Decipher Genomic Classifier Measured on Prostate Biopsy Predicts Metastasis Risk.

OBJECTIVES To evaluate the ability of the Decipher genomic classifier in predicting metastasis from analysis of prostate needle biopsy diagnostic tumor tissue specimens. MATERIALS AND METHODS Fifty-seven patients with available biopsy specimens were identified from a cohort of 169 men treated with radical prostatectomy in a previously reported Decipher validation study at Cleveland Clinic. A Cox multivariable proportional hazards model and survival C-index were used to evaluate the performance of Decipher. RESULTS With a median follow up of 8 years, 8 patients metastasized and 3 died of prostate cancer. The Decipher plus National Comprehensive Cancer Network (NCCN) model had an improved C-index of 0.88 (95% confidence interval [CI] 0.77-0.96) compared to NCCN alone (C-index 0.75, 95% CI 0.64-0.87). On multivariable analysis, Decipher was the only significant predictor of metastasis when adjusting for age, preoperative prostate-specific antigen and biopsy Gleason score (Decipher hazard ratio per 10% increase 1.72, 95% CI 1.07-2.81, P = .02). CONCLUSION Biopsy Decipher predicted the risk of metastasis at 10 years post radical prostatectomy. While further validation is required on larger cohorts, preoperative knowledge of Decipher risk derived from biopsy could indicate the need for multimodality therapy and help set patient expectations of therapeutic burden.

[1]  David L Rimm,et al.  Development and Clinical Validation of an In Situ Biopsy-Based Multimarker Assay for Risk Stratification in Prostate Cancer , 2015, Clinical Cancer Research.

[2]  M. Cooperberg,et al.  The CAPRA‐S score , 2011, Cancer.

[3]  R. Tibshirani The lasso method for variable selection in the Cox model. , 1997, Statistics in medicine.

[4]  T. Lumley,et al.  Time‐Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker , 2000, Biometrics.

[5]  D. Firth Bias reduction of maximum likelihood estimates , 1993 .

[6]  F. Feng,et al.  Genomic classifier identifies men with adverse pathology after radical prostatectomy who benefit from adjuvant radiation therapy. , 2015, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[7]  A. D'Amico,et al.  Which, when and why? Rational use of tissue-based molecular testing in localized prostate cancer , 2015, Prostate Cancer and Prostatic Disease.

[8]  M. Kattan,et al.  A genomic classifier improves prediction of metastatic disease within 5 years after surgery in node-negative high-risk prostate cancer patients managed by radical prostatectomy without adjuvant therapy. , 2015, European urology.

[9]  Michael W Kattan,et al.  Postoperative nomogram predicting the 10-year probability of prostate cancer recurrence after radical prostatectomy. , 2005, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[10]  P. Febbo,et al.  A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling. , 2014, European urology.

[11]  L. Egevad,et al.  The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma , 2005, The American journal of surgical pathology.

[12]  M. Cooperberg,et al.  A Straightforward Tool for Improved Prediction of Outcomes After Radical Prostatectomy , 2011 .

[13]  B. Trock,et al.  Tissue-based Genomics Augments Post-prostatectomy Risk Stratification in a Natural History Cohort of Intermediate- and High-Risk Men. , 2016, European urology.

[14]  P. Febbo,et al.  The Impact of a Biopsy Based 17‐Gene Genomic Prostate Score on Treatment Recommendations in Men with Newly Diagnosed Clinically Prostate Cancer Who are Candidates for Active Surveillance , 2015, Urology practice.

[15]  E. Klein,et al.  Applying precision medicine to the active surveillance of prostate cancer , 2015, Cancer.

[16]  M. Cooperberg,et al.  Genomic Predictors of Outcome in Prostate Cancer. , 2015, European urology.