Establishment and internal validation of a risk prediction model for urinary incontinence after transurethral holmium laser enucleation of the prostate
10.3969/j.issn.1009-8291.2023.03.010
- VernacularTitle:经尿道钬激光前列腺剜除术后尿失禁发生风险预测模型的建立及内部验证
- Author:
Yijie JIA
1
;
Guangchen ZHOU
1
Author Information
1. Department of Urology, Jiangsu Subei People’s Hospital, Yangzhou 225001, China
- Publication Type:Journal Article
- Keywords:
benign prostatic hyperplasia;
holmium laser enucleation of the prostate;
PSA;
IPSS;
QoL;
prostate volume (PV);
urinary incontinence;
prediction model
- From:
Journal of Modern Urology
2023;28(3):222-226
- CountryChina
- Language:Chinese
-
Abstract:
【Objective】 To establish a model for predicting the risk of urinary incontinence after holmium laser enucleation of the prostate (HoLEP). 【Methods】 The clinical data of 258 patients with benign prostatic hyperplasia (BPH) who underwent HoLEP in our hospital during Jan.2019 and Feb.2022 were retrospectively analyzed. According to the occurrence of urinary incontinence after surgery, they were divided into the urinary incontinence group (n=84) and non-urinary incontinence group (n=174). Lasso regression was used to screen the predictors of urinary incontinence after HoLEP. Logistic regression was used to establish a suitable model, and a nomogram of urinary incontinence after HoLEP was drawn. Bootstrap was used to verify and draw the calibration curve of the model, calculate the C index, and draw the clinical decision curve to further verify the accuracy and identification ability of the model. 【Results】 Predictors including International Prostate Symptom Score (IPSS), Quality of Life Score (QoL), body mass index (BMI), diabetes, prostate volume (PV), and prostate-specific antigen (PSA) were selected, based on which a prediction model was constructed. The area under the receiver operating characteristic (ROC) curve of the prediction model was 0.766 0, and the 95% confidence interval was 0.704-0.828. Bootstrap internal validation showed a C-index of 0.766 2, and the calibration model curve coincided well with the actual model curve. The clinical decision curve analysis showed that the model had high accuracy, and net benefit in the probability of urinary incontinence was within 10% to 82%. 【Conclusion】 IPSS, QoL, diabetes, prostate volume, and PSA are predictors that can affect the occurrence of urinary incontinence after HoLEP. The model has high accuracy, identification ability and net benefit.
