Background: Advanced liver fibrosis can result in serious complications (even patient's death) after partial hepatectomy. Preoperatively percutaneous liver biopsy is an invasive and expensive method to assess liver fibrosis. We aim to establish a noninvasive model, on the basis of preoperative biomarkers, to predict liver fibrosis in hepatocellular carcinoma (HCC) patients with hepatitis B virus (HBV) infection.
Methods: The HBV-infected liver cancer patients who had received hepatectomy were retrospectively and prospectively enrolled in this study. Univariate analysis was used to compare the variables of the patients with mild to moderate liver fibrosis and with severe liver fibrosis. The significant factors were selected into binary logistic regression analysis. Factors determined to be significant were used to establish a noninvasive model. Then the diagnostic accuracy of this novel model was examined based on sensitivity, specificity and area under the receiver-operating characteristic curve (AUC).
Results: This study included 2,176 HBV-infected HCC patients who had undergone partial hepatectomy (1,682 retrospective subjects and 494 prospective subjects). Regression analysis indicated that total bilirubin and prothrombin time had positive correlation with liver fibrosis. It also demonstrated that blood platelet count and fibrinogen had negative correlation with liver fibrosis. The AUC values of the model based on these four factors for predicting significant fibrosis, advanced fibrosis and cirrhosis were 0.79-0.83, 0.83-0.85 and 0.85-0.88, respectively.
Conclusion: The results showed that this novel preoperative model was an excellent noninvasive method for assessing liver fibrosis in HBV-infected HCC patients.
Citation： Gao Hengyi, Zhu Feng, Wang Min, Zhang Hang, Ye Dawei, Yang Jiayin, Jiang Li, Liu Chang, Qin Renyi, Yan Lunan, Xiao Guangqin. Preoperatively staging liver fibrosis using noninvasive method in Hepatitis B virus-infected hepatocellular carcinoma patients. West China medical Virtual Journal, 2000, 1(1): 4289-4300-. doi: 10.18632/oncotarget.14024 Copy