中文English
ISSN 1001-5256 (Print)
ISSN 2097-3497 (Online)
CN 22-1108/R

Risk factors for the development of advanced liver fibrosis in nonalcoholic fatty liver disease and establishment of a nomogram model

DOI: 10.12449/JCH240812
Research funding:

Traditional Chinese Medicine Science Research Project of Henan Province (2018JDZX005);

Traditional Chinese Medicine Science Research Project of Henan Province (2022JDZX006);

“Double First Class” Creation of Engineering Traditional Chinese Medicine Discipline Project Task Book (HSRP-DFCTCM-2023-8-16);

Subject Construction Project of Traditional Chinese Medicine in Henan Province (STG-ZYXKY-2020024);

National Famous TCM Doctor Studio Construction (Guozhongyiyao Renjiaohan [2022] No.245)

More Information
  • Corresponding author: ZHAO Wenxia, zhao-wenxia@163.com (ORCID: 0000-0001-6666-9469)
  • Received Date: 2023-11-22
  • Accepted Date: 2023-12-11
  • Published Date: 2024-08-25
  •   Objective  To investigate the risk factors for the development of advanced liver fibrosis by analyzing the clinical features of patients with in nonalcoholic fatty liver disease (NAFLD) and advanced liver fibrosis, and to establish a nomogram model for predicting the risk of advanced liver fibrosis.  Methods  A retrospective analysis was performed for the clinical data of 406 NAFLD patients who attended The First Affiliated Hospital of Henan University of Chinese Medicine from January 2022 to October 2023, and according to whether liver stiffness measurement (LSM) measured by FibroScan was ≥11.0 kPa, the patients were divided into advanced liver fibrosis group with 65 patients and non-advanced liver fibrosis group with 341 patients. Related data were collected, including general information, laboratory markers, and medical history. The independent-samples t test was used for comparison of normally distributed continuous data between two groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups; the chi-square test was used for comparison of categorical data between two groups. A multivariate Logistic regression analysis was used to identify independent risk factors, and a nomogram model was established based on these factors. The receiver operating characteristic (ROC) curve was used to evaluate the discriminatory ability of the nomogram model, and the calibration curve was used to evaluate its effectiveness.  Results  The univariate analysis showed that there were significant differences between the advanced liver fibrosis group and the non-advanced liver fibrosis group in age, controlled attenuation parameter (CAP), total bilirubin, direct bilirubin (DBil), indirect bilirubin, globin, alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase (ALP), gamma-glutamyl transpeptidase (GGT), glucose, body mass index (BMI), and history of diabetes (all P<0.05). The multivariate Logistic regression analysis showed that CAP (odds ratio [OR]=1.015, 95% confidence interval [CI]: 1.006‍ ‍—‍ ‍1.024, P=0.010), DBil (OR=1.345, 95%CI: 1.139‍ ‍—‍ ‍1.590, P=0.001), ALP (OR=1.019, 95%CI: 1.008‍ ‍—‍ ‍1.029, P=0.001), GGT (OR=1.004, 95%CI: 1.000‍ ‍—‍ ‍1.008, P=0.035) and BMI (OR=1.240, 95%CI: 1.137‍ ‍—‍ ‍1.353, P=0.001) were independent risk factors for the development of advanced liver fibrosis in NAFLD. A nomogram model was established based on the results of the multivariate Logistic regression analysis. The ROC curve analysis showed that this nomogram model had an area under the ROC curve of 0.841 (95%CI: 0.791‍ ‍—‍ ‍0.891) in predicting the development of advanced liver fibrosis in the NAFLD population, and the calibration curve showed a good degree of fitting between the observed and predicted values for the development of advanced liver fibrosis.  Conclusion  Elevated levels of CAP, BMI, DBil, ALP, and GGT are independent risk factors for advanced liver fibrosis in NAFLD. The nomogram model established based on these factors has good predictive performance and a certain value in predicting advanced liver fibrosis.

     

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