title: PSA density is superior than PSA and Gleason score for adverse pathologic features prediction in patients with clinically localized prostate cancer.
abstract: BACKGROUND
  Prostate-specific antigen (PSA) and its kinetics have changed prostate cancer screening and diagnosis. The aim of the present study was to evaluate their value in prostate cancer prognosis by determining the predictive potential of PSA density for adverse pathologic features after radical prostatectomy, in terms of positive surgical margins (PSM), extracapsular disease (ECD), seminal vesicle invasion (SVI) and/or lymph node invasion (LNI), and to compare their predictive ability with preoperative PSA and biopsy Gleason score.
  
  
  METHODS
  We retrospectively analysed 285 patients diagnosed with prostate cancer and underwent a retropubic radical prostatectomy for clinically localized disease. Data concerning preoperative PSA, biopsy Gleason score and PSA density were collected and analyzed. PSA density was calculated by dividing preoperative PSA and the pathological volume of the prostate.
  
  
  RESULTS
  There was a significant difference in PSA density values between patients with PSM, ECD, SVI and LNI. Areas under the curve for PSA density were higher than those of PSA and Gleason score for all parameters of adverse pathology. In multivariate analyses, it was shown that PSA density and Gleason score were the only statistically significant predictors for PSM and ECD, PSA density and PSA for SVI and only PSA density for LNI.
  
  
  CONCLUSIONS
  PSA density is an accurate predictor for adverse pathology prediction in patients undergoing radical prostatectomy. These results demonstrate that this parameter is useful to determine the aggressiveness of prostate cancer and can be used as an adjunct in predicting outcomes after surgery.
authors.affiliation: Patras University Hospital, Urology Department, Patras, Greece.
authors.forename: Stavros
authors.initials: S
authors.lastname: Sfoungaristos
authors.forename: Petros
authors.initials: P
authors.lastname: Perimenis