A competing risks model for correlated data based on the subdistribution hazard
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Family-based follow-up study designs are important in epidemiology as they enable investigations of disease aggregation within families. Such studies are subject to methodological complications since data may include multiple endpoints as well as intra-family correlation. The methods herein are developed for the analysis of age of onset with multiple disease types for family-based follow-up studies. The proposed model expresses the marginalized frailty model in terms of the subdistribution hazards (SDH). As with Pipper and Martinussen’s (Scand J Stat 30:509–521, 2003) model, the proposed multivariate SDH model yields marginal interpretations of the regression coefficients while allowing the correlation structure to be specified by a frailty term. Further, the proposed model allows for a direct investigation of the covariate effects on the cumulative incidence function since the SDH is modeled rather than the cause specific hazard. A simulation study suggests that the proposed model generally offers improved performance in terms of bias and efficiency when a sufficient number of events is observed. The proposed model also offers type I error rates close to nominal. The method is applied to a family-based study of breast cancer when death in absence of breast cancer is considered a competing risk.
KeywordsFamilial aggregation Competing risks Cumulative incidence function Semi-parametric
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- Nielsen G, Gill R, Andersen P, Sørensen T (1992) A counting process approach to maximum likelihood estimation in frailty models. Scand J Stat 18: 25–43Google Scholar
- R Development Core Team: (2009) R: a language and environment for statistical computing. R foundation for statistical computing. Vienna, AustriaGoogle Scholar
- Rutter J, Smith A, Dávilla M, Sigurdson A, Giusti R, Pinede M, Doody M, Tucker M, Greene M, Zhang J, Struewing J (2005) Mutational analysis of the BRCA1-interacting genes ZNF350/ZBRK1 and BRIP1/BACH1 among BRCA1 and BRCA2-negative probands from breast-ovarian cancer families and among early-onset breast cancer cases and reference individuals. Hum Mutat 22: 121–128CrossRefGoogle Scholar
- Struewing J, Brody L, Erdos M, Kase R, Giambarresi T, Smith S, Collins F, Tucker M (1995) Detection of eight BRCA1 mutations in 10 breast/ovarian cancer families, including 1 family with male breast cancer. Am J Hum Genet 57: 1–7Google Scholar