Tai An-Shun, Tsai Chun-An, Lin Sheng-Hsuan
Institute of Statistics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
Stat Med. 2021 Jul 30;40(17):3953-3974. doi: 10.1002/sim.9008. Epub 2021 Jun 10.
In medical research, the development of mediation analysis with a survival outcome has facilitated investigation into causal mechanisms. However, studies have not discussed the death-truncation problem for mediators, the problem being that conventional mediation parameters cannot be well defined in the presence of a truncated mediator. In the present study, we systematically defined the completeness of causal effects to uncover the gap, in conventional causal definitions, between the survival and nonsurvival settings. We propose a novel approach to redefining natural direct and indirect effects, which are generalized forms of conventional causal effects for survival outcomes. Furthermore, we developed three statistical methods for the binary outcome of survival status and formulated a Cox model for survival time. We performed simulations to demonstrate that the proposed methods are unbiased and robust. We also applied the proposed method to explore the effect of hepatitis C virus infection on mortality, as mediated through hepatitis B viral load.
在医学研究中,生存结局中介分析的发展推动了对因果机制的研究。然而,研究尚未讨论中介变量的死亡截断问题,该问题在于在存在截断中介变量的情况下,传统的中介参数无法得到很好的定义。在本研究中,我们系统地定义了因果效应的完整性,以揭示传统因果定义在生存与非生存情况下的差异。我们提出了一种重新定义自然直接效应和间接效应的新方法,它们是生存结局传统因果效应的广义形式。此外,我们针对生存状态的二元结局开发了三种统计方法,并为生存时间制定了Cox模型。我们进行了模拟,以证明所提出的方法是无偏且稳健的。我们还应用所提出的方法来探究丙型肝炎病毒感染通过乙型肝炎病毒载量介导对死亡率的影响。