TY - JOUR
T1 - Survival mediation analysis with the death-truncated mediator
T2 - The completeness of the survival mediation parameter
AU - Tai, An Shun
AU - Tsai, Chun An
AU - Lin, Sheng Hsuan
N1 - Publisher Copyright:
© 2021 John Wiley & Sons Ltd.
PY - 2021/7/30
Y1 - 2021/7/30
N2 - 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.
AB - 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.
KW - Cox proportional hazards model
KW - death-truncated mediator
KW - inverse odds ratio weighting
KW - inverse probability weighting
KW - regression-based method
KW - survival mediation analysis
UR - http://www.scopus.com/inward/record.url?scp=85107402945&partnerID=8YFLogxK
U2 - 10.1002/sim.9008
DO - 10.1002/sim.9008
M3 - Article
C2 - 34111901
AN - SCOPUS:85107402945
SN - 0277-6715
VL - 40
SP - 3953
EP - 3974
JO - Statistics in Medicine
JF - Statistics in Medicine
IS - 17
ER -