You have accessJournal of UrologyCME1 Apr 2023MP78-10 IMPROVING PREDICTIVE UTILITY OF URETHRAL STRICTURE CLASSIFICATION SYSTEMS BASED ON SURVIVAL ANALYSIS OF STRICTURE-SPECIFIC VARIABLES Keith Rourke, Subash Subramanian, and Nathan Hoy Keith RourkeKeith Rourke More articles by this author , Subash SubramanianSubash Subramanian More articles by this author , and Nathan HoyNathan Hoy More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003355.10AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Urethroplasty is generally regarded as the most effective treatment of urethral stricture. However, recurrences and complications can occur even in the most skilled hands and reliably predicting these outcomes remains elusive. Several existing classification systems (U-Score and LSE) exist but remain largely unvalidated. The purpose of this study is to examine stricture-specific factors associated with recurrence after anterior urethroplasty in order to better refine existing classification systems. METHODS: A retrospective review was performed of men undergoing anterior urethroplasty at a single center from 2003-2021. Stricture-specific variables of location, etiology, length, number, prior urethroplasty and previous endoscopic treatment were identified. Additionally, U Scores (US) and LSE Scores were calculated. Success was defined as easy passage of a flexible cystoscope at routine follow-up with no change in urinary function thereafter. Complications were defined as a Clavien >1 complication during the 90-day perioperative time period. Associations between clinical variables and stricture recurrence were evaluated using univariable and multivariable Cox regression analysis. Variables independently associated with stricture recurrence were sub-stratified using Kaplan-Meier analysis and arranged into a survival-analysis based classification system. Receiver operator characteristic (ROC) analysis was performed on U-Score (US), LSE and refined classification system. RESULTS: 1573 patients underwent anterior urethroplasty over the study period with a median patient age of 47 years (IQR 34-59) and stricture length of 4 cm (IQR 3-6). Urethroplasty success was 92.0% (1447) at a median follow-up of 90 months. On multivariable Cox regression, stricture length (Hazard Ratio 1.09, 95%CI 1.04-1.16, p=0.001), etiology (HR 1.16, 95%CI 1.06-1.28, p=0.002), revision urethroplasty (HR 1.56, 95%CI 1.07-2.28, p=0.02), stricture number (HR 2.34, 95%CI 1.01-7.43, p=0.05), and location (HR 1.32, 95%CI 1.04-1.68, p=0.02) were independently associated with stricture recurrence after anterior urethroplasty. On Kaplan-Meier analysis there was clustering within each independent variable which allowed revision to a stricture-specific classification termed “LERNS” (Length, Etiology, Revision, Number and Segment). On ROC analysis, area under the curve (AUC) for LERNS indicated excellent discrimination as a predictive tool for stricture recurrence (AUC 0.76, 95%CI 0.71-0.80, p<0.001). This was superior to both US (AUC 0.71, 95%CI 0.66-0.75, p<0.001) and LSE (AUC 0.69, 95%CI 0.64-0.74, p<0.001) confirmed with bootstrap analysis using 1000 replicates. On ROC analysis, both US (AUC 0.57, 95%CI 0.51-0.62, p=0.01) and LERNS (AUC 0.58, 95%CI 0.53-0.63, p=0.001) significantly predicting 90-day complications but with overall poor diagnostic discrimination. CONCLUSIONS: While increasing U-Score and LSE scale are both associated with stricture recurrence, modifying these systems as “LERNS” (Length, Etiology, Revision, Number, Segment) provides excellent discrimination when predicting stricture recurrence. However, accurately predicting 90-day complications will likely require further incorporation of patient-specific parameters. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e1135 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Keith Rourke More articles by this author Subash Subramanian More articles by this author Nathan Hoy More articles by this author Expand All Advertisement PDF downloadLoading ...
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