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

Abstract

PurposeTo 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 MethodsFrom 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.ResultsMean age, TPV, and IPSS were 6.2 (±7.3, SD) years, 48.5 (±25.9) ml, and 17.9 (±7.9), respectively. The mean BOO index was 35.1 (±25.2) 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).ConclusionsOur study demonstrated that TPV, Qmax, and PVR are independent predictors of urodynamic BOO.

Development and validation of a clinical nomogram predicting bladder outlet obstruction via routine clinical parameters in men with refractory nonneurogenic lower urinary tract symptoms

“…Although our clinical nomogram targets men with refractory LUTS, its accuracy is comparable to that of the previously published nomogram or predictive model in men with treatment-naïve or common LUTS (73.5%–83.2%) 1127. The predictive model proposed by Kim et al 27 was constructed by a combination of Qmax, PVR volume, and TPV. Notably, De Nunzio et al 11 selected only Qmax and transitional zone volume as independent statistical predictors of BOO in the development of their nomogram.…”

Clinical significance of peripheral zone thickness in men with lower urinary tract symptoms/benign prostatic hyperplasia

“…This weak statistical association may be because the urology clinic‐based study populations do not reflect community or primary care setting populations; it may also be due to the lack of knowledge of how age becomes a principal factor in influencing relationships among urinary symptom score, Q max , and TPV . In addition, prostatic enlargement alone cannot predict the presence of BOO, although TPV is statistically correlated with BOO in pressure‐flow studies .…”

“…However, there is conflicting published evidence about whether the TZI is associated with urinary symptoms . During the last decade, there have been several reports on IPP and PUA . Chia et al.…”

Contemporary diagnosis of lower urinary tract dysfunction.

“…It was also confirmed that prostate size is associated with the likelihood of BOO 37 . Flow rate is reduced in many men with symptoms of LUT dysfunction, and the combination of prostate enlargement and reduced flow rate with or without post-void residual is a better predictor of BOO than reported symptoms alone 38– 40 . Grading of BOO with a pressure flow plot has become standard for elderly males.…”