一种基于等级的方法来提高推断无的2/3期临床试验的效率,并优化剂量
Xin Wang1, Min Chen1, Shuyu Chu1
1Bristol Myers Squibb Company, 86 Morris Ave, Summit, NJ 07901, USA.
Contemporary clinical trials
|July 19, 2023
概括
无的2/3相适应设计加速了药物开发. 一种基于等级的新方法通过控制I型错误和增加功率来改善剂量选择,与现有的调整相比.
科学领域:
- 临床试验的设计
- 生物统计学 生物统计学
- 制药发展 制药发展
背景情况:
- 无的2/3阶段适应性设计整合了剂量选择和确认试验.
- 瘤学药物开发越来越关注最大有效剂量,需要强大的剂量选择方法.
- 对2期和3期数据的综合分析可能会因剂量选择和终点相关性而导致I型错误.
研究的目的:
- 提出一种新的统计方法,用于在无的2/3相适应设计中选择剂量.
- 解决I型错误的通货膨胀问题,提高组合分析中的统计能力.
- 为现有方法提供替代方案,如Sidák和传统的Dunnett调整.
主要方法:
- 使用基于生物标志物等级的顺序测试统计数据来选择剂量.
- 纳入所选剂量的排名顺序和终点之间的相关性.
- 为未知相关性提出基于等级的Dunnett调整,包括传统的Dunnett调整.
主要成果:
- 提出的方法有效地控制了整体的I型错误.
- 新方法显示统计能力均高于Sidák和传统的Dunnett调整.
- 在所有考虑的剂量和终点之间的相关情景中,性能是稳健的.
结论:
- 提出的基于等级的统计方法在无的2/3期适应性试验中为剂量选择提供了优越的方法.
- 这种方法提高了瘤学和其他领域的临床试验设计的效率和可靠性.
- 它提供了一种更强大,更准确的方式来结合第2阶段和第3阶段的数据,用于监管决策.
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