Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models.
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Authors
Milne, Roger L
Giles, Graham G
Southey, Melissa C
Lee, Andrew
Winship, Ingrid
Hopper, John L
Terry, Mary Beth
Publication Date
2021-10-16Journal Title
Cancers (Basel)
ISSN
2072-6694
Publisher
MDPI AG
Volume
13
Issue
20
Language
eng
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Li, S. X., Milne, R. L., Nguyen-Dumont, T., English, D. R., Giles, G. G., Southey, M. C., Antoniou, A. C., et al. (2021). Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models.. Cancers (Basel), 13 (20) https://doi.org/10.3390/cancers13205194
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.
Keywords
Discrimination, Breast cancer, calibration, Risk Model
Sponsorship
This work was primarily supported by grant 1129136 from the Australian National Health and Medical Research Council (NHMRC) (https://www.nhmrc.gov.au/). MCCS cohort recruitment was funded by Cancer Council Victoria (https://www.cancervic.org.au/) and VicHealth (https://www.vichealth.vic.gov.au/). The MCCS was further supported by
Australian NHMRC grants 209057, 396414 and 1074383, and ongoing follow-up and data management has been funded by Cancer Council Victoria since 1995. Cases and their vital status were ascertained through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index and the Australian Cancer Database.TN-D is a recipient of a Career Development Fellowship from the National Breast Cancer Foundation (Australia). JLH and MCS are Senior Principal and Senior Research Fellows of the National Health and Medical Research Council (Australia), respectively. ACA and AJL are supported by grants from Cancer Research UK (C12292/A20861 and PPRPGM19 Nov20\100002).
Funder references
Cancer Research UK (20861)
Cancer Research UK (C12292/A31369)
Identifiers
PMC8534072, 34680343
External DOI: https://doi.org/10.3390/cancers13205194
This record's URL: https://www.repository.cam.ac.uk/handle/1810/332092
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