title: Age-specific PCA3 score reference values for diagnosis of prostate cancer.
abstract: OBJECTIVE
  We evaluated the impact of age on PCA3 score and the utility of age-specific reference values in predicting initial prostate biopsy (pBx) outcomes.
  
  
  METHODS
  This single-center, retrospective study included 205 men who underwent an initial 14-core TRUS-guided pBx due to PSA > 3.0 ng/ml or suspicious digital-rectal examination (DRE). PCA3 scores were measured with the Progensa assay. Linear regression models were fit to identify factors that impact PCA3 score and to determine age-specific reference values. Predictive accuracies of logistic regression models predicting presence of prostate cancer (PCa) were analyzed.
  
  
  RESULTS
  The positive biopsy rate was 37%. In multivariable linear regression, age (P < 0.001), presence of PCa (P < 0.001), and multifocal HG-PIN (P = 0.012) were independent predictors of PCA3 score. Age showed the strongest impact on PCA3 score (T = 4.77). The upper 95% confidence interval of PCA3 score in each age category was defined as the age-specific limit. A PCA3-score over the age-specific limit (PCA3-age) was associated with an 4.17-fold increased odds of being diagnosed with PCa (P < 0.001). In multivariable logistic regression models predicting the presence of PCa, predictive accuracy of a base model (age, DRE, PSA, volume) increased from 69.6 to 75.4% (P = 0.037) by adding the continuous PCA3 score, to 73.9% (P = 0.098) with the 35 cutoff (PCA3-35) and to 77.1% (P = 0.008) with PCA3-age.
  
  
  CONCLUSIONS
  PCA3 score increases with age, independent of PCa presence. Age-specific PCA3 score reference values are superior to PSA, continuous PCA3 score, and PCA3-35 in predicting initial pBx outcome. Therefore, an age-adjusted PCA3 score should be used for interpretation of the results.
authors.affiliation: Department of Urology, Medical University of Vienna, Vienna, Austria.
authors.forename: Tobias
authors.initials: T
authors.lastname: Klatte
authors.forename: Matthias
authors.initials: M
authors.lastname: Waldert
authors.forename: Michela
authors.initials: M
authors.lastname: de Martino
authors.forename: Georg
authors.initials: G
authors.lastname: Schatzl
authors.forename: Christine
authors.initials: C
authors.lastname: Mannhalter
authors.forename: Mesut
authors.initials: M
authors.lastname: Remzi
mesh_terms: D000368:Aged; D000375:Aging / Q000378:metabolism*; D000951:Antigens, Neoplasm / Q000378:metabolism*; D014408:Biomarkers, Tumor / Q000378:metabolism*; D001706:Biopsy; D015331:Cohort Studies; D003661:Decision Support Techniques; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D017430:Prostate-Specific Antigen / Q000097:blood; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000378:metabolism* / Q000473:pathology; D012016:Reference Values; D012189:Retrospective Studies
chemical_list: D000951:Antigens, Neoplasm; D014408:Biomarkers, Tumor; C479341:prostate cancer antigen 3, human; D017430:Prostate-Specific Antigen