Mp51-03 Preoperative or Intraoperative Renal Biopsy Increases the Accuracy in Predicting Lymph Node Invasion in Patients With Renal Cell Carcinoma

You have accessJournal of UrologyKidney Cancer: Epidemiology & Evaluation/Staging/Surveillance II (MP51)1 May 2024MP51-03 PREOPERATIVE OR INTRAOPERATIVE RENAL BIOPSY INCREASES THE ACCURACY IN PREDICTING LYMPH NODE INVASION IN PATIENTS WITH RENAL CELL CARCINOMA Federico Belladelli, Chiara Re, Francesco Cei, Giacomo Musso, Giuseppe Rosiello, Daniele Cignoli, Daniela Canibus, Francesco Fiorio, Roberto Bertini, Andrea Salonia, Francesco De Cobelli, Giorgio Brembilla, Morgan Rouprêt, Antonio Esposito, Anna Palmisano, Ciro Piccolo, Marco Gambirasio, Roberta Lucianò, Nazario Tenace, Alberto Briganti, Francesco Montorsi, Alessandro Larcher, and Umberto Capitanio Federico BelladelliFederico Belladelli , Chiara ReChiara Re , Francesco CeiFrancesco Cei , Giacomo MussoGiacomo Musso , Giuseppe RosielloGiuseppe Rosiello , Daniele CignoliDaniele Cignoli , Daniela CanibusDaniela Canibus , Francesco FiorioFrancesco Fiorio , Roberto BertiniRoberto Bertini , Andrea SaloniaAndrea Salonia , Francesco De CobelliFrancesco De Cobelli , Giorgio BrembillaGiorgio Brembilla , Morgan RouprêtMorgan Rouprêt , Antonio EspositoAntonio Esposito , Anna PalmisanoAnna Palmisano , Ciro PiccoloCiro Piccolo , Marco GambirasioMarco Gambirasio , Roberta LucianòRoberta Lucianò , Nazario TenaceNazario Tenace , Alberto BrigantiAlberto Briganti , Francesco MontorsiFrancesco Montorsi , Alessandro LarcherAlessandro Larcher , and Umberto CapitanioUmberto Capitanio View All Author Informationhttps://doi.org/10.1097/01.JU.0001009492.49624.4b.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: There is still debate regarding the role of lymph node dissection (LND) in patients with renal cell carcinoma (RCC). Specifically, it is still unclear which patients may benefit from LND and how information from renal mass biopsies may improve clinical decision-making. We aimed to identify predictors of lymph node invasion (LNI) by using clinical variables only (preoperative characteristics) and by adding the pathological information which can be derived during surgery relying on biopsy and intraoperative pathology. METHODS: Within a prospectively maintained database, patients with renal masses who underwent surgery with LND at a single tertiary center were identified. The Boruta machine learning algorithm was employed to select the relevant variables of interest among different pre-surgical clinical variables (age, sex, BMI, presence of comorbidities, smoke, presence of symptoms, lesion number, clinical size, cT, cN, lesion side and position, preoperative haemoglobin, platelets, and creatinine). Therefore, a predictive nomogram was derived from a multivariable logistic model developed to predict LNI at final pathology. Final pathology histological data was then used as a simulation for pre-operative biopsy data. ROC curve was used to test the accuracy of the prediction for each risk group. Decision Curve Analysis (DCA) was used to compare the clinical only vs. clinical + biopsy model. RESULTS: Overall, 3,626 patients underwent either PN or RN for RCC. Of these, 31% (n=1,114) underwent LND and 103 (3%) showed pathologically confirmed LNI. Boruta identified clinical lesion size, cT, cN, preoperative hemoglobin, platelets, and creatinine as variable of interest. The logistic model-derived nomogram showed an accuracy of 0.82 when predicting LNI at final pathology. At simulation of biopsy and intraoperative pathology, the inclusion of histology and grading in the predictive model increased the accuracy up to 0.88. At DCA, the clinical+biobsy model provided a higher net benefit when compared to the clinical-only model (Figure 1). CONCLUSIONS: Information which can be retrieved by a preoperative or an intraoperative renal biopsy can be used to accurately predict the risk of LNI. Download PPT Source of Funding: None © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e842 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Federico Belladelli More articles by this author Chiara Re More articles by this author Francesco Cei More articles by this author Giacomo Musso More articles by this author Giuseppe Rosiello More articles by this author Daniele Cignoli More articles by this author Daniela Canibus More articles by this author Francesco Fiorio More articles by this author Roberto Bertini More articles by this author Andrea Salonia More articles by this author Francesco De Cobelli More articles by this author Giorgio Brembilla More articles by this author Morgan Rouprêt More articles by this author Antonio Esposito More articles by this author Anna Palmisano More articles by this author Ciro Piccolo More articles by this author Marco Gambirasio More articles by this author Roberta Lucianò More articles by this author Nazario Tenace More articles by this author Alberto Briganti More articles by this author Francesco Montorsi More articles by this author Alessandro Larcher More articles by this author Umberto Capitanio More articles by this author Expand All Advertisement PDF downloadLoading ...