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10-year performance of four models of breast cancer risk: a validation study.

Authors :
John E.M.
Daly M.B.
Buys S.S.
Hopper J.L.
MacInnis R.J.
Chung W.K.
Knight J.A.
Southey M.C.
Milne R.L.
Goldgar D.
Giles G.G.
McLachlan S.-A.
Friedlander M.L.
Weideman P.C.
Glendon G.
Nesci S.
Andrulis I.L.
Phillips K.-A.
Terry M.B.
Liao Y.
Whittemore A.S.
Leoce N.
Buchsbaum R.
Zeinomar N.
Dite G.S.
John E.M.
Daly M.B.
Buys S.S.
Hopper J.L.
MacInnis R.J.
Chung W.K.
Knight J.A.
Southey M.C.
Milne R.L.
Goldgar D.
Giles G.G.
McLachlan S.-A.
Friedlander M.L.
Weideman P.C.
Glendon G.
Nesci S.
Andrulis I.L.
Phillips K.-A.
Terry M.B.
Liao Y.
Whittemore A.S.
Leoce N.
Buchsbaum R.
Zeinomar N.
Dite G.S.
Publication Year :
2019

Abstract

Background: Independent validation is essential to justify use of models of breast cancer risk prediction and inform decisions about prevention options and screening. Few independent validations had been done using cohorts for common breast cancer risk prediction models, and those that have been done had small sample sizes and short follow-up periods, and used earlier versions of the prediction tools. We aimed to validate the relative performance of four commonly used models of breast cancer risk and assess the effect of limited data input on each one's performance. Method(s): In this validation study, we used the Breast Cancer Prospective Family Study Cohort (ProF-SC), which includes 18 856 women from Australia, Canada, and the USA who did not have breast cancer at recruitment, between March 17, 1992, and June 29, 2011. We selected women from the cohort who were 20-70 years old and had no previous history of bilateral prophylactic mastectomy or ovarian cancer, at least 2 months of follow-up data, and information available about family history of breast cancer. We used this selected cohort to calculate 10-year risk scores and compare four models of breast cancer risk prediction: the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm model (BOADICEA), BRCAPRO, the Breast Cancer Risk Assessment Tool (BCRAT), and the International Breast Cancer Intervention Study model (IBIS). We compared model calibration based on the ratio of the expected number of breast cancer cases to the observed number of breast cancer cases in the cohort, and on the basis of their discriminatory ability to separate those who will and will not have breast cancer diagnosed within 10 years as measured with the concordance statistic (C-statistic). We did subgroup analyses to compare the performance of the models at 10 years in BRCA1 or BRCA2 mutation carriers (ie, BRCA-positive women), tested non-carriers and untested participants (ie, BRCA-negative women), and partic

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1305132392
Document Type :
Electronic Resource