Establishment and validation of a simple noninvasive model to predict significant liver fibrosis in patients with chronic hepatitis B.

Background: There have been still few valuable noninvasive models that can be used as indirect markers of liver fibrosis in chronic hepatitis B (CHB) infection.

Methods: In 374 patients with chronic hepatitis B virus infection, the correlation between the conventional parameters and significant fibrosis confirmed by liver biopsy was assessed using univariate analysis and logistic regression. A model was established and assessed by the receiver operating characteristic (ROC) curves. Then it was validated in 108 prospectively enrolled patients. A part of the patients were followed up with cirrhosis as the end point, using survival analysis to assess the prognostic value of the model.

Results: A model named AIAG was constructed consisting of age, international normalized ratio, albumin, and gamma-glutamyltransferase which could discriminate between CHB patients with and without significant fibrosis. The area under ROC curves was 0.842 (95% CI, 0.795-0.888) for the training group (n = 250) and 0.806 (95% CI, 0.730-0.882) for the validation group (n = 124). In the training group, using a cut-off score of <0.32, the presence of significant fibrosis could be excluded with high accuracy (90% negative predictive value); similarly, applying a cut-off score of >0.72, the presence of significant fibrosis could be correctly identified with high accuracy (93% positive predictive value). Similar results have been shown in the internal and external validation groups. In the follow-up study, we found that the AIAG score may have good prognostic values to predict the progression of clinically overt cirrhosis in CHB patients.

Conclusions: AIAG, a simple marker panel consisting of conventional parameters, could easily predict significant fibrosis with a high degree of accuracy.