MP33-16 PATIENT SELECTION FOR MULTIPARAMETRIC PROSTATE MRI: IDENTIFYING CLINICAL PREDICTORS FOR ACTIONABLE PIRADS LESIONS ON IMAGING

You have accessJournal of UrologyProstate Cancer: Detection & Screening III1 Apr 2017MP33-16 PATIENT SELECTION FOR MULTIPARAMETRIC PROSTATE MRI: IDENTIFYING CLINICAL PREDICTORS FOR ACTIONABLE PIRADS LESIONS ON IMAGING Vinay Patel, Paras Shah, Daniel Moreira, Arvin George, Geoffrey Gaunay, Jose Vilaro, Manish Vira, and Simon Hall Vinay PatelVinay Patel More articles by this author , Paras ShahParas Shah More articles by this author , Daniel MoreiraDaniel Moreira More articles by this author , Arvin GeorgeArvin George More articles by this author , Geoffrey GaunayGeoffrey Gaunay More articles by this author , Jose VilaroJose Vilaro More articles by this author , Manish ViraManish Vira More articles by this author , and Simon HallSimon Hall More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.1012AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Despite a favorable sensitivity profile for high grade and large volume disease, indiscriminate use of multiparametric prostate MRI (mpMRI) adds prohibitory cost with uncertain benefit. Our study aims to identify clinical predictors of suspicious lesions on imaging to improve patient selection for mpMRI. METHODS We performed a retrospective review of 839 patients undergoing mpMRI for elevated PSA between March 2012 and October 2014. mpMRI was performed on 3T magnet with pelvic phased array and endorectal coils. Baseline clinical and biochemical patient characteristics were analyzed with univariable and multivariable logistic regression to identify predictors of a positive MRI (PIRADS score 3-5). Using these variables, we constructed a nomogram to predict a positive MRI. RESULTS Among 839 patients without prior history of prostate cancer, MRI was positive in 272 (32.4%) patients. Increasing age (P=0.001), abnormal digital rectal exam (P=0.002), prior negative biopsy (P<0.001), increasing pre-MRI PSA (P<0.001), lower prostate volume (P<0.001), and PSA velocity (P=0.044) were significant predictors of a positive MRI in univariable analysis. On multivariable analysis, age (P=0.048), positive digital rectal exam (P=0.017), prior negative biopsy (P=0.061), pre-MRI PSA (P<0.001), and prostate volume (P<0.001) remained independent predictors (Table). A nomogram predicting probability of a positive mpMRI based on these variables demonstrated good calibration and a concordance index of 0.7 (Figure). CONCLUSIONS Many of the clinical variables traditionally associated with increased PCa risk are also independently associated with a positive mpMRI. A nomogram including these variables can help identify men who are more likely to benefit from a prostate mpMRI while reducing cost by limiting the number of negative studies. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e423 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Vinay Patel More articles by this author Paras Shah More articles by this author Daniel Moreira More articles by this author Arvin George More articles by this author Geoffrey Gaunay More articles by this author Jose Vilaro More articles by this author Manish Vira More articles by this author Simon Hall More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...