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MP03-09 MRI-BASED NOMOGRAM PREDICTING THE PROBABILITY OF DIAGNOSING A CLINICALLY SIGNIFICANT PROSTATE CANCER WITH MRI-US FUSION BIOPSY

2017; Lippincott Williams & Wilkins; Volume: 197; Issue: 4S Linguagem: Inglês

10.1016/j.juro.2017.02.126

1527-3792

Giuseppe Simone, Rocco Papalia, Emanuela Altobelli, Alessandro Giacobbe, Luigi Benecchi, Gabriele Tuderti, Leonardo Misuraca, Salvatore Guaglianone, Devis Collura, Giovanni Muto, Michele Gallucci, Mariaconsiglia Ferriero,

Prostate Cancer Treatment and Research

You have accessJournal of UrologyProstate Cancer: Detection & Screening I1 Apr 2017MP03-09 MRI-BASED NOMOGRAM PREDICTING THE PROBABILITY OF DIAGNOSING A CLINICALLY SIGNIFICANT PROSTATE CANCER WITH MRI-US FUSION BIOPSY Giuseppe Simone, Rocco Papalia, Emanuela Altobelli, Alessandro Giacobbe, Luigi Benecchi, Gabriele Tuderti, Leonardo Misuraca, Salvatore Guaglianone, Devis Collura, Giovanni Muto, Michele Gallucci, and Mariaconsiglia Ferriero Giuseppe SimoneGiuseppe Simone More articles by this author , Rocco PapaliaRocco Papalia More articles by this author , Emanuela AltobelliEmanuela Altobelli More articles by this author , Alessandro GiacobbeAlessandro Giacobbe More articles by this author , Luigi BenecchiLuigi Benecchi More articles by this author , Gabriele TudertiGabriele Tuderti More articles by this author , Leonardo MisuracaLeonardo Misuraca More articles by this author , Salvatore GuaglianoneSalvatore Guaglianone More articles by this author , Devis ColluraDevis Collura More articles by this author , Giovanni MutoGiovanni Muto More articles by this author , Michele GallucciMichele Gallucci More articles by this author , and Mariaconsiglia FerrieroMariaconsiglia Ferriero More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.126AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Identifying clinically significant prostate cancers is the main objective of prostate cancer diagnosis. The aim of this study was to develop, to internally validate and to calibrate a nomogram to predict the probability of detecting a clinically significant prostate cancer. METHODS Prospectively collected data from 3 tertiary referral center series of 478 consecutive patients who underwent MRI-US fusion biopsy using the UroStation (Koelis, France) were used to build the nomogram. A logistic regression model is created to identify predictors of PCa diagnosis with MRI-US fusion biopsy. Predictive accuracy was quantified using the concordance index (CI). Internal validation with 200 bootstrap resampling and calibration plot were performed. RESULTS Mean age was 66.3 yrs (± 7.98) and mean PSA levels were 9.8 ng/mL (± 7.98). The overall PCa detection rate was 57.4%. Age, PSA serum levels, PIRADS score at MRI report, number of targeted and number of systematic cores taken were included in the model (Figure 1). Predictive accuracy was 0.81. On internal validation the CI was 0.81 and predicted probability was well calibrated (Figure 2).Limitations include the lack of external validation and the absence of patients with races different by Caucasian in the development cohort. CONCLUSIONS Predicting the risk of a clinically significant PCa is the goal of physicians. This nomogram provides a high accuracy in predicting the probability of diagnosing a clinically significant PCa with MRI-US fusion biopsy. The ease to use makes this nomogram a clinical tool for both patients and physicians. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e22-e23 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Giuseppe Simone More articles by this author Rocco Papalia More articles by this author Emanuela Altobelli More articles by this author Alessandro Giacobbe More articles by this author Luigi Benecchi More articles by this author Gabriele Tuderti More articles by this author Leonardo Misuraca More articles by this author Salvatore Guaglianone More articles by this author Devis Collura More articles by this author Giovanni Muto More articles by this author Michele Gallucci More articles by this author Mariaconsiglia Ferriero More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...