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贝叶斯概括的时刻方法应用于生存分析中的伪观测

Léa Orsini¹, Caroline Brard², Emmanuel Lesaffre^3,4

¹Oncostat U1018, Inserm, University Paris-Saclay, Villejuif, France. lea.orsini@gustaveroussy.fr.

Lifetime data analysis

|September 21, 2025

概括

这项研究引入了一种新的贝叶斯生存分析方法,使用伪观测和时刻的概括方法 (GMM). 这种方法避免了指定基线危险函数,提供与现有方法可比的有效推断.

科学领域:

生物统计学生物统计学
统计建模统计建模
生存分析的分析.

背景情况:

对生存回归的贝叶斯推断对决策有价值,但需要指定基线危险函数.
这种规范可能具有挑战性,需要采用替代方法.
现有的频率主义方法,如通用估计方程 (GEE),用于伪观测分析.

研究的目的:

提出一种新的贝叶斯式生存回归方法,可以绕过指定基线危险函数的需求.
用伪观测和通用时刻方法 (GMM) 来直接估计生存函数参数.
评估频率主义和贝叶斯GMM在贝叶斯框架内分析伪观测的表现.

主要方法:

将被审查的生存数据转换为使用伪观测的纵向数据.
从生存函数进行参数估计,应用通用时刻方法 (GMM).
通过伪概率函数将GMM扩展到贝叶斯框架.
通过模拟研究和现实世界的临床试验数据,与Cox,GEE和贝叶斯分段指数模型进行比较.

主要成果:

频率主义和贝叶斯主义GMM都为生存回归提供了有效的推断.
在模拟研究中,GMM方法表现出与基准方法 (Cox,GEE,贝叶斯分段指数) 相当的性能.
业绩强,除了小样本和高审查率的场景外.
对Ewing肉瘤临床试验的后期分析产生了与基准方法一致的结果.

结论:

建议使用伪观测和GMM的贝叶斯方法对于生存分析是有效的.
这种方法提供了一个可行的替代方案,当基线危害规范是困难的.
这些发现支持伪观测在贝叶斯生存分析中的实用性,提供了新的见解.

关键词:

贝叶斯分析是贝叶斯分析.时刻的一般化方法.伪观测是一种假观测.对生存分析的分析.

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