ArticleJournal of the National Cancer Institute2015
Practical problems with clinical guidelines for breast cancer prevention based on remaining lifetime risk.
Article in Journal of the National Cancer Institute, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Defining Lifetime Risk Thresholds for Breast Cancer Surgical Prevention.JAMA oncology · 2025Article
- Plasma metabolomics profiles and breast cancer risk.Breast cancer research : BCR · 2024Article
- Validation of an Abridged Breast Cancer Risk Prediction Model for the General Population.Cancer prevention research (Philadelphia, Pa.) · 2023Article
- Should Age-Dependent Absolute Risk Thresholds Be Used for Risk Stratification in Risk-Stratified Breast Cancer Screening?Journal of personalized medicine · 2021Article
- Estimating the Breast Cancer Burden in Germany and Implications for Risk-based Screening.Cancer prevention research (Philadelphia, Pa.) · 2021Article
- Comparing 5-Year and Lifetime Risks of Breast Cancer using the Prospective Family Study Cohort.Journal of the National Cancer Institute · 2021Article
- The Steroid Metabolome and Breast Cancer Risk in Women with a Family History of Breast Cancer: The Novel Role of Adrenal Androgens and Glucocorticoids.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2021Article
- Circulating growth factor concentrations and breast cancer risk: a nested case-control study of IGF-1, IGFBP-3, and breast cancer in a family-based cohort.Breast cancer research : BCR · 2020Article
- Improving the diagnostic accuracy of a stratified screening strategy by identifying the optimal risk cutoff.Cancer causes & control : CCC · 2019Article
- Comparison of Questionnaire-Based Breast Cancer Prediction Models in the Nurses' Health Study.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2019Article
- Age-specific breast cancer risk by body mass index and familial risk: prospective family study cohort (ProF-SC).Breast cancer research : BCR · 2018Article
- Use of the BOADICEA Web Application in clinical practice: appraisals by clinicians from various countries.Familial cancer · 2018Article
- Counselling framework for moderate-penetrance cancer-susceptibility mutations.Nature reviews. Clinical oncology · 2016Review
- Cohort Profile: The Breast Cancer Prospective Family Study Cohort (ProF-SC).International journal of epidemiology · 2016Article
- iPrevent®: a tailored, web-based, decision support tool for breast cancer risk assessment and management.Breast cancer research and treatment · 2016Article
- Breast Cancer Risk Prediction Using Clinical Models and 77 Independent Risk-Associated SNPs for Women Aged Under 50 Years: Australian Breast Cancer Family Registry.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2016Article
- Assessing absolute changes in breast cancer risk due to modifiable risk factors.Breast cancer research and treatment · 2015Article
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6 authors.
Funding
Abstract
backgroundClinical guidelines for breast cancer chemoprevention and MRI screening involve estimates of remaining lifetime risk (RLR); in the United States, women with an RLR of 20% or higher meet "high-risk" criteria for MRI screening.
methodsWe prospectively followed 1764 women without breast cancer to compare the RLRs and 10-year risks assigned by the risk models International Breast Cancer Intervention Study (IBIS) and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) and to compare both sets of model-assigned 10-year risks to subsequent incidence of breast cancer in the cohort. We used chi-square statistics to assess calibration and the area under the receiver operating characteristic curve (AUC) to assess discrimination. All statistical tests are two-sided.
resultsThe models classified different proportions of women as high-risk (IBIS = 59.3% vs BOADICEA = 20.1%) using the RLR threshold of 20%. The difference was smaller (IBIS = 52.9% vs BOADICEA = 43.2%) using a 10-year risk threshold of 3.34%. IBIS risks (mean = 4.9%) were better calibrated to observed breast cancer incidence (5.2%, 95% confidence interval (CI) = 4.2% to 6.4%) than were those of BOADICEA (mean = 3.7%) overall and within quartiles of model risk (P = .20 by IBIS and P = .07 by BOADICEA). Both models gave similar discrimination, with AUCs of 0.67 (95% CI = 0.61 to 0.73) using IBIS and 0.68 (95% CI = 0.62 to 0.74) using BOADICEA. Model sensitivities at thresholds for a 20% false-positive rate were also similar, with 41.8% using IBIS and 38.0% using BOADICEA.
conclusionRLR-based guidelines for high-risk women are limited by discordance between commonly used risk models. Guidelines based on short-term risks would be more useful, as models are generally developed and validated under a short fixed time horizon (≤10 years).
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