根据OS预后得分进行匹配,以构建肺癌临床试验中的外部对照
Hugo Loureiro1,2,3, Andreas Roller4, Meike Schneider4
1Data and Analytics, Pharma Research and Early Development, Roche Innovation Center Munich (RICM), Penzberg, Germany.
Clinical pharmacology and therapeutics
|November 17, 2023
概括
瘤学中的外部控制 (eControls) 可以使用预后得分来改善. 与倾向分数相比,ROPRO预后分数方法显示了更可靠的对照组构造和更低的误差在估计生存结果.
科学领域:
- 在瘤学瘤学.
- 生物统计学 生物统计学
- 现实世界的证据.
背景情况:
- 外部控制 (eControls) 是来自历史数据的非随机控制臂.
- 由于缺乏随机化,实验和eControl队列之间的混是一个重大挑战.
- 预测得分被提议以平衡混变量,但它们在构建瘤eControls中的表现未得到分析.
研究的目的:
- 评估预后得分的性能,以构建可靠的eControls用于瘤学研究.
- 为了比较ROPRO的准确性,一个预后得分,与倾向性得分 (5Vars,ROPROvars) 在估计整体生存危险比率.
主要方法:
- 使用三种方法构建了eControls:ROPRO预测得分,5共变性倾向得分 (5Vars) 和27共变性倾向得分 (ROPROvars).
- 使用电子健康记录衍生的非识别数据库.
- 对11例高级非小细胞肺癌病例估计整体生存 (OS) 危险比率 (HR) 的性能进行比较.
主要成果:
- 与5Vars (MAD 0.081) 和ROPROvars (MAD 0.087) 相比,ROPRO eControls的OS HR误差较低 (MAD 0.072),而ROPRO eControls的OS HR误差则较小.
- 在III期研究中,所有方法的OS HR错误都减少了.
- 罗普罗电子控制队列平均包括更多的患者 (6.54%-11.7%),而不是倾向评分方法.
结论:
- 预测得分,特别是ROPRO,与倾向得分相比,可靠地复制了对照.
- 预测得分可以容纳许多变量,而不会显著增加倾向得分的变化,从而保持匹配的患者数量.
- 这项研究验证了预后分数作为构建瘤学中强大的eControls的优越方法.
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