ArticleCancers2021
Validation of Breast Cancer Risk Models by Race/Ethnicity, Family History and Molecular Subtypes.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- Development and performance of female breast cancer incidence risk prediction models: a systematic review and meta-analysis.Annals of medicine · 2025Pooled it
- Advanced Versus Invasive Breast Cancer Risk in a Screening Population: Implications for Risk-based Prevention and Screening Strategies.Journal of general internal medicine · 2026Article
- Evaluating the Gail Model: Racial Disparities in Breast Cancer Risk Assessment.Annals of surgical oncology · 2026Article
- Five-Year Absolute Risk-Based and Age-Based Breast Cancer Screening in the US.JAMA network open · 2026Article
- Impact of Affordable Care Act Provisions on the Racial Makeup of Patients Enrolled at a Deep South, High-Risk Breast Cancer Clinic.Journal of racial and ethnic health disparities · 2025Article
- Feasibility of risk assessment for breast cancer molecular subtypes.Breast cancer research and treatment · 2024Article
- Validation of the Mirai model for predicting breast cancer risk in Mexican women.Insights into imaging · 2024Article
- A constrained maximum likelihood approach to developing well-calibrated models for predicting binary outcomes.Lifetime data analysis · 2024Article
- Extending the Breast Cancer Surveillance Consortium Model of Invasive Breast Cancer.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2024Article
- A nomogram for predicting overall survival of breast cancer with regional lymph node metastasis in young women.Translational cancer research · 2024Article
- Inequities in referrals to a breast cancer risk assessment and prevention clinic: a mixed methods study.BMC primary care · 2023Article
- Variability Among Breast Cancer Risk Classification Models When Applied at the Level of the Individual Woman.Journal of general internal medicine · 2023Article
- Breast density quantitative measures and breast cancer risk among screened Black women.JNCI cancer spectrum · 2023Article
- Comparison of Mammography AI Algorithms with a Clinical Risk Model for 5-year Breast Cancer Risk Prediction: An Observational Study.Radiology · 2023Observational
- Combining Breast Cancer Risk Prediction Models.Cancers · 2023Article
- The Landmark Series-Addressing Disparities in Breast Cancer Screening: New Recommendations for Black Women.Annals of surgical oncology · 2023Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors at 4 institutions in 1 country.
Funding
Abstract
(1) Background: The purpose of this study is to compare the performance of four breast cancer risk prediction models by race, molecular subtype, family history of breast cancer, age, and BMI. (2) Methods: Using a cohort of women aged 40-84 without prior history of breast cancer who underwent screening mammography from 2006 to 2015, we generated breast cancer risk estimates using the Breast Cancer Risk Assessment tool (BCRAT), BRCAPRO, Breast Cancer Surveillance Consortium (BCSC) and combined BRCAPRO+BCRAT models. Model calibration and discrimination were compared using observed-to-expected ratios (O/E) and the area under the receiver operator curve (AUC) among patients with at least five years of follow-up. (3) Results: We observed comparable discrimination and calibration across models. There was no significant difference in model performance between Black and White women. Model discrimination was poorer for HER2+ and triple-negative subtypes compared with ER/PR+HER2-. The BRCAPRO+BCRAT model displayed improved calibration and discrimination compared to BRCAPRO among women with a family history of breast cancer. Across models, discriminatory accuracy was greater among obese than non-obese women. When defining high risk as a 5-year risk of 1.67% or greater, models demonstrated discordance in 2.9% to 19.7% of patients. (4) Conclusions: Our results can inform the implementation of risk assessment and risk-based screening among women undergoing screening mammography.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.