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. Neurourol. Urodynam. 35:235-240, 2016.

The diagnosis of benign prostatic obstruction: Development of a clinical nomogram

Autorino, Riccardo;
2016

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. Neurourol. Urodynam. 35:235-240, 2016.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/388231
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