首页|Establishment and Validation of a nomogram for Predicting the Risk of Liver Fibrosis in Chronic HBV Infection
Establishment and Validation of a nomogram for Predicting the Risk of Liver Fibrosis in Chronic HBV Infection
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NETL
NSTL
万方数据
维普
Objective: To establish a non-invasive quantitative and visual predictive model for assessing the occurrence of significant fibrosis in chronic HBV infection, and to present nomogram to validate the efficacy. Methods: A total of 180 patients with chronic HBV infection that were admitted to the Department of Infectious Liver Diseases of the First Affiliated Hospital of Hainan Medical University from January 2019 to December 2021 with informed consent and underwent liver biopsy puncture were selected.131 patients and 49 patients were randomly divided into a model group and a validation group according to randomization. The patients were divided into non-significant fibrosis and significant fibrosis groups in the modeling group. To collect the clinic information, serological examination, liver elastography and liver histopathology results and to establish a rosette model to predict the risk of chronic HBV infection with significant fibrosis. Results: A total of 180 patients with chronic HBV infection were included, and 113 patients (62.7％) had significant fibrosis. In the modeling set,84 patients(64.1％) had significant fibrosis. In the modeled group, comparison of HBV DNA, PLT, ALT, AST, ALP, ALB, PAB, IL-6, HA, PⅢP, CIV, L.N and LSM for non-significant fibrosis and significant fibrosis showed statistically significant differences. The 氈2 values of the H-L goodness-of-fit test for the modelling and validation groups were 4.988 and 0.527, respectively, corresponding to P values of 0.08 and 0.77, suggesting that the nomogram has good predictive accuracy; the area under the ROC curve of the column line plot predicting the occurrence of significant fibrosis after HBV infection for the modelling and validation groups was 0.843[95％CI(0.775-0.910)] and 0.776[95％CI(0.714-0.838)], suggesting that the column line plot model has good discrimination. Conclusion: After stepwise regression analysis, it was established that ALB, HA, PⅢP, LSM and IL-6 were more closely associated with the occurrence of significant fibrosis after HBV infection, and a visualization of the occurrence of significant fibrosis column line graph model was established by comprehensive assessment, and validation was given that all were superior to the traditional models FIB-4 and APRI.
Chronic HBV infectionLiver fibrosisNomogram
HUANG Sheng-kai、FU Wei、SUN Long
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海南省自然科学基金Youth Cultivation Fund Project of the First Affiliated Hospital of Hainan Medical University
NETL
NSTL
万方数据
维普
