Bradley A Erickson1, Kevin J Flynn2, Amy E Hahn3, Katherine Cotter2, Nejd F Alsikafi4, Benjamin N Breyer5, Joshua A Broghammer6, Jill C Buckley7, Sean P Elliott8, Jeremy B Myers9, Andrew C Peterson10, Keith F Rourke11, Thomas G Smith12, Alex J Vanni13, Bryan B Voelzke14, Lee C Zhao15. 1. University of Iowa, Department of Urology, Iowa City, IA. Electronic address: brad-erickson@uiowa.edu. 2. University of Iowa, Department of Urology, Iowa City, IA. 3. University of Iowa, Department of Biostatistics, Iowa City, IA. 4. Uropartners, Gurnee, IL. 5. University of California, San Francisco, Department of Urology and Epidemiology and Biostatistics, San Francisco, CA. 6. University of Kansas, Department of Urology. 7. University of California, San Diego, Department of Urology, San Diego, CA. 8. University of Minnesota, Department of Urology, Minneapolis, MN. 9. University of Utah, Division of Urology, Salt Lake City, UT. 10. Duke University, Division of Urology. 11. University of Alberta, Department of Urology, Edmonton, Alberta. 12. MD Anderson Cancer Center, Department of Urology Houston, TX. 13. Lahey Hospital and Medical Center, Department of Urology, Burlington, MA. 14. Spokane Urology, Spokane, WA. 15. New York University, Department of Urology, New York, NY.
Abstract
OBJECTIVE: To develop and validate a clinical classification system for urethral stricture disease (USD) based on the retrograde urethrogram (RUG), physical exam, and stricture-specific patient history. MATERIALS AND METHODS: Three elements were chosen to be included in the classification system: 1) Length of urethral stricture (L); 2) Stricture segment/location (S); 3) Stricture Etiology (E) (LSE classification system). Each element was divided into clinically relevant sub-categories. A three-step development and validation process then ensued, culminating in an in-person Trauma and Urologic Reconstruction Network of Surgeons (TURNS) meeting, at which the final classification system was unanimously agreed upon by attendees based on interrater reliability data obtained from the classifying of 22 clinical vignettes. A final validation step involved retrospectively classifying cases in the TURNS database to determine if classification influenced surgical technique and was associated with presumed stricture etiology. RESULTS: The final LSE classification system was found to have an interrater reliability of 0.79 (individual components 0.76, 0.70 and 0.93 respectfully). Retrospective classification of the 2162 TURNS strictures revealed the segment (S) to be strongly associated with urethroplasty type (p = 0.0005) and stricture etiology (E) (p = 0.0005). CONCLUSION: We developed and validated a novel, easy to use, urethral stricture classification system. The system's ability to aid in directing treatments, predict treatment outcomes, and facilitate collaborative research efforts will require further study. Published by Elsevier Inc.
OBJECTIVE: To develop and validate a clinical classification system for urethral stricture disease (USD) based on the retrograde urethrogram (RUG), physical exam, and stricture-specific patient history. MATERIALS AND METHODS: Three elements were chosen to be included in the classification system: 1) Length of urethral stricture (L); 2) Stricture segment/location (S); 3) Stricture Etiology (E) (LSE classification system). Each element was divided into clinically relevant sub-categories. A three-step development and validation process then ensued, culminating in an in-person Trauma and Urologic Reconstruction Network of Surgeons (TURNS) meeting, at which the final classification system was unanimously agreed upon by attendees based on interrater reliability data obtained from the classifying of 22 clinical vignettes. A final validation step involved retrospectively classifying cases in the TURNS database to determine if classification influenced surgical technique and was associated with presumed stricture etiology. RESULTS: The final LSE classification system was found to have an interrater reliability of 0.79 (individual components 0.76, 0.70 and 0.93 respectfully). Retrospective classification of the 2162 TURNS strictures revealed the segment (S) to be strongly associated with urethroplasty type (p = 0.0005) and stricture etiology (E) (p = 0.0005). CONCLUSION: We developed and validated a novel, easy to use, urethral stricture classification system. The system's ability to aid in directing treatments, predict treatment outcomes, and facilitate collaborative research efforts will require further study. Published by Elsevier Inc.
Authors: Malte W Vetterlein; Valentin Zumstein; Luis A Kluth; Silke Riechardt; Roland Dahlem; Margit Fisch Journal: World J Urol Date: 2020-10-06 Impact factor: 4.226