临床试验中的测量代表性:模拟表明当前方法在精准医学背景下如何失败
Andrew Friedson1, Abigail Humphreys2, June Cha1
1Milken Institute, Washington, District of Columbia, United States of America.
PloS one
|March 10, 2026
概括
评估临床试验的代表性至关重要. 现有的方法可能不准确地评估针对特定患者群体的研究,特别是在精准医学中,可能会扭曲结果.
科学领域:
- 临床研究方法论临床研究方法论
- 医疗服务研究 医疗服务研究
- 生物统计学 生物统计学
背景情况:
- 临床试验的代表性对于评估干预的有效性和通用性至关重要.
- 目前评估代表性的方法受到疾病登记册数据质量的限制,可能不适合精确群体.
- 评估研究代表性对于确保临床发现的广泛适用性至关重要.
研究的目的:
- 评估现有的临床试验代表性措施对目标人群和注册数据之间的人口差异的敏感性.
- 确定对比群体的变化如何影响代表性指标的准确性.
- 突出评估临床试验代表性的潜在不准确性,特别是在精准医学研究中.
主要方法:
- 美国癌症临床试验 (2017-2023) 的人口统计数据 (性别,种族,种族) 与美国癌症统计数据库进行了比较.
- 使用精确的二项式测试来计算代表性指标.
- 在对比人群中引入模拟的人口变化来测试度量敏感性.
主要成果:
- 试验和注册人群之间的5个百分点的人口差异改变了24% (性别),40% (种族) 和32% (种族) 的研究中的代表性测试结果.
- 登记册和模拟人口之间较大的人口差异与指标性能下降相关.
- 当治疗针对人口统计学上不同的子组时,准确度的损失是显著的.
结论:
- 衡量临床试验代表性的现有方法在应用到精准医学队伍时显示精度降低.
- 这些指标对人口统计学变化的敏感性需要谨慎地解释研究代表性,特别是在向治疗中.
- 对于精准医学环境,需要进一步完善代表性评估方法.
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