Comparison of Liver Disease State Progression in Patients With Eradication of Versus Persistent Infection With Hepatitis C Virus

Markov Chain Analysis

Toshifumi Tada; Hidenori Toyoda; Takashi Kumada; Akemi Kurisu; Aya Sugiyama; Tomoyuki Akita; Masayuki Ohisa; Hiroshi Aikata; Daiki Miki; Kazuaki Chayama; Junko Tanaka


J Viral Hepat. 2021;28(3):538-547. 

In This Article

Abstract and Introduction


To investigate the long-term prognosis of liver disease in patients with hepatitis C virus (HCV) eradication after antiviral therapy versus those with persistent HCV infection. Four hundred and eighty patients (5259 person-years [PYs]) who received interferon-based therapy and achieved sustained virologic response and 848 patients (3853 PYs) with persistent HCV infection were included. In the analysis of 1-year liver disease state transition probability matrices using Markov chain models, progression to cirrhosis from the chronic hepatitis state was observed (0.00%–0.63%) in patients with HCV eradication. Among patients with chronic hepatitis or cirrhosis and HCV eradication, hepatocellular carcinoma (HCC) development was observed in males aged ≥ 50 years (0.97%–1.96%) and females aged ≥ 60 years (0.26%–5.00%). Additionally, in patients with cirrhosis and HCV eradication, improvement to chronic hepatitis was also observed (4.94%–10.64%). Conversely, in patients with chronic hepatitis and persistent HCV infection, progression to cirrhosis was observed in males aged ≥ 30 years and female aged ≥ 40 years (0.44%–1.99%). In males aged ≥ 40 years and female aged ≥ 50 years with cirrhosis, the transition probability for HCC was relatively high (4.17%–14.02%). Under the assumption of either chronic hepatitis or cirrhosis at age 40 or 60 years as the starting condition for simulation over the next 30 or 40 years, respectively, the probability of HCC was higher in patients with persistent HCV infection than those with HCV eradication. In conclusion, HCV eradication can reduce the risk of developing cirrhosis or HCC in patients with chronic HCV infection.


Approximately 71 million people worldwide are chronically infected with hepatitis C virus (HCV). Chronic HCV infection is associated with chronic hepatitis, cirrhosis and hepatocellular carcinoma (HCC), particularly in the Asia-Pacific region, Middle East and North Africa, South America and Western Europe.[1,2] In addition, HCV infection is a major cause of liver dysfunction and progression of fibrosis. Persistent HCV infection leads to long-term sequelae such as cirrhosis and HCC.

Interferon (IFN)-based therapy has been used to treat patients with chronic HCV-related liver diseases such as chronic hepatitis and compensated cirrhosis. Many researchers have reported that IFN-based therapy is effective for decreasing serum alanine aminotransferase (ALT) levels, eradicating HCV RNA and improving liver function, and retarding fibrosis in patients with chronic HCV infection.[3–7] Liver-related mortality and non–liver-related mortality have been reported to be lower among patients with HCV eradication.[8,9] IFN-based therapy clearly decreases the rate of all-cause mortality and improves life expectancy.[8–12] Well-tolerated, highly efficacious and safe[13] direct-acting antiviral (DAA) therapy for chronic HCV infection, with cure rates > 95%, has ushered in a new era in which eradication of HCV is conceivable. Many patients with chronic HCV infection, including those with chronic liver diseases such as chronic hepatitis and cirrhosis, have recently achieved sustained virologic response (SVR) with DAA therapy.[13] Therefore, clarifying the long-term outcomes of liver disease (eg > 30 years) in patients with HCV eradication versus patients with persistent HCV infection is important for estimating the benefits of DAA-based therapy.

Markov chain models are useful for simulating and evaluating chronic disease progression.[14,15] In a Markov chain model, the clinical disease states are defined individually and integrated into a system of transitional probabilities from one state to another within cycles of a given duration, usually 1 year. In addition, this model is useful because transitional probabilities can be obtained from a relatively small cohort of patients who are followed regularly for only a few years.

In this study, we investigated the long-term prognosis of liver disease in patients with chronic HCV infection who received IFN-based therapy and achieved SVR versus those who did not receive antiviral therapy and had persistent HCV infection. We used Markov chain models to obtain the transitional probabilities of HCV-related liver disease states in this cohort.