title: Factors predicting prostatic biopsy Gleason sum under grading.
abstract: OBJECTIVE
  We determined clinical factors affecting the under grading of biopsy Gleason sum compared with prostatectomy pathology and developed a model predicting the probability of under grading.
  
  
  METHODS
  We analyzed a cohort of 1,701 patients treated for prostate cancer at our institution between 1988 and 2007 with complete biopsy and pathological data available. Patients with a biopsy Gleason sum of 7 or less were included in our analysis. Cases were categorized as under graded or not under graded by comparing biopsy and radical prostatectomy Gleason sums. Logistic regression was used to determine the predictors of under grading based on clinical variables (race, age at diagnosis, body mass index, prostate weight, diagnostic prostate specific antigen, biopsy positive-to-total core ratio, maximal cancer percent in positive cores and time from diagnosis to surgery). A nomogram was developed to calculate the probability of under grading. Results were validated using bootstrapping.
  
  
  RESULTS
  Under grading occurred in 46.6% of our cohort. Significant variables predicting under grading were age at diagnosis, biopsy Gleason sum, diagnostic prostate specific antigen, prostate weight, biopsy positive-to-total core ratio and maximal percent of cancer in cores (p <0.05). Nomogram predictive accuracy was 72.4%.
  
  
  CONCLUSIONS
  The risk of Gleason sum under grading can be predicted to a satisfactory level using our nomogram. Predicting under grading would improve patient consulting and identify those who should consider repeat biopsy, ultimately enhancing the accuracy of prostate cancer diagnosis.
authors.affiliation: Division of Urologic Surgery, Duke University Medical Center, Durham, North Carolina 27710, USA.
authors.forename: Danielle A
authors.initials: DA
authors.lastname: Stackhouse
authors.forename: Leon
authors.initials: L
authors.lastname: Sun
authors.forename: Florian R
authors.initials: FR
authors.lastname: Schroeck
authors.forename: Jayakrishnan
authors.initials: J
authors.lastname: Jayachandran
authors.forename: Arthur A
authors.initials: AA
authors.lastname: Caire
authors.forename: Cyril O
authors.initials: CO
authors.lastname: Acholo
authors.forename: Cary N
authors.initials: CN
authors.lastname: Robertson
authors.forename: David M
authors.initials: DM
authors.lastname: Albala
authors.forename: Thomas J
authors.initials: TJ
authors.lastname: Polascik
authors.forename: Craig F
authors.initials: CF
authors.lastname: Donatucci
authors.forename: Kelly E
authors.initials: KE
authors.lastname: Maloney
authors.forename: Judd W
authors.initials: JW
authors.lastname: Moul
mesh_terms: D000368:Aged; D001707:Biopsy, Needle / Q000379:methods*; D015331:Cohort Studies; D016001:Confidence Intervals; D005629:Frozen Sections; D006801:Humans; D007150:Immunohistochemistry; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009361:Neoplasm Invasiveness / Q000473:pathology*; D009367:Neoplasm Staging; D049451:Nomograms; D016017:Odds Ratio; D011237:Predictive Value of Tests; D011300:Preoperative Care; D011336:Probability; D011379:Prognosis; D017430:Prostate-Specific Antigen / Q000097:blood; D011468:Prostatectomy / Q000379:methods* / Q000401:mortality; D011471:Prostatic Neoplasms / Q000401:mortality* / Q000473:pathology* / Q000601:surgery; D012189:Retrospective Studies; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D016019:Survival Analysis; D016896:Treatment Outcome; D047368:Tumor Burden
chemical_list: D017430:Prostate-Specific Antigen