Cosimo De Nunzio1, Riccardo Autorino2, Alexander Bachmann3, Alberto Briganti4, Simon Carter5, Felix Chun6, Giacomo Novara7, Roman Sosnowski8, Nickesh Thiruchelvam9, Andrea Tubaro1, Sascha Ahyai6. 1. Department of Urology, Sant' Andrea Hospital "La Sapienza,", Rome, Italy. 2. Department of Urology, Urology Clinic, Second University of Naples, Naples, Italy. 3. Department of Urology, Urologische Klinik, Universitätsspital Basel, Basel, Switzerland. 4. Department of Urology, Vita-Salute University San Raffaele, Milan, Italy. 5. Department of Urology, London Clinic, London, United Kingdom. 6. Department of Urology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany. 7. Department of Oncological and Surgical Sciences, Urology Clinic, University of Padua, Padua, Italy. 8. Department of Urology, M. Sklodowska-Curie Memorial Cancer Center, Warsaw, Poland. 9. Department of Urology, Addenbrookes Hospital, Cambridge, United Kingdom.
Abstract
AIMS: To develop a nomogram predicting benign prostatic obstruction (BPO). METHODS: We included in this study 600 men with lower urinary tract symptoms (LUTS) and benign prostatic enlargement (BPE) who underwent standardized pressure flow studies (PFS) between 1996 and 2000. Complete clinical and urodynamic data were available for all patients. Variables assessed in univariate and multivariate logistic regression models consisted of IPSS, PSA, prostate size, maximal urinary flow rate (Qmax) at free flow, residual urine (RU), and bladder wall thickness (BWT). These were used to predict significant BPO (defined as a Schäfer grade ≥ 3 in PFS). RESULTS: A preliminary multivariate model, including IPSS, Qmax at free flow and RU, suggested that only Qmax at free flow was a statistically significant predictor of BPO (P = 0.00) with a predictive accuracy (PA) of 82%. Further development of the multivariate model showed how the inclusion of BWT did not increase PA. Only transitional zone volume (TZV) proved to be an additional statistically significant predictor for BPO (P = 0.00). The combination of Qmax at free flow and TZV demonstrated a PA of 83.2% and were included in the final nomogram format. CONCLUSIONS: We developed a clinical nomogram, which is both accurate and well calibrated, which can be helpful in the management of patients with LUTS and BPE. External validation is warranted to confirm our findings.
AIMS: To develop a nomogram predicting benign prostatic obstruction (BPO). METHODS: We included in this study 600 men with lower urinary tract symptoms (LUTS) and benign prostatic enlargement (BPE) who underwent standardized pressure flow studies (PFS) between 1996 and 2000. Complete clinical and urodynamic data were available for all patients. Variables assessed in univariate and multivariate logistic regression models consisted of IPSS, PSA, prostate size, maximal urinary flow rate (Qmax) at free flow, residual urine (RU), and bladder wall thickness (BWT). These were used to predict significant BPO (defined as a Schäfer grade ≥ 3 in PFS). RESULTS: A preliminary multivariate model, including IPSS, Qmax at free flow and RU, suggested that only Qmax at free flow was a statistically significant predictor of BPO (P = 0.00) with a predictive accuracy (PA) of 82%. Further development of the multivariate model showed how the inclusion of BWT did not increase PA. Only transitional zone volume (TZV) proved to be an additional statistically significant predictor for BPO (P = 0.00). The combination of Qmax at free flow and TZV demonstrated a PA of 83.2% and were included in the final nomogram format. CONCLUSIONS: We developed a clinical nomogram, which is both accurate and well calibrated, which can be helpful in the management of patients with LUTS and BPE. External validation is warranted to confirm our findings.
Authors: Arvind P Ganpule; Rohan S Batra; Nitiraj B Shete; Abhishek G Singh; Ravindra B Sabnis; Mahesh R Desai Journal: Am J Clin Exp Urol Date: 2021-06-15
Authors: Lorenzo G Luciani; Daniele Mattevi; Daniele Ravanelli; Umberto Anceschi; Guido Giusti; Tommaso Cai; Umberto Rozzanigo Journal: Int J Environ Res Public Health Date: 2022-08-08 Impact factor: 4.614