWD) in the adaptive designs to support interim or final decision making. In this paper, we propose a novel framework of incorporating external RWD in adaptive design to improve interim and/or final analysis decision making. Within this framework, researchers can prespecify the decision process and choose the timing and amount of borrowing while maintaining objectivity and controlling of type I error. Simulation studies in various scenarios are provided to describe power, type I error, and other performance metrics for interim/final decision making. A case study in non-small cell lung cancer is used for illustration on proposed design framework.
摘要：
自适应设计,例如组顺序设计(以及具有额外自适应功能的设计)或自适应平台试验，在未满足的医疗需求试验中，是典型的有效设计策略，特别是从全球区域产生证据。这样的设计允许临时决策，并在必要时进行调整以研究设计，同时保持研究的完整性和操作特点。然而,在激烈的竞争环境和更快为患者提供有效治疗的愿望的推动下，在已经功能设计中的创新仍然与进一步推动药物开发走向更有效的道路密切相关。实现这一点的一种方法是在自适应设计中利用外部现实世界数据(RWD)来支持临时或最终决策。在本文中,我们提出了一个新的框架，将外部RWD纳入自适应设计，以改善临时和/或最终分析决策。在这个框架内,研究人员可以预先指定决策过程并选择借用的时间和金额，同时保持客观性并控制I型错误。提供了各种场景中的仿真研究来描述功率，I型错误,和其他绩效指标，用于中期/最终决策。非小细胞肺癌的案例研究用于说明所提出的设计框架。
