title: Clinical utility of five genetic variants for predicting prostate cancer risk and mortality.
abstract: BACKGROUND
  A recent report suggests that the combination of five single-nucleotide polymorphisms (SNPs) at 8q24, 17q12, 17q24.3 and a family history of the disease may predict risk of prostate cancer. The present study tests the performance of these factors in prediction models for prostate cancer risk and prostate cancer-specific mortality.
  
  
  METHODS
  SNPs were genotyped in population-based samples from Caucasians in King County, Washington. Incident cases (n = 1,308), aged 35-74, were compared to age-matched controls (n = 1,266) using logistic regression to estimate odds ratios (OR) associated with genotypes and family history. Cox proportional hazards models estimated hazard ratios for prostate cancer-specific mortality according to genotypes.
  
  
  RESULTS
  The combination of SNP genotypes and family history was significantly associated with prostate cancer risk (p(trend) = 1.5 x 10(-20)). Men with > or =5 risk factors had an OR of 4.9 (95% CI 1.6-18.5) compared to men with none. However, this combination of factors did not improve the ROC curve after accounting for known risk predictors (i.e., age, serum PSA, family history). Neither the individual nor combined risk factors was associated with prostate cancer-specific mortality.
  
  
  CONCLUSIONS
  Genotypes for five SNPs plus family history are associated with a significant elevation in risk for prostate cancer and may explain up to 45% of prostate cancer in our population. However, they do not improve prediction models for assessing who is at risk of getting or dying from the disease, once known risk or prognostic factors are taken into account. Thus, this SNP panel may have limited clinical utility.
authors.affiliation: Fred Hutchinson Cancer Research Center, Seattle, Washington 98109-1024, USA.
authors.forename: Claudia A
authors.initials: CA
authors.lastname: Salinas
authors.forename: Joseph S
authors.initials: JS
authors.lastname: Koopmeiners
authors.forename: Erika M
authors.initials: EM
authors.lastname: Kwon
authors.forename: Liesel
authors.initials: L
authors.lastname: FitzGerald
authors.forename: Daniel W
authors.initials: DW
authors.lastname: Lin
authors.forename: Elaine A
authors.initials: EA
authors.lastname: Ostrander
authors.forename: Ziding
authors.initials: Z
authors.lastname: Feng
authors.forename: Janet L
authors.initials: JL
authors.lastname: Stanford
mesh_terms: D000328:Adult; D000368:Aged; D016022:Case-Control Studies; D002886:Chromosomes, Human, Pair 17 / Q000235:genetics*; D002898:Chromosomes, Human, Pair 8 / Q000235:genetics*; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005838:Genotype; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D011471:Prostatic Neoplasms / Q000235:genetics*; D012372:ROC Curve; D012307:Risk Factors