将芬克尔斯坦-舒恩菲尔德测试概括为包含多个交替值
Yunhan Mou1, Tassos Kyriakides1,2, Scott Hummel3,4
1Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA.
Biometrical journal. Biometrische Zeitschrift
|February 28, 2026
概括
多个值的Finkelstein-Schoenfeld测试 (FS-MT) 提供了一种灵活的方式来分析心血管试验数据与复合终点. 这种新方法通过更好地纳入非致命事件来增强标准的芬克尔斯坦-舒恩菲尔德 (FS) 测试.
科学领域:
- 生物统计学 生物统计学
- 临床试验 临床试验
- 心血管研究研究心血管研究
背景情况:
- 结合致命和非致命事件的复合终点在心血管临床试验中很常见.
- 标准的芬克尔斯坦-舒恩菲尔德 (FS) 测试优先考虑致命事件,可能不足利用来自重大非致命事件的数据.
- 现有的方法可能无法完全捕捉复合终点中的所有事件的临床重要性.
研究的目的:
- 引入具有多个值 (FS-MT) 的Finkelstein-Schoenfeld测试,作为分析复合终点的更灵活的替代方案.
- 扩大传统的FS测试的功能,包括连续的,交替的值.
- 在FS-MT框架内开发一个权重适应方法来确定值.
主要方法:
- 拟议的FS-MT测试扩展了FS测试,通过连续应用多个值,并在不同的事件类型中交替进行.
- 开发了一种加权的自适应方法,以优化FS-MT测试的值选择.
- 进行了模拟研究,以评估FS-MT在各种条件下的操作特性 (随访时间,事件相关性,治疗效应).
- 使用Digitalis调查小组试验数据进行了一项案例研究,以证明FS-MT的实际应用.
主要成果:
- 模拟表明FS-MT测试保留了FS测试的统计特性.
- 该FS-MT测试允许更灵活地利用来自较低优先级,非致命事件的信息.
- 在不同的场景中评估了该方法的性能,证明了它的稳定性.
- 该案例研究说明了FS-MT方法的实际实用性和应用.
结论:
- 与标准FS测试相比,FS-MT测试在心血管试验中分析复合终点提供了统计学上合理和更灵活的方法.
- 这种方法允许通过更好地整合致命和非致命事件的信息来更全面地评估治疗效应.
- 开发的R包"FSMT"有助于在临床研究中实施这种先进的统计方法.
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