Development of Decision Support Formulas for the Prediction of Bladder Outlet Obstruction and Prostatic Surgery in Patients With Lower Urinary Tract Symptom/Benign Prostatic Hyperplasia: Part I, Development of the Formula and its Internal Validation.
- Author:
Min Soo CHOO
1
;
Changwon YOO
;
Sung Yong CHO
;
Seong Jin JEONG
;
Chang Wook JEONG
;
Ja Hyeon KU
;
Seung June OH
Author Information
- Publication Type:Original Article
- Keywords: Prostatic Hyperplasia; Decision Support Systems, Clinical; Nomograms; Urinary Bladder Neck Obstruction; Prostatectomy
- MeSH: Aged; Calibration; Cohort Studies; Decision Support Systems, Clinical; Humans; Logistic Models; Male; Nomograms; Prospective Studies; Prostate; Prostatectomy; Prostatic Hyperplasia*; Residual Volume; ROC Curve; Sensitivity and Specificity; Urinary Bladder Neck Obstruction*; Urinary Bladder*; Urinary Tract*
- From:International Neurourology Journal 2017;21(Suppl 1):S55-S65
- CountryRepublic of Korea
- Language:English
- Abstract: PURPOSE: As the elderly population increases, a growing number of patients have lower urinary tract symptom (LUTS)/benign prostatic hyperplasia (BPH). The aim of this study was to develop decision support formulas and nomograms for the prediction of bladder outlet obstruction (BOO) and for BOO-related surgical decision-making, and to validate them in patients with LUTS/BPH. METHODS: Patient with LUTS/BPH between October 2004 and May 2014 were enrolled as a development cohort. The available variables included age, International Prostate Symptom Score, free uroflowmetry, postvoid residual volume, total prostate volume, and the results of a pressure-flow study. A causal Bayesian network analysis was used to identify relevant parameters. Using multivariate logistic regression analysis, formulas were developed to calculate the probabilities of having BOO and requiring prostatic surgery. Patients between June 2014 and December 2015 were prospectively enrolled for internal validation. Receiver operating characteristic curve analysis, calibration plots, and decision curve analysis were performed. RESULTS: A total of 1,179 male patients with LUTS/BPH, with a mean age of 66.1 years, were included as a development cohort. Another 253 patients were enrolled as an internal validation cohort. Using multivariate logistic regression analysis, 2 and 4 formulas were established to estimate the probabilities of having BOO and requiring prostatic surgery, respectively. Our analysis of the predictive accuracy of the model revealed area under the curve values of 0.82 for BOO and 0.87 for prostatic surgery. The sensitivity and specificity were 53.6% and 87.0% for BOO, and 91.6% and 50.0% for prostatic surgery, respectively. The calibration plot indicated that these prediction models showed a good correspondence. In addition, the decision curve analysis showed a high net benefit across the entire spectrum of probability thresholds. CONCLUSIONS: We established nomograms for the prediction of BOO and BOO-related prostatic surgery in patients with LUTS/BPH. Internal validation of the nomograms demonstrated that they predicted both having BOO and requiring prostatic surgery very well.
