TY - JOUR
T1 - A Multi-State Survival Model for Time to Breast Cancer Mortality among a Cohort of Initially Disease-Free Women
AU - Rosner, Bernard
AU - Glynn, Robert J.
AU - Heather Eliassen, A.
AU - Hankinson, Susan E.
AU - Tamimi, Rulla M.
AU - Chen, Wendy Y.
AU - Holmes, Michelle D.
AU - Mu, Yi
AU - Peng, Cheng
AU - Colditz, Graham A.
AU - Willett, Walter C.
AU - Tworoger, Shelley S.
N1 - Publisher Copyright:
©2022 American Association for Cancer Research.
PY - 2022/8
Y1 - 2022/8
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85135597505&partnerID=8YFLogxK
U2 - 10.1158/1055-9965.EPI-21-1471
DO - 10.1158/1055-9965.EPI-21-1471
M3 - Article
C2 - 35654356
AN - SCOPUS:85135597505
SN - 1055-9965
VL - 31
SP - 1582
EP - 1592
JO - Cancer Epidemiology Biomarkers and Prevention
JF - Cancer Epidemiology Biomarkers and Prevention
IS - 8
ER -