The P.R.OS.T.A.T.E Nomogram for the Preoperative Prediction of Clinical Efficacy of Transurethral Resection of the Prostate in Benign Prostatic Hyperplasia Patients.

Abstract

PurposeTransurethral resection of the prostate (TURP) is often indicated for benign prostatic hyperplasia (BPH). Some patients, however, fail to adequately respond to these interventions. Accordingly, a powerful prediction model for TURP efficacy is warranted. This study aimed to create a nomogram with preoperative parameters for the prediction of individual TURP efficacy.MethodsClinical data from 356 BPH subjects who underwent TURP were retrospectively collected between November 2015 and June 2021 for nomogram development. The prediction model was developed using multivariable logistic regression analysis and presented as a nomogram. Nomogram performance was assessed through calibration curves and the concordance index (C-index). An independent validation cohort containing 177 consecutive patients in the corresponding period was used for external validation. The optimal cutoff value was determined through receiver operating characteristic curve (ROC) analysis by maximizing the Youden index, and its accuracy was assessed through sensitivity, specificity and predictive values.ResultsIn multivariate analysis of the primary cohort, the independent factors for TURP efficacy were age, International Prostate Symptom Score (IPSS), intravesical prostatic protrusion (IPP), bladder wall thickness (BWT), peripheral zone thickness (PT) and transitional zone thickness (TT), all of which were included in the nomogram. The calibration curve for survival probability showed good agreement between the nomogram predictions and actual observations. The C-index for predicting TURP efficacy was 0.860 (95% confidence interval [CI], 0.808–0.911). The optimal cutoff total nomogram score was 177, with a maximum Youden index of 0.643. The sensitivity, specificity, positive predictive value, and negative predictive value for predicting TURP efficacy were 70.6%, 75.6%, 90.6%, and 43.7% in the validation cohort, respectively. Logistic regression analysis in the validation cohort demonstrated that the area under the curve (AUC) was 0.806 (95% CI, 0.733–0.879).ConclusionThe P.R.OS.T.A.T.E nomogram objectively and accurately predicted TURP efficacy, thereby facilitating the clinical decision-making process.