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Hepatitis C-related liver-fibrosis regression after direct-acting antiviral therapy

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posted on 2022-07-28, 23:33 authored by Muhammad Qasim Malik

Background: In low- and middle-income countries (LMICs), hepatitis C virus (HCV) treatment uptake is increasing given availability of generic highly effective direct-acting antiviral (DAA) therapies. To optimise post-treatment cirrhosis surveillance in resource-limited settings, there is a need to identify people who remain at risk of liver disease progression after DAA cure. Methods: The ‘Enhancing hepatitis C linkage to care’ (ENHANCE) study was a single-arm nonrandomized intervention study that took place in Tehran, Iran in 2018–2020 with the aim of increasing HCV treatment uptake among people who use drugs (PWUDs). HCV FibroScan®, a noninvasive technique of liver stiffness measurement using transient elastography, was used to measure liver fibrosis. This sub-study includes those who received 24 weeks of DAA therapy and had FibroScan® performed before treatment initiation and 12 weeks after end of treatment. Between the two time points, significant fibrosis regression was assessed on the basis absolute and percent change in liver stiffness as well as a > 30% reduction in liver fibrosis. Findings: The primary study population comprised 201 (19%) people who had HCV. Of the individuals who had HCV, 39 (19%) received 24 weeks of DAA therapy. After exclusion of those with incomplete data, 22 participants were included in the analysis of fibrosis regression, less than half (45%, n = 10) of whom had significant fibrosis regression after treatment. In the unadjusted analysis, pre-treatment fibrosis score was the strongest predictor of post-DAA fibrosis regression (regression coefficient -0.89, 95% CI -1.74, -0.04, P 0.039) Interpretation: Degree of fibrosis regression is related to the severity of baseline fibrosis. As people with high fibrosis are at an elevated risk of liver-related morbidity and mortality, baseline data can be used for the identification of these people for post-cure follow-up. This can help optimise the limited resources of LMICs which are insufficient to maintain follow-up of all individuals.


Table of Contents

1. Introduction -- 2. Method -- 3. Results -- 4. Discussion -- 5. Conclusion -- 6. References -- 7. Appendix


A thesis submitted as partial fulfilment of the requirements of the degree of Master of Public Health (Research)

Awarding Institution

Macquarie University

Degree Type

Thesis masters research


Master of Research, Department of Health Systems and Populations, Faculty of Medicine and Health Sciences, Macquarie University

Department, Centre or School

Department of Health Systems and Populations

Year of Award


Principal Supervisor

Janaki Amin

Additional Supervisor 1

Maryam Alavi


Copyright disclaimer: Copyright Muhammad Qasim Malik 2021




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