title: Breast Cancer Risk Prediction Using Clinical Models and 77 Independent Risk-Associated SNPs for Women Aged Under 50 Years: Australian Breast Cancer Family Registry.
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 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.
  
  
  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%.
  
  
  CONCLUSIONS
  Our estimates of the increased performance of clinical risk prediction models from including genetic information could be used to inform targeted screening and prevention.
authors.affiliation: Centre for Epidemiology and Biostatistics, The University of Melbourne, Victoria, Australia.
authors.forename: Gillian S
authors.initials: GS
authors.lastname: Dite
authors.affiliation: Centre for Epidemiology and Biostatistics, The University of Melbourne, Victoria, Australia. Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia.
authors.forename: Robert J
authors.initials: RJ
authors.lastname: MacInnis
authors.affiliation: Centre for Epidemiology and Biostatistics, The University of Melbourne, Victoria, Australia.
authors.forename: Adrian
authors.initials: A
authors.lastname: Bickerstaffe
authors.affiliation: Centre for Epidemiology and Biostatistics, The University of Melbourne, Victoria, Australia.
authors.forename: James G
authors.initials: JG
authors.lastname: Dowty
authors.affiliation: Genetic Technologies Ltd., Fitzroy, Australia.
authors.forename: Richard
authors.initials: R
authors.lastname: Allman
authors.affiliation: Centre for Epidemiology and Biostatistics, The University of Melbourne, Victoria, Australia.
authors.forename: Carmel
authors.initials: C
authors.lastname: Apicella
authors.affiliation: Centre for Epidemiology and Biostatistics, The University of Melbourne, Victoria, Australia. Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia.
authors.forename: Roger L
authors.initials: RL
authors.lastname: Milne
authors.affiliation: Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Victoria, Australia.
authors.forename: Helen
authors.initials: H
authors.lastname: Tsimiklis
authors.affiliation: Centre for Epidemiology and Biostatistics, The University of Melbourne, Victoria, Australia. Division of Cancer Medicine, Peter MacCallum Cancer Centre, Melbourne, Australia. Sir Peter MacCallum Department of Oncology, The University of Melbourne, Victoria, Australia.
authors.forename: Kelly-Anne
authors.initials: KA
authors.lastname: Phillips
authors.affiliation: Centre for Epidemiology and Biostatistics, The University of Melbourne, Victoria, Australia. Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia.
authors.forename: Graham G
authors.initials: GG
authors.lastname: Giles
authors.affiliation: Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York.
authors.forename: Mary Beth
authors.initials: MB
authors.lastname: Terry
authors.affiliation: Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Victoria, Australia.
authors.forename: Melissa C
authors.initials: MC
authors.lastname: Southey
authors.affiliation: Centre for Epidemiology and Biostatistics, The University of Melbourne, Victoria, Australia. j.hopper@unimelb.edu.au.
authors.forename: John L
authors.initials: JL
authors.lastname: Hopper
mesh_terms: D000328:Adult; D001315:Australia; D001943:Breast Neoplasms / Q000235:genetics*; D016022:Case-Control Studies; D005260:Female; D020022:Genetic Predisposition to Disease; D006801:Humans; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide; D012042:Registries; D018570:Risk Assessment; D012307:Risk Factors; D055815:Young Adult