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.

Validation of the Decipher Test for predicting adverse pathology in candidates for prostate cancer active surveillance.

ABSTACT: BACKGROUND: Many 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. METHODS: Decipher 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). RESULTS: Decipher 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). CONCLUSION: Decipher 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.

Development of a Patient-Based Model for Estimating Operative Times for Robot-Assisted Radical Prostatectomy.

OBJECTIVES: To develop a methodology for predicting operative times for robot-assisted radical prostatectomy (RARP) using preoperative patient, disease, procedural, and surgeon variables to facilitate operating room (OR) scheduling. METHODS: The model included preoperative metrics: body mass index (BMI), American Society of Anesthesiologists score, clinical stage, National Comprehensive Cancer Network risk, prostate weight, nerve-sparing status, extent and laterality of lymph node dissection, and operating surgeon (six surgeons were included in the study). A binary decision tree was fit using a conditional inference tree method to predict operative times. The variables most associated with operative time were determined using permutation tests. Data were split at the value of the variable that results in the largest difference in mean for surgical time across the split. This process was repeated recursively on the resultant data. RESULTS: A total of 1709 RARPs were included. The variable most strongly associated with operative time was the surgeon (surgeons 2 and 4-102 minutes shorter than surgeons 1, 3, 5, and 6, p < 0.001). Among surgeons 2 and 4, BMI had the strongest association with surgical time (p < 0.001). Among patients operated by surgeons 1, 3, 5, and 6, RARP time was again most strongly associated with the surgeon performing RARP. Surgeons 1, 3, and 6 were on average 76 minutes faster than surgeon 5 (p < 0.001). The regression tree output in the form of box plots showed operative time median and ranges according to patient, disease, procedural, and surgeon metrics. CONCLUSION: We developed a methodology that can predict operative times for RARP based on patient, disease and surgeon variables. This methodology can be utilized for quality control, facilitate OR scheduling, and maximize OR efficiency.

Development of a Nationally Representative Coordinated Registry Network for Prostate Ablation Technologies.

PURPOSE: The accumulation of data through a prospective, multicenter coordinated registry network is a practical way to gather real world evidence on the performance of novel prostate ablation technologies. Urological oncologists, targeted biopsy experts, industry representatives and representatives of the FDA (Food and Drug Administration) convened to discuss the role, feasibility and important data elements of a coordinated registry network to assess new and existing prostate ablation technologies. MATERIALS AND METHODS: A multiround Delphi consensus approach was performed which included the opinion of 15 expert urologists, representatives of the FDA and leadership from high intensity focused ultrasound device manufacturers. Stakeholders provided input in 3 consecutive rounds with conference calls following each round to obtain consensus on remaining items. Participants agreed that these elements initially developed for high intensity focused ultrasound are compatible with other prostate ablation technologies. Coordinated registry network elements were reviewed and supplemented with data elements from the FDA common study metrics. RESULTS: The working group reached consensus on capturing specific patient demographics, treatment details, oncologic outcomes, functional outcomes and complications. Validated health related quality of life questionnaires were selected to capture patient reported outcomes, including the IIEF-5 (International Index of Erectile Function-5), the I-PSS (International Prostate Symptom Score), the EPIC-26 (Expanded Prostate Cancer Index Composite-26) and the MSHQ-EjD (Male Sexual Health Questionnaire for Ejaculatory Dysfunction). Group consensus was to obtain followup multiparametric magnetic resonance imaging and prostate biopsy approximately 12 months after ablation with additional imaging or biopsy performed as clinically indicated. CONCLUSIONS: A national prostate ablation coordinated registry network brings forth vital practice pattern and outcomes data for this emerging treatment paradigm in the United States. Our multiple stakeholder consensus identifies critical elements to evaluate new and existing energy modalities and devices.

Practice trends in the management of prostate disease by family practice physicians and general internists: an internet-based survey.

OBJECTIVES: To assess, using an Internet-based survey, the practice patterns of primary care physicians in the management of prostate disease and to assess the differences between family physicians and general internists. Prostate cancer and benign prostatic hyperplasia are common in the elderly population. The optimal management of these diseases is debated. METHODS: An 18-item survey was designed and administered on an Internet website. Members of the Society of General Internal Medicine and members of the Illinois, North Carolina, and New York chapters of the Academy of Family Physicians were surveyed. RESULTS: A total of 354 responses were obtained from 381 primary care physicians who viewed the survey web page. For patients 50 years old and older, 75% of physicians (87% of family physicians and 69% of general internists; P <0.001) recommended annual prostate cancer screening with digital rectal examination and 49% (67% of family physicians and 40% of general internists; P <0.001) recommended annual prostate cancer screening with prostate-specific antigen measurement. For patients diagnosed with prostate cancer, 76% of the primary care physicians estimated that less than one half of their patients are seen by a radiation oncologist. For the treatment and/or prevention of prostate cancer, 62% of physicians surveyed (76% of family physicians and 55% of general internists; P <0.001) believe there is a potential role for alternative herbal and nutritional therapies. CONCLUSIONS: Compared with general internists, family physicians are more likely to screen for prostate cancer and are more likely to believe there is a role for alternative therapies for prostate cancer.