在不成比例的危险下使用平均危险比率计算样本大小
Ina Dormuth1, Markus Pauly1,2, Geraldine Rauch3,4
1Department of Statistics, TU Dortmund University, Dortmund, Germany.
Biometrical journal. Biometrische Zeitschrift
|August 12, 2024
概括
平均危险比率 (AHR) 为具有不成比例危险的临床试验提供了一个强大的替代传统危险比率. 基于模拟的AHR测试样本大小计算提高了统计能力,提高了样本效率.
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
- 生存分析的分析.
背景情况:
- 在临床试验中,时间到事件的终点至关重要.
- 危险比率 (HRs) 是常用的,但假设比例危险 (PHs).
- 不成比例的危险 (N-PHs) 限制了标准HRs的解释性和适用性.
研究的目的:
- 引入并促进实际应用平均危险比率 (AHR) 作为影响度量.
- 开发和评估用于AHR测试的样本大小计算方法.
- 在风险不成比例的场景中解决HR的局限性.
主要方法:
- 开发了用于AHR测试的样本大小计算方法.
- 进行了广泛的模拟研究,以评估样本大小计算可靠性.
- 模拟涵盖了各种生存和审查分布,包括比例和非比例的危险.
主要成果:
- 平均危险比率 (AHR) 可以有效地处理时间变化的影响,而不需要相应的危险.
- 基于模拟的样本大小计算方法对于设计使用N-PHs的临床试验是可靠的.
- 与传统方法相比,利用AHR可以提高统计能力和更高效的样本大小.
结论:
- 平均危险比率 (AHR) 是分析时间到事件数据的宝贵工具,特别是当危险不成比例时.
- 基于模拟的样本大小计算提高了使用AHR的临床试验的设计.
- 通过AHR,可以更强大,更有效地检测到时间到事件结果中的群体差异.
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