ArticleBreast cancer research : BCR2023
A model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old.
Article in Breast cancer research : BCR, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 4 citations in OpenAlex.
- Tutorial: translating a validated breast cancer prediction model into a web-based decision aid using R Shiny.Annals of translational medicine · 2026Article
- Social Drivers of Guideline-Discordant Breast Cancer Screening by Age and Mortality Risk.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026Article
- Developing a website to help women aged 55 + incorporate risk in decision-making about breast cancer screening and prevention medications.Patient education and counseling · 2025Article
- Population attributable risk of a competing-risk model for breast cancer and non-breast cancer death among women ≥ 65 years.Breast cancer research and treatment · 2025Article
- Validating a model for predicting breast cancer and nonbreast cancer death in women aged 55 years and older.Journal of the National Cancer Institute · 2024Article
- A contemporary review of breast cancer risk factors and the role of artificial intelligence.Frontiers in oncology · 2024Review
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundGuidelines recommend shared decision making (SDM) for mammography screening for women ≥ 75 and not screening women with < 10-year life expectancy. High-quality SDM requires consideration of women's breast cancer (BC) risk, life expectancy, and values but is hard to implement because no models simultaneously estimate older women's individualized BC risk and life expectancy.
methodsUsing competing risk regression and data from 83,330 women > 55 years who completed the 2004 Nurses' Health Study (NHS) questionnaire, we developed (in 2/3 of the cohort, n = 55,533) a model to predict 10-year non-breast cancer (BC) death. We considered 60 mortality risk factors and used best-subsets regression, the Akaike information criterion, and c-index, to identify the best-fitting model. We examined model performance in the remaining 1/3 of the NHS cohort (n = 27,777) and among 17,380 Black Women's Health Study (BWHS) participants, ≥ 55 years, who completed the 2009 questionnaire. We then included the identified mortality predictors in a previously developed competing risk BC prediction model and examined model performance for predicting BC risk.
resultsMean age of NHS development cohort participants was 70.1 years (± 7.0); over 10 years, 3.1% developed BC, 0.3% died of BC, and 20.1% died of other causes; NHS validation cohort participants were similar. BWHS participants were younger (mean age 63.7 years [± 6.7]); over 10-years 3.1% developed BC, 0.4% died of BC, and 11.1% died of other causes. The final non-BC death prediction model included 21 variables (age; body mass index [BMI]; physical function [3 measures]; comorbidities [12]; alcohol; smoking; age at menopause; and mammography use). The final BC prediction model included age, BMI, alcohol and hormone use, family history, age at menopause, age at first birth/parity, and breast biopsy history. When risk factor regression coefficients were applied in the validation cohorts, the c-index for predicting 10-year non-BC death was 0.790 (0.784-0.796) in NHS and 0.768 (0.757-0.780) in BWHS; for predicting 5-year BC risk, the c-index was 0.612 (0.538-0.641) in NHS and 0.573 (0.536-0.611) in BWHS.
conclusionsWe developed and validated a novel competing-risk model that predicts 10-year non-BC death and 5-year BC risk. Model risk estimates may help inform SDM around mammography screening.
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