Development and Validation of a Clinical Prognostic Stage Group System for Nonmetastatic Prostate Cancer Using Disease-Specific Mortality Results From the International Staging Collaboration for Cancer of the Prostate.

Importance: In 2016, the American Joint Committee on Cancer (AJCC) established criteria to evaluate prediction models for staging. No localized prostate cancer models were endorsed by the Precision Medicine Core committee, and 8th edition staging was based on expert consensus. Objective: To develop and validate a pretreatment clinical prognostic stage group system for nonmetastatic prostate cancer. Design, Setting, and Participants: This multinational cohort study included 7 centers from the United States, Canada, and Europe, the Shared Equal Access Regional Cancer Hospital (SEARCH) Veterans Affairs Medical Centers collaborative (5 centers), and the Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE) registry (43 centers) (the STAR-CAP cohort). Patients with cT1-4N0-1M0 prostate adenocarcinoma treated from January 1, 1992, to December 31, 2013 (follow-up completed December 31, 2017). The STAR-CAP cohort was randomly divided into training and validation data sets; statisticians were blinded to the validation data until the model was locked. A Surveillance, Epidemiology, and End Results (SEER) cohort was used as a second validation set. Analysis was performed from January 1, 2018, to November 30, 2019. Exposures: Curative intent radical prostatectomy (RP) or radiotherapy with or without androgen deprivation therapy. Main Outcomes and Measures: Prostate cancer-specific mortality (PCSM). Based on a competing-risk regression model, a points-based Score staging system was developed. Model discrimination (C index), calibration, and overall performance were assessed in the validation cohorts. Results: Of 19 684 patients included in the analysis (median age, 64.0 [interquartile range (IQR), 59.0-70.0] years), 12 421 were treated with RP and 7263 with radiotherapy. Median follow-up was 71.8 (IQR, 34.3-124.3) months; 4078 (20.7%) were followed up for at least 10 years. Age, T category, N category, Gleason grade, pretreatment serum prostate-specific antigen level, and the percentage of positive core biopsy results among biopsies performed were included as variables. In the validation set, predicted 10-year PCSM for the 9 Score groups ranged from 0.3% to 40.0%. The 10-year C index (0.796; 95% CI, 0.760-0.828) exceeded that of the AJCC 8th edition (0.757; 95% CI, 0.719-0.792), which was improved across age, race, and treatment modality and within the SEER validation cohort. The Score system performed similarly to individualized random survival forest and interaction models and outperformed National Comprehensive Cancer Network (NCCN) and Cancer of the Prostate Risk Assessment (CAPRA) risk grouping 3- and 4-tier classification systems (10-year C index for NCCN 3-tier, 0.729; for NCCN 4-tier, 0.746; for Score, 0.794) as well as CAPRA (10-year C index for CAPRA, 0.760; for Score, 0.782). Conclusions and Relevance: Using a large, diverse international cohort treated with standard curative treatment options, a proposed AJCC-compliant clinical prognostic stage group system for prostate cancer has been developed. This system may allow consistency of reporting and interpretation of results and clinical trial design.

Performance of clinicopathologic models in men with high risk localized prostate cancer: impact of a 22-gene genomic classifier.

BACKGROUND: Prostate cancer exhibits biological and clinical heterogeneity even within established clinico-pathologic risk groups. The Decipher genomic classifier (GC) is a validated method to further risk-stratify disease in patients with prostate cancer, but its performance solely within National Comprehensive Cancer Network (NCCN) high-risk disease has not been undertaken to date. METHODS: A multi-institutional retrospective study of 405 men with high-risk prostate cancer who underwent primary treatment with radical prostatectomy (RP) or radiation therapy (RT) with androgen-deprivation therapy (ADT) at 11 centers from 1995 to 2005 was performed. Cox proportional hazards models were used to determine the hazard ratios (HR) for the development of metastatic disease based on clinico-pathologic variables, risk groups, and GC score. The area under the receiver operating characteristic curve (AUC) was determined for regression models without and with the GC score. RESULTS: Over a median follow-up of 82 months, 104 patients (26%) developed metastatic disease. On univariable analysis, increasing GC score was significantly associated with metastatic disease ([HR]: 1.34 per 0.1 unit increase, 95% confidence interval [CI]: 1.19-1.50, p < 0.001), while age, serum PSA, biopsy GG, and clinical T-stage were not (all p > 0.05). On multivariable analysis, GC score (HR: 1.33 per 0.1 unit increase, 95% CI: 1.19-1.48, p < 0.001) and GC high-risk (vs low-risk, HR: 2.95, 95% CI: 1.79-4.87, p < 0.001) were significantly associated with metastasis. The addition of GC score to regression models based on NCCN risk group improved model AUC from 0.46 to 0.67, and CAPRA from 0.59 to 0.71. CONCLUSIONS: Among men with high-risk prostate cancer, conventional clinico-pathologic data had poor discrimination to risk stratify development of metastatic disease. GC score was a significant and independent predictor of metastasis and may help identify men best suited for treatment intensification/de-escalation.

Bringing Prostate Cancer Germline Genetics into Clinical Practice.

PURPOSE: Until recently the role of germline genetics in prostate cancer care was not well defined. While important questions remain, we reviewed the current understanding of germline genetic alterations related to prostate cancer. We discuss the clinical implications for genetic counseling, genetic testing, early detection and treatment in men with these mutations. MATERIALS AND METHODS: We searched PubMed® for English language articles published since 2001 with the key words "germline mutations," "BRCA," "family history" or "prostate cancer genetics." We also used relevant data from websites, including the Centers for Medicare and Medicaid Services, National Comprehensive Cancer Network®, Bureau of Labor Statistics and National Society of Genetic Counselors websites. RESULTS: A number of germline mutations in DNA damage repair genes ( BRCA1, BRCA2, CHEK2, ATM and PALB2) and in DNA mismatch repair genes ( MLH1, MSH2, MSH6 and PMS2) can drive the development of prostate cancer. Careful genetic counseling coupled with multipanel gene testing can help identify men with these mutations and provide enhanced understanding of the disease risk. Cascade testing of family members can then have an impact extending well beyond the index patient. In men with a pathogenic germline mutation the optimal early detection paradigm is not well defined. Data from the IMPACT study ( ClinicalTrials.gov NCT00261456) that the cancer detection rate is substantially elevated in BRCA1 and BRCA2 carriers at prostate specific antigen greater than 3 ng/ml has helped establish the importance of close prostate specific antigen screening in these men. Additionally, BRCA2 and likely other DNA damage repair mutations are associated with aggressive disease, although it is not yet clear how this impacts localized disease management. However, there is strong evidence that patients with metastatic, castration resistant prostate cancer who have DNA damage repair defects respond positively to targeting PARP enzymes. In many cancers there is also evidence that patients with an increased tumor mutational burden, such as in Lynch syndrome, are particularly sensitive to immune checkpoint inhibitors. CONCLUSIONS: Emerging evidence supports the implementation of germline genetic counseling and testing as a key component of prostate cancer management. Further research is needed to elucidate the clinical significance of lesser known germline mutations and develop optimal screening, early detection and treatment paradigms in this patient population.