Combined Serum Golgi Membrane Glycoprotein 73 Improves the Accuracy of Transient Elastography for Significant Fibrosis Detection in Patients with Chronic HBV Infections

Abstract

Background: Golgi membrane glycoprotein 73 (GP73) serum level is a potential biomarker for diagnosing significant fibrosis and cirrhosis in chronic liver diseases. Objectives: The current study aimed to evaluate the accuracy of GP73 serum levels as a biomarker in the diagnosis of significant liver fibrosis in patients with hepatitis B virus (HBV). A new promising algorithm was developed by combining LSM and GP73 to predict significant liver fibrosis. Methods: Information on the following parameters were obtained from 165 patients with HBV: liver stiffness measurement (LSM), serum GP73 level, and some other fibrosis criteria approved for clinical practice. The area under the curve (AUC) and sensitivity and specificity of GP73 were compared with LSM, aminotransferase-to-platelet ratio index (APRI), and 4-factor based fibrosis index (FIB-4) for diagnosing significant fibrosis. Results: Compared to the non-significant liver fibrosis patients, the HBV infected patients with significant fibrosis showed a higher level of serum GP73 [64.05 (24.41 - 144.39) versus 91.30 (31.81 - 200.05) ng/mL, P < 0.001]. Concerning significant fibrosis diagnosis, GP73 exhibited advantages regarding the AUC (0.702), sensitivity (69.3%), and specificity (66.0%). Besides, GP73 did not show any advantage over LSM and APRI, but it had a better performance than FIB-4 in significant fibrosis detection. For the newly developed algorithm combining GP73 with LSM, the AUC, sensitivity, and specificity were 0.848, 77.4%, and 83.5%, respectively; hence, it's superior to LSM (0.832, 72.6%, and 83.5%, respectively; P = 0.016) for diagnosing significant fibrosis. Conclusions: This study demonstrated that GP73 can be considered as a new effective biomarker for diagnosing liver fibrosis. The accuracy of significant fibrosis detection in patients with HBV infection can be improved by the new algorithm that contains GP73 and LSM.