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Pooling controls from nested case-control studies with the proportional risks model.
Chang, Yen; Ivanova, Anastasia; Albanes, Demetrius; Fine, Jason P; Shin, Yei Eun.
Afiliación
  • Chang Y; Department of Biostatistics, University of North Carolina, 135 Dauer Drive, Chapel Hill,North Carolina 27599, USA.
  • Ivanova A; Department of Biostatistics, University of North Carolina, 135 Dauer Drive, Chapel Hill,North Carolina 27599, USA.
  • Albanes D; Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics,National Cancer Institute, 9609 Medical Center Drive, Rockville, Maryland 20892, USA.
  • Fine JP; Department of Statistics, University of Pittsburgh, 230 S Bouquet Street, Pittsburgh, Pennsylvania 15260, USA.
  • Shin YE; Department of Statistics, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea.
Biostatistics ; 2024 Sep 10.
Article en En | MEDLINE | ID: mdl-39255366
ABSTRACT
The standard approach to regression modeling for cause-specific hazards with prospective competing risks data specifies separate models for each failure type. An alternative proposed by Lunn and McNeil (1995) assumes the cause-specific hazards are proportional across causes. This may be more efficient than the standard approach, and allows the comparison of covariate effects across causes. In this paper, we extend Lunn and McNeil (1995) to nested case-control studies, accommodating scenarios with additional matching and non-proportionality. We also consider the case where data for different causes are obtained from different studies conducted in the same cohort. It is demonstrated that while only modest gains in efficiency are possible in full cohort analyses, substantial gains may be attained in nested case-control analyses for failure types that are relatively rare. Extensive simulation studies are conducted and real data analyses are provided using the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) study.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Biostatistics Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Biostatistics Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido