A joint model for recurrent events and a semi-competing risk in the presence of multi-level clustering.
Stat Methods Med Res
; 28(10-11): 2897-2911, 2019.
Article
em En
| MEDLINE
| ID: mdl-30062911
ABSTRACT
Clinical trial designs often include multiple levels of clustering in which patients are nested within clinical sites and recurrent outcomes are nested within patients who may also experience a semi-competing risk. Traditional survival methods that analyze these processes separately may lead to erroneous inferences as they ignore possible dependencies. To account for the association between recurrent events and a semi-competing risk in the presence of two levels of clustering, we developed a semi-parametric joint model. The Gaussian quadrature with a piecewise constant baseline hazard was used to estimate the unspecified baseline hazards and the likelihood. Simulations showed that the proposed joint model has good statistical properties (i.e. <5% bias and 95% coverage) compared to the shared frailty and joint frailty models when informative censoring and multiple levels of clustering were present. The proposed method was applied to data from an AIDS clinical trial to investigate the impact of antiretroviral treatment on recurrent AIDS-defining events in the presence of a semi-competing risk of death and multi-level clustering and showed a significant dependency between AIDS-defining events and death at the patient level but not at the clinic level.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Projetos de Pesquisa
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Ensaios Clínicos como Assunto
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Modelos Estatísticos
Tipo de estudo:
Etiology_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Stat Methods Med Res
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Estados Unidos