Urethral stricture disease is a common urological condition characterized by narrowing of the urethral lumen, resulting in obstructive voiding symptoms, recurrent urinary tract infections, and significant impairment in quality of life [1]. Successful management requires accurate preoperative assessment and careful surgical planning, as treatment options vary depending on stricture characteristics such as etiology, location, length, and number. Although minimally invasive techniques such as urethral dilatation and direct vision internal urethrotomy (DVIU) are widely used, they are associated with high recurrence rates and often provide only temporary relief [2]. Urethroplasty remains the gold standard for definitive management, offering superior long-term success rates and improved patient outcomes [3].

Predicting the complexity of urethroplasty and its outcomes remains challenging. A reliable preoperative assessment tool is essential for guiding surgical decision-making and facilitating patient counseling regarding risks and expected benefits. In this context, urethral scoring systems have been developed to objectively quantify stricture severity based on clinical and anatomical parameters. These scoring systems incorporate variables such as etiology, anatomical location, stricture length, and number of strictures to estimate surgical complexity and prognosis.

The U-Score is one such system that assigns numerical values to key variables including location (1–2), etiology (1–2), stricture length (1–3), and number (1–2), generating a total score ranging from 4 to 9. Another classification method, the LSE system, evaluates Length, Segment (location), and Etiology to provide a structured description of urethral strictures. While originally designed for standardized reporting, recent adaptations of the LSE system have incorporated composite scoring to enhance its clinical utility [4,5]. Both systems have shown associations with operative difficulty, duration of surgery, and recurrence rates; however, their validation in larger populations with long-term follow-up remains limited.

Recent studies have attempted to refine predictive models using multivariable statistical techniques. Retrospective analyses, such as those conducted at the University of Alberta, have evaluated variables including stricture location, etiology, length, number, prior urethroplasty, and prior endoscopic interventions using Cox regression analysis to predict outcomes [6]. Surgical success has been defined by the ability to pass a flexible cystoscope at follow-up without deterioration in urinary function.

Given these considerations, the present study aims to evaluate the effectiveness of a urethral scoring system in predicting the need for complex urethroplasty in patients with urethral stricture. By correlating scoring parameters with surgical complexity, this study seeks to improve preoperative planning, enable individualized treatment strategies, and enhance overall patient outcomes.

MATERIAL AND METHODS

This prospective cross-sectional observational study was conducted in the Department of General Surgery, M.G.M. Medical College & M.Y. Hospital, Indore over a period of 1 year after obtaining approval from the Institutional Ethics Committee. Prior to enrollment, all patients provided written informed consent in their vernacular language.

A total of 60 patients aged 18–65 years, diagnosed with urethral stricture and planned for urethroplasty, were included in the study. All patients were evaluated preoperatively through detailed history, clinical examination, and relevant investigations as per institutional protocol.

Sample size was calculated using Cochran’s formula based on a prevalence rate of 0.6%, with a 95% confidence interval and 2% margin of error. The calculated sample size was 57, which was adjusted for a 10% non-response rate, resulting in a final sample size of 60 patients.

Inclusion Criteria

• Age between 18–65 years
• Diagnosed cases of urethral stricture planned for urethroplasty
• Patients willing to provide informed consent

Exclusion Criteria

• Patients with untreated urethral malignancy or other conditions affecting surgical outcomes
• Patients not willing to participate
• Patients lost to follow-up

METHODOLOGY

After obtaining informed consent, patients fulfilling the inclusion criteria were enrolled in the study. Baseline data were collected using a prestructured proforma, including demographic details such as age and sex, along with clinical presentation.

All patients underwent routine preoperative investigations, including complete blood count (CBC), liver function test (LFT), renal function test (RFT), and serum electrolytes. Additional evaluation included urine analysis, uroflowmetry, retrograde urethrogram (RGU), and/or voiding cystourethrogram (VCUG) to assess stricture characteristics such as location, length, and number.

