title: Percentage of biopsy cores positive for malignancy and biochemical failure following prostate cancer radiotherapy in 3,264 men: statistical significance without predictive performance.
abstract: OBJECTIVE
  To define and incorporate the impact of the percentage of positive biopsy cores (PPC) into a predictive model of prostate cancer radiotherapy biochemical outcome.
  
  
  METHODS
  The data of 3264 men with clinically localized prostate cancer treated with external beam radiotherapy at four institutions were retrospectively analyzed. Standard prognostic and treatment factors plus the number of biopsy cores collected and the number positive for malignancy by transrectal ultrasound-guided biopsy were available. The primary endpoint was biochemical failure (bF, Phoenix definition). Multivariate proportional hazards analyses were performed and expressed as a nomogram and the model's predictive ability assessed using the concordance index (c-index).
  
  
  RESULTS
  The cohort consisted of 21% low-, 51% intermediate-, and 28% high-risk cancer patients, and 30% had androgen deprivation with radiotherapy. The median PPC was 50% (interquartile range [IQR] 29-67%), and median follow-up was 51 months (IQR 29-71 months). Percentage of positive biopsy cores displayed an independent association with the risk of bF (p=0.01), as did age, prostate-specific antigen value, Gleason score, clinical stage, androgen deprivation duration, and radiotherapy dose (p<0.001 for all). Including PPC increased the c-index from 0.72 to 0.73 in the overall model. The influence of PPC varied significantly with radiotherapy dose and clinical stage (p=0.02 for both interactions), with doses<66 Gy and palpable tumors showing the strongest relationship between PPC and bF. Intermediate-risk patients were poorly discriminated regardless of PPC inclusion (c-index 0.65 for both models).
  
  
  CONCLUSIONS
  Outcome models incorporating PPC show only minor additional ability to predict biochemical failure beyond those containing standard prognostic factors.
authors.affiliation: Peter MacCallum Cancer Centre and University of Melbourne, Melbourne, Australia. scott.williams@petermac.org
authors.forename: Scott G
authors.initials: SG
authors.lastname: Williams
authors.forename: Mark K
authors.initials: MK
authors.lastname: Buyyounouski
authors.forename: Tom
authors.initials: T
authors.lastname: Pickles
authors.forename: Larry
authors.initials: L
authors.lastname: Kestin
authors.forename: Alvaro
authors.initials: A
authors.lastname: Martinez
authors.forename: Alexandra L
authors.initials: AL
authors.lastname: Hanlon
authors.forename: Gillian M
authors.initials: GM
authors.lastname: Duchesne
mesh_terms: D000368:Aged; D000726:Androgen Antagonists / Q000627:therapeutic use; D001706:Biopsy / Q000379:methods / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009364:Neoplasm Recurrence, Local / Q000097:blood; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D011379:Prognosis; D011467:Prostate / Q000000981:diagnostic imaging / Q000473:pathology*; D017430:Prostate-Specific Antigen / Q000097:blood; D011471:Prostatic Neoplasms / Q000097:blood / Q000188:drug therapy / Q000473:pathology* / Q000532:radiotherapy*; D012189:Retrospective Studies; D018084:Ultrasonography, Interventional
chemical_list: D000726:Androgen Antagonists; D017430:Prostate-Specific Antigen