The changing burden of hepatitis C virus infection in the United States: model-based predictions

Abstract

Background: Chronic hepatitis C virus (HCV) infection causes a substantial health and economic burden in the United States. With the availability of direct-acting antiviral agents, recently approved therapies and those under development, and 1-time birth-cohort screening, the burden of this disease is expected to decrease.

Objective: To predict the