在一般参数回归模型中比较评估治疗效应异质性的方法
Yao Chen1, Sophie Sun2, Konstantinos Sechidis3
1Advanced Methodology and Data Science, Novartis Pharmaceuticals Corporation, East Hanover, New Jersey, USA.
Statistics in medicine
|January 22, 2026
概括
本研究比较了在回归模型中评估治疗效果异质性的方法. 基于剩余分数的方法被强调为识别治疗效果修饰物的实用和可靠工具.
科学领域:
- 生物统计学 生物统计学
- 统计建模 统计建模
- 临床试验分析临床试验分析
背景情况:
- 评估治疗效果的异质性对于个性化医疗至关重要.
- 参数回归模型是常用的,但需要强大的方法来评估异质性.
研究的目的:
- 在参数回归模型中审查和比较评估治疗效果异质性的方法.
- 强调和评价治疗效果异质性的基于分数剩余的测试.
主要方法:
- 标准概率比率测试,引导概率比率测试和Goeman的全球测试的比较.
- 专注于基于分数残余的治疗效果测试,包括变体.
- 在临床试验中的模拟研究和说明.
主要成果:
- 基于剩余分数的方法证明了其实用性,灵活性和可靠性.
- 这些方法有效地探索治疗效果异质性和修饰剂.
- 提供了关于治疗效果异质性的决策指导.
结论:
- 建议使用基于剩余分数的方法来评估治疗效果的异质性.
- 这些方法为临床决策提供了宝贵的见解.
- 这项研究证实了这些方法在现实世界临床环境中的实用性.
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