Skip to main content

Breast cancer risk prediction using clinical models and 77 independent risk-associated SNPs for women aged under 50 years: Australian breast cancer family registry

59Citations
Citations of this article
57Readers
Mendeley users who have this article in their library.

Abstract

Background: The extent to which clinical breast cancer risk prediction models can be improved by including information on known susceptibility SNPs is not known. Methods: Using 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 riskassociated 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. Results: The 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. Conclusions: By combining a 77 SNP-based score with clinical models, the AUC for predicting breast cancer before age 50 years improved by >20%. Impact: Our estimates of the increased performance of clinical risk prediction models from including genetic information could be used to inform targeted screening and prevention.

Cite

CITATION STYLE

APA

Dite, G. S., Macinnis, R. J., Bickerstaffe, A., Dowty, J. G., Allman, R., Apicella, C., … Hopper, J. L. (2016). Breast cancer risk prediction using clinical models and 77 independent risk-associated SNPs for women aged under 50 years: Australian breast cancer family registry. Cancer Epidemiology Biomarkers and Prevention, 25(2), 359–365. https://doi.org/10.1158/1055-9965.EPI-15-0838

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free