将外部控制纳入随机临床试验的设计:实体瘤的案例研究
Emily M Damone1, Jiawen Zhu2, Herbert Pang2
1Department of Biostatistics, University of North Carolina, 3109 McGavran-Greenberg Hall, CB #7420, Chapel Hill, NC, 27599, USA.
BMC medical research methodology
|November 2, 2024
概括
混合控制试验通过结合历史外部数据来提高效率. 一种新的Case Weighted Adaptive Power Prior方法在临床试验设计的模拟中证明了优越的功率和受控的类型-1错误.
科学领域:
- 临床试验方法论 临床试验方法论
- 生物统计学 生物统计学
- 瘤学研究研究
背景情况:
- 历史的外部控制数据对于设计未来的临床试验越来越重要.
- 混合控制设计提供了更高的效率,需要更少的患者和资源.
- 混合设计的统计方法,考虑对照组差异,是不发达的.
研究的目的:
- 为了说明混合对照试验的分析框架,当随机对照试验 (RCT) 不可行时.
- 为了比较混合控制试验分析的五种统计方法的性能.
- 通过模拟来评估这些设计的操作特性.
主要方法:
- 利用两个已完成的非状非小细胞肺癌 (NSCLC) RCT 和电子健康记录数据库.
- 对混合控制设计的五种不同的统计分析方法进行了比较.
- 进行模拟研究以评估每个方法的功率和1型错误控制.
主要成果:
- 案例加权自适应功率先验方法产生了与原始试验结论一致的危险比率估计和更窄的置信区间.
- 模拟研究表明,Case Weighted Adaptive Power Prior方法获得了最高的统计功率.
- 案例加权自适应功率先验方法证明了在具有一致样本大小的模拟中得到良好控制的1型错误.
结论:
- 拟议的混合控制框架允许透明的试验设计,解决对照组的差异.
- 该框架有效控制1型错误,同时利用外部数据提高效率.
- 病例加权自适应功率先验方法是混合控制试验分析的强有力的方法.
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