title: Operator is an independent predictor of detecting prostate cancer at transrectal ultrasound guided prostate biopsy.
abstract: OBJECTIVE
  We investigated whether interoperator differences exist in the setting of prostate cancer detection by transrectal ultrasound guided prostate biopsy. Our secondary aim was to investigate whether a learning curve exists for prostate cancer detection.
  
  
  METHODS
  A prospective database from 2000 to 2008 including 9,072 transrectal ultrasound guided prostate biopsies at our institution was limited to 4,724 done at initial presentation. Biopsies were performed by 4 uroradiologists. The OR for detecting cancer on transrectal ultrasound guided prostate biopsy was calculated for likely independent prognostic variables, including operator. We also examined the rate of biopsy positivity in increments, comparing the first and last cohorts. The senior radiologist (AT) with the most biopsies (75%) was considered the referent for prostate cancer detection. Univariate and multivariate logistic regression modeling was used to determine significant covariates with p <0.05 deemed relevant.
  
  
  RESULTS
  Prostate cancer was detected in 2,331 men (49.3%). Operators performed a median of 514 transrectal ultrasound guided prostate biopsies (range 187 to 3,509) with a prostate cancer detection rate of 43.8% to 52.4% (p = 0.001). Other significant covariates were prostate specific antigen, suspicious lesions on ultrasound, nodule on digital rectal examination, smaller prostate volume and increasing patient age. Operator was a significant multivariate predictor of cancer detection (OR 0.67 to 0.89, p = 0.003). No learning curve was detected and biopsy rates were consistent throughout the series.
  
  
  CONCLUSIONS
  Significant differences in prostate cancer detection exist among operators who perform transrectal ultrasound guided prostate biopsy even in the same setting. The volume of previously performed transrectal ultrasound guided prostate biopsies does not appear to influence the positive prostate cancer detection rate, nor could a learning curve be identified. Differences in prostate cancer detection among operators are likely related to unknown differences in expertise or technique. Further research is needed.
authors.affiliation: Department of Urology, University Health Network, University of Toronto, Toronto, Ontario, Canada.
authors.forename: Nathan
authors.initials: N
authors.lastname: Lawrentschuk
authors.forename: Ants
authors.initials: A
authors.lastname: Toi
authors.forename: Gina A
authors.initials: GA
authors.lastname: Lockwood
authors.forename: Andrew
authors.initials: A
authors.lastname: Evans
authors.forename: Antonio
authors.initials: A
authors.lastname: Finelli
authors.forename: Martin
authors.initials: M
authors.lastname: O'Malley
authors.forename: Myles
authors.initials: M
authors.lastname: Margolis
authors.forename: Sangeet
authors.initials: S
authors.lastname: Ghai
authors.forename: Neil E
authors.initials: NE
authors.lastname: Fleshner
mesh_terms: D000368:Aged; D001706:Biopsy / Q000379:methods; D002983:Clinical Competence; D003950:Diagnostic Techniques, Urological / Q000592:standards / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D012007:Rectum; D014463:Ultrasonography