Discussion on "Causal mediation of semicompeting risks" by Yen-Tsung Huang
- PMID: 34510405
- DOI: 10.1111/biom.13519
Discussion on "Causal mediation of semicompeting risks" by Yen-Tsung Huang
Abstract
Huang proposes a method for assessing the impact of a point treatment on mortality either directly or mediated by occurrence of a nonterminal health event, based on data from a prospective cohort study in which the occurrence of the nonterminal health event may be preemptied by death but not vice versa. The author uses a causal mediation framework to formally define causal quantities known as natural (in)direct effects. The novelty consists of adapting these concepts to a continuous-time modeling framework based on counting processes. In an effort to posit "scientifically interpretable estimands," statistical and causal assumptions are introduced for identification. In this commentary, we argue that these assumptions are not only difficult to interpret and justify, but are also likely violated in the hepatitis B motivating example and other survival/time to event settings as well.
Keywords: causal inference; mediation; semicompeting risks; survival analysis.
© 2021 The International Biometric Society.
Comment in
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Rejoinder to "Causal mediation of semicompeting risks".Biometrics. 2021 Dec;77(4):1170-1174. doi: 10.1111/biom.13518. Epub 2021 Aug 1. Biometrics. 2021. PMID: 34333767 No abstract available.
Comment on
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Causal mediation of semicompeting risks.Biometrics. 2021 Dec;77(4):1143-1154. doi: 10.1111/biom.13525. Epub 2021 Aug 1. Biometrics. 2021. PMID: 34195991
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