Zhong Weibin, Liu Jing-Ou, Wang Chenguang
Biostatistics and Data Management, Regeneron Pharmaceuticals, Tarrytown, New York, USA.
Stat Med. 2025 Sep;44(20-22):e70209. doi: 10.1002/sim.70209.
Typical phase 1 oncology studies identify the maximum tolerated dose as the "optimal" dose for subsequent phases. With the advancement of molecular targeted agents and immunotherapies, however, evaluating two or more doses has become increasingly critical for dose selection. Such evaluation is often done in phase 2 studies in a randomized manner. In this article, we evaluate the strategy of applying an adaptive phase 2/3 seamless design for dose selection in oncology studies. Specifically, we consider the "drop-the-losers" design, where multiple treatment arms and a control arm are administered during the initial stage, and a more effective arm is identified for later stages by a binary surrogate endpoint such as overall response. We derive the theoretical type I error inflation scale and conduct simulation studies to illustrate the impact of various factors on the type I error inflation in such designs. Furthermore, we demonstrate the findings through the design of a lung cancer trial and introduce a software that implements the proposed design.
典型的1期肿瘤学研究将最大耐受剂量确定为后续阶段的“最佳”剂量。然而，随着分子靶向药物和免疫疗法的发展，评估两种或更多剂量对于剂量选择变得越来越关键。这种评估通常在2期研究中以随机方式进行。在本文中，我们评估了在肿瘤学研究中应用适应性2/3期无缝设计进行剂量选择的策略。具体而言，我们考虑“淘汰失败者”设计，即在初始阶段给予多个治疗组和一个对照组，并通过二元替代终点（如总缓解率）确定后期更有效的治疗组。我们推导了理论I型错误膨胀尺度，并进行模拟研究以说明各种因素对这类设计中I型错误膨胀的影响。此外，我们通过一项肺癌试验的设计展示研究结果，并介绍一款实现所提出设计的软件。
