Construction and evaluation of a nomogram prediction model for biliary stricture after liver transplantation
10.19405/j.cnki.issn1000-1492.2025.01.022
- VernacularTitle:肝移植术后胆管狭窄列线图预测模型的构建与评价
- Author:
Hongyue Xie
1
;
Xiaoliang Xu
2
;
Qiaoyu Liu
2
;
Beicheng Sun
3
Author Information
1. Dept of Hepatobiliary and Liver Transplantation，Nanjing Drum Tower Hospital，Chinese Academy of Medical Sciences ＆ Peking Union Medical College，Nanjing 210008
2. Dept of Hepatobiliary Pancreas and Transplantation，The First Affiliated Hospital of Anhui Medical University，Hefei 230022
3. Dept of Hepatobiliary and Liver Transplantation，Nanjing Drum Tower Hospital，Chinese Academy of Medical Sciences ＆ Peking Union Medical College，Nanjing 210008; Dept of Hepatobiliary Pancreas and Transplantation，The First Affiliated Hospital of Anhui Medical University，Hefei 230022
- Publication Type:Journal Article
- Keywords:
liver transplantation;
complications after liver transplantation;
biliary stricture;
prediction model;
no- mogram;
risk factor
- From:
Acta Universitatis Medicinalis Anhui
2025;60(1):152-158
- CountryChina
- Language:Chinese
-
Abstract:
Objective : To explore the risk factors of biliary stricture after liver transplantation and to construct a nomogram prediction model.
Methods : The clinical data of 208 liver transplant recipients in hospital were retrospectively analyzed, including 54 cases in the biliary stricture group and 154 cases in the non-biliary stricture group. Multivariate Logistic regression analysis was used to screen out independent predictors, fit the prediction model and construct a visual nomogram to evaluate the prediction model. Survival curves were drawn and multivariate Cox regression analysis was performed.
Results :Autoimmune liver diseases(OR=6.610,95%CI: 1.410-30.99), alanine aminotransferase(ALT)(OR=1.007,95%CI: 1.003-1.011), warm ischemia time(OR=1.972,95%CI: 1.399-2.780), cold ischemia time(OR=1.016,95%CI: 1.010-1.022), cytomegalovirus infection(OR=6.037,95%CI: 1.480-24.63) and hepatic vascular stenosis(OR=7.784,95%CI: 2.312-26.20) were independent predictors of biliary stricture after liver transplantation. The area under the curve(AUC) of the nomogram prediction model was 0.921, the cut-off value was 0.238, the sensitivity was 0.889, and the specificity was 0.838. The model showed good discrimination. The Brier score was 0.092, Hosmer-Lemeshow goodness-of-fit testP=0.253, Calibration curve(B=1 000) was in good agreement, and the model showed good calibration. Decision curve analysis(DCA) showed that the application of the model could benefit liver transplant recipients. The postoperative follow-up time was 27-60 months. The cumulative survival rate of the non-biliary stricture group was better than that of the biliary stricture group(P=0.019), but multivariate Cox regression analysis showed that biliary stricture(HR=1.194, 95%CI: 0.624-2.285) was not an independent risk factor for survival after liver transplantation.
Conclusion :The nomogram model based on autoimmune liver diseases, ALT, warm ischemia time, cold ischemia time, cytomegalovirus infection and hepatic vascular stenosis performs well and can be used to predict the occurrence of biliary stricture after liver transplantation.
- Full text:2026012117172920550肝移植术后胆管狭窄列线图预测模型的构建与评价_解鸿跃.pdf
