Guido Barbagli1, Marco Bandini2, Sofia Balò1, Nicola Fossati3, Francesco Montorsi3, Salvatore Sansalone4, Denis Butnaru5, Massimo Lazzeri6. 1. Centro Chirurgico Toscano, Arezzo, Italy. 2. Unit of Urology, Urological Research Institute (URI), IRCCS Ospedale San Raffaele, Vita-Salute San Raffaele University, Via Olgettina 60, 20132, Milan, Italy. bandini.marco@hsr.it. 3. Unit of Urology, Urological Research Institute (URI), IRCCS Ospedale San Raffaele, Vita-Salute San Raffaele University, Via Olgettina 60, 20132, Milan, Italy. 4. Department of Experimental Medicine and Surgery, University of Tor Vergata, Rome, Italy. 5. Institute for Regenerative Medicine, Sechenov First Moscow State Medical University, Moscow, Russia. 6. Department of Urology, Humanitas Clinical and Research Center IRCCS, Rozzano, Milan, Italy.
Abstract
PURPOSE: To design a dedicated risk calculator for patients with penile urethra stricture who are scheduled to urethroplasty that might be used to counsel patients according to their pre-operative risk of failure. METHODS: Patients treated with penile urethroplasty at our center (1994-2018) were included in the study. Patients received 1-stage or staged penile urethroplasty. Patients with failed hypospadias repair, lichen sclerosus or incomplete clinical records were excluded. Treatment failure was defined as any required postoperative instrumentation, including dilation. Univariable Cox regression identified predictors of post-operative treatment failure and Kaplan-Meier analysis plotted the failure-free survival rates according to such predictors. Multivariable Cox regression-based risk calculator was generated to predict the risk of treatment failure at 10 years after surgery. RESULTS: 261 patients met the inclusion criteria. Median follow-up was 113 months. Out of 216 patients, 201 (77%) were classified as success and 60 (23%) failures. Former smoker (hazard ratio [HR] 2.12, p = 0.025), instrumentation-derived stricture (HR 2.55, p = 0.006), and use of grafts (HR 1.83, p = 0.037) were predictors of treatment failure. Model-derived probabilities showed that the 10-year risk of treatment failure varied from 5.8 to 41.1% according to patient's characteristics. CONCLUSIONS: Long-term prognosis in patients who underwent penile urethroplasty is uncertain. To date, our risk-calculator represents the first tool that might help physicians to predict the risk of treatment failure at 10 years. According to our model, such risk is largely influenced by the etiology of the stricture, the use of graft, and patient's smoking habits.
PURPOSE: To design a dedicated risk calculator for patients with penile urethra stricture who are scheduled to urethroplasty that might be used to counsel patients according to their pre-operative risk of failure. METHODS:Patients treated with penile urethroplasty at our center (1994-2018) were included in the study. Patients received 1-stage or staged penile urethroplasty. Patients with failed hypospadias repair, lichen sclerosus or incomplete clinical records were excluded. Treatment failure was defined as any required postoperative instrumentation, including dilation. Univariable Cox regression identified predictors of post-operative treatment failure and Kaplan-Meier analysis plotted the failure-free survival rates according to such predictors. Multivariable Cox regression-based risk calculator was generated to predict the risk of treatment failure at 10 years after surgery. RESULTS: 261 patients met the inclusion criteria. Median follow-up was 113 months. Out of 216 patients, 201 (77%) were classified as success and 60 (23%) failures. Former smoker (hazard ratio [HR] 2.12, p = 0.025), instrumentation-derived stricture (HR 2.55, p = 0.006), and use of grafts (HR 1.83, p = 0.037) were predictors of treatment failure. Model-derived probabilities showed that the 10-year risk of treatment failure varied from 5.8 to 41.1% according to patient's characteristics. CONCLUSIONS: Long-term prognosis in patients who underwent penile urethroplasty is uncertain. To date, our risk-calculator represents the first tool that might help physicians to predict the risk of treatment failure at 10 years. According to our model, such risk is largely influenced by the etiology of the stricture, the use of graft, and patient's smoking habits.
Authors: Marco Bandini; Guido Barbagli; Riccardo Leni; Giuseppe O Cirulli; Giuseppe Basile; Sofia Balò; Francesco Montorsi; Salvatore Sansalone; Andrea Salonia; Alberto Briganti; Denis Butnaru; Massimo Lazzeri Journal: World J Urol Date: 2021-04-15 Impact factor: 4.226