title: Combined value of validated clinical and genomic risk stratification tools for predicting prostate cancer mortality in a high-risk prostatectomy cohort.
abstract: BACKGROUND
  Risk prediction models that incorporate biomarkers and clinicopathologic variables may be used to improve decision making after radical prostatectomy (RP). We compared two previously validated post-RP classifiers-the Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) and the Decipher genomic classifier (GC)-to predict prostate cancer-specific mortality (CSM) in a contemporary cohort of RP patients.
  
  
  OBJECTIVE
  To evaluate the combined prognostic ability of CAPRA-S and GC to predict CSM.
  
  
  METHODS
  A cohort of 1010 patients at high risk of recurrence after RP were treated at the Mayo Clinic between 2000 and 2006. High risk was defined by any of the following: preoperative prostate-specific antigen >20 ng/ml, pathologic Gleason score ≥8, or stage pT3b. A case-cohort random sample identified 225 patients (with cases defined as patients who experienced CSM), among whom CAPRA-S and GC could be determined for 185 patients.
  
  
  METHODS
  The scores were evaluated individually and in combination using concordance index (c-index), decision curve analysis, reclassification, cumulative incidence, and Cox regression for the prediction of CSM.
  
  
  CONCLUSIONS
  Among 185 men, 28 experienced CSM. The c-indices for CAPRA-S and GC were 0.75 (95% confidence interval [CI], 0.55-0.84) and 0.78 (95% CI, 0.68-0.87), respectively. GC showed higher net benefit on decision curve analysis, but a score combining CAPRA-S and GC did not improve the area under the receiver-operating characteristic curve after optimism-adjusted bootstrapping. In 82 patients stratified to high risk based on CAPRA-S score ≥6, GC scores were likewise high risk for 33 patients, among whom 17 had CSM events. GC reclassified the remaining 49 men as low to intermediate risk; among these men, three CSM events were observed. In multivariable analysis, GC and CAPRA-S as continuous variables were independently prognostic of CSM, with hazard ratios (HRs) of 1.81 (p<0.001 per 0.1-unit change in score) and 1.36 (p=0.01 per 1-unit change in score). When categorized into risk groups, the multivariable HR for high CAPRA-S scores (≥6) was 2.36 (p=0.04) and was 11.26 (p<0.001) for high GC scores (≥0.6). For patients with both high GC and high CAPRA-S scores, the cumulative incidence of CSM was 45% at 10 yr. The study is limited by its retrospective design.
  
  
  CONCLUSIONS
  Both GC and CAPRA-S were significant independent predictors of CSM. GC was shown to reclassify many men stratified to high risk based on CAPRA-S ≥6 alone. Patients with both high GC and high CAPRA-S risk scores were at markedly elevated post-RP risk for lethal prostate cancer. If validated prospectively, these findings suggest that integration of a genomic-clinical classifier may enable better identification of those post-RP patients who should be considered for more aggressive secondary therapies and clinical trials.
  
  
  RESULTS
  The Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) and the Decipher genomic classifier (GC) were significant independent predictors of prostate cancer-specific mortality. These findings suggest that integration of a genomic-clinical classifier may enable better identification of those post-radical prostatectomy patients who should be considered for more aggressive secondary therapies and clinical trials.
authors.affiliation: Departments of Urology and Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA. Electronic address: mcooperberg@urology.ucsf.edu.
authors.forename: Matthew R
authors.initials: MR
authors.lastname: Cooperberg
authors.affiliation: GenomeDx Biosciences, Vancouver, British Columbia, Canada.
authors.forename: Elai
authors.initials: E
authors.lastname: Davicioni
authors.affiliation: GenomeDx Biosciences, Vancouver, British Columbia, Canada.
authors.forename: Anamaria
authors.initials: A
authors.lastname: Crisan
authors.affiliation: Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
authors.forename: Robert B
authors.initials: RB
authors.lastname: Jenkins
authors.affiliation: GenomeDx Biosciences, Vancouver, British Columbia, Canada.
authors.forename: Mercedeh
authors.initials: M
authors.lastname: Ghadessi
authors.affiliation: Department of Urology, Mayo Clinic, Rochester, MN, USA.
authors.forename: R Jeffrey
authors.initials: RJ
authors.lastname: Karnes
mesh_terms: D000368:Aged; D014408:Biomarkers, Tumor / Q000097:blood / Q000235:genetics*; D023281:Genomics / Q000379:methods; D006801:Humans; D007610:Kallikreins / Q000097:blood; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D008910:Minnesota; D060787:Neoplasm Grading; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D017430:Prostate-Specific Antigen / Q000097:blood; D011468:Prostatectomy / Q000009:adverse effects / Q000401:mortality; D011471:Prostatic Neoplasms / Q000097:blood / Q000175:diagnosis* / Q000235:genetics / Q000401:mortality / Q000473:pathology / Q000601:surgery*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D016896:Treatment Outcome
chemical_list: D014408:Biomarkers, Tumor; C549870:KLK3 protein, human; D007610:Kallikreins; D017430:Prostate-Specific Antigen
keywords: Biomarkers; CAPRA-S; Prostate neoplasms; Prostatectomy; RNA; Risk stratification