title: Using Breast Cancer Risk Associated Polymorphisms to Identify Women for Breast Cancer Chemoprevention.
abstract: BACKGROUND
  Breast cancer can be prevented with selective estrogen receptor modifiers (SERMs) and aromatase inhibitors (AIs). The US Preventive Services Task Force recommends that women with a 5-year breast cancer risk ≥3% consider chemoprevention for breast cancer. More than 70 single nucleotide polymorphisms (SNPs) have been associated with breast cancer. We sought to determine how to best integrate risk information from SNPs with other risk factors to risk stratify women for chemoprevention.
  
  
  METHODS
  We used the risk distribution among women ages 35-69 estimated by the Breast Cancer Surveillance Consortium (BCSC) risk model. We modeled the effect of adding 70 SNPs to the BCSC model and examined how this would affect how many women are reclassified above and below the threshold for chemoprevention.
  
  
  RESULTS
  We found that most of the benefit of SNP testing a population is achieved by testing a modest fraction of the population. For example, if women with a 5-year BCSC risk of >2.0% are tested (~21% of all women), ~75% of the benefit of testing all women (shifting women above or below 3% 5-year risk) would be derived. If women with a 5-year risk of >1.5% are tested (~36% of all women), ~90% of the benefit of testing all women would be derived.
  
  
  CONCLUSIONS
  SNP testing is effective for reclassification of women for chemoprevention, but is unlikely to reclassify women with <1.5% 5-year risk. These results can be used to implement an efficient two-step testing approach to identify high risk women who may benefit from chemoprevention.
authors.affiliation: Department of Medicine, University of California, San Francisco, California, United States of America.|Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California, United States of America.|Institute for Human Genetics, University of California, San Francisco, California, United States of America.
authors.forename: Elad
authors.initials: E
authors.lastname: Ziv
authors.affiliation: Department of Medicine, University of California, San Francisco, California, United States of America.|Department of Epidemiology and Biostatistics, University of California, San Francisco, California, United States of America.
authors.forename: Jeffrey A
authors.initials: JA
authors.lastname: Tice
authors.affiliation: Department of Surgery and University of Vermont Cancer Center, University of Vermont, Burlington, Vermont, United States of America.
authors.forename: Brian
authors.initials: B
authors.lastname: Sprague
authors.affiliation: Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic College of Medicine, Rochester, Minnesota, United States of America.
authors.forename: Celine M
authors.initials: CM
authors.lastname: Vachon
authors.affiliation: San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, California, United States of America.
authors.forename: Steven R
authors.initials: SR
authors.lastname: Cummings
authors.affiliation: Department of Medicine, University of California, San Francisco, California, United States of America.|Department of Epidemiology and Biostatistics, University of California, San Francisco, California, United States of America.|General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, California, United States of America.
authors.forename: Karla
authors.initials: K
authors.lastname: Kerlikowske
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics* / Q000517:prevention & control; D018890:Chemoprevention; D005260:Female; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D006801:Humans; D020641:Polymorphism, Single Nucleotide