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在精准医学中解决不朽时间偏差:实用指南和方法开发

Deirdre Weymann^1,2, Emanuel Krebs¹, Dean A Regier^1,3

¹Cancer Control Research, BC Cancer, Vancouver, British Columbia, Canada.

Health services research

|September 3, 2024

概括

多重归算 (MI) 在准确医学研究中为调整不朽时间偏差提供了优势. 这种方法尽量减少数据丢失,更好地量化不确定性,改善现实世界的证据生成.

科学领域:

生物统计学生物统计学
流行病学流行病学
医疗保健服务研究医疗服务研究

背景情况:

不朽时间偏差是观察性研究中的一个重大挑战,特别是在精准医学评估中.
现有的调整方法具有理论上的局限性,这可能会影响现实世界的证据的有效性.

研究的目的:

为了比较常见的不朽时间调整方法的优点和局限性.
提出和评估一种使用多重归算 (MI) 进行不朽时间偏差调整的新方法.
为在精准医学研究中实施MI提供实际指导.

主要方法:

对基准分析,时间分布匹配和时间依赖分析与拟议的MI方法进行比较分析.
开发MI应用的实用指南,包括归算方法选择,模型规范和分析聚合.
一个现实世界的案例研究,使用匹配的队列设计来评估晚期癌症中全基因组和转录组分析的生存益处,应用时间分布匹配和MI.
引导模拟以评估对缺失数据和样本大小的归算灵敏度.

主要成果:

理论上,多重归算 (MI) 通过最小化信息丢失和更好地描述统计不确定性,在其他方法上提供了优势.
MI明确解释了影响不朽时间分布的患者特征,减少了潜在的偏差.
在案例研究中,MI和时间分布匹配产生了类似的生存分析结果,尽管MI产生了更高的标准误差.
假定的永生时间在模拟场景中保持稳定.

结论:

强大的永生时间调整方法对于在精准医学中产生公正的,决策级的真实世界证据至关重要.
多重归算 (MI) 是解决这些评估中不朽时间偏差的一个有希望和有效的解决方案.

关键词:

不朽的时间偏差多重的归算是多重的归算.精准医学是一门精准医学.现实世界的证据.统计方法统计方法

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