MP2-18 PREOPERATIVE SELECTION ALGORITHM FOR ELIGIBLE NEOADJUVANT CHEMOTHERAPY PATIENTS IN UPPER TRACT UROTHELIAL CARCINOMAS (2015)

You have accessJournal of UrologyBladder Cancer: Upper Tract TCC I1 Apr 2015MP2-18 PREOPERATIVE SELECTION ALGORITHM FOR ELIGIBLE NEOADJUVANT CHEMOTHERAPY PATIENTS IN UPPER TRACT UROTHELIAL CARCINOMAS Shingo Moriyama, Kazutaka Saito, Junichiro Ishioka, Masaya Ito, Manabu Tatokoro, Soichiro Yoshida, Minato Yokoyama, Yoh Matsuoka, Noboru Numao, Yasuhisa Fujii, and Kazunori Kihara Shingo MoriyamaShingo Moriyama More articles by this author , Kazutaka SaitoKazutaka Saito More articles by this author , Junichiro IshiokaJunichiro Ishioka More articles by this author , Masaya ItoMasaya Ito More articles by this author , Manabu TatokoroManabu Tatokoro More articles by this author , Soichiro YoshidaSoichiro Yoshida More articles by this author , Minato YokoyamaMinato Yokoyama More articles by this author , Yoh MatsuokaYoh Matsuoka More articles by this author , Noboru NumaoNoboru Numao More articles by this author , Yasuhisa FujiiYasuhisa Fujii More articles by this author , and Kazunori KiharaKazunori Kihara More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.141AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES There is insufficient evidence regarding the efficacy of perioperative systemic chemotherapies for upper tract urothelial carcinoma (UTUC). Neoadjuvant chemotherapy (NACT) might be advantageous, because the loss of renal function after radical nephroureterectomy (RNU) renders a patient ineligible for cisplatin-based chemotherapy. We aimed to create a selection algorithm for NACT using prediction models of adverse pathology and postoperative renal dysfunction based on preoperative parameters in UTUC. METHODS A total of 500 patients who received RNU for non-metastatic UTUC between 1995 and 2013 were enrolled in this study. We defined eligible NACT patients as those who had unfavorable pathology (positive lymph node or pT3/4 with positive lymphovascular invasion) and postoperative-deteriorated renal function (estimated glomerular filtration rate [eGFR] < 60 ml/min/1.73m2). We developed a selection algorithm for NACT-eligible patients with a two-step analysis using scoring models for pathological outcomes and renal function. RESULTS As the first step, we developed a pathological risk scoring model consisting of cT ≥ 2, tumor located at the ureter, C reactive protein ≥ 0.8, body mass index (BMI) < 20, absence of bladder tumor and non-smoker. This model showed a predictive ability by area under the curve (AUC) of 0.71. Of 500 patients, 303 were identified as having a high risk of unfavorable pathological outcomes. As the second step, after the exclusion of 111 patients with preoperative renal dysfunction, a scoring model predicting postoperative renal dysfunction was developed in the remaining 192 patients. This model consisted of preoperative eGFR < 90, hydronephrosis grade ≤ 1, tumor located in the renal pelvis, age > 65 and BMI > 22 (AUC 0.75). One hundred and thirty-four patients were predicted to have a high risk of postoperative renal dysfunction, and NACT was recommended for those patients. In selecting eligible NACT patients, this algorithm has a prediction ability with 76% (25/33) sensitivity and 77% (358/467) specificity. CONCLUSIONS We developed a preoperative selection algorithm for the eligible NACT patients in UTUC. This algorithm might contribute to effective decision making in regard to providing NACT. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e17-e18 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.Metrics Author Information Shingo Moriyama More articles by this author Kazutaka Saito More articles by this author Junichiro Ishioka More articles by this author Masaya Ito More articles by this author Manabu Tatokoro More articles by this author Soichiro Yoshida More articles by this author Minato Yokoyama More articles by this author Yoh Matsuoka More articles by this author Noboru Numao More articles by this author Yasuhisa Fujii More articles by this author Kazunori Kihara More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...