• Gillian S Dite, Robert J MacInnis, Adrian Bickerstaffe, James G Dowty, Richard Allman, Carmel Apicella, Roger L Milne, Helen Tsimiklis, Kelly-Anne Phillips, Graham G Giles, Mary Beth Terry, Melissa C South... more ey, and John L Hopper. less
• Centre for Epidemiology and Biostatistics, The University of Melbourne, Victoria, Australia.
• Cancer Epidemiol. Biomarkers Prev. 2016 Feb 1; 25 (2): 359-65.

BackgroundThe extent to which clinical breast cancer risk prediction models can be improved by including information on known susceptibility SNPs is not known.MethodsUsing 750 cases and 405 controls from the population-based Australian Breast Cancer Family Registry who were younger than 50 years at diagnosis and recruitment, respectively, Caucasian and not BRCA1 or BRCA2 mutation carriers, we derived absolute 5-year risks of breast cancer using the BOADICEA, BRCAPRO, BCRAT, and IBIS risk prediction models and combined these with a risk score based on 77 independent risk-associated SNPs. We used logistic regression to estimate the OR per adjusted SD for log-transformed age-adjusted 5-year risks. Discrimination was assessed by the area under the receiver operating characteristic curve (AUC). Calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test. We also constructed reclassification tables and calculated the net reclassification improvement.ResultsThe ORs for BOADICEA, BRCAPRO, BCRAT, and IBIS were 1.80, 1.75, 1.67, and 1.30, respectively. When combined with the SNP-based score, the corresponding ORs were 1.96, 1.89, 1.80, and 1.52. The corresponding AUCs were 0.66, 0.65, 0.64, and 0.57 for the risk prediction models, and 0.70, 0.69, 0.66, and 0.63 when combined with the SNP-based score.ConclusionsBy combining a 77 SNP-based score with clinical models, the AUC for predicting breast cancer before age 50 years improved by >20%.ImpactOur estimates of the increased performance of clinical risk prediction models from including genetic information could be used to inform targeted screening and prevention.©2015 American Association for Cancer Research.

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