Survival mediation analysis with the death-truncated mediator: The completeness of the survival mediation parameter

An Shun Tai, Chun An Tsai, Sheng Hsuan Lin*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)3953-3974
Number of pages22
JournalStatistics in Medicine
Volume40
Issue number17
DOIs
StatePublished - 30 Jul 2021

Keywords

  • Cox proportional hazards model
  • death-truncated mediator
  • inverse odds ratio weighting
  • inverse probability weighting
  • regression-based method
  • survival mediation analysis

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