规划和实施剂量优化试验的统计学和实际考虑因素。
Statistical and practical considerations in planning and conduct of dose-optimization trials.
机构信息
Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Biostatistics and Research Decision Sciences, Merck and Co., Inc, Rahway, NJ, USA.
出版信息
Clin Trials. 2024 Jun;21(3):273-286. doi: 10.1177/17407745231207085. Epub 2024 Jan 19.
The U.S. Food and Drug Administration launched Project Optimus with the aim of shifting the paradigm of dose-finding and selection toward identifying the optimal biological dose that offers the best balance between benefit and risk, rather than the maximum tolerated dose. However, achieving dose optimization is a challenging task that involves a variety of factors and is considerably more complicated than identifying the maximum tolerated dose, both in terms of design and implementation. This article provides a comprehensive review of various design strategies for dose-optimization trials, including phase 1/2 and 2/3 designs, and highlights their respective advantages and disadvantages. In addition, practical considerations for selecting an appropriate design and planning and executing the trial are discussed. The article also presents freely available software tools that can be utilized for designing and implementing dose-optimization trials. The approaches and their implementation are illustrated through real-world examples.
美国食品和药物管理局启动了“Optimus 计划”,旨在将剂量发现和选择范式转变为确定最佳生物学剂量,以在获益和风险之间取得最佳平衡,而不是最大耐受剂量。然而,实现剂量优化是一项具有挑战性的任务,涉及多种因素,在设计和实施方面都比确定最大耐受剂量复杂得多。本文全面回顾了剂量优化试验的各种设计策略,包括 1/2 期和 2/3 期设计,并强调了它们各自的优缺点。此外,还讨论了选择合适设计和规划及执行试验的实际考虑因素。文章还介绍了可用于设计和实施剂量优化试验的免费软件工具。通过实际示例说明了这些方法及其实施。