title: Mammographic Breast Density and Common Genetic Variants in Breast Cancer Risk Prediction.
abstract: BACKGROUND
  Known prediction models for breast cancer can potentially by improved by the addition of mammographic density and common genetic variants identified in genome-wide associations studies known to be associated with risk of the disease. We evaluated the benefit of including mammographic density and the cumulative effect of genetic variants in breast cancer risk prediction among women in a Singapore population.
  
  
  METHODS
  We estimated the risk of breast cancer using a prospective cohort of 24,161 women aged 50 to 64 from Singapore with available mammograms and known risk factors for breast cancer who were recruited between 1994 and 1997. We measured mammographic density using the medio-lateral oblique views of both breasts. Each woman's genotype for 75 SNPs was simulated based on the genotype frequency obtained from the Breast Cancer Association Consortium data and the cumulative effect was summarized by a genetic risk score (GRS). Any improvement in the performance of our proposed prediction model versus one containing only variables from the Gail model was assessed by changes in receiver-operating characteristic and predictive values.
  
  
  RESULTS
  During 17 years of follow-up, 680 breast cancer cases were diagnosed. The multivariate-adjusted hazard ratios (95% confidence intervals) were 1.60 (1.22-2.10), 2.20 (1.65-2.92), 2.33 (1.71-3.20), 2.12 (1.43-3.14), and 3.27 (2.24-4.76) for the corresponding mammographic density categories: 11-20cm2, 21-30cm2, 31-40cm2, 41-50cm2, 51-60cm2, and 1.10 (1.03-1.16) for GRS. At the predicted absolute 10-year risk thresholds of 2.5% and 3.0%, a model with mammographic density and GRS could correctly identify 0.9% and 0.5% more women who would develop the disease compared to a model using only the Gail variables, respectively.
  
  
  CONCLUSIONS
  Mammographic density and common genetic variants can improve the discriminatory power of an established breast cancer risk prediction model among females in Singapore.
authors.affiliation: NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
authors.forename: Charmaine Pei Ling
authors.initials: CP
authors.lastname: Lee
authors.affiliation: Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
authors.forename: Hyungwon
authors.initials: H
authors.lastname: Choi
authors.affiliation: National Cancer Centre, Singapore, Singapore.
authors.forename: Khee Chee
authors.initials: KC
authors.lastname: Soo
authors.affiliation: National Cancer Centre, Singapore, Singapore.
authors.forename: Min-Han
authors.initials: MH
authors.lastname: Tan
authors.affiliation: National Cancer Centre, Singapore, Singapore.
authors.forename: Wen Yee
authors.initials: WY
authors.lastname: Chay
authors.affiliation: Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
authors.forename: Kee Seng
authors.initials: KS
authors.lastname: Chia
authors.affiliation: Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
authors.forename: Jenny
authors.initials: J
authors.lastname: Liu
authors.affiliation: Human Genetics, Genome Institute of Singapore, Singapore, Singapore.
authors.forename: Jingmei
authors.initials: J
authors.lastname: Li
authors.affiliation: Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore; Department of Surgery, National University Hospital, Singapore, Singapore; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Mikael
authors.initials: M
authors.lastname: Hartman
mesh_terms: D000071060:Breast Density; D001943:Breast Neoplasms / Q000453:epidemiology / Q000235:genetics* / Q000473:pathology*; D005260:Female; D005500:Follow-Up Studies; D005787:Gene Frequency; D014644:Genetic Variation; D005838:Genotype; D006801:Humans; D042361:Mammary Glands, Human / Q000002:abnormalities*; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide; D011159:Population Surveillance; D011446:Prospective Studies; D012372:ROC Curve; D012306:Risk; D012846:Singapore / Q000453:epidemiology