Discussion on "Causal mediation of semicompeting risks" by Yen‐Tsung Huang. Issue 4 (12th September 2021)

• Record Type: Journal Article
• Authors: Fulcher, Isabel R.; Shpitser, Ilya; Didelez, Vanessa; Zhou, Kali; Scharfstein, Daniel O.
• Is Part Of: Biometrics. Volume 77:Issue 4(2021)
• Page Start: 1165
• Page End: 1169
• Publication Date: 2021-09-12
• Subjects: causal inference -- mediation -- semicompeting risks -- survival analysis; Biometry -- Periodicals; 570.15195
• DOI: 10.1111/biom.13519
• Languages: English
• ISSNs: 0006-341X

Abstract

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.