首页|Discussion on “Causal mediation of semicompeting risks” by Yen‐Tsung Huang

Discussion on “Causal mediation of semicompeting risks” by Yen‐Tsung Huang

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  • NSTL
  • Wiley
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.

causal inferencemediationsemicompeting riskssurvival analysis

Isabel R. Fulcher、Ilya Shpitser、Vanessa Didelez、Kali Zhou、Daniel O. Scharfstein

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Department of Global Health and Social Medicine,Harvard Medical School

Department of Computer Science,Johns Hopkins University

Leibniz Institute for Prevention Research and Epidemiology – BIPS, Bremen,University of Bremen

Division of Gastrointestinal and Liver Diseases,University of Southern California

Department of Population Health Sciences,University of Utah School of Medicine

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2021

10.1111/biom.13519

Biometrics

Biometrics

EISCI
ISSN：0006-341X
年,卷(期)：2021.77(4)
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