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

Author:

Rosner Bernard12ORCID,Glynn Robert J.12ORCID,Eliassen A. Heather134ORCID,Hankinson Susan E.145ORCID,Tamimi Rulla M.146ORCID,Chen Wendy Y.17ORCID,Holmes Michelle D.14ORCID,Mu Yi1ORCID,Peng Cheng1ORCID,Colditz Graham A.18ORCID,Willett Walter C.34ORCID,Tworoger Shelley S.149ORCID

Affiliation:

1. 1Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.

2. 2Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.

3. 3Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.

4. 4Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.

5. 5Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, Massachusetts.

6. 6Department of Population Health Sciences, Weill Cornell Medicine, New York, New York.

7. 7Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.

8. 8Siteman Cancer Center and Washington University School of Medicine, Saint Louis, Missouri.

9. 9Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida.

Abstract

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

Funder

NCI

Publisher

American Association for Cancer Research (AACR)

Subject

Oncology,Epidemiology

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3