ArticleBreast cancer research and treatment2017
Breast cancer risk prediction: an update to the Rosner-Colditz breast cancer incidence model.
Article in Breast cancer research and treatment, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
- Adverse childhood experiences, adult adiposity, and risk of young-onset breast cancer subtypes in a population-based case-control study.Cancer causes & control : CCC · 2026Article
- Accelerating discovery of cancer causes for prevention in the era of rising early-onset cancers.Cell · 2026Review
- Development and validation of a risk prediction model for premenopausal breast cancer in 19 cohorts.Breast cancer research : BCR · 2025Article
- Feasibility of risk assessment for breast cancer molecular subtypes.Breast cancer research and treatment · 2024Article
- Early life body size and puberty markers as predictors of breast cancer risk later in life: A neural network analysis.PloS one · 2024Article
- A Validated Risk Prediction Model for Breast Cancer in US Black Women.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2021Article
- Automated percent mammographic density, mammographic texture variation, and risk of breast cancer: a nested case-control study.NPJ breast cancer · 2021Article
- Cancer Progress and Priorities: Breast Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2021Review
- Simplified Breast Risk Tool Integrating Questionnaire Risk Factors, Mammographic Density, and Polygenic Risk Score: Development and Validation.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2021Article
- Deep Learning Image Analysis of Benign Breast Disease to Identify Subsequent Risk of Breast Cancer.JNCI cancer spectrum · 2021Article
- Risk Models for Breast Cancer and Their Validation.Statistical science : a review journal of the Institute of Mathematical Statistics · 2020Article
- Article
- Addition of a polygenic risk score, mammographic density, and endogenous hormones to existing breast cancer risk prediction models: A nested case-control study.PLoS medicine · 2018Article
- Assessing Risk of Breast Cancer: A Review of Risk Prediction Models.Journal of breast imagingReview
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8 authors.
Funding
Abstract
purposeTo update and expand the Rosner-Colditz breast cancer incidence model by evaluating the contributions of more recently identified risk factors as well as predicted percent mammographic density (MD) to breast cancer risk.
methodsUsing data from the Nurses' Health Study (NHS) and NHSII, we added adolescent somatotype (9 unit scale), vegetable intake (servings/day), breastfeeding (months), physical activity (MET-h/week), and predicted percent MD to the Rosner-Colditz model to determine whether these variables improved model discrimination. We evaluated all invasive as well as ER+/PR+, ER+/PR-, and ER-/PR- breast cancer.
resultsIn the NHS/NHSII, we accrued over 5200 cases of invasive breast cancer over more than 20 years of follow-up with complete data on the risk factors. Adolescent somatotype and predicted percent MD significantly improved the original Rosner-Colditz model for all invasive breast cancer (change in age-adjusted AUC = 0.020, p < 0.001). The relative risk (RR) of invasive breast cancer for a 4-unit increase in adolescent somatotype was 0.62 (95% CI 0.56, 0.70), whereas the RR for a 20-unit increase in predicted percent MD was 1.32 (95% CI 1.28, 1.36). Adolescent somatotype and predicted percent MD also significantly improved the ER+/PR+model (change in age-adjusted AUC = 0.020, p < 0.001) as well as the ER+/PR- model (change in age-adjusted AUC = 0.012, p = 0.007). Adolescent somatotype, predicted percent MD, breastfeeding, and vegetable intake improved the ER-/PR- model (change in AUC = 0.031, p < 0.0001). The RR of ER-/PR- disease for 5 vegetable servings/day increase was 0.83 (95% CI 0.70, 0.99), while the RR for every 12 months of breastfeeding was 0.88 (95% CI 0.77, 1.01). Physical activity did not improve risk classification in any model.
conclusionAdolescent somatotype and predicted percent MD significantly improved breast cancer risk classification using the Rosner-Colditz model. Further, risk factors specific to ER- disease, such as breastfeeding and vegetable intake, may also help improve risk prediction of this aggressive subtype.
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