Mp52-04 Nomogram Predicting Locally Advanced Prostate Cancer in Patients With Clinically Organ-Confined Disease Who Underwent Robot-Assisted Radical Prostatectomy: A Retrospective Multicenter Cohort Study in Japan (The Msug94 Group)

You have accessJournal of UrologyProstate Cancer: Localized: Surgical Therapy II (MP52)1 May 2024MP52-04 NOMOGRAM PREDICTING LOCALLY ADVANCED PROSTATE CANCER IN PATIENTS WITH CLINICALLY ORGAN-CONFINED DISEASE WHO UNDERWENT ROBOT-ASSISTED RADICAL PROSTATECTOMY: A RETROSPECTIVE MULTICENTER COHORT STUDY IN JAPAN (THE MSUG94 GROUP) Makoto Kawase, Takayuki Goto, Shin Ebara, Tomoyuki Tatenuma, Takeshi Sasaki, Takuma Ishihara, Yoshinori Ikehata, Akinori Nakayama, Masahiro Toide, Tatsuaki Yoneda, Kazushige Sakaguchi, Jun Teishima, Takashi Kobayashi, Kazuhide Makiyama, Takahiro Inoue, Hiroshi Kitamura, Kazutaka Saito, Fumitaka Koga, Shinji Urakami, and Takuya Koie Makoto KawaseMakoto Kawase , Takayuki GotoTakayuki Goto , Shin EbaraShin Ebara , Tomoyuki TatenumaTomoyuki Tatenuma , Takeshi SasakiTakeshi Sasaki , Takuma IshiharaTakuma Ishihara , Yoshinori IkehataYoshinori Ikehata , Akinori NakayamaAkinori Nakayama , Masahiro ToideMasahiro Toide , Tatsuaki YonedaTatsuaki Yoneda , Kazushige SakaguchiKazushige Sakaguchi , Jun TeishimaJun Teishima , Takashi KobayashiTakashi Kobayashi , Kazuhide MakiyamaKazuhide Makiyama , Takahiro InoueTakahiro Inoue , Hiroshi KitamuraHiroshi Kitamura , Kazutaka SaitoKazutaka Saito , Fumitaka KogaFumitaka Koga , Shinji UrakamiShinji Urakami , and Takuya KoieTakuya Koie View All Author Informationhttps://doi.org/10.1097/01.JU.0001008864.84854.b7.04AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: We created a clinically applicable nomogram to predict locally advanced prostate cancer using preoperative parameters and performed external validation using an external independent validation cohort. METHODS: From a retrospective multicenter cohort study of 3622 Japanese patients with prostate cancer who underwent robot-assisted radical prostatectomy at 10 institutions, the patients were divided into two groups (the MSUG cohort and the validation cohort). Locally advanced prostate cancer was defined as pathological T stage ≥3a. A multivariable logistic regression model was used to identify factors strongly associated with locally advanced prostate cancer. Bootstrap-area under the curve was calculated to assess the internal validity of the prediction model. A nomogram was created as a practical application of the prediction model, and a web application was released to predict the probability of locally advanced prostate cancer. RESULTS: A total of 2530 and 427 patients in the MSUG and validation cohorts, respectively, met the criteria for this study. On multivariable analysis, initial prostate-specific antigen, prostate volume, number of cancer-positive and negative biopsy cores, biopsy grade group, and clinical T stage diagnosed by MRI were independent predictors of locally advanced prostate cancer. The nomogram predicting locally advanced prostate cancer was demonstrated (area under the curve 0.72). Using a nomogram cutoff of 0.26, 464 of 1162 patients (39.9%) could be correctly diagnosed with pT3, and 2311 of 2524 patients (91.6%) could avoid underdiagnosis. CONCLUSIONS: We developed a clinically applicable nomogram with external validation to predict the probability of locally advanced prostate cancer in patients undergoing robot-assisted radical prostatectomy. Download PPTDownload PPT Source of Funding: None © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e852 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Makoto Kawase More articles by this author Takayuki Goto More articles by this author Shin Ebara More articles by this author Tomoyuki Tatenuma More articles by this author Takeshi Sasaki More articles by this author Takuma Ishihara More articles by this author Yoshinori Ikehata More articles by this author Akinori Nakayama More articles by this author Masahiro Toide More articles by this author Tatsuaki Yoneda More articles by this author Kazushige Sakaguchi More articles by this author Jun Teishima More articles by this author Takashi Kobayashi More articles by this author Kazuhide Makiyama More articles by this author Takahiro Inoue More articles by this author Hiroshi Kitamura More articles by this author Kazutaka Saito More articles by this author Fumitaka Koga More articles by this author Shinji Urakami More articles by this author Takuya Koie More articles by this author Expand All Advertisement PDF downloadLoading ...