Non-Invasive Clinical Parameters for the Prediction of Urodynamic Bladder Outlet Obstruction: Analysis Using Causal Bayesian Networks

Authors

Myong Kim, Seoul National University Hospital
Abhilash Cheeti, Department of Computer Science, School of Computing and Information Sciences, Florida International UniversityFollow
Changwon Yoo, Department of Biostatistics, Florida International UniversityFollow
Minsoo Choo, Seoul National University HospitalFollow
Jae-Seung Paick, Seoul National University HospitalFollow
Seung-June Oh, Seoul National University HospitalFollow

Date of this Version

11-15-2014

Document Type

Article

Abstract

Purpose: To identify non-invasive clinical parameters to predict urodynamic bladder outlet obstruction (BOO) in patients with benign prostatic hyperplasia (BPH) using causal Bayesian networks (CBN). Subjects and Methods: From October 2004 to August 2013, 1,381 eligible BPH patients with complete data were selected for analysis. The following clinical variables were considered: age, total prostate volume (TPV), transition zone volume (TZV), prostate specific antigen (PSA), maximum flow rate (Qmax), and post-void residual volume (PVR) on uroflowmetry, and International Prostate Symptom Score (IPSS). Among these variables, the independent predictors of BOO were selected using the CBN model. The predictive performance of the CBN model using the selected variables was verified through a logistic regression (LR) model with the same dataset. Results: Mean age, TPV, and IPSS were 6.2 (67.3, SD) years, 48.5 (625.9) ml, and 17.9 (67.9), respectively. The mean BOO index was 35.1 (625.2) and 477 patients (34.5%) had urodynamic BOO (BOO index $40). By using the CBN model, we identified TPV, Qmax, and PVR as independent predictors of BOO. With these three variables, the BOO prediction accuracy was 73.5%. The LR model showed a similar accuracy (77.0%). However, the area under the receiver operating characteristic curve of the CBN model was statistically smaller than that of the LR model (0.772 vs. 0.798, p = 0.020). Conclusions: Our study demonstrated that TPV, Qmax, and PVR are independent predictors of urodynamic BOO.

Comments

Originally published in PLOS One.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.

Recommended Citation

Kim M, Cheeti A, Yoo C, Choo M, Paick J-S, et al. (2014) Non-Invasive Clinical Parameters for the Prediction of Urodynamic Bladder Outlet Obstruction: Analysis Using Causal Bayesian Networks. PLoS ONE 9(11): e113131. doi:10.1371/journal.pone.0113131