You have accessJournal of UrologyCME1 Apr 2023MP36-05 CLINIC SCORE - A NOVEL PREDICTION MODEL OF COLLAGENASE CLOSTRIDIUM HISTOLYTICUM OUTCOMES IN MEN WITH PEYRONIE’S DISEASE Courtney Pierce, Benjamin Green, Joshua Savage, Klint Brearton, Matthew Ziegelmann, Sevann Helo, Tobias Kohler, and Landon Trost Courtney PierceCourtney Pierce More articles by this author , Benjamin GreenBenjamin Green More articles by this author , Joshua SavageJoshua Savage More articles by this author , Klint BreartonKlint Brearton More articles by this author , Matthew ZiegelmannMatthew Ziegelmann More articles by this author , Sevann HeloSevann Helo More articles by this author , Tobias KohlerTobias Kohler More articles by this author , and Landon TrostLandon Trost More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003270.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Since the FDA approval of Collagenase Clostridium Histolyticum (CCH), few studies have been able to identify variables which predict curve improvements, with baseline extent of curvature most highly correlated. In addition to extent of baseline curvature, our team has previously identified curve direction and plaque calcification as additional predictive variables. We therefore sought to create an integrated predictive model which incorporated several factors to better estimate anticipated outcomes. METHODS: A prospective database has been maintained of men undergoing CCH injections for PD. Data were reviewed to identify variables predictive of curve improvements in men with isolated curvature as well as among those with key characteristics, including indentations, hourglass deformities, penile tapering, and calcification. A predictive model was subsequently developed to improve correlations between disease factors and subsequent CCH outcomes. The final model (CLINiC Score) assigned points as follows: +1 point for every 10 degrees of curvature (C for Curvature), +5 points for penile narrowing >25% (IN for INdent), +3 points for narrowing 0-25%, -4 points for pure lateral curvatures (L for Lateral), and -2 points for plaque calcification (C for Calcification). Patients were assigned scores based on the CLINiC model, and results were correlated with final curve outcomes. RESULTS: A total of 476 PD men were included in the current analysis. Baseline variables for the cohort included a mean age of 55.6 yrs (SD 10.9), PD duration 31.9 months (SD 61.4), composite curvature 64.6 degrees (SD 23.9), 47% with indentations, 42% with hourglass deformity, and 17% with calcification. The mean CLINiC score for the cohort was 6.9 (SD 3.4). For the overall cohort, the use of the CLINiC score increased the correlation coefficient from 0.35 to 0.46 (r-squared 0.13 vs 0.21), with a predictive linear formula of 2.1 - 3.2*CLINiC score. The difference was more pronounced among a subset cohort of men who had pure lateral curvatures, plaque calcification, or narrowing deformity. In comparing the CLINiC predictive model to baseline curve alone, the correlation coefficient increased to 0.54 (r-squared 0.29, p<0.0001) compared to 0.38 (r-squared 0.15, p<0.001). The linear equation to predict curve improvement outcomes using the CLINiC score was 2.2 - 3.5*total CLINiC score. CONCLUSIONS: Use of a novel scoring system (CLINiC) improves upon baseline curvature alone to predict post-CCH curve improvements, with the difference more pronounced among men with pure lateral curvatures, plaque calcification, and/or narrowing deformities. External validation is warranted. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e480 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Courtney Pierce More articles by this author Benjamin Green More articles by this author Joshua Savage More articles by this author Klint Brearton More articles by this author Matthew Ziegelmann More articles by this author Sevann Helo More articles by this author Tobias Kohler More articles by this author Landon Trost More articles by this author Expand All Advertisement PDF downloadLoading ...
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