Archivos espanoles de urologia · 2024
Development of a Nomogram Model to Predict the Risk of Stricture Recurrence after Urethroplasty: A Retrospective Study.
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Guo Hang, Dai Zhenghao, Zhong Lichang, Jiang Yiwen, Lu Yuting, Liang Tao
Аннотация
OBJECTIVE: A retrospective study was performed to analyse the influencing factors of stricture recurrence after urethroplasty and to establish a predictive nomogram model.
METHODS: The clinical data of patients who underwent urethroplasty in our hospital from January 2021 to June 2023 were retrospectively analysed. Depending on whether stenosis occurs six months after surgery, the patients were divided into recurrence and nonrecurrence groups. Logistic regression analysis was performed on the indicators with statistically significant differences between the two groups in single factor analysis to analyse the influencing factors of postoperative recurrence risk of stricture. X64.4.1.3 version R language and external source packages were used to build the nomogram model. The nomogram was internally validated through 10-fold cross-validation, and C-index was calculated. The area under the curve (AUC) of the receiver operating characteristic curve was employed to evaluate the results of the internal validation.
RESULTS: Amongst 105 patients who underwent urethroplasty in our hospital, 15 patients with recurrence were included in the recurrence group, and 90 patients without recurrence were included in the nonrecurrence group. The length of stricture segment, history of urethroplasty and smoking history within 3 months before surgery were risk factors for stricture recurrence, with odds ratio (OR) values of 1.874 (95% CI: 1.103-5.725), 1.670 (95% CI: 1.105-2.904) and 1.740 (95% CI: 1.456-5.785), respectively. The constructed nomogram obtained an average AUC of 0.842 and an average C-index of 0.794, calculated after 200 times of 10-fold cross-validation.
CONCLUSIONS: From the data of this study, it can be deduced that the influencing factors of stricture recurrence after urethroplasty include the length of stricture segment, history of urethroplasty and smoking history of 3 months before surgery. Using the above factors as a basis to construct a predictive nomogram model is helpful to screen high-risk patients with recurrence of stricture after urethroplasty.
METHODS: The clinical data of patients who underwent urethroplasty in our hospital from January 2021 to June 2023 were retrospectively analysed. Depending on whether stenosis occurs six months after surgery, the patients were divided into recurrence and nonrecurrence groups. Logistic regression analysis was performed on the indicators with statistically significant differences between the two groups in single factor analysis to analyse the influencing factors of postoperative recurrence risk of stricture. X64.4.1.3 version R language and external source packages were used to build the nomogram model. The nomogram was internally validated through 10-fold cross-validation, and C-index was calculated. The area under the curve (AUC) of the receiver operating characteristic curve was employed to evaluate the results of the internal validation.
RESULTS: Amongst 105 patients who underwent urethroplasty in our hospital, 15 patients with recurrence were included in the recurrence group, and 90 patients without recurrence were included in the nonrecurrence group. The length of stricture segment, history of urethroplasty and smoking history within 3 months before surgery were risk factors for stricture recurrence, with odds ratio (OR) values of 1.874 (95% CI: 1.103-5.725), 1.670 (95% CI: 1.105-2.904) and 1.740 (95% CI: 1.456-5.785), respectively. The constructed nomogram obtained an average AUC of 0.842 and an average C-index of 0.794, calculated after 200 times of 10-fold cross-validation.
CONCLUSIONS: From the data of this study, it can be deduced that the influencing factors of stricture recurrence after urethroplasty include the length of stricture segment, history of urethroplasty and smoking history of 3 months before surgery. Using the above factors as a basis to construct a predictive nomogram model is helpful to screen high-risk patients with recurrence of stricture after urethroplasty.