Population attributable risk of a competing-risk model for breast cancer and non-breast cancer death among women ≥ 65 years

Mara A Schonberg; Emily A Wolfson; A Heather Eliassen; Bernard A Rosner; Andrea Z LaCroix; Rebecca A Nelson; Rowan T Chlebowski; Long H Ngo

doi:10.1007/s10549-025-07683-w

Population attributable risk of a competing-risk model for breast cancer and non-breast cancer death among women ≥ 65 years

Breast Cancer Res Treat. 2025 Mar 25. doi: 10.1007/s10549-025-07683-w. Online ahead of print.

Authors

Mara A Schonberg^#¹, Emily A Wolfson^#², A Heather Eliassen^{3

4}, Bernard A Rosner^{3

4

5}, Andrea Z LaCroix⁶, Rebecca A Nelson⁷, Rowan T Chlebowski⁸, Long H Ngo^{2

9}

Affiliations

¹ Division of General Medicine and Primary Care, Department of Medicine, Harvard Medical School, Beth Israel Deaconess Medical Center, 1309 Beacon, Office 219, Brookline, Boston, MA, USA. mschonbe@bidmc.harvard.edu.
² Division of General Medicine and Primary Care, Department of Medicine, Harvard Medical School, Beth Israel Deaconess Medical Center, 1309 Beacon, Office 219, Brookline, Boston, MA, USA.
³ Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA.
⁴ Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Harvard School of Public Health, Boston, MA, USA.
⁵ Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁶ Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, San Diego, CA, USA.
⁷ Department of Computational and Quantitative Medicine, City of Hope, Duarte, CA, USA.
⁸ The Lundquist Institute, Torrance, CA, USA.
⁹ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

^# Contributed equally.

PMID: 40128438
DOI: 10.1007/s10549-025-07683-w

Abstract

Purpose: To inform decision making around mammography-screening frequency and cessation, we previously used Fine-Gray competing-risk regression to develop and validate a model to estimate older women's 10-year risk of breast cancer and their competing risk of non-breast cancer (non-BC) death. Here, we aimed to understand the amount of incident breast cancer and non-BC death risk explained by our model among women ≥ 65y.

Methods: We included women ≥ 65y who completed the 2004 Nurses' Health Study questionnaire (NHS, n = 59,662) or who participated in the Women's Health Initiative-Extension Study (WHI-ES, n = 82,528). We calculated our model's full and risk factor-specific population attributable risk (PAR%) for incident breast cancer and non-BC death.

Results: Mean age of the NHS participants was 73.5y (SD 5.2); 3.1% were diagnosed with breast cancer and 26.1% experienced non-BC death within 10 years. Mean age of WHI-ES participants was 73.6y (SD 5.4); 4.2% were diagnosed with breast cancer and 17.7% experienced non-BC death within 10 years. The full-model PAR% for breast cancer was 58.8% (22.7-80.6) in NHS and 54.8% (24.8-75.2%) in WHI-ES. Modifiable risk factors explained approximately 1/3 of breast cancer risk; BMI ≥ 30 had a PAR% of 6.5% (3.1-9.9%) in NHS and 12.2% (8.5-16.0%) in WHI-ES. For non-BC death, the full-model PAR% was 94.2% (91.4-96.1%) in NHS and 86.2% (80.9-90.0%) in WHI-ES.

Conclusions: Our competing-risk model explained the majority of breast cancers and non-BC deaths in women ≥ 65y, and we identified risk factors (e.g., elevated BMI) that may be targeted to reduce the burden of breast cancer in older women.

Keywords: Breast cancer risk; Competing mortality risk; Women 55+.

Abstract

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