Complex non-invasive fibrosis models are more accurate than simple models in non-alcoholic fatty liver disease.

Journal of gastroenterology and hepatology

Adams LA, George J, Bugianesi E, Rossi E, de Boer WB, van der Poorten D, Ching HL, Bulsara M, Jeffrey GP

2011 J. Gastroenterol. Hepatol. Volume 26 Issue 10

PubMed 21950746 DOI 10.1111/j.1440-1746.2011.06774.x

FibroTest Reliability Independant Team vs. Biomarkers Metabolic Diseases Fibrosis


Significant hepatic fibrosis is prognostic of liver morbidity and mortality in non-alcoholic fatty liver disease (NAFLD); however, it remains unclear whether non-invasive fibrosis models can determine this end-point. We therefore compared the accuracy of simple bedside versus complex fibrosis models across a range of fibrosis in a multi-centre NAFLD cohort.


Simple (APRI, BARD) and complex (Hepascore, Fibrotest, FIB4) fibrosis models were calculated in 242 NAFLD subjects undergoing liver biopsy. Significant (F2-4) and advanced fibrosis (F3,4) were defined using Kleiner criteria. Models were compared using area under the receiver operator characteristic curves (AUC). Cut-offs were determined by Youden Index or 90% predictive values.


For significant fibrosis, non-invasive fibrosis models had modest accuracy (AUC 0.707-0.743) with BARD being least accurate (AUC 0.609, P < 0.05 vs others). Using single cut-offs, sensitivities and predictive values were < 80%; using two cut-offs, > 75% of subjects fell within indeterminate ranges. Simple models had significantly more subjects within indeterminate ranges than complex models (99.1-100% vs 82.1-84.4% respectively, P < 0.05 for all). For advanced fibrosis, complex models were more accurate than BARD (AUC 0.802-0.858 vs 0.701, P < 0.05). Using two cut-offs, complex models had fewer individuals within indeterminate ranges than BARD (11.1-32.3% vs 70.7%, P < 0.01 for all). For cirrhosis, complex models had higher AUC values than simple models.


In NAFLD subjects, non-invasive models have modest accuracy for determining significant fibrosis and have predictive values less than 90% in the majority of subjects. Complex models are more accurate than simple bedside models across a range of fibrosis.

Citation Reference: