A Multi-State Survival Model for Time to Breast Cancer Mortality among a Cohort of Initially Disease-Free Women

Background: Identifying risk factors for aggressive forms of Results: Some established risk factors (e.g., family history, breast cancer is important. Tumor factors (e.g., stage) are important estrogen plus progestin therapy) were not associated with lethal predictors of prognosis, but may be intermediates between prebreast cancer. Controlling for age, the strongest risk factors for diagnosis risk factors and mortality. Typically, separate models are lethal breast cancer were weight gain since age 18: > 30 kg versus fit for incidence and mortality postdiagnosis. These models have not ± 5 kg, RR ¼ 1.94 [95% confidence interval (CI) ¼ 1.38–2.74], been previously integrated to identify risk factors for lethal breast nulliparity versus age at first birth (AAFB) < 25, RR ¼ 1.60 (95% cancer in cancer-free women. CI ¼ 1.16–2.22), and current smoking ≥ 15 cigarettes/day versus Methods: We combined models for breast cancer incidence and never, RR ¼ 1.42 (95% CI ¼ 1.07–1.89). breast cancer–specific mortality among cases into a multi-state Conclusions: Some breast cancer incidence risk factors are not survival model for lethal breast cancer. We derived the model from associated with lethal breast cancer; other risk factors for lethal cancer-free postmenopausal Nurses’ Health Study women in 1990 breast cancer are not associated with disease incidence. using baseline risk factors. A total of 4,391 invasive breast cancer Impact: This multi-state survival model may be useful for cases were diagnosed from 1990 to 2014 of which 549 died because identifying prediagnosis factors that lead to more aggressive and of breast cancer over the same period. ultimately lethal breast cancer.