Each patient was assessed preoperatively using a urethral scoring system based on parameters including etiology, anatomical location, length, and number of strictures. Urethroplasty was performed according to standard surgical protocols, and intraoperative findings were recorded to determine surgical complexity.

The correlation between urethral scoring system parameters and the complexity of urethroplasty was analyzed. Postoperative follow-up was conducted to assess outcomes and complications.

Statistical Analysis

Data were entered into Microsoft Excel and analyzed using JAMOVI software. Continuous variables were expressed as mean ± standard deviation (SD), while categorical variables were presented as frequencies and percentages. Comparisons were performed using the unpaired t-test for continuous variables and Chi-square test for categorical variables. A p-value <0.05 was considered statistically significant.

RESULTS

The present study included 60 patients diagnosed with urethral stricture and undergoing urethroplasty. The age of the study population ranged widely, with the majority of patients (31.7%) belonging to the 20–30 years age group, followed by 31–40 years and >60 years (21.7% each). Very few patients (5.0%) were in the 51–60 years age group. The difference in age distribution was statistically significant (χ² = 11.0, p ≈ 0.026). All patients in the study were male (100%), which is consistent with the known epidemiology of urethral stricture disease (p < 0.00001). [Table 1]

Table 1: Demographic Characteristics

With respect to etiology, the most common causes of urethral stricture were iatrogenic (36.7%) and trauma (35%), followed by idiopathic (15%) and infection (13.3%). The variation in etiology was statistically significant (χ² ≈ 10.27, p ≈ 0.016). The bulbar urethra (55%) was the most frequent site of stricture, followed by penile (21.7%), posterior (13.3%), and pan-urethral (10%), showing a highly significant distribution (χ² ≈ 26.53, p < 0.0001). Most patients had single strictures (86.7%), while multiple strictures were less common (13.3%), which was statistically significant (χ² ≈ 32.27, p < 0.00001). Regarding spongiofibrosis, the majority had moderate (43.3%) or mild (38.3%) fibrosis, with fewer cases of severe fibrosis (18.3%) (χ² ≈ 6.7, p ≈ 0.035). [Table 2]

Table 2: Etiology and Stricture Characteristics

Analysis of previous interventions showed that 25% of patients had undergone prior dilatation, while the majority (75%) were primary cases (χ² = 15, p ≈ 0.0001). Similarly, 16.7% had a history of previous DVIU, and only 8.3% had undergone prior urethroplasty, indicating that most cases were primary presentations. These findings were statistically significant (p < 0.00001). [Table 3]

Table 3: Previous Interventions

Regarding operative details, complex urethroplasty was performed in 60% of patients, whereas 40% underwent simple procedures; however, this difference was not statistically significant (χ² = 2.4, p ≈ 0.12). Among surgical techniques, buccal mucosal graft (BMG) urethroplasty (46.7%) and excision and primary anastomosis (EPA) (45%) were most commonly performed, while staged procedures were less frequent (8.3%), with a statistically significant distribution (χ² ≈ 15.7, p ≈ 0.0004). Most procedures had an operative time of 121–150 minutes (35%), though this variation was not statistically significant (p ≈ 0.088). Intraoperative complications were rare, occurring in only 5% of patients, while postoperative complications were observed in 18.3%. Both findings were statistically significant (p < 0.00001). The overall success rate was 93.3%, with only 6.7% failure, indicating excellent surgical outcomes (χ² ≈ 45.07, p < 0.00001). [Table 4]

Table 4: Operative Details and Outcomes

Descriptive statistical analysis revealed that the mean duration of symptoms was 14.1 ± 6.24 months, with a range of 3–23 months. The mean stricture length was 2.39 ± 1.12 cm, while the average hospital stay was 5.55 ± 1.75 days. The mean urethral scoring parameters were as follows: length score 1.77 ± 0.72, location score 1.45 ± 0.50, etiology score 1.85 ± 0.36, and fibrosis score 1.80 ± 0.73. The mean total urethral score was 6.87 ± 1.20, indicating a moderate disease burden in the study population. [Table 5]

Table 5: Descriptive Statistics and Urethral Score

DISCUSSION

The aim of the present study was to evaluate the effectiveness of a urethral scoring system in predicting the need for complex urethroplasty in patients with urethral stricture disease. With the increasing emphasis on individualized surgical planning and improved outcomes, structured scoring systems have gained importance in objectively assessing disease severity and guiding surgical decision-making. The urethral scoring system used in this study incorporates key parameters such as etiology, location, length, and number of strictures, thereby providing a comprehensive preoperative assessment.

In the current study, all patients were male, which is consistent with the epidemiology of urethral stricture disease. The majority of patients belonged to the younger age group (20–40 years), which correlates with findings reported by Raykar et al. [7], who observed a similar age distribution with a mean age of 34.5 years. The predominance of bulbar urethral strictures (55%) in our study is also in agreement with previous literature, where the bulbar urethra is most frequently affected due to its anatomical and vascular characteristics [7].

The etiological distribution in the present study showed that iatrogenic (36.7%) and traumatic (35%) causes were the most common, together accounting for the majority of cases. This is comparable to findings by Raykar et al. [7], where traumatic strictures were predominant. The increasing incidence of iatrogenic strictures reflects the growing use of urethral instrumentation and catheterization in clinical practice. These etiological factors are clinically significant as they are often associated with longer strictures and increased spongiofibrosis, thereby contributing to increased surgical complexity.

The most important finding of this study is the significant association between the urethral scoring system and surgical complexity. Higher scores were associated with complex urethroplasty procedures such as buccal mucosal graft (BMG) and staged repairs, whereas lower scores were associated with simpler procedures such as excision and primary anastomosis (EPA). These findings are consistent with the study by Wiegand et al. [8], who introduced the UREThRAL stricture score and demonstrated a strong correlation between increasing scores and surgical complexity.

Similarly, Eswara et al. [9] validated the U-score and reported that higher scores were significantly associated with high-complexity urethroplasty and increased operative time. Alwaal et al. [10] further supported these findings by demonstrating that higher U-scores not only predict surgical complexity but are also associated with increased recurrence rates. Mathur et al. [11] also reported that higher urethral stricture scores correlate with more complex surgical procedures, with stricture length and location being the most influential parameters.

Tobia et al. [12] demonstrated that higher U-scores significantly increase the probability of complex urethroplasty, with high-risk groups showing up to 77.9% likelihood of complex surgery. Additionally, Kurtzman et al. [13] reported that both the LSE system and urethral stricture score are significantly associated with surgical complexity, further validating the role of structured scoring systems in clinical practice.

However, some variability exists in the literature. Chaitanya et al. [14] reported no statistically significant correlation between urethral stricture score and surgical complexity in their study. This discrepancy may be attributed to differences in study design, patient selection, or variability in surgical expertise.

The present study demonstrated a high overall success rate of 93.3%, with minimal intraoperative (5%) and postoperative complications (18.3%). These findings are comparable to previous studies, including Raykar et al. [7], who reported success rates of approximately 80% for urethroplasty. The low complication rates observed in this study highlight the importance of proper preoperative assessment and surgical planning.

Operative time was relatively longer in patients undergoing complex urethroplasty, which is consistent with findings reported by Eswara et al. [9], who demonstrated a linear relationship between U-score and operative duration. The ability of the scoring system to predict surgical complexity preoperatively allows for better preparation, including allocation of operative time and resources.

The clinical implications of this study are significant. The urethral scoring system provides an objective and reproducible method for evaluating urethral strictures, thereby improving surgical planning, optimizing resource utilization, and enhancing patient counseling. Surgeons can anticipate the complexity of the procedure and select the most appropriate surgical technique, reducing intraoperative uncertainty and improving outcomes.

Despite these promising findings, certain limitations must be considered. The study was conducted in a single tertiary care center with a relatively small sample size, which may limit the generalizability of the results. Additionally, long-term follow-up was not included, preventing assessment of recurrence rates. Variability in surgical expertise and lack of incorporation of advanced imaging modalities may also influence outcomes.

