使用临床试验中的倾向性得分来估计治疗效果,以历史对照为基础
Saki Kanamori1, Masahiro Takeuchi2,3
1Department of Clinical Medicine (Biostatistics), Graduate School of Pharmaceutical Sciences, Kitasato University, 5-9-1, Shirokane, Minato-ku, Tokyo, 108-8641, Japan. kanamoris@pharm.kitasato-u.ac.jp.
BMC medical research methodology
|February 23, 2024
概括
一个新的倾向分数 (PS) 模型在将随机对照试验 (RCT) 数据与历史对照组合时改善治疗效果估计. 当数据集之间的共变量分布不同时,这种方法特别有效.
科学领域:
- 生物统计学 生物统计学
- 临床试验设计 临床试验设计
- 卫生经济学 卫生经济学
背景情况:
- 临床试验需要对照组来评估治疗效果.
- 罕见或难治性疾病试验中的伦理考虑限制了对照组的分配.
- 历史对照数据提供了一个解决方案,以补充临床试验中的对照组.
研究的目的:
- 提出一种新的倾向分数 (PS) 模型,用于整合随机对照试验 (RCT) 和历史对照数据.
- 评估拟议方法在估计治疗效果方面的表现.
主要方法:
- 开发一个新的PS模型,将数据源 (RCT与历史) 结合起来.
- 使用模拟数据评估拟议的方法.
- 与传统方法进行治疗效果估计的比较.
主要成果:
- 当共变量分布对齐时,拟议方法和常规方法之间的性能相似.
- 建议方法在RCT和历史数据之间的共变量分布有显著差异时具有优异的性能.
结论:
- 拟议的PS模型有效地估计了利用历史控制数据在RCT中的治疗效应.
- 这种方法即使在共同变量分布的相似性未知的情况下也是有价值的.
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