Noninvasive predictive models of liver fibrosis in patients with chronic hepatitis B

Objective: The aim of the present study was to establish noninvasive diagnostic models for liver fibrosis and assess their predictive accuracy (AC). Methods: A total of 349 patients with chronic hepatitis B virus infection were evaluated, who underwent liver biopsy and pathologic examination at Beijing Ditan Hospital affiliated to Capital Medical University. Patients were subdivided in disease-immune tolerant (n = 125) and immune reactive HBeAg positive ( n = 224) groups. Diagnostic models were based on independent markers of liver fibrosis. Receiver operating characteristic (ROC) curves were used to set cutoff values and determine the diagnostic value of the models. Results: Wang I and Wang II models were constructed using independent disease markers. Wang I model cutoff values <= 1.75 and > 5.84 were used to identify patients in the immune tolerant phase with or without significant fibrosis. The area under the ROC curve (AUC) for this model was 0.866 (95% CI, 0.790, 0.942) and an AC of 92.0% was obtained. Wang II model cutoff values <= 3.79 and > 7.06 were used to identify immune reactive HBeAg-positive patients with or without significant fibrosis. AUC was 0.872 ( 95% CI, 0.824, 0.920), with an AC of 88.0%. Conclusions: Both Wang models enabled noninvasive liver fibrosis assessment with reliable predictive power and reproducibility for diagnosis of fibrosis in immune tolerant and immune reactive HBeAg-positive patients. With further development, these models may provide a clinical alternative to liver biopsy.