Model Selection for the Competing-Risks Model With and Without Masking

Technometrics ◽  
2005 ◽  
Vol 47 (4) ◽  
pp. 457-467 ◽  
Author(s):  
Radu V Craiu ◽  
Thomas C. M Lee
Keyword(s):  
Model Selection ◽  
Competing Risks ◽  
Competing Risks Model ◽  
Selection For

scholarly journals Dependence Model Selection for Semi-Competing Risks Data

2020 ◽  
Vol 10 (02) ◽  
pp. 228-238
Author(s):  
Jin-Jian Hsieh ◽  
Cheng-Fang Tsai
Keyword(s):  
Model Selection ◽  
Competing Risks ◽  
Competing Risks Data ◽  
Selection For

scholarly journals A competing risks model with binary time varying covariates for estimation of breast cancer risks in BRCA1 families

2021 ◽  
pp. 096228022110089
Author(s):  
Yun-Hee Choi ◽  
Hae Jung ◽  
Saundra Buys ◽  
Mary Daly ◽  
Esther M John ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Competing Risks ◽  
Brca1 Mutation ◽  
Prophylactic Surgery ◽  
Time Varying ◽  
Cancer Risks ◽  
Competing Risks Model ◽  
Time Varying Covariates ◽  
Risk Reducing

Mammographic screening and prophylactic surgery such as risk-reducing salpingo oophorectomy can potentially reduce breast cancer risks among mutation carriers of BRCA families. The evaluation of these interventions is usually complicated by the fact that their effects on breast cancer may change over time and by the presence of competing risks. We introduce a correlated competing risks model to model breast and ovarian cancer risks within BRCA1 families that accounts for time-varying covariates. Different parametric forms for the effects of time-varying covariates are proposed for more flexibility and a correlated gamma frailty model is specified to account for the correlated competing events.We also introduce a new ascertainment correction approach that accounts for the selection of families through probands affected with either breast or ovarian cancer, or unaffected. Our simulation studies demonstrate the good performances of our proposed approach in terms of bias and precision of the estimators of model parameters and cause-specific penetrances over different levels of familial correlations. We applied our new approach to 498 BRCA1 mutation carrier families recruited through the Breast Cancer Family Registry. Our results demonstrate the importance of the functional form of the time-varying covariate effect when assessing the role of risk-reducing salpingo oophorectomy on breast cancer. In particular, under the best fitting time-varying covariate model, the overall effect of risk-reducing salpingo oophorectomy on breast cancer risk was statistically significant in women with BRCA1 mutation.

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