title: Head-to-head comparison of prostate health index and urinary PCA3 for predicting cancer at initial or repeat biopsy.
abstract: OBJECTIVE
  We performed a head-to-head comparison of the PHI (Prostate Health Index) and PCA3.
  
  
  METHODS
  We evaluated PHI and PCA3 performance in 211 patients undergoing initial (116) or repeat (95) prostate biopsy. Multivariable logistic regression analysis was done using the AUC to test the accuracy of PHI and PCA3 for predicting prostate cancer in the overall population and in each setting. Decision curve analysis was used to compare the clinical benefit of different models.
  
  
  RESULTS
  Overall, the AUC of the PHI (0.70) was significantly higher than the AUC of PCA3 (0.59), total prostate specific antigen (0.56) and free-to-total prostate specific antigen (0.60) (p = 0.043, 0.002 and 0.037, respectively). PHI was more accurate than PCA3 for predicting prostate cancer in the initial setting (AUC 0.69 vs 0.57) and in the repeat setting (AUC 0.72 vs 0.63), although no statistically significant difference was observed. Including PCA3 in the base multivariable model (prostate specific antigen plus free-to-total prostate specific antigen plus prostate volume) did not increase predictive accuracy in either setting (AUC 0.79 vs 0.80 and 0.75 vs 0.76, respectively). Conversely, including PHI in the base multivariable model improved predictive accuracy by 5% (AUC 0.79 to 0.84) and 6% (AUC 0.75 to 0.81) in the initial and repeat prostate biopsy settings, respectively. On decision curve analysis the highest net benefit was observed when PHI was added to the base multivariable model.
  
  
  CONCLUSIONS
  PHI and PCA3 provide a significant increase in sensitivity and specificity compared to all other examined markers and they may help guide biopsy decisions. PCA3 does not increase the accuracy of predicting prostate cancer when PHI is assessed.
authors: Department of Urology, University Vita-Salute, Scientific Institute H San Raffaele, Milan, Italy. scattoni.vincenzo@hsr.it
authors: Vincenzo
authors: V
authors: Scattoni
authors: Massimo
authors: M
authors: Lazzeri
authors: Giovanni
authors: G
authors: Lughezzani
authors: Stefano
authors: S
authors: De Luca
authors: Roberto
authors: R
authors: Passera
authors: Enrico
authors: E
authors: Bollito
authors: Donato
authors: D
authors: Randone
authors: Firas
authors: F
authors: Abdollah
authors: Umberto
authors: U
authors: Capitanio
authors: Alessandro
authors: A
authors: Larcher
authors: Giuliana
authors: G
authors: Lista
authors: Giulio Maria
authors: GM
authors: Gadda
authors: Vittorio
authors: V
authors: Bini
authors: Francesco
authors: F
authors: Montorsi
authors: Giorgio
authors: G
authors: Guazzoni
mesh_terms: D000951:Antigens, Neoplasm / Q000652:urine*; D019540:Area Under Curve; D014408:Biomarkers, Tumor / Q000097:blood / Q000652:urine; D001706:Biopsy; D006801:Humans; D016015:Logistic Models; D008297:Male; D011237:Predictive Value of Tests; D011446:Prospective Studies; D011471:Prostatic Neoplasms / Q000175:diagnosis*; D012680:Sensitivity and Specificity; D018709:Statistics, Nonparametric
chemical_list: D000951:Antigens, Neoplasm; D014408:Biomarkers, Tumor; C479341:prostate cancer antigen 3, human
keywords: BMM; DCA; DRE; HGPIN; PBx; PCA3; PCa; PCa gene 3; PSA; [−2]proPSA; base multivariable model; biopsy; decision curve analysis; digital rectal examination; fPSA; free PSA; high grade prostatic intraepithelial neoplasia; p2PSA; prostate; prostate biopsy; prostate cancer; prostate cancer antigen 3, human; prostate specific antigen; prostate-specific antigen; prostatic neoplasms; tPSA; total PSA