ArticleBreast cancer research and treatment2019
Validation of the breast cancer surveillance consortium model of breast cancer risk.
Article in Breast cancer research and treatment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 2 of them syntheses that pooled it.
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Who cites it
59 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Development and performance of female breast cancer incidence risk prediction models: a systematic review and meta-analysis.Annals of medicine · 2025Pooled it
- Artificial Intelligence-Driven Mammography-Based Future Breast Cancer Risk Prediction: A Systematic Review.Journal of the American College of Radiology : JACR · 2024Pooled it
- Trial
- Effect of Personalized Breast Cancer Risk Tool on Chemoprevention and Breast Imaging: ENGAGED-2 Trial.JNCI cancer spectrum · 2021Trial
- Advanced Versus Invasive Breast Cancer Risk in a Screening Population: Implications for Risk-based Prevention and Screening Strategies.Journal of general internal medicine · 2026Article
- WISDOM randomized trial comparing risk-based versus annual breast cancer screening: study cohort characteristics and design.NPJ breast cancer · 2026Article
- Performance of three breast cancer risk assessment tools in US Black women.Breast cancer research : BCR · 2026Article
- Overdiagnosis of Papillary Thyroid Cancer.JAMA network open · 2026Article
- ABUS-based glandular tissue component classification for breast cancer risk prediction in Chinese women with dense breasts: a retrospective study.BMC medical imaging · 2026Article
- Breast cancer risk level and prediction of tumor aggressiveness in the Athena Breast Health Network.Breast cancer research and treatment · 2026Article
- Five-Year Absolute Risk-Based and Age-Based Breast Cancer Screening in the US.JAMA network open · 2026Article
- WISDOM Randomized Trial Comparing Risk-Based Versus Annual Breast Cancer Screening: Study Cohort Characteristics and Design.Research square · 2025Article
- Evaluating mammographic density's contribution to improve a breast cancer risk model with questionnaire-based and polygenic factors.NPJ breast cancer · 2025Article
- Translating risk-based breast cancer screening to limited-resource settings.BMC global and public health · 2025Article
- A systematic review of determinants of breast cancer risk among women with benign breast disease.NPJ breast cancer · 2025Article
- A roadmap to reduce the incidence and mortality of breast cancer by rethinking our approach to women's health.Breast cancer research and treatment · 2025Review
- Investigating the added value of incorporatingmammographic density to an integrated breastcancer risk model with questionnaire-based riskfactors and polygenic risk score.Research square · 2024Article
- Relative Timing of Mammography and MRI for Breast Cancer Screening: Impact on Performance Evaluation.Journal of the American College of Radiology : JACR · 2024Article
- Variability in Breast Density Estimation and Its Impact on Breast Cancer Risk Assessment.Journal of breast cancer · 2024Article
- Deep Learning for Breast Cancer Risk Prediction: Application to a Large Representative UK Screening Cohort.Radiology. Artificial intelligence · 2024Article
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Authors and funding
7 authors.
Funding
Abstract
purposeIn order to use a breast cancer prediction model in clinical practice to guide screening and prevention, it must be well calibrated and validated in samples independent from the one used for development. We assessed the accuracy of the breast cancer surveillance consortium (BCSC) model in a racially diverse population followed for up to 10 years.
methodsThe BCSC model combines breast density with other risk factors to estimate a woman's 5- and 10-year risk of invasive breast cancer. We validated the model in an independent cohort of 252,997 women in the Chicago area. We evaluated calibration using the ratio of expected to observed (E/O) invasive breast cancers in the cohort and discrimination using the area under the receiver operating characteristic curve (AUROC).
resultsIn an independent cohort of 252,997 women (median age 50 years, 26% non-Hispanic Black), the BCSC model was well calibrated (E/O = 0.94, 95% confidence interval [CI] 0.90-0.98), but underestimated the incidence of invasive breast cancer in younger women and in women with low mammographic density. The AUROC was 0.633, similar to that observed in prior validation studies.
conclusionsThe BCSC model is a well-validated risk assessment tool for breast cancer that may be particularly useful when assessing the utility of supplemental screening in women with dense breasts.
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