A Novel Non-invasive Model for the Prediction of Advanced Liver Fibrosis in Chronic Hepatitis B Patients With NAFLD

Jian Wang; Rui Huang; Jiacheng Liu; Ruimin Lai; Yilin Liu; Chuanwu Zhu; Yuanwang Qiu; Zebao He; Shengxia Yin; Yuxin Chen; Xiaomin Yan; Weimao Ding; Qi Zheng; Jie Li; Chao Wu


J Viral Hepat. 2023;30(4):287-296. 

In This Article

Abstract and Introduction


There are still lack of non-invasive models to evaluate liver fibrosis in chronic hepatitis B (CHB) patients with nonalcoholic fatty liver disease (NAFLD). We aimed to establish a predictive model for advanced fibrosis in these patients. A total of 504 treatment-naive CHB patients with NAFLD who underwent liver biopsy were enrolled and randomly divided into a training set (n = 336) and a validation set (n = 168). Receiver operating characteristic (ROC) curve was used to compare predicting accuracy for the different models. One hundred fifty-six patients (31.0%) had advanced fibrosis. In the training set, platelet, prothrombin time, type 2 diabetes, HBeAg positivity and globulin were significantly associated with advanced fibrosis by multivariable analysis. A predictive model namely PPDHG for advanced fibrosis was developed based on these parameters. The areas under the ROC curve (AUROC) of PPDHG with an optimal cut-off value of −0.980 in predicting advanced fibrosis was 0.817 (95% confidence interval 0.772 to 0.862), with a sensitivity of 81.82% and a specificity of 66.81%. The predicting accuracy of PPDHG for advanced fibrosis was significantly superior to AST to platelet ratio index (APRI), fibrosis-4 score (FIB-4) and NAFLD fibrosis score (NFS). Further analysis revealed that the AUROC of PPDHG remained significantly higher than FIB-4 and NFS indexes, while it was comparable with APRI for predicting advanced fibrosis in the validation set. PPDHG had a better predicting performance than established models for advanced fibrosis in CHB patients with NAFLD. The application of PPDHG can reduce the necessary for liver biopsy in these patients.


Chronic hepatitis B virus (HBV) infection has always been one of leading cause of cirrhosis, and hepatocellular carcinoma (HCC).[1] Nearly one third of patients with cirrhosis are attributed to chronic hepatitis B (CHB).[2] With the prevalence of obesity and lifestyle change, nonalcoholic fatty liver disease (NAFLD) is becoming the most common liver disease with the estimated prevalence rate of 30% worldwide.[3] Although the disease progression of simple steatosis is relatively slow, nonalcoholic steatohepatitis, a severe type of NAFLD, is closely associated with liver cirrhosis and HCC.[4] Therefore, as the two most common chronic liver diseases, the pattern of CHB patients with NAFLD deserve more attention. It is estimated that the prevalence of steatosis in CHB patients is approximately 32.8% which is similar to that of general population.[5] Numerous studies reported that concurrent NAFLD could accelerate the progression of liver fibrosis and was an important risk factor of HCC as well as other severe complications.[6–8] Advanced liver fibrosis is a risk factor for the development of HCC and liver-related mortality in both CHB and NAFLD.[9,10] Thus, accurately assessing advanced liver fibrosis is necessary to formulate optimal therapy and prevent progression of disease in CHB patients with NAFLD.

Liver biopsy has always been recognized as the gold standard for the assessment of liver fibrosis stage. However, several shortcomings limit the widespread utilization of liver biopsy in clinical practice.[11,12] Therefore, non-invasive models are needed to predict liver fibrosis and reduce the needs of liver biopsy. Aspartate transaminase (AST) to platelet (PLT) ratio index (APRI) and the fibrosis-4 score (FIB-4) were initially developed to assess liver fibrosis and cirrhosis in patients with chronic hepatitis C.[13,14] A lot of studies demonstrated that APRI and FIB-4 could be used to predict the stage of liver fibrosis in CHB patients with moderate accuracy and were recommended as substitutions of liver biopsy in resource-limited regions.[15–17] However, the performance of APRI and FIB-4 in predicting liver fibrosis in CHB patients with NAFLD is unclear. In addition, the NAFLD fibrosis score (NFS), containing liver function and metabolic parameters, was demonstrated to identify NAFLD patients with and without advanced fibrosis independently.[18] However, there is still little knowledge about whether the coexistence of CHB may affect the accuracy of NFS for predicting liver fibrosis in patients with NAFLD. In addition, transient elastography is a promising measure for assessing the degree of liver fibrosis and steatosis in chronic liver diseases.[19] However, the accuracy for evaluating liver fibrosis is susceptible by steatosis and obesity, which may limit the clinical application in CHB patients with NAFLD.[15] Therefore, it has been a challenge for evaluating liver fibrosis non-invasively in CHB patients with NAFLD.

Overall, there is a lack of non-invasive model to evaluate liver fibrosis in CHB patients with NAFLD. Thus, this study aimed to establish a novel model for assessing advanced liver fibrosis by a multicentre cohort of CHB patients with NAFLD.