title: Genetic variants and family history predict prostate cancer similar to prostate-specific antigen.
abstract: OBJECTIVE
  Although prostate-specific antigen (PSA) is the best biomarker for predicting prostate cancer, its predictive performance needs to be improved. Results from the Prostate Cancer Prevention Trial revealed the overall performance measured by the areas under curve of the receiver operating characteristic at 0.68. The goal of the present study is to assess the ability of genetic variants as a PSA-independent method to predict prostate cancer risk.
  
  
  METHODS
  We systematically evaluated all prostate cancer risk variants that were identified from genome-wide association studies during the past year in a large population-based prostate cancer case-control study population in Sweden, including 2,893 prostate cancer patients and 1,781 men without prostate cancer.
  
  
  RESULTS
  Twelve single nucleotide polymorphisms were independently associated with prostate cancer risk in this Swedish study population. Using a cutoff of any 11 risk alleles or family history, the sensitivity and specificity for predicting prostate cancer were 0.25 and 0.86, respectively. The overall predictive performance of prostate cancer using genetic variants, family history, and age, measured by areas under curve was 0.65 (95% confidence interval, 0.63-0.66), significantly improved over that of family history and age (0.61%; 95% confidence interval, 0.59-0.62; P = 2.3 x 10(-10)).
  
  
  CONCLUSIONS
  The predictive performance for prostate cancer using genetic variants and family history is similar to that of PSA. The utility of genetic testing, alone and in combination with PSA levels, should be evaluated in large studies such as the European Randomized Study for Prostate Cancer trial and Prostate Cancer Prevention Trial.
authors.affiliation: Center for Cancer Genomics, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.
authors.forename: S Lilly
authors.initials: SL
authors.lastname: Zheng
authors.forename: Jielin
authors.initials: J
authors.lastname: Sun
authors.forename: Fredrik
authors.initials: F
authors.lastname: Wiklund
authors.forename: Zhengrong
authors.initials: Z
authors.lastname: Gao
authors.forename: Pär
authors.initials: P
authors.lastname: Stattin
authors.forename: Lina D
authors.initials: LD
authors.lastname: Purcell
authors.forename: Hans-Olov
authors.initials: HO
authors.lastname: Adami
authors.forename: Fang-Chi
authors.initials: FC
authors.lastname: Hsu
authors.forename: Yi
authors.initials: Y
authors.lastname: Zhu
authors.forename: Jan
authors.initials: J
authors.lastname: Adolfsson
authors.forename: Jan-Erik
authors.initials: JE
authors.lastname: Johansson
authors.forename: Aubrey R
authors.initials: AR
authors.lastname: Turner
authors.forename: Tamara S
authors.initials: TS
authors.lastname: Adams
authors.forename: Wennuan
authors.initials: W
authors.lastname: Liu
authors.forename: David
authors.initials: D
authors.lastname: Duggan
authors.forename: John D
authors.initials: JD
authors.lastname: Carpten
authors.forename: Bao-Li
authors.initials: BL
authors.lastname: Chang
authors.forename: William B
authors.initials: WB
authors.lastname: Isaacs
authors.forename: Jianfeng
authors.initials: J
authors.lastname: Xu
authors.forename: Henrik
authors.initials: H
authors.lastname: Grönberg
mesh_terms: D000368:Aged; D019540:Area Under Curve; D014408:Biomarkers, Tumor / Q000032:analysis; D016022:Case-Control Studies; D005192:Family Health; D055106:Genome-Wide Association Study; D006801:Humans; D008297:Male; D020641:Polymorphism, Single Nucleotide; D011237:Predictive Value of Tests; D017430:Prostate-Specific Antigen / Q000032:analysis*; D011471:Prostatic Neoplasms / Q000235:genetics*; D012372:ROC Curve; D012307:Risk Factors; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D017430:Prostate-Specific Antigen