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Direct and indirect treatment effects in the presence of semicompeting risks.
Deng, Yuhao; Wang, Yi; Zhou, Xiao-Hua.
Afiliação
  • Deng Y; Beijing International Center for Mathematical Research, Peking University, 100871 Beijing, China.
  • Wang Y; Department of Biostatistics, School of Public Health, 48109 Ann Arbor, Michigan, USA.
  • Zhou XH; Beijing International Center for Mathematical Research, Peking University, 100871 Beijing, China.
Biometrics ; 80(2)2024 Mar 27.
Article em En | MEDLINE | ID: mdl-38742906
ABSTRACT
Semicompeting risks refer to the phenomenon that the terminal event (such as death) can censor the nonterminal event (such as disease progression) but not vice versa. The treatment effect on the terminal event can be delivered either directly following the treatment or indirectly through the nonterminal event. We consider 2 strategies to decompose the total effect into a direct effect and an indirect effect under the framework of mediation analysis in completely randomized experiments by adjusting the prevalence and hazard of nonterminal events, respectively. They require slightly different assumptions on cross-world quantities to achieve identifiability. We establish asymptotic properties for the estimated counterfactual cumulative incidences and decomposed treatment effects. We illustrate the subtle difference between these 2 decompositions through simulation studies and two real-data applications in the Supplementary Materials.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Simulação por Computador Limite: Humans Idioma: En Revista: Biometrics Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Simulação por Computador Limite: Humans Idioma: En Revista: Biometrics Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China