AbstactBackgroundMany men diagnosed with prostate cancer are active surveillance (AS) candidates. However, AS may be associated with increased risk of disease progression and metastasis due to delayed therapy. Genomic classifiers, e.g., Decipher, may allow better risk-stratify newly diagnosed prostate cancers for AS.MethodsDecipher was initially assessed in a prospective cohort of prostatectomies to explore the correlation with clinically meaningful biologic characteristics and then assessed in diagnostic biopsies from a retrospective multicenter cohort of 266 men with National Comprehensive Cancer Network (NCCN) very low/low and favorable-intermediate risk prostate cancer. Decipher and Cancer of the Prostate Risk Assessment (CAPRA) were compared as predictors of adverse pathology (AP) for which there is universal agreement that patients with long life-expectancy are not suitable candidates for AS (primary pattern 4 or 5, advanced local stage [pT3b or greater] or lymph node involvement).ResultsDecipher from prostatectomies was significantly associated with adverse pathologic features (p-values < 0.001). Decipher from the 266 diagnostic biopsies (64.7% NCCN-very-low/low and 35.3% favorable-intermediate) was an independent predictor of AP (odds ratio 1.29 per 10% increase, 95% confidence interval [CI] 1.03–1.61, p-value 0.025) when adjusting for CAPRA. CAPRA area under curve (AUC) was 0.57, (95% CI 0.47–0.68). Adding Decipher to CAPRA increased the AUC to 0.65 (95% CI 0.58–0.70). NPV, which determines the degree of confidence in the absence of AP for patients, was 91% (95% CI 87–94%) and 96% (95% CI 90–99%) for Decipher thresholds of 0.45 and 0.2, respectively. Using a threshold of 0.2, Decipher was a significant predictor of AP when adjusting for CAPRA (p-value 0.016).ConclusionDecipher can be applied to prostate biopsies from NCCN-very-low/low and favorable-intermediate risk patients to predict absence of adverse pathologic features. These patients are predicted to be good candidates for active surveillance.

Background We aimed to validate Decipher to predict adverse pathology (AP) at radical prostatectomy (RP) in men with National Comprehensive Cancer Network (NCCN) favorable-intermediate risk (F-IR) prostate cancer (PCa), and to better select FIR candidates for active surveillance (AS). Methods In all, 647 patients diagnosed with NCCN very low/low risk (VL/LR) or FIR prostate cancer were identified from a multi-institutional PCa biopsy database; all underwent RP with complete postoperative clinicopathological information and Decipher genomic risk scores. The performance of all risk assessment tools was evaluated using logistic regression model for the endpoint of AP, defined as grade group 3−5, pT3b or higher, or lymph node invasion. Results The median age was 61 years (interquartile range 56-66) for 220 patients with NCCN FIR disease, 53% classified as low-risk by Cancer of the Prostate Risk Assessment (CAPRA 0−2) and 47% as intermediate-risk (CAPRA 3−5). Decipher classified 79%, 13% and 8% of men as low-, intermediate-and high-risk with 13%, 10%, and 41% rate of AP, respectively. Decipher was an independent predictor of AP with an odds ratio of 1.34 per 0.1 unit increased (p value = 0.002) and remained significant when adjusting by CAPRA. Notably, FIR with Decipher low or intermediate score did not associate with significantly higher odds of AP compared to VL/LR. Conclusions NCCN risk groups, including FIR , are highly heterogeneous and should be replaced with multivariable riskstratification. In particular, incorporating Decipher may be useful for safely expanding the use of AS in this patient population.

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In a genomic analysis of prostatectomy specimens, metabolic gene expression, but not BMI, was associated with PCa metastases. Cancer 2017;123:2240-2247. © 2017 American Cancer Society.