ArticleJCO precision oncology2021
Polygenic Breast Cancer Risk for Women Veterans in the Million Veteran Program.
Article in JCO precision oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 4 of them syntheses that pooled it.
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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.
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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
12 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Identifying and Addressing Barriers to Live Primary Prostate Cancer Cell Research in Veterans.Cancer research communications · 2026Pooled it
- An Evidence Map of the Women Veterans' Health Literature, 2016 to 2023: A Systematic Review.JAMA network open · 2025Pooled it
- The Landscape of Care for Women Veterans with Cancer: An Evidence Map.Journal of general internal medicine · 2024Pooled it
- Breast cancer risk prediction using machine learning: a systematic review.Frontiers in oncology · 2024Pooled it
- Insights into genetic modifiers of breast cancer risk in carriers of BRCA1 and BRCA2 pathogenic variants.Hereditary cancer in clinical practice · 2025Review
- Current understanding of the impact of United States military airborne hazards and burn pit exposures on respiratory health.Particle and fibre toxicology · 2024Review
- Wasm-iCARE: a portable and privacy-preserving web module to build, validate, and apply absolute risk models.JAMIA open · 2024Article
- Addition of polygenic risk score to a risk calculator for prediction of breast cancer in US Black women.Breast cancer research : BCR · 2024Article
- Wasm-iCARE: a portable and privacy-preserving web module to build, validate, and apply absolute risk models.ArXiv · 2023Article
- Predicting Breast Cancer Risk for Women Veterans of African Ancestry in the Million Veteran Program.Health equity · 2023Article
- Development and Validation of a Breast Cancer Polygenic Risk Score on the Basis of Genetic Ancestry Composition.JCO precision oncology · 2022Article
- Deep Learning vs Traditional Breast Cancer Risk Models to Support Risk-Based Mammography Screening.Journal of the National Cancer Institute · 2022Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Accurate breast cancer (BC) risk assessment allows personalized screening and prevention. Prospective validation of prediction models is required before clinical application. Here, we evaluate clinical- and genetic-based BC prediction models in a prospective cohort of women from the Million Veteran Program. MATERIALS AND
methodsClinical BC risk prediction models were validated in combination with a genetic polygenic risk score of 313 (PRS313) single-nucleotide polymorphisms in genetic females without prior BC diagnosis (n = 35,130, mean age 49 years) with 30% non-Hispanic African ancestry (AA). Clinical risk models tested were Breast and Prostate Cancer Cohort Consortium, literature review, and Breast Cancer Risk Assessment Tool, and implemented with or without PRS313. Prediction accuracy and association with incident breast cancer was evaluated with area under the receiver operating characteristic curve (AUC), hazard ratios, and proportion with high absolute lifetime risk.
resultsThree hundred thirty-eight participants developed incident breast cancers with a median follow-up of 3.9 years (2.5 cases/1,000 person-years), with 196 incident cases in women of European ancestry and 112 incident cases in AA women. Individualized Coherent Absolute Risk Estimator-literature review in combination with PRS313 had an AUC of 0.708 (95% CI, 0.659 to 0.758) in women with European or non-African ancestries and 0.625 (0.539 to 0.711) in AA women. Breast Cancer Risk Assessment Tool with PRS313 had an AUC of 0.695 (0.62 to 0.729) in European or non-AA and 0.675 (0.626 to 0.723) in AA women. Incorporation of PRS313 with clinical models improved prediction in European but not in AA women. Models estimated up to 9% of European and 18% of AA women with absolute lifetime risk > 20%.
conclusionClinical and genetic BC risk models predict incident BC in a large prospective multiracial cohort; however, more work is needed to improve genetic risk estimation in AA women.
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