A Non-invasive Model for Predicting Liver Inflammation in Chronic Hepatitis B Patients With Normal Serum Alanine Aminotransferase Levels.

Xiaoke Li,Shuo Li,Xiaobin Zao,Ningyi Zhang,Yufeng Xing,Xuehua Sun,Xu Cao,Guangdong Tong,Zhenhua Zhou,Zhiyi Han,Zhiguo Li,Yueqiu Gao,Jiaxin Zhang,Xiaoling Chi,Hongbo Du,Ludan Zhang,Hang Xiao ,Daoguo Zhou ,Peng Zhāng ,Yongan Ye

doi:10.3389/fmed.2021.688091

Abstract

Background and Aims: Chronic hepatitis B (CHB) patients with normal alanine aminotransferase (ALT) levels are at risk of disease progression. Currently, liver biopsy is suggested to identify this population. We aimed to establish a non-invasive diagnostic model to identify patients with significant liver inflammation.Method: A total of 504 CHB patients who had undergone liver biopsy with normal ALT levels were randomized into a training set (n = 310) and a validation set (n = 194). Independent variables were analyzed by stepwise logistic regression analysis. After the predictive model for diagnosing significant inflammation (Scheuer's system, G ≥ 2) was established, a nomogram was generated. Discrimination and calibration aspects of the model were measured using the area under the receiver operating characteristic curve (AUC) and assessment of a calibration curve. Clinical significance was evaluated by decision curve analysis (DCA).Result: The model was composed of 4 variables: aspartate aminotransferase (AST) levels, γ-glutamyl transpeptidase (GGT) levels, hepatitis B surface antigen (HBsAg) levels, and platelet (PLT) counts. Good discrimination and calibration of the model were observed in the training and validation sets (AUC = 0.87 and 0.86, respectively). The best cutoff point for the model was 0.12, where the specificity was 83.43%, the sensitivity was 77.42%, and the positive likelihood and negative likelihood ratios were 4.67 and 0.27, respectively. The model's predictive capability was superior to that of each single indicator.Conclusion: This study provides a non-invasive approach for predicting significant liver inflammation in CHB patients with normal ALT. Nomograms may help to identify target patients to allow timely initiation of antiviral treatment.

Highlights

Hepatitis B virus (HBV) infection is a global public health problem and a major contributor to liver cirrhosis and liver cancer
We explored whether use of the lower upper limit of normal (ULN) of alanine aminotransferase (ALT) level, which was suggested by AASLD guideline (35 IU/L in males and 25 IU/L in females, that are lower than the conventional threshold of 40 IU/L), can improve the detection of hepatocyte inflammation
We focused on effectively diagnosing significant liver inflammation in a population with completely normal serum ALT levels

Summary

Introduction

Hepatitis B virus (HBV) infection is a global public health problem and a major contributor to liver cirrhosis and liver cancer. The prevalence of chronic HBV infection varies geographically from 2 to 8%, and there are ∼240,000,000 chronic HBV surface antigen (HBsAg) carriers globally [1]. China has the largest chronic hepatitis B (CHB) population in the world. Aggressive antiviral treatment is essential to disrupt the progression of the disease, the initiation of which depends on whether the levels of serum liver enzymes, especially alanine aminotransferase (ALT), are abnormal. Various guidelines use an abnormal ALT level as a significant indicator to assess disease progression in CHB patients and to guide the initiation of antiviral therapy. Chronic hepatitis B (CHB) patients with normal alanine aminotransferase (ALT) levels are at risk of disease progression. We aimed to establish a non-invasive diagnostic model to identify patients with significant liver inflammation

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