Estimation of stage-specific fibrosis progression rates in chronic hepatitis C virus infection: a meta-analysis and meta-regression

Abstract

Published estimates of liver fibrosis progression in individuals with chronic hepatitis C virus (HCV) infection are heterogeneous. We aimed to estimate stage-specific fibrosis progression rates and their determinants in these individuals. A systematic review of published prognostic studies was undertaken. Study inclusion criteria were as follows: (1) presence of HCV infection determined by serological assays; (2) available information about age at assessment of liver disease or HCV acquisition; (3) duration of HCV infection; and (4) histological and/or clinical diagnosis of cirrhosis. Annual stage-specific transition probabilities (F0-->F1, ... , F3-->F4) were derived using the Markov maximum likelihood estimation method and a meta-analysis was performed. The impact of potential covariates was evaluated using meta-regression. A total of 111 studies of individuals with chronic HCV infection (n = 33,121) were included. Based on the random effects model, the estimated annual mean (95% confidence interval) stage-specific transition probabilities were: F0-->F1 0.117 (0.104-0.130); F1-->F2 0.085 (0.075-0.096); F2-->F3 0.120 (0.109-0.133); and F3-->F4 0.116 (0.104-0.129). The estimated prevalence of cirrhosis at 20 years after the infection was 16% (14%-19%) for all studies, 18% (15%-21%) for cross-sectional/retrospective studies, 7% (4%-14%) for retrospective-prospective studies, 18% (16%-21%) for studies conducted in clinical settings, and 7% (4%-12%) for studies conducted in nonclinical settings. Duration of infection was the most consistent factor significantly associated with progression of fibrosis.

Conclusion: Our large systematic review provides increased precision in estimating fibrosis progression in chronic HCV infection and supports nonlinear disease progression. Estimates of progression to cirrhosis from studies conducted in clinical settings were lower than previous estimates.