ArticleBreast cancer research : BCR2018
Prospective validation of the NCI Breast Cancer Risk Assessment Tool (Gail Model) on 40,000 Australian women.
Article in Breast cancer research : BCR, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 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
- Identifying Breast Cancer Risk in Patients Undergoing Gender-Affirming Chest Masculinization Surgery.Journal of surgical oncology · 2026Article
- Application of Artificial Intelligence in Breast Ultrasound Diagnosis.Diagnostics (Basel, Switzerland) · 2026Review
- Perceptions of breast cancer risk after breast density notification in a population-based screening program.Breast cancer research and treatment · 2025Article
- Cohort Profile: Lifepool.International journal of epidemiology · 2025Article
- Improving the Estimation of Prediction Increment Measures in Logistic and Survival Analysis.Cancers · 2025Article
- Comparison of Machine Learning Models for Classification of Breast Cancer Risk Based on Clinical Data.Cancer reports (Hoboken, N.J.) · 2025Article
- The Impact of a Breast Cancer Risk Assessment on the Decision for Gender-Affirming Chest Masculinization Surgery in Transgender and Gender-Diverse Individuals: A Pilot Single-Arm Educational Intervention Trial.Annals of surgical oncology · 2024Observational
- Article
- Risk-Stratified Breast Cancer Screening in Malaysia: Challenges and Opportunities.Asian Pacific journal of cancer prevention : APJCP · 2024Review
- The Gail Model and Its Use in Preventive Screening: A Comparison of the Corbelli Study.Cureus · 2024Article
- Addition of polygenic risk score to a risk calculator for prediction of breast cancer in US Black women.Breast cancer research : BCR · 2024Article
- Breast Cancer Risk Assessment Tools for Stratifying Women into Risk Groups: A Systematic Review.Cancers · 2023Review
- Is using the Gail model to calculate the risk of breast cancer in the Venezuelan population justified?Ecancermedicalscience · 2023Review
- Pathways to ovarian cancer diagnosis: a qualitative study.BMC women's health · 2022Article
- Assessment of the Risk of Breast Cancer Development Applying NCI Tool among Iraqi Women.Asian Pacific journal of cancer prevention : APJCP · 2021Article
- Gail model utilization in predicting breast cancer risk in Egyptian women: a cross-sectional study.Breast cancer research and treatment · 2021Article
- Resilience, pain, and the brain: Relationships differ by sociodemographics.Journal of neuroscience research · 2021Observational
- Validation of breast cancer risk assessment tools on a French-Canadian population-based cohort.BMJ open · 2021Article
- Incorporating cortisol into the NAPLS2 individualized risk calculator for prediction of psychosis.Schizophrenia research · 2021Article
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Authors and funding
10 authors at 3 institutions in 1 country.
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Abstract
backgroundThere is a growing interest in delivering more personalised, risk-based breast cancer screening protocols. This requires population-level validation of practical models that can stratify women into breast cancer risk groups. Few studies have evaluated the Gail model (NCI Breast Cancer Risk Assessment Tool) in a population screening setting; we validated this tool in a large, screened population.
methodsWe used data from 40,158 women aged 50-69 years (via the lifepool cohort) participating in Australia's BreastScreen programme. We investigated the association between Gail scores and future invasive breast cancer, comparing observed and expected outcomes by Gail score ranked groups. We also used machine learning to rank Gail model input variables by importance and then assessed the incremental benefit in risk prediction obtained by adding variables in order of diminishing importance.
resultsOver a median of 4.3 years, the Gail model predicted 612 invasive breast cancers compared with 564 observed cancers (expected/observed (E/O) = 1.09, 95% confidence interval (CI) 1.00-1.18). There was good agreement across decile groups of Gail scores (χ
conclusionsThis study confirms that the Gail model (or a reduced model excluding information on hyperplasia and ethnicity) can effectively stratify a screened population aged 50-69 years according to the risk of future invasive breast cancer. This information has the potential to enable more personalised, risk-based screening strategies that aim to improve the balance of the benefits and harms of screening.
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