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Discussion on "Causal mediation of semicompeting risks" by Yen-Tsung Huang.
Fulcher, Isabel R; Shpitser, Ilya; Didelez, Vanessa; Zhou, Kali; Scharfstein, Daniel O.
Afiliação
  • Fulcher IR; Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA.
  • Shpitser I; Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA.
  • Didelez V; Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany and Departments of Mathematics and Computer Science, University of Bremen, Bremen, Germany.
  • Zhou K; Division of Gastrointestinal and Liver Diseases, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
  • Scharfstein DO; Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, Utah, USA.
Biometrics ; 77(4): 1165-1169, 2021 12.
Article em En | MEDLINE | ID: mdl-34510405
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelos Estatísticos Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Biometrics Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelos Estatísticos Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Biometrics Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos