Efficacy of Symptoms of Lower Urinary Tract Dysfunction Research Network Symptom Index-29 Questionnaire in Assessing Alpha-blocker Treatment Response in Patients With Benign Prostatic Hyperplasia: A Prospective, Multicenter, Cohort Study

Abstract

OBJECTIVE To evaluate the efficacy of the symptoms of the Lower Urinary Tract Dysfunction Research Network Symptom Index-29 (LURN SI-29) questionnaire in assessing alpha-blocker treatment response in patients with lower urinary tract symptoms (LUTS). METHODS This prospective, non-randomized, multicentre trial included males with LUTS who visited urology outpatient clinics between January and April 2023. The most employed LUTS questionnaire is the International Prostate Symptom Score (IPSS), while the LURN SI-29 was also utilized. Prospective monitoring comprised the completion of IPSS and LURN SI-29 forms, uroflowmetry, and residual urine assessment prior to the initiation of alpha-blocker therapy and at the conclusion of the first month of treatment. RESULTS The study cohort comprised 135 patients. There was a significant enhancement in the mean IPSS, which decreased from 18.4 to 11.2 (P = .001). Furthermore, the mean LURN SI-29 score exhibited a significant decline, from 37.02 to 22.4 (P = .001). The improvement in IPSS and LURN SI-29 scores was 67.1% +/- 54.3% and 64.2% +/- 34.1%, respectively. Additionally, these improvements were found to be correlated (Pearson correlation coefficient = 0.79, R2 = 0.63, P = .001). The mean Qmax increased from 10.3 to 11.9 ml/s (P = .001). No significant difference was identified between alpha-blocker types. CONCLUSION A strong correlation was observed between LURN SI-29 and IPSS among patients with LUTS who were initiated on alpha-blocker therapy. LURN-SI-29 may be employed for the purpose of evaluating the efficacy of alpha-blocker therapy and may additionally offer insight into the domains of incontinence, post-micturition symptoms, and pain. UROLOGY 196: 249-253, 2025. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.