Decipher identifies men with otherwise clinically favorable-intermediate risk disease who may not 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 F-IR candidates for active surveillance (AS). METHODS: In all, 647 patients diagnosed with NCCN very low/low risk (VL/LR) or F-IR 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 F-IR 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, F-IR with Decipher low or intermediate score did not associate with significantly higher odds of AP compared to VL/LR. CONCLUSIONS: NCCN risk groups, including F-IR, are highly heterogeneous and should be replaced with multivariable risk-stratification. In particular, incorporating Decipher may be useful for safely expanding the use of AS in this patient population.

Utility of Risk Models in Decision Making After Radical Prostatectomy: Lessons from a Natural History Cohort of Intermediate- and High-Risk Men.

BACKGROUND: Current guidelines suggest adjuvant radiation therapy for men with adverse pathologic features (APFs) at radical prostatectomy (RP). We examine at-risk men treated only with RP until the time of metastasis. OBJECTIVE: To evaluate whether clinicopathologic risk models can help guide postoperative therapeutic decision making. DESIGN, SETTING, AND PARTICIPANTS: Men with National Comprehensive Cancer Network intermediate- or high-risk localized prostate cancer undergoing RP in the prostate-specific antigen (PSA) era were identified (n=3089). Only men with initial undetectable PSA after surgery and who received no therapy prior to metastasis were included. APFs were defined as pT3 disease or positive surgical margins. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Area under the receiver operating characteristic curve (AUC) for time to event data was used to measure the discrimination performance of the risk factors. Cumulative incidence curves were constructed using Fine and Gray competing risks analysis to estimate the risk of biochemical recurrence (BCR) or metastasis, taking censoring and death due to other causes into consideration. RESULTS AND LIMITATIONS: Overall, 43% of the cohort (n=1327) had APFs at RP. Median follow-up for censored patients was 5 yr. Cumulative incidence of metastasis was 6% at 10 yr after RP for all patients. Cumulative incidence of metastasis among men with APFs was 7.5% at 10 yr after RP. Among men with BCR, the incidence of metastasis was 38% 5 yr after BCR. At 10 yr after RP, time-dependent AUC for predicting metastasis by Cancer of the Prostate Risk Assessment Postsurgical or Eggener risk models was 0.81 (95% confidence interval [CI], 0.72-0.97) and 0.78 (95% CI, 0.67-0.97) in the APF population, respectively. At 5 yr after BCR, these values were lower (0.58 [95% CI, 0.50-0.66] and 0.70 [95% CI, 0.63-0.76]) among those who developed BCR. Use of risk model cut points could substantially reduce overtreatment while minimally increasing undertreatment (ie, use of an Eggener cut point of 2.5% for treatment of men with APFs would spare 46% from treatment while only allowing for metastatic events in 1% at 10 yr after RP). CONCLUSIONS: Use of risk models reduces overtreatment and should be a routine part of patient counseling when considering adjuvant therapy. Risk model performance is significantly reduced among men with BCR. PATIENT SUMMARY: Use of current risk models can help guide decision making regarding therapy after surgery and reduce overtreatment.