title: Preoperative determination of prostate cancer tumor volume: analysis through biopsy fragments.
abstract: OBJECTIVE
  Preoperative determination of prostate cancer (PCa) tumor volume (TV) is still a big challenge. We have assessed variables obtained in prostatic biopsy aiming at determining which is the best method to predict the TV in radical prostatectomy (RP) specimens.
  
  
  METHODS
  Biopsy findings of 162 men with PCa submitted to radical prostatectomy were revised. Preoperative characteristics, such as PSA, the percentage of positive fragments (PPF), the total percentage of cancer in the biopsy (TPC), the maximum percentage of cancer in a fragment (MPC), the presence of perineural invasion (PNI) and the Gleason score were correlated with postoperative surgical findings through an univariate analysis of a linear regression model.
  
  
  RESULTS
  The TV correlated significantly to the PPF, TPC, MPC, PSA and to the presence of PNI (p < 0.001). However, the Pearson correlation analysis test showed an R2 of only 24%, 12%, 17% and 9% for the PPF, TPC, MPC, and PSA respectively. The combination of the PPF with the PSA and the PNI analysis showed to be a better model to predict the TV (R2 of 32.3%). The TV could be determined through the formula: Volume = 1.108 + 0.203 x PSA + 0.066 x PPF + 2.193 x PNI.
  
  
  CONCLUSIONS
  The PPF seems to be better than the TPC and the MPC to predict the TV in the surgical specimen. Due to the weak correlation between those variables and the TV, the PSA and the presence of PNI should be used together.
authors.affiliation: Division of Urology, University of Sao Paulo Medical School, Sao Paulo, Brazil. antunesuro@uol.com.br
authors.forename: Alberto A
authors.initials: AA
authors.lastname: Antunes
authors.forename: Miguel
authors.initials: M
authors.lastname: Srougi
authors.forename: Marcos F
authors.initials: MF
authors.lastname: Dall'Oglio
authors.forename: Alexandre
authors.initials: A
authors.lastname: Crippa
authors.forename: Adriano J
authors.initials: AJ
authors.lastname: Nesrallah
authors.forename: Luciano J
authors.initials: LJ
authors.lastname: Nesrallah
authors.forename: Katia R
authors.initials: KR
authors.lastname: Leite
mesh_terms: D000328:Adult; D000368:Aged; D001707:Biopsy, Needle; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D009361:Neoplasm Invasiveness; D009367:Neoplasm Staging; D011300:Preoperative Care; D011379:Prognosis; D011467:Prostate; D017430:Prostate-Specific Antigen / Q000032:analysis; D011468:Prostatectomy; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000601:surgery; D018709:Statistics, Nonparametric; D047368:Tumor Burden
chemical_list: D017430:Prostate-Specific Antigen