TY - JOUR
T1 - Validation of a Genomic Risk Classifier to Predict Prostate Cancer-specific Mortality in Men with Adverse Pathologic Features
AU - Karnes, R. Jeffrey
AU - Choeurng, Voleak
AU - Ross, Ashley E.
AU - Schaeffer, Edward M.
AU - Klein, Eric A.
AU - Freedland, Stephen J.
AU - Erho, Nicholas
AU - Yousefi, Kasra
AU - Takhar, Mandeep
AU - Davicioni, Elai
AU - Cooperberg, Matthew R.
AU - Trock, Bruce J.
N1 - Publisher Copyright:
© 2017 European Association of Urology
PY - 2018/2
Y1 - 2018/2
N2 - Background Risk of prostate cancer-specific mortality (PCSM) is highly variable for men with adverse pathologic features at radical prostatectomy (RP); a majority will die of other causes. Accurately stratifying PCSM risk can improve therapy decisions. Objective Validate the 22 gene Decipher genomic classifier (GC) to predict PCSM in men with adverse pathologic features after RP. Design, setting, and participants Men with adverse pathologic features: pT3, pN1, positive margins, or Gleason score > 7 who underwent RP in 1987–2010 at Johns Hopkins, Cleveland Clinic, Mayo Clinic, and Durham Veteran's Affairs Hospital. We also analyzed subgroups at high risk (prostate-specific antigen > 20 ng/ml, RP Gleason score 8–10, or stage > pT3b), or very high risk of PCSM (biochemical recurrence in < 2 yr [BCR2], or men who developed metastasis after RP [MET]). Outcome measurements and statistical analysis Logistic regression evaluated the association of GC with PCSM within 10 yr of RP (PCSM10), adjusted for the Cancer of the Prostate Risk Assessment Postsurgical Score (CAPRA-S). GC performance was evaluated with area under the receiver operating characteristic curve (AUC) and decision curves. Results and limitations Five hundred and sixty-one men (112 with PCSM10), median follow-up 13.0 yr (patients without PCSM10). For high GC score (> 0.6) versus low-intermediate (≤ 0.6), the odds ratio for PCSM10 adjusted for CAPRA-S was 3.91 (95% confidence interval: 2.43–6.29), with AUC = 0.77, an increase of 0.04 compared with CAPRA-S. Subgroup odds ratios were 3.96, 3.06, and 1.95 for high risk, BCR2, or MET, respectively (all p < 0.05), with AUCs 0.64–0.72. GC stratified cumulative PCSM10 incidence from 2.8% to 30%. Combined use of case-control and cohort data is a potential limitation. Conclusions In a large cohort with the longest follow-up to date, Decipher GC demonstrated clinically important prediction of PCSM at 10 yr, independent of CAPRA-S, in men with adverse pathologic features, BCR2, or MET after RP. Patient summary Decipher genomic classifier may improve treatment decision-making for men with adverse or high risk pathology after radical prostatectomy. In men with adverse pathology or early disease progression after prostatectomy, the Decipher 22 gene genomic classifier predicts risk of prostate cancer death. When combined with the Cancer of the Prostate Risk Assessment Postsurgical Score it further stratifies risk, which may be useful for decisions about postprostatectomy treatment.
AB - Background Risk of prostate cancer-specific mortality (PCSM) is highly variable for men with adverse pathologic features at radical prostatectomy (RP); a majority will die of other causes. Accurately stratifying PCSM risk can improve therapy decisions. Objective Validate the 22 gene Decipher genomic classifier (GC) to predict PCSM in men with adverse pathologic features after RP. Design, setting, and participants Men with adverse pathologic features: pT3, pN1, positive margins, or Gleason score > 7 who underwent RP in 1987–2010 at Johns Hopkins, Cleveland Clinic, Mayo Clinic, and Durham Veteran's Affairs Hospital. We also analyzed subgroups at high risk (prostate-specific antigen > 20 ng/ml, RP Gleason score 8–10, or stage > pT3b), or very high risk of PCSM (biochemical recurrence in < 2 yr [BCR2], or men who developed metastasis after RP [MET]). Outcome measurements and statistical analysis Logistic regression evaluated the association of GC with PCSM within 10 yr of RP (PCSM10), adjusted for the Cancer of the Prostate Risk Assessment Postsurgical Score (CAPRA-S). GC performance was evaluated with area under the receiver operating characteristic curve (AUC) and decision curves. Results and limitations Five hundred and sixty-one men (112 with PCSM10), median follow-up 13.0 yr (patients without PCSM10). For high GC score (> 0.6) versus low-intermediate (≤ 0.6), the odds ratio for PCSM10 adjusted for CAPRA-S was 3.91 (95% confidence interval: 2.43–6.29), with AUC = 0.77, an increase of 0.04 compared with CAPRA-S. Subgroup odds ratios were 3.96, 3.06, and 1.95 for high risk, BCR2, or MET, respectively (all p < 0.05), with AUCs 0.64–0.72. GC stratified cumulative PCSM10 incidence from 2.8% to 30%. Combined use of case-control and cohort data is a potential limitation. Conclusions In a large cohort with the longest follow-up to date, Decipher GC demonstrated clinically important prediction of PCSM at 10 yr, independent of CAPRA-S, in men with adverse pathologic features, BCR2, or MET after RP. Patient summary Decipher genomic classifier may improve treatment decision-making for men with adverse or high risk pathology after radical prostatectomy. In men with adverse pathology or early disease progression after prostatectomy, the Decipher 22 gene genomic classifier predicts risk of prostate cancer death. When combined with the Cancer of the Prostate Risk Assessment Postsurgical Score it further stratifies risk, which may be useful for decisions about postprostatectomy treatment.
KW - Adverse pathologic features
KW - CAPRA-S
KW - Genomic classifier
KW - Prostate cancer-specific mortality
KW - Radical prostatectomy
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U2 - 10.1016/j.eururo.2017.03.036
DO - 10.1016/j.eururo.2017.03.036
M3 - Article
C2 - 28400167
AN - SCOPUS:85017245778
SN - 0302-2838
VL - 73
SP - 168
EP - 175
JO - European urology
JF - European urology
IS - 2
ER -