Diagnostic performance of a new algorithm combining simple, non invasive and inexpensive tests for predicting the presence of liver severe fibrosis and cirrhosis in patients with chronic hepatitis b

Background: Various non-invasive methods for scoring fibrosis have been developed to overcome the limitations of liver biopsy. These technics have been not fully validated for the assessment of liver fibrosis in chronic hepatitis B. The objective of this study was to evaluate the usefulness of new combining simple, non-invasive and inexpensive tests in terms of predicting liver severe fibrosis and cirrhosis in patients with chronic hepatitis B. Methods There is a prospective cross-sectional study conducted on 408 consecutive patients from 3 centers who benefited from a liver biopsy for chronic hepatitis B. Using our cohort, we derived a decision tree, with a cost matrix penalizing type II error, predicting patients in stages F0-F1, F2 or F3-F4. The final decision contains nine leafs using the following variables: prothrombin time, platelets, ALT, GGT and age. Results 408 patients in training set were used to create a “decision tree algorithm”. Our “decision three algorithm” classified patients in F0-F1, F2 or F3-F4. Considering F0-F1 and F2 as negative test result, specificity was 97.6% and negative predictive value was 88.3%. Conclusion A new algorithm combining simple, non-invasive and inexpensive test has a better diagnostic value than usual scores in predicting fibrosis in patients with chronic hepatitis B.