title: Potential usefulness of single nucleotide polymorphisms to identify persons at high cancer risk: an evaluation of seven common cancers.
abstract: OBJECTIVE
  To estimate the likely number and predictive strength of cancer-associated single nucleotide polymorphisms (SNPs) that are yet to be discovered for seven common cancers.
  
  
  METHODS
  From the statistical power of published genome-wide association studies, we estimated the number of undetected susceptibility loci and the distribution of effect sizes for all cancers. Assuming a log-normal model for risks and multiplicative relative risks for SNPs, family history (FH), and known risk factors, we estimated the area under the receiver operating characteristic curve (AUC) and the proportion of patients with risks above risk thresholds for screening. From additional prevalence data, we estimated the positive predictive value and the ratio of non-patient cases to patient cases (false-positive ratio) for various risk thresholds.
  
  
  RESULTS
  Age-specific discriminatory accuracy (AUC) for models including FH and foreseeable SNPs ranged from 0.575 for ovarian cancer to 0.694 for prostate cancer. The proportions of patients in the highest decile of population risk ranged from 16.2% for ovarian cancer to 29.4% for prostate cancer. The corresponding false-positive ratios were 241 for colorectal cancer, 610 for ovarian cancer, and 138 or 280 for breast cancer in women age 50 to 54 or 40 to 44 years, respectively.
  
  
  CONCLUSIONS
  Foreseeable common SNP discoveries may not permit identification of small subsets of patients that contain most cancers. Usefulness of screening could be diminished by many false positives. Additional strong risk factors are needed to improve risk discrimination.
authors.affiliation: National Cancer Institute, Rockville, MD 20852-7244, USA.
authors.forename: Ju-Hyun
authors.initials: JH
authors.lastname: Park
authors.forename: Mitchell H
authors.initials: MH
authors.lastname: Gail
authors.forename: Mark H
authors.initials: MH
authors.lastname: Greene
authors.forename: Nilanjan
authors.initials: N
authors.lastname: Chatterjee
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D019540:Area Under Curve; D055088:Early Detection of Cancer / Q000379:methods*; D005192:Family Health; D005260:Female; D020022:Genetic Predisposition to Disease; D006801:Humans; D008297:Male; D008495:Medical Oncology / Q000379:methods; D008875:Middle Aged; D008954:Models, Biological; D015233:Models, Statistical; D009369:Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide; D011237:Predictive Value of Tests; D012306:Risk; D012307:Risk Factors