ArticleJNCI cancer spectrum2021
Prospective Evaluation of the Addition of Polygenic Risk Scores to Breast Cancer Risk Models.
Article in JNCI cancer spectrum, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Independent evaluation of melanoma polygenic risk scores in UK and Australian prospective cohorts.The British journal of dermatology · 2022Pooled it
- Systemic immune activation in hereditary cancer predisposition syndromes: a cross-sectional study.BMC medicine · 2026Article
- WDCN: a comprehensive neural network based approach for estimating breast cancer risk.Briefings in bioinformatics · 2026Article
- Performance of three breast cancer risk assessment tools in US Black women.Breast cancer research : BCR · 2026Article
- Performance of different polygenic risk scores for breast cancer risk prediction: in-depth evaluations across large UK and Australian cohorts.European journal of human genetics : EJHG · 2026Article
- Adapting the BOADICEA breast and ovarian cancer risk models for the ethnically diverse UK population.British journal of cancer · 2025Article
- Implementing integrated genomic risk assessments for breast cancer: lessons learned from the Electronic Medical Records and Genomics study.JAMIA open · 2025Article
- Association of Polygenic-Based Breast Cancer Risk Prediction With Patient Management.JCO precision oncology · 2025Article
- Evaluating the performance of the Breast and Ovarian Analysis of Disease Incidence Algorithm model in predicting 10-year breast cancer risks in UK Biobank.Journal of the National Cancer Institute · 2025Article
- Overlap of high-risk individuals across family history, genetic & non-genetic breast cancer risk models: Analysis of 180,398 women from European & Asian ancestries.medRxiv : the preprint server for health sciences · 2025Article
- Polygenic risk scores stratify breast cancer risk among women with benign breast disease.Journal of the National Cancer Institute · 2025Article
- Polygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction.Breast cancer research : BCR · 2024Article
- Causation and familial confounding as explanations for the associations of polygenic risk scores with breast cancer: Evidence from innovative ICE FALCON and ICE CRISTAL analyses.Genetic epidemiology · 2024Article
- Validation of the BOADICEA model in a prospective cohort ofJournal of medical genetics · 2024Article
- Differences in polygenic score distributions in European ancestry populations: implications for breast cancer risk prediction.medRxiv : the preprint server for health sciences · 2024Article
- Addition of polygenic risk score to a risk calculator for prediction of breast cancer in US Black women.Breast cancer research : BCR · 2024Article
- Review
- Review: Predictive approaches to breast cancer risk.Heliyon · 2023Review
- Validation of the BOADICEA model for predicting the likelihood of carrying pathogenic variants in eight breast and ovarian cancer susceptibility genes.Scientific reports · 2023Article
- Incorporating Alternative Polygenic Risk Scores into the BOADICEA Breast Cancer Risk Prediction Model.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023Article
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14 authors.
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Abstract
Background: The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm and the International Breast Cancer Intervention Study breast cancer risk models are used to provide advice on screening intervals and chemoprevention. We evaluated the performance of these models, which now incorporate polygenic risk scores (PRSs), using a prospective cohort study. Methods: We used a case-cohort design, involving women in the Melbourne Collaborative Cohort Study aged 50-75 years when surveyed in 2003-2007, of whom 408 had a first primary breast cancer diagnosed within 10 years (cases), and 2783 were from the subcohort. Ten-year risks were calculated based on lifestyle factors, family history data, and a 313-variant PRS. Discrimination was assessed using a C-statistic compared with 0.50 and calibration using the ratio of expected to observed number of cases (E/O). Results: When the PRS was added to models with lifestyle factors and family history, the C-statistic (95% confidence interval [CI]) increased from 0.57 (0.54 to 0.60) to 0.62 (0.60 to 0.65) using IBIS and from 0.56 (0.53 to 0.59) to 0.62 (0.59 to 0.64) using BOADICEA. IBIS underpredicted risk (E/O = 0.62, 95% CI = 0.48 to 0.80) for women in the lowest risk category (<1.7%) and overpredicted risk (E/O = 1.40, 95% CI = 1.18 to 1.67) in the highest risk category (≥5%), using the Hosmer-Lemeshow test for calibration in quantiles of risk and a 2-sided Conclusions: Although the inclusion of a 313 genetic variant PRS doubles discriminatory accuracy (relative to reference 0.50), models with and without this PRS have relatively modest discrimination and might require recalibration before their clinical and wider use are promoted.
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