Model consisting of ultrasonographic and simple blood indexes accurately identify compensated hepatitis B cirrhosis


Professor Jin-Lin Hou, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China. Email:


Background and Aim:  Several models for significant fibrosis or cirrhosis have been introduced for hepatitis C, but are seldom for hepatitis B. The present study retrospectively evaluates the relationship between ultrasonography, blood tests, and fibrosis stage, and constructs a model for predicting compensated cirrhosis.

Methods:  A total of 653 patients with chronic hepatitis B who underwent liver biopsies, ultrasonographic scanning, and routine blood tests were retrospectively analyzed. The patients were divided into the model set and validation set. Blood tests and ultrasonographic indexes were analyzed statistically. An ultrasonographic scoring system consisting of liver parenchyma, gallbladder, hepatic vessel, and splenomegaly was introduced.

Results:  There were significant differences between cirrhosis and other fibrosis stages in ultrasonographic indexes of liver parenchyma, gallbladder, hepatic vessel, and splenomegaly. Ultrasonographic scores were significantly different between F4 and other fibrosis, and significantly correlated with fibrosis stage. Apart from alanine aminotransferase and alkaline phosphatase, blood tests and patients' age were correlated with fibrosis, and were significantly different between patients with and without cirrhosis. The model for cirrhosis indexes consisting of ultrasonographic score, patient's age, and variables, including platelet, albumin, and bilirubin predicted cirrhosis with area under receiver–operator curve of 0.907 in the model set and 0.849 in the validation set. Using proper cut-off values, nearly 81% patients could be accurately assessed for the absence or presence of cirrhosis.

Conclusion:  The model consisting of ultrasonographic score, patients' age, blood variables of platelet, albumin, and bilirubin can identify hepatitis B cirrhosis with a high degree of accuracy. The application of this model would greatly reduce the number of biopsies.