MP28-01 A 17-GENE PANEL FOR PREDICTION OF ADVERSE PATHOLOGY AT RADICAL PROSTATECTOMY: PROSPECTIVE VALIDATION

You have accessJournal of UrologyProstate Cancer: Markers I1 Apr 2017MP28-01 A 17-GENE PANEL FOR PREDICTION OF ADVERSE PATHOLOGY AT RADICAL PROSTATECTOMY: PROSPECTIVE VALIDATION Scott Eggener, Tim Richardson, Steven Rosenberg, Evan Goldfischer, Ruixiao Lu, Allan Shindel, John Bennett, Lawrence Karsh, Howard Korman, Phillip Febbo, and Bela Denes Scott EggenerScott Eggener More articles by this author , Tim RichardsonTim Richardson More articles by this author , Steven RosenbergSteven Rosenberg More articles by this author , Evan GoldfischerEvan Goldfischer More articles by this author , Ruixiao LuRuixiao Lu More articles by this author , Allan ShindelAllan Shindel More articles by this author , John BennettJohn Bennett More articles by this author , Lawrence KarshLawrence Karsh More articles by this author , Howard KormanHoward Korman More articles by this author , Phillip FebboPhillip Febbo More articles by this author , and Bela DenesBela Denes More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.814AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Adverse pathology (AP, defined as pathological Gleason grade > 4+3 and/or >pT3) is a strong predictor of biochemical recurrence, metastasis, and cancer specific mortality in men with prostate cancer (PCa). A 17 gene tissue-based RTPCR assay (Oncotype Dx® Genomic Prostate Score™, GPS) has been validated as a predictor of AP in multiple retrospective cohorts. In this study, we aim to prospectively validate GPS as a predictor of AP in men with clinically low-risk PCa treated with radical prostatectomy (RP). METHODS A pre-specified analysis from a 1200-patient prospective study was performed on patients who elected RP as initial PCa management. The primary endpoint was AP. Descriptive statistics are reported on demographic and clino-pathological characteristics. Binary logistic regression was performed to determine the association between GPS and AP. The odds ratio (OR) per 20 GPS units and 95% confidence interval (CI) were calculated. All analyses were conducted using SAS 9.4. RESULTS Of 1200 patients enrolled from 21 sites in the study, RP was selected as initial management by 150 patients; 122 (81%) had complete surgical pathology data available. Median age was 63 yrs. (range 50-79), with 38% > 65 yrs. In this cohort, 11 (9%), 39 (32%), and 72 (59%) had NCCN Very Low-, Low-, and Intermediate-Risk disease. Biological risk (GPS+NCCN) differed from NCCN risk in 28 cases (23%). At surgery, 41 (34%) of patients had AP. Among NCCN VL, Low-Risk and Intermediate-Risk men, 1 (10%), 11 (28%), and 29 (40%) had AP at RP. Combining GPS and NCCN led to redistribution of VL, Low-Risk, and Intermediate-Risk groups and modified rates of AP at RP (Table 1). GPS was a significant predictor of AP (OR per 20 GPS units: 2.4; 95% CI: [1.3, 4.4]; p= 0.004) and remained significant after adjusting for NCCN (OR per 20 units: 2.2; 95% CI: [1.2-4.1]; p=0.01). CONCLUSIONS We report the first prospective validation of a biopsy-based genomic marker in prostate cancer. GPS is a strong predictor of AP in contemporary PCa patients. Patients with GPS+NCCN intermediate-risk categorization have twice the rate of AP as those with GPS+NCCN very low/low risk. GPS refines risk stratification and may help inform decision-making for patients with clinically low risk PCa. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e337-e338 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Scott Eggener More articles by this author Tim Richardson More articles by this author Steven Rosenberg More articles by this author Evan Goldfischer More articles by this author Ruixiao Lu More articles by this author Allan Shindel More articles by this author John Bennett More articles by this author Lawrence Karsh More articles by this author Howard Korman More articles by this author Phillip Febbo More articles by this author Bela Denes More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...