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临床试验中的竞争风险:它们是否重要,我们应该如何考虑它们?

John Gregson¹, Stuart J Pocock¹, Stefan D Anker²

¹Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom.

Journal of the American College of Cardiology

|September 4, 2024

概括

这项研究引入了一种新的多重归算方法,以准确分析临床试验中的竞争风险,如非心血管死亡. 这种方法改进了传统方法,这些方法在处理患者死亡率数据时可能会误导.

科学领域:

生物统计学生物统计学
临床试验方法论临床试验方法论
流行病学流行病学

背景情况:

随机试验中的患者随访通常涉及与主要结果无关的死亡,称为竞争风险.
传统的统计方法 (例如,考克斯模型) 可能会误导患者数据,假设幸存者与死亡者相似.
现有的竞争性风险模型,如Fine和Grey模型,可以被滥用并导致误导性结论.

研究的目的:

提出和评估一种替代的统计方法来处理临床试验数据中的竞争风险.
开发一种方法,可信地解释了在经历竞争事件的患者中感兴趣的结果高风险.
为评估竞争性风险的影响提供一个逻辑框架,而不是假设一个唯一的解决方案.

主要方法:

开发一种新的多重归算方法来模拟竞争风险.
拟议方法应用于三项心血管临床试验的数据.
通过模拟研究进行验证,以评估方法的性能和稳定性.

主要成果:

拟议的多重归算方法为分析竞争性风险提供了一个合理的框架.
心血管试验和模拟中的说明性例子凸显了传统方法的局限性.
该方法提供了一个逻辑的方式来探索竞争风险的影响,承认固有的不确定性.

结论:

临床试验中对竞争性风险的传统分析可能具有误导性.
拟议的多重归算方法为处理竞争性风险提供了更合适和细微的方法.
提供了实用建议,用于在未来的临床试验中更好地分析竞争风险.

关键词:

考克斯的比例危险模型.精细和灰色的模型.临床试验是指临床试验中的临床试验.竞争的风险竞争的风险.事件结果事件的结果.多重的归算是多重的归算.

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