title: Comparison of models to predict clinical failure after radical prostatectomy.
abstract: BACKGROUND
  Models are available to accurately predict biochemical disease recurrence (BCR) after radical prostatectomy (RP). Because not all patients experiencing BCR will progress to metastatic disease, it is appealing to determine postoperatively which patients are likely to manifest systemic disease.
  
  
  METHODS
  The study cohort consisted of 881 patients undergoing RP between 1985 and 2003. Clinical failure (CF) was defined as metastases, a rising prostate-specific antigen (PSA) in a castrate state, or death from prostate cancer. The cohort was randomized into training and validation sets. The accuracy of 4 models to predict clinical outcome within 5 years of RP were compared: 'postoperative BCR nomogram' and 'Cox regression CF model' based on standard clinical and pathologic parameters, and 2 CF 'systems pathology' models that integrate clinical and pathologic parameters with quantitative histomorphometric and immunofluorescent biomarker features ('systems pathology Models 1 and 2').
  
  
  RESULTS
  When applied to the validation set, the concordance index for the postoperative BCR nomogram was 0.85, for the Cox regression CF model 0.84, for systems pathology Model 1 0.81, and for systems pathology Model 2 0.85.
  
  
  CONCLUSIONS
  Models predicting either BCR or CF after RP exhibit similarly high levels of accuracy because standard clinical and pathologic variables appear to be the primary determinants of both outcomes. It is possible that introducing current or novel biomarkers found to be uniquely associated with disease progression may further enhance the accuracy of the systems pathology-based platform.
authors.affiliation: Section of Urology, University of Chicago, Chicago, Illinois, USA.
authors.forename: Scott E
authors.initials: SE
authors.lastname: Eggener
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Vickers
authors.forename: Angel M
authors.initials: AM
authors.lastname: Serio
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Donovan
authors.forename: Faisal M
authors.initials: FM
authors.lastname: Khan
authors.forename: Valentina
authors.initials: V
authors.lastname: Bayer-Zubek
authors.forename: David
authors.initials: D
authors.lastname: Verbel
authors.forename: Carlos
authors.initials: C
authors.lastname: Cordon-Cardo
authors.forename: Victor E
authors.initials: VE
authors.lastname: Reuter
authors.forename: Fernando J
authors.initials: FJ
authors.lastname: Bianco
authors.forename: Peter T
authors.initials: PT
authors.lastname: Scardino
mesh_terms: D000368:Aged; D006801:Humans; D008297:Male; D008875:Middle Aged; D009362:Neoplasm Metastasis; D011237:Predictive Value of Tests; D017430:Prostate-Specific Antigen / Q000378:metabolism; D011468:Prostatectomy; D011471:Prostatic Neoplasms / Q000401:mortality / Q000601:surgery*; D012680:Sensitivity and Specificity; D013598:Systems Theory; D017211:Treatment Failure; D054928:Validation Studies as Topic
chemical_list: D017430:Prostate-Specific Antigen