Time-dependent mediators in survival analysis: Modeling direct and indirect effects with the additive hazards model

Aalen, Odd O., Stensrud, Mats J., Didelez, Vanessa, Daniel, Rhian ORCID: https://orcid.org/0000-0001-5649-9320, Roysland, Kjetil and Srohmaier, Susanne 2020. Time-dependent mediators in survival analysis: Modeling direct and indirect effects with the additive hazards model. Biometrical Journal 62 (3) , pp. 532-549. 10.1002/bimj.201800263

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Abstract

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 nonparametric 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 generalize and formalize the method of dynamic path analysis (Fosen, Ferkingstad, Borgan, & Aalen, 2006; Strohmaier et al., 2015). An application to data from a clinical trial on blood pressure medication is given.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Medicine
Publisher:	Wiley-VCH Verlag
ISSN:	0323-3847
Related URLs:	Publisher
Date of Acceptance:	15 January 2019
Last Modified:	26 Oct 2022 07:34
URI:	https://orca.cardiff.ac.uk/id/eprint/125195

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