title: Gleason 6 prostate cancer in one or two biopsy cores can harbor more aggressive disease.
abstract: OBJECTIVE
  Patients with Gleason (GL) 6 prostate cancer in one or two biopsy cores can be upgraded and/or upstaged at the time of surgery, which may adversely impact long-term outcome. A novel model for prediction of adverse pathologic outcomes was developed using preoperative characteristics.
  
  
  METHODS
  Between 2003 and 2007, 1159 patients underwent robot-assisted radical prostatectomy (RARP) at our institution. GL 6 prostate cancer in one or two biopsy cores was identified in 416 (36%) patients. Logistic regression analyses were used to assess the rate of GL ≥7 and/or extraprostatic extension at RARP. Covariates consisted of age, body mass index (BMI), number of positive cores, greatest percent of cancer in a core (GPC), clinical stage, and preoperative prostate-specific antigen (PSA) level. After backward variable selection, the developed model was internally validated using the area under the curve and subjected to methods of calibration.
  
  
  RESULTS
  Respectively, 278 (67%) and 138 (33%) patients had one or two positive biopsy cores. At RARP, 90 (22%) patients were upgraded to GL ≥7 and 37 (9%) had extraprostatic extension. The novel model relied on age, BMI, preoperative PSA level, and GPC for prediction of adverse pathologic outcomes and was 69% accurate. Calibration plot revealed a virtually perfect relationship between predicted and observed probabilities.
  
  
  CONCLUSIONS
  In patients with GL 6 prostate cancer in one or two biopsy cores, 25% have more ominous pathology at RARP. The model provides an individual assessment of adverse outcomes at surgery. Consequently, it may be considered when counseling patients regarding their management options.
authors.affiliation: Section of Urology, Department of Surgery, University of Chicago Medical Center, Chicago, Illinois, USA.
authors.forename: Mark H
authors.initials: MH
authors.lastname: Katz
authors.forename: Sergey
authors.initials: S
authors.lastname: Shikanov
authors.forename: Maxine
authors.initials: M
authors.lastname: Sun
authors.forename: Firas
authors.initials: F
authors.lastname: Abdollah
authors.forename: Lars
authors.initials: L
authors.lastname: Budaeus
authors.forename: Edward M
authors.initials: EM
authors.lastname: Gong
authors.forename: Scott E
authors.initials: SE
authors.lastname: Eggener
authors.forename: Gary D
authors.initials: GD
authors.lastname: Steinberg
authors.forename: Gregory P
authors.initials: GP
authors.lastname: Zagaja
authors.forename: Arieh L
authors.initials: AL
authors.lastname: Shalhav
authors.forename: Pierre I
authors.initials: PI
authors.lastname: Karakiewicz
authors.forename: Kevin C
authors.initials: KC
authors.lastname: Zorn
mesh_terms: D000328:Adult; D000368:Aged; D001706:Biopsy; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009367:Neoplasm Staging; D011467:Prostate / Q000473:pathology* / Q000601:surgery; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000601:surgery; D016896:Treatment Outcome