You have accessJournal of UrologyProstate Cancer: Staging I1 Apr 2016PD42-10 NUCLEAR GRADE PREDICTS PROSTATE CANCER OUTCOMES AMONG RADICAL PROSTATECTOMY PATIENTS Daniel Kim, Lauren Hurwitz, Huai-Ching Kuo, Jennifer Cullen, Sally Elsamanoudi, Yongmei Chen, Inger Rosner, David McLeod, and Isabel Sesterhenn Daniel KimDaniel Kim More articles by this author , Lauren HurwitzLauren Hurwitz More articles by this author , Huai-Ching KuoHuai-Ching Kuo More articles by this author , Jennifer CullenJennifer Cullen More articles by this author , Sally ElsamanoudiSally Elsamanoudi More articles by this author , Yongmei ChenYongmei Chen More articles by this author , Inger RosnerInger Rosner More articles by this author , David McLeodDavid McLeod More articles by this author , and Isabel SesterhennIsabel Sesterhenn More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2016.02.1762AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Nuclear architecture helps in the classification of grading for most malignant tumors; however, nuclear grade (NG) is not currently used as part of the assessment for prostate cancer (PCa). This study evaluated NG as a predictor of PCa outcomes in a large, racially diverse cohort of radical prostatectomy (RP) patients, enrolled in an equal access health care setting. METHODS This retrospective cohort study examined patients enrolled in the Center for Prostate Disease Research (CPDR) multi-center national and biospecimen databases, who were diagnosed with PCa between 1987 and 2013 and underwent RP for treatment of PCa. Donated whole-mount prostate specimens were examined by the Joint Pathology Center (JPC) and classified for NG status, based on the Mostofi/WHO system. Demographic, clinical, pathologic, treatment and outcomes data were obtained as part of ongoing CPDR data collection activities. Unadjusted Kaplan Meier (KM) estimation curves and multivariable Cox Proportional Hazards (PH) analyses were used to evaluate two time-to-event endpoints: biochemical recurrence (BCR) and distant metastasis (dMET). RESULTS Of the 1690 RP patients who met the study criteria, 1579 (93.4%) were assessed for NG. Higher NG was significantly associated with higher D’Amico risk stratum (p<0.0001), worse biopsy Gleason sum (GS) (p<0.0001), worse pathologic GS (p<0.0001), higher cT-Stage (p=0.0356), higher pT stage (p<0.0001), positive margin status (p=0.0002), presence of extra-capsular extension (p<0.0001), and seminal vesicle involvement (p<0.0001). KM curves showed a significant difference in odds of BCR (p<0.0001) and dMET (p<0.0001) with poorer outcomes for highest versus lowest NG (Figure 1). The Cox PH model of time to BCR revealed worse outcomes for highest versus lowest NG category (HR 3 vs. 1=2.20, p=0.0038). Similarly, the Cox PH model for distant metastasis showed worse outcomes for highest versus lowest NG category: (HR 3 vs. 1= 21.39, p=0.0049). CONCLUSIONS There are conflicting data on the utility of NG in predicting PCa outcomes. This study showed that the Mostofi/WHO NG system was useful in predicting worse PCa outcomes for patients with a higher NG. Incorporation of NG into contemporary PCa grading may be useful for improving informed treatment decision-making. © 2016FiguresReferencesRelatedDetails Volume 195Issue 4SApril 2016Page: e991 Advertisement Copyright & Permissions© 2016MetricsAuthor Information Daniel Kim More articles by this author Lauren Hurwitz More articles by this author Huai-Ching Kuo More articles by this author Jennifer Cullen More articles by this author Sally Elsamanoudi More articles by this author Yongmei Chen More articles by this author Inger Rosner More articles by this author David McLeod More articles by this author Isabel Sesterhenn More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...