Urethral stricture is a relatively common condition that causes a broad spectrum of symptoms, complications, and reduction in patient-reported quality of life.^1,2 Endoscopic treatments are most commonly performed but typically provide only short-term relief and can complicate future treatment.^3,4 Urethroplasty is considered the most efficacious treatment for establishing urethral patency and improving patient quality of life.^5-7 However, a key component of informed consent for any surgery is full disclosure of the risks and benefits of the procedure. In the case of urethroplasty this requires patient- and stricture-specific predictors of success (benefit) and complications (risk). While urethroplasty is performed with the intention of providing long-term relief, recurrences and complications can occur even in the most skilled hands, and reliably predicting these outcomes remains elusive. Elsewhere in urology, classification systems have been used to assist in predicting outcomes and patient counselling. Several tools have been developed to facilitate informed discussion of urethroplasty outcomes. The U-Score is a classification tool that provides a numerical score based on points for stricture length (1-3 points), stricture number (1-2), location (1-2), and etiology (1-2) for a total of 4-9 points.^7,8 Another system known as LSE provides further details based on sub-groups of urethral stricture Length, location (Segment), and Etiology.⁹ The LSE system is more complex with respect to cutoff values for each variable and was developed primarily as a classification system to standardize stricture reporting. LSE does not explicitly provide a numerical score; however, this system has recently been modified to provide a composite score.¹⁰ Both systems have recently been demonstrated to be associated with surgical complexity, operative time, and stricture recurrence.^10,11 However, neither of these systems has been incorporated widely, and they lack validation with respect to predictive ability in large patient populations with long-term follow-up.

Recently we undertook the task of developing a modified classification based on survival analysis of stricture-specific variables. A retrospective review was performed of men undergoing anterior urethroplasty at the University of Alberta from 2003-2021. Stricture-specific variables of location, etiology, length, number of strictures, prior urethroplasty, and previous endoscopic treatment were evaluated using multivariable Cox regression analysis. Success was defined as the inability to easily pass a flexible cystoscope at routine follow-up with no change in urinary function thereafter.

Of the 1,573 patients undergoing anterior urethroplasty over the study period, the success rate was 92.0% at a median follow-up of 90 months. On multivariable Cox regression, stricture length (HR 1.09, 95% CI 1.04-1.16, P = .001), etiology (HR 1.16, 95% CI 1.06-1.28, P = .002), revision urethroplasty (HR 1.56, 95% CI 1.07-2.28, P = .02), stricture number (HR 2.34, 95% CI 1.01-7.43, P = .05), and location (HR 1.32, 95% CI 1.04-1.68, P = .02) were independently associated with stricture recurrence after anterior urethroplasty, while failed endoscopic treatment was not.

On Kaplan-Meier survival analysis there was stratification and clustering within each variable. These stratified factors independently associated with recurrence after anterior urethroplasty were used to developed a modified stricture-specific classification system based on stricture length (L), etiology (E), revision status (R), number (N), and urethral segment (S). This revised system, termed LERNS, is described in the Table. In this modified system, a score is assigned based on stricture Length (1-4), Etiology (1-4), Revision status (1-2), Number of strictures (1-2) and stricture Segment (1-3) for a total score from 5-15.

Subsequently, U-Scores, LSE, and LERNS scores were calculated for each patient and evaluated for diagnostic ability using receiver operating characteristic analysis. Based on this analysis, the 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 < .001). This was superior to both U-Score (AUC 0.71, 95% CI 0.66-0.75, P < .001) and LSE (AUC 0.69, 95% CI 0.64-0.74, P < .001; see Figure). These findings were confirmed with bootstrap analysis using 1,000 replicates.

Figure. Receiver operation characteristic analysis examining diagnostic ability of U-Score, LSE (length [L], location [segment, S], and etiology [E]) scale, and LERNS (stricture length [L], etiology [E], revision status [R], number [N], and urethral segment [S]) score to predict stricture recurrence.

While increasing U-Score and LSE scale are both associated with stricture recurrence, modifying these systems as the LERNS (Length, Etiology, Revision, Number, Segment) system provides excellent and improved discrimination when predicting stricture recurrence. We plan on working to further validate this easy-to-use classification system while simultaneously developing an open-use online predictive tool for counselling of patients contemplating urethroplasty.