The development of a non-invasive model to predict the presence of non-alcoholic steatohepatitis in patients with non-alcoholic fatty liver disease.

Background: Non-alcoholic steatohepatitis (NASH) is an advanced and aggressive form of non-alcoholic fatty liver disease (NAFLD), which remains difficult to diagnose without a liver biopsy. Hyperferritinemia has increasingly been associated with the presence of NASH. Hence, we sought to explore the relationship between ferritin and NASH and to develop a composite model based on ferritin to predict the presence of NASH.

Methods: A total of 405 patients with biopsy-proven NAFLD were enrolled in the study. Comparison was explored to assess differences between patients with and without NASH, upon which a scoring model was established using variables found to be independent predictors of NASH.

Results: Among all patients with NAFLD, 291 (72%) had biopsy-proven NASH, and 114 (28%) had non-NASH. Mean age was 48 ± 12 years, and 56% were female. Ferritin was significantly higher in NASH compared with non-NASH patients (184 vs 126, respectively; P < 0.001) but lacked diagnostic accuracy for predicting NASH alone (area under the curve [AUC 0.62]). The addition of other significant variables such as aspartate aminotransferase, body mass index, platelet count, diabetes, and hypertension to ferritin improved the prediction of NASH with an AUC 0.81 (95% confidence interval: 0.76-0.86). Internal validation of the model using imputed data sets demonstrated that AUC did not change materially.

Conclusions: While higher ferritin was significantly associated with NASH, ferritin alone lacked diagnostic accuracy to predict NASH. However, incorporating several easily obtainable variables with ferritin allowed the construction of a novel scoring system that can be easily applied in the clinical setting to guide management of NAFLD.