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.