论文标题
生存分析中的时间依赖性介体：通过添加危害模型对直接和间接效应进行建模
Time-dependent mediators in survival analysis: Modelling direct and indirect effects with the additive hazards model
论文作者
论文摘要
我们讨论了生存数据的因果中介分析，并根据添加剂危害模型提出了一种新方法。重点是动态的观点，即了解直接和间接影响如何随着时间而发展。因此，重要的是，我们允许时间变化。为了在如此纵向生存环境中定义直接和间接的影响，我们采用介入方法（Didelez（2018）），在该方法中，将治疗分为影响介体的一个方面，以及影响生存的不同方面。通常，这导致了非参数G形式的版本（Robins（1986））。在本文中，我们证明，将G形式与添加危害模型和介体过程的顺序线性模型相结合，从而在相对存活以及累积危害方面为直接和间接效应提供了简单且可解释的表达式。我们的结果将动态路径分析的方法推广并形式化（Fosen等人（2006），Strohmaier等人（2015））。给出了来自临床试验的血压药物数据的数据。
We discuss causal mediation analyses for survival data and propose a new approach based on the additive hazards model. The emphasis is on a dynamic point of view, that is, understanding how the direct and indirect effects develop over time. Hence, importantly, we allow for a time varying mediator. To define direct and indirect effects in such a longitudinal survival setting we take an interventional approach (Didelez (2018)) where treatment is separated into one aspect affecting the mediator and a different aspect affecting survival. In general, this leads to a version of the non-parametric g-formula (Robins (1986)). In the present paper, we demonstrate that combining the g-formula with the additive hazards model and a sequential linear model for the mediator process results in simple and interpretable expressions for direct and indirect effects in terms of relative survival as well as cumulative hazards. Our results generalise and formalise the method of dynamic path analysis (Fosen et al. (2006), Strohmaier et al. (2015)). An application to data from a clinical trial on blood pressure medication is given.
