Development of a novel diagnostic algorithm to predict NASH in HCV-positive patients.

ABSTRACT

Non-alcoholic steato-hepatitis (NASH) is a severe disease characterised by liver inflammation and progressive hepatic fibrosis, which may progress to cirrhosis and hepatocellular carcinoma. Clinical evidence suggests that in hepatitis C virus patients steatosis and NASH are associated with faster fibrosis progression and hepatocellular carcinoma. A safe and reliable non-invasive diagnostic method to detect NASH at its early stages is still needed to prevent progression of the disease. We prospectively enrolled 91 hepatitis C virus-positive patients with histologically proven chronic liver disease 77 patients were included in our study; of these, 10 had NASH. For each patient, various clinical and serological variables were collected. Different algorithms combining squamous cell carcinoma antigen-immunoglobulin-M (SCCA-IgM) levels with other common clinical data were created to provide the probability of having NASH. Our analysis revealed a statistically significant correlation between the histological presence of NASH and SCCA-IgM, insulin, homeostasis model assessment, haemoglobin, high-density lipoprotein and ferritin levels, and smoke. Compared to the use of a single marker, algorithms that combined four, six or seven variables identified NASH with higher accuracy. The best diagnostic performance was obtained with the logistic regression combination, which included all seven variables correlated with NASH. The combination of SCCA-IgM with common clinical data shows promising diagnostic performance for the detection of NASH in hepatitis C virus patients.