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Mammographic screening and prophylactic surgery such as risk-reducingsalpingo oophorectomy (RRSO) can potentially reduce breast cancer risks amongmutation carriers of BRCA families. The evaluation of these interventions isusually complicated by the fact that their effects on breast cancer may changeover time and by the presence of competing risks. We introduce a correlatedcompeting risks model to model breast and ovarian cancer risks within BRCA1families that accounts for time-varying covariates (TVCs). Different parametricforms for these TVCs are proposed for more flexibility and a correlated gammafrailty model is specified to account for the correlated competing events. Wealso introduced a new ascertainment correction approach that accounts for theselection of families through probands affected with either breast or ovariancancer, or unaffected. Our simulation studies demonstrate the good performancesof our proposed approach in terms of bias and precision of the estimators ofmodel parameters and cause-specific penetrances over different levels offamilial correlations. We apply our new approach to 498 BRCA1 mutation carrierfamilies recruited through the Breast Cancer Family Registry. Our resultsdemonstrate the importance of the functional form of the TVC when assessing therole of RRSO on breast cancer. In particular, under the best fitting TVC model,the overall effect of RRSO on breast cancer risk was statistically significantin women with BRCA1.

A Competing Risks Model with Binary Time Varying Covariates for Estimation of Breast Cancer Risks in BRCA1 Families