Changes in Serum Interferon Gamma and Interleukin-10 in Relation to Direct-Acting Antiviral Therapy of Chronic Hepatitis C Genotype 4: A Pilot Study

Introduction

This study analyzes the changing levels of circulating inflammatory cytokines Interferon gamma (IFN-γ) and interleukin (IL)-10 (as the main cytokines of T-helper-1 and T-helper-2 immune responses) in patients with chronic hepatitis C virus (HCV) infection undergoing therapy with direct-acting antivirals (DAAs) and to correlate them with laboratory markers.

Methods

This Pilot study included 50 HCV monoinfected patients who received DAAs for 12 or 24 weeks. They were followed up monthly during therapy and 3 months after the end of the treatment. Liver disease was determined by transient elastography, in addition to FIB-4 indices. Analysis of IFN-gamma and IL-10 was carried out using an enzyme-linked immunosorbent assay.

Results

All patients carried HCV genotype 4. The Sustained virological response was 100% and 92% in cirrhotics and noncirrhotics, respectively. There was no significant difference between groups in baseline IL-10 or IFN-gamma. In noncirrhotics, IL-10 showed a significant reduction at Week 4 after treatment start. In cirrhotics, IL-10 showed a significant reduction at Week 4 after treatment starts and a significant reduction at Week 12 after the end of the treatment. At Week 12 after the end of the treatment, serum IL-10 levels were significantly lower in cirrhotics. IFN-γ showed nonsignificant changes in noncirrhotics. A significant increase of IFN-γ occurred in cirrhotics from Week 4 after treatment starts to 12 weeks after the end of the treatment. IFN-γ was significantly higher in cirrhotics at Week 12 after the end of the treatment. IFN-γ and IL-10 showed different correlations with laboratory markers.

Conclusion

Viral eradication induced by DAAs caused a significant change in IL-10 and IFN-gamma.

Validation of a machine learning approach using FIB-4 and APRI scores assessed by the metavir scoring system: A cohort study

BACKGROUND AND STUDY AIM

The study aim was to improve and validate the accuracy of the fibrosis-4 (FIB-4) and aspartate aminotransferase-to-platelet ratio index (APRI) scores for use in a potential machine-learning (ML) method that accurately predicts the extent of liver fibrosis.

PATIENTS AND METHODS

This retrospective multicenter study included 69,106 patients with chronic hepatitis C planned for antiviral therapy from January 2010-December 2014 with liver biopsy results. FIB-4 and APRI scores were calculated and their performance for predicting significant liver fibrosis (F3-F4) assessed against the Metavir scoring system. ML was used for feature selection and reduction to identify the most relevant attributes (CfsSubseteval/best first) for prediction.

RESULTS

In this study, 57,492 (83.2%) patients were F0-F2, and 11,615 (16.8%) patients were F3-F4. The revalidation of FIB-4 and APRI showed lower accuracy and higher disagreement with the biopsy results, with AUCs of 0.68 and 0.58, respectively. FIB-4 diagnosed fewer (14%) F3-F4 patients, and the high specificity and negative predictive values of FIB-4 and APRI reflected the low prevalence of F3-F4 in the study population. Out of 15 attributes, age (>35 years), AFP (>6.5 ng/ml), and platelet count (<150,000/mm³) were the most relevant risk attributes, and patients with one or more of these risk factors were likely to be F3-F4, with a classification accuracy of ≤ 92% and receiver operating characteristics area of 0.74.

CONCLUSION

FIB-4 and APRI scores were not very accurate and missed diagnosing most of the F3-F4 patients. ML implementation improved medical decisions and minimized the required clinical data to three risk factors.