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Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models

SIMPLE SUMMARY: Australia has one of the world’s highest breast cancer incidences. For most women who are not classified as at high risk, eligibility and frequency of breast cancer screening in Australia is based solely on their age. Breast cancer risk models can help to optimise early detection and...

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Detalles Bibliográficos
Autores principales: Li, Sherly X., Milne, Roger L., Nguyen-Dumont, Tú, English, Dallas R., Giles, Graham G., Southey, Melissa C., Antoniou, Antonis C., Lee, Andrew, Winship, Ingrid, Hopper, John L., Terry, Mary Beth, MacInnis, Robert J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534072/
https://www.ncbi.nlm.nih.gov/pubmed/34680343
http://dx.doi.org/10.3390/cancers13205194
Descripción
Sumario:SIMPLE SUMMARY: Australia has one of the world’s highest breast cancer incidences. For most women who are not classified as at high risk, eligibility and frequency of breast cancer screening in Australia is based solely on their age. Breast cancer risk models can help to optimise early detection and management of breast cancer. We evaluated six commonly used models over 15 years follow-up using an Australian community-based cohort of 7608 women aged 50–65 years. The BOADICEA and IBIS models best discriminated women who were at higher risk of developing breast cancer from those at lower risk, but no model apart from BOADICEA accurately predicted absolute risk across the risk spectrum. The BOADICEA model could be of clinical use for women of similar demography. ABSTRACT: Prospective validation of risk models is needed to assess their clinical utility, particularly over the longer term. We evaluated the performance of six commonly used breast cancer risk models (IBIS, BOADICEA, BRCAPRO, BRCAPRO-BCRAT, BCRAT, and iCARE-lit). 15-year risk scores were estimated using lifestyle factors and family history measures from 7608 women in the Melbourne Collaborative Cohort Study who were aged 50–65 years and unaffected at commencement of follow-up two (conducted in 2003–2007), of whom 351 subsequently developed breast cancer. Risk discrimination was assessed using the C-statistic and calibration using the expected/observed number of incident cases across the spectrum of risk by age group (50–54, 55–59, 60–65 years) and family history of breast cancer. C-statistics were higher for BOADICEA (0.59, 95% confidence interval (CI) 0.56–0.62) and IBIS (0.57, 95% CI 0.54–0.61) than the other models (p-difference ≤ 0.04). No model except BOADICEA calibrated well across the spectrum of 15-year risk (p-value < 0.03). The performance of BOADICEA and IBIS was similar across age groups and for women with or without a family history. For middle-aged Australian women, BOADICEA and IBIS had the highest discriminatory accuracy of the six risk models, but apart from BOADICEA, no model was well-calibrated across the risk spectrum.