Non-invasive algorithm of enhanced liver fibrosis and liver stiffness measurement with transient elastography for advanced liver fibrosis in chronic hepatitis B

BackgroundThe accuracy of Enhanced Liver Fibrosis (ELF; ADVIA Centaur, Siemens Healthcare Diagnostics, Tarrytown, NY, USA) in assessing liver fibrosis in chronic hepatitis B (CHB) is to be determined. AimTo derive and validate a combined ELF-liver stiffness measurement (LSM) algorithm to predict advanced fibrosis in CHB patients. MethodsUsing the data of a previously reported cohort of 238 CHB patients, an ALT-based LSM algorithm for liver fibrosis was used as a training cohort to evaluate the performance of ELF against liver histology. The best combined ELF-LSM algorithm was then validated in new cohort of 85 CHB patients not previously reported. ResultsIn the training cohort, LSM has better performance of diagnosing advanced (F3) fibrosis (area under the receiver operating characteristics curve [AUROC] 0.83, 95% confidence interval [CI 0.76-0.91] than ELF (AUROC 0.69, 95% CI 0.63-0.75). The optimal cut-off values of ELF were 8.4 to exclude advanced fibrosis, and 10.8 to confirm advanced fibrosis. In the training cohort, an ELF8.4 had a sensitivity of 95% to exclude advanced fibrosis; an ELF>10.8 had a specificity of 92% to confirm advanced fibrosis. In the combined algorithm, low ELF or low LSM could be used to exclude advanced fibrosis as both of them had high sensitivity (90%). To confirm advanced fibrosis, agreement between high ELF and high LSM could improve the negative predictive value specificity (from 65% and 74% to 80%). ConclusionsAn Enhanced Liver Fibrosis - liver stiffness measurement algorithm could improve the accuracy of prediction of either ELF or LSM alone. Liver biopsy could be correctly avoided in approximately 60% of patients.