MP53-12 MODERN MULTI-PARAMETRIC PROSTATE MRI (MPMRI) INDEPENDENTLY PREDICTS PATHOLOGY T3 DISEASE AT THE TIME OF RADICAL PROSTATECTOMY

You have accessJournal of UrologyProstate Cancer: Staging I1 Apr 2018MP53-12 MODERN MULTI-PARAMETRIC PROSTATE MRI (MPMRI) INDEPENDENTLY PREDICTS PATHOLOGY T3 DISEASE AT THE TIME OF RADICAL PROSTATECTOMY Erica Jessen, Seungjun Ahn, Sandeep Gurram, Ardeshir Rastinehad, Lee Richstone, Michael Schwartz, Louis Kavoussi, Byron Gaing, Robert Villani, Eran Ben-Levi, Simon Hall, and Manish Vira Erica JessenErica Jessen More articles by this author , Seungjun AhnSeungjun Ahn More articles by this author , Sandeep GurramSandeep Gurram More articles by this author , Ardeshir RastinehadArdeshir Rastinehad More articles by this author , Lee RichstoneLee Richstone More articles by this author , Michael SchwartzMichael Schwartz More articles by this author , Louis KavoussiLouis Kavoussi More articles by this author , Byron GaingByron Gaing More articles by this author , Robert VillaniRobert Villani More articles by this author , Eran Ben-LeviEran Ben-Levi More articles by this author , Simon HallSimon Hall More articles by this author , and Manish ViraManish Vira More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.1683AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Current predictive models for prostate cancer (PC) pathologic staging do not incorporate prostate imaging to predict non organ confined disease (≥pT3). The most commonly used variables in these models include serum PSA, clinical stage, Gleason score and biopsy (bx) characteristics. Our objective was to incorporate mpMRI parameters along with known clinical variables into a model to predict ≥pT3 disease at the time of RP. METHODS A retrospective analysis of all patients between 2012 and 2017 who underwent a radical prostatectomy (RP) and a preoperative mpMRI was performed. Patient data were recorded including serum PSA, DRE, bx Gleason score, number of positive bx cores, maximum tumor core length, maximum percent core involvement, and pathologic extent of tumor at prostatectomy. MRI parameters recorded included overall suspicion score, lesion size, and status of capsular involvement (none, abutting, bulging, and extension). A crude comparison of pathologic staging for each separate predictor variables was performed using univariate ordinal logistic regression. Factors that were significantly associated with pathologic staging were entered into the multivariable model. The outcome (pathologic staging) was analyzed using multivariable ordinal logistic regression. The proportional odds assumption was checked for all models. Results were considered statistically significant when p < 0.05. RESULTS A total of 221 patients with mean age of 61.2 (SD=6.7) years were included in the analysis. The multivariable ordinal logistic regression analysis showed that serum PSA (p < 0.003), overall suspicion score (p<0.037), extension on mpMRI (p<0.005) were significantly associated with pathologic staging, given all other factors in model fixed. Moreover, patients with presence of extension on an MRI had 6.53 times greater cumulative odds of worse pathologic stage compared to patients without extension (p < 0.002). Interestingly, on multivariable analysis, the main effects of maximum core tumor length (p < 0.101), maximum tumor percent involvement of core (p < 0.578), and Gleason prognostic grade group (p < 0.066) were not significantly associated with pathologic staging. CONCLUSIONS The current study shows that mpMRI provides significant information towards pathologic staging of PC independent of PSA, Gleason score and clinical staging. The results suggest that mpMRI should certainly be incorporated into existing nomogram prediction tools and perhaps become a standard imaging modality prior to RP. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e708 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Erica Jessen More articles by this author Seungjun Ahn More articles by this author Sandeep Gurram More articles by this author Ardeshir Rastinehad More articles by this author Lee Richstone More articles by this author Michael Schwartz More articles by this author Louis Kavoussi More articles by this author Byron Gaing More articles by this author Robert Villani More articles by this author Eran Ben-Levi More articles by this author Simon Hall More articles by this author Manish Vira More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...