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ISSN 2097-3497 (Online)
CN 22-1108/R
Volume 37 Issue 7
Jul.  2021
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Article Navigation >  Journal of Clinical Hepatology  > 2021  >  37(7): 1529-1533

Value of a nomogram model in predicting significant liver injury in patients with immune-tolerant phase chronic hepatitis B

DOI: 10.3969/j.issn.1001-5256.2021.07.010
  • 1.

    Department of Liver Diseases, Fifth Medical Center of Chinese PLA General Hospital, Beijing 100039, China

  • 2.

    The Second Clinical Medical School of Southern Medical University, Guangzhou 510515, China

  • 3.

    Peking University 302 Clinical Medical School, Beijing 100039, China

Research funding:

Medical Big Data and Artificial Intelligence Development Fund of Chinese PLA General Hospital (2019MBD-024);

the Capital Characteristic Clinic Project of Beijing Municipal Science and Technology Commission (Z181100001718034);

Key Project of Jumei Special Fund for Hepatobiliary Disease Prevention and Treatment (2018JM12603003)

  • Received Date: 2021-04-07
  • Accepted Date: 2021-04-21
  • Published Date: 2021-07-20
    Abstract
  •   Objective  To investigate the high-risk factors for significant liver injury in patients with immune-tolerant phase chronic hepatitis B (IT-CHB), and to establish a nomogram predictive model.  Methods  A retrospective analysis was performed for the data of 382 patients with chronic HBV infection who underwent liver biopsy in The Fifth Medical Center of Chinese PLA General Hospital from August 2002 to December 2017, and according to the presence or absence of significant liver injury, the patients were divided into significant liver injury group (≥G2/S2) with 82 patients and non-significant liver injury group with 300 patients. The independent samples t-test was used for comparison of normally distributed continuous data between groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups; the Kruskal-Wallis H test was used for comparison between multiple groups; the chi-square test was used for comparison of categorical data between groups. The Spearman rank correlation test was used to investigate correlation. Univariate and multivariate logistic regression analyses were used to screen out high-risk factors and establish a nomogram model. Concordance index (C-index), the receiver operating characteristic (ROC) curve, calibration curve, and the bootstrap method were used to evaluate the discrimination and calibration abilities of the nomogram.  Results  There were significant differences between the two groups in age, HBV DNA load, alanine aminotransferase, aspartate aminotransferase (AST), and platelet count (PLT) (t=-7.071, Z=-4.924, -3.693, -6.945, -0.585 and -5.723, all P < 0.001). The logistic regression analysis showed that age (odds ratio [OR]=1.074, 95% confidence interval [CI]: 1.043-1.107, P < 0.001), HBV DNA load (OR=0.442, 95%CI: 0.314-0.624, P < 0.001), AST(OR=1.096, 95%CI: 1.051-1.142, P < 0.001), and PLT(OR=0.992, 95%CI: 0.986-0.998, P=0.006) were high-risk factors for significant liver injury. The nomogram model established based on the above factors had a C-index of 0.845 in predicting significant liver injury and had a well-fitted calibration curve, with an area under the ROC curve (AUC) of 0.845 (95%CI: 0.795-0.895), which was significantly better than aspartate aminotransferase-to-platelet ratio index (AUC=0.781, 95%CI: 0.723-0.840) and fibrosis-4(AUC=0.802, 95%CI: 0.746-0.859).  Conclusion  There is a high proportion of IT-CHB patients with significant liver injury. The nomogram model established based on age, HBV DNA, AST, and PLT has a good predictive accuracy and can be used to predict significant liver injury in IT-CHB patients individually, reduce the need for liver biopsy, and provide a reference for precise antiviral treatment.

     

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