Abstract
Although a liver stiffness measurement-based model can precisely predict significant intrahepatic inflammation, transient elastography is not commonly available in a primary care center. Additionally, high body mass index and bilirubinemia have notable effects on the accuracy of transient elastography. The present study aimed to create a noninvasive scoring system for the prediction of intrahepatic inflammatory activity related to chronic hepatitis B, without the aid of transient elastography. A total of 396 patients with chronic hepatitis B were enrolled in the present study. Liver biopsies were performed, liver histology was scored using the Scheuer scoring system, and serum markers and liver function were investigated. Inflammatory activity scoring models were constructed for both hepatitis B envelope antigen (+) and hepatitis B envelope antigen (−) patients. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve were 86.00%, 84.80%, 62.32%, 95.39%, and 0.9219, respectively, in the hepatitis B envelope antigen (+) group and 91.89%, 89.86%, 70.83%, 97.64%, and 0.9691, respectively, in the hepatitis B envelope antigen (−) group. Significant inflammation related to chronic hepatitis B can be predicted with satisfactory accuracy by using our logistic regression-based scoring system.
Highlights
Liver biopsy-based histology is critical for prognosis evaluation and decision making with regard to antiviral treatment in patients with chronic hepatitis B (CHB)
We constructed a predictive model based on serum markers for significant inflammation related to CHB
least absolute shrinkage and selection operator (LASSO) logistic regression and MCP logistic regression have been proposed for the assessment of data with large number of independent variables[19,20]
Summary
Liver biopsy-based histology is critical for prognosis evaluation and decision making with regard to antiviral treatment in patients with chronic hepatitis B (CHB). The key information provided by liver biopsy includes the stage of fibrosis, grade of inflammation, and presence of accompanying diseases. For the noninvasive prediction of fibrosis related to chronic hepatitis C (CHC), several scoring systems have been developed, such as the APRI and FIB-4 index[1,2]. For the prediction of fibrosis related to CHB, the APRI and FIB-4 index might have moderate or even unsatisfactory sensitivity and accuracy[3,4]. LSM cannot replace liver biopsy currently, as it cannot provide information on intrahepatic inflammation. We reported an LSM-based prediction model for inflammatory activity related to CHB, which has high accuracy with balanced sensitivity and specificity[14]. The present study aims to create a noninvasive scoring system for the prediction of intrahepatic inflammatory activity related to CHB, without the aid of transient elastography
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