ArticleJournal of the National Cancer Institute2017
Projecting Individualized Absolute Invasive Breast Cancer Risk in US Hispanic Women.
Article in Journal of the National Cancer Institute, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 3 of them syntheses that pooled it.
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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
33 citing papers in PubMed, 3 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
- A systematic review of prediction models for risk of breast cancer.BMC cancer · 2025Pooled it
- A systematic review and quality assessment of individualised breast cancer risk prediction models.British journal of cancer · 2019Pooled it
- RiskPath: Explainable deep learning for multistep biomedical prediction in longitudinal data.Patterns (New York, N.Y.) · 2025Article
- Plasma metabolomics profiles and breast cancer risk.Breast cancer research : BCR · 2024Article
- Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2024Article
- Role of Breast Cancer Risk Estimation Models to Identify Women Eligible for Genetic Testing and Risk-Reducing Surgery.Biomedicines · 2024Review
- Disparities in Breast Cancer Care-How Factors Related to Prevention, Diagnosis, and Treatment Drive Inequity.Healthcare (Basel, Switzerland) · 2024Review
- Assessment of Lifetime Risk for Cardiovascular Disease: Time to Move Forward.Current cardiology reviews · 2024Review
- Risk of cancer versus risk of cancer diagnosis? Accounting for diagnostic bias in predictions of breast cancer risk by race and ethnicity.Journal of medical screening · 2023Article
- Will Absolute Risk Estimation for Time to Next Screen Work for an Asian Mammography Screening Population?Cancers · 2023Article
- Combining Breast Cancer Risk Prediction Models.Cancers · 2023Article
- Deep Learning vs Traditional Breast Cancer Risk Models to Support Risk-Based Mammography Screening.Journal of the National Cancer Institute · 2022Article
- PREDICTION OF HEREDITARY CANCERS USING NEURAL NETWORKS.The annals of applied statistics · 2022Article
- Prospective evaluation of a breast-cancer risk model integrating classical risk factors and polygenic risk in 15 cohorts from six countries.International journal of epidemiology · 2022Article
- Validation of Breast Cancer Risk Models by Race/Ethnicity, Family History and Molecular Subtypes.Cancers · 2021Article
- Breast Cancer Population Attributable Risk Proportions Associated with Body Mass Index and Breast Density by Race/Ethnicity and Menopausal Status.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Article
- Key steps for effective breast cancer prevention.Nature reviews. Cancer · 2020Review
- Performance of Breast Cancer Risk-Assessment Models in a Large Mammography Cohort.Journal of the National Cancer Institute · 2020Article
- Microbial Alterations and Risk Factors of Breast Cancer: Connections and Mechanistic Insights.Cells · 2020Review
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Background: There is no model to estimate absolute invasive breast cancer risk for Hispanic women. Methods: The San Francisco Bay Area Breast Cancer Study (SFBCS) provided data on Hispanic breast cancer case patients (533 US-born, 553 foreign-born) and control participants (464 US-born, 947 foreign-born). These data yielded estimates of relative risk (RR) and attributable risk (AR) separately for US-born and foreign-born women. Nativity-specific absolute risks were estimated by combining RR and AR information with nativity-specific invasive breast cancer incidence and competing mortality rates from the California Cancer Registry and Surveillance, Epidemiology, and End Results program to develop the Hispanic risk model (HRM). In independent data, we assessed model calibration through observed/expected (O/E) ratios, and we estimated discriminatory accuracy with the area under the receiver operating characteristic curve (AUC) statistic. Results: The US-born HRM included age at first full-term pregnancy, biopsy for benign breast disease, and family history of breast cancer; the foreign-born HRM also included age at menarche. The HRM estimated lower risks than the National Cancer Institute's Breast Cancer Risk Assessment Tool (BCRAT) for US-born Hispanic women, but higher risks in foreign-born women. In independent data from the Women's Health Initiative, the HRM was well calibrated for US-born women (observed/expected [O/E] ratio = 1.07, 95% confidence interval [CI] = 0.81 to 1.40), but seemed to overestimate risk in foreign-born women (O/E ratio = 0.66, 95% CI = 0.41 to 1.07). The AUC was 0.564 (95% CI = 0.485 to 0.644) for US-born and 0.625 (95% CI = 0.487 to 0.764) for foreign-born women. Conclusions: The HRM is the first absolute risk model that is based entirely on data specific to Hispanic women by nativity. Further studies in Hispanic women are warranted to evaluate its validity.
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