Further multicentric studies with larger sample sizes and long-term follow-up are required to validate the predictive accuracy of urethral scoring systems. Incorporation of imaging modalities such as urethral ultrasonography or MRI, along with patient-specific factors, may further enhance the predictive value. Prospective studies evaluating score-based surgical planning may help establish this scoring system as a standard tool in the management of urethral stricture disease.

CONCLUSION

Urethral stricture disease requires precise preoperative evaluation to ensure optimal surgical outcomes. A structured urethral scoring system provides an objective method to assess stricture characteristics and predict the need for complex urethroplasty. Higher scores correlate with increased surgical complexity, facilitating better planning, appropriate selection of surgical technique, and improved patient counseling. The observed high success rates and low complication profile reinforce its clinical applicability. Such scoring systems can enhance decision-making and resource utilization in routine practice. Further large-scale, multicentric studies with long-term follow-up are recommended to validate its predictive accuracy and establish its role in standard clinical protocols.

REFERENCES

1. Wessells H, Angermeier KW, Elliott S, Gonzalez CM, Kodama R, Peterson AC, et al. Male urethral stricture: American Urological Association guideline. J Urol. 2017;197(1):182–190.
2. Steenkamp JW, Heyns CF, de Kock ML. Internal urethrotomy versus dilation as treatment for male urethral strictures: a prospective randomized comparison. J Urol. 1997;157(1):98–101.
3. Barbagli G, Lazzeri M. Surgical treatment of anterior urethral stricture diseases: brief overview. Int Braz J Urol. 2007;33(4):461–469.
4. Buckley JC, Heyns CF, Gilling P, Carney J. SIU/ICUD Consultation on urethral strictures: anterior urethra—epidemiology, etiology, anatomy, and nomenclature of urethral strictures. Urology. 2014;83(3 Suppl):S2–S7.
5. Xu YM, Sa YL, Fu Q, Zhang J, Song LJ. Urethral stricture score system: a novel method for describing anterior urethral strictures. Urology. 2011;78(2):447–451.
6. Breyer BN, McAninch JW, Whitson JM, Eisenberg ML, Mehdizadeh JF, Myers JB, et al. Multivariate analysis of risk factors for long-term urethroplasty outcome. J Urol. 2010;183(2):613–617.
7. Raykar RR, Jadhav RR. A clinical study of evaluation of different modalities of treatment and etiology of stricture urethra. Int Surg J. 2019;6(4):1148–1152.
8. Wiegand LR, Brandes SB. The urethral stricture score: a novel method for describing anterior urethral strictures. Can Urol Assoc J. 2012;6(4):260–264.
9. Eswara JR, Han J, Raup VT. Refinement and validation of the urethral stricture score in categorizing anterior urethral stricture complexity. Urology. 2015;85(2):479–483.
10. Alwaal A, Sanford TH, Harris CR, Osterberg EC, McAninch JW, Breyer BN. Urethral stricture score is associated with anterior urethroplasty complexity and outcome. J Urol. 2016.
11. Mathur R, Patil LA, Khan F. Evaluating efficacy of various operative procedures done in anterior urethral stricture using urethral stricture score. Urol Ann. 2016;8:42–45.
12. Tobia IP, Gil SA, Nanni FD, Favre GA, Giudice CR. Simplified urethral score system for predicting complex anterior urethroplasty. Actas Urol Esp. 2022;46:348–353.
13. Chaitanya SV, Kumar NA, Satish B, Manoj B, Reddy K. Codifying anterior urethral strictures with urethral stricture score. Int J Contemp Med Res. 2018;5(10):J1–J4.
14. Kurtzman JT, Kosber R, Kerr P, Brandes SB. Evaluating Tools for Characterizing Anterior Urethral Stricture Disease: A Comparison of the LSE System and the Urethral Stricture Score. J Urol. 2022 Nov;208(5):1083-1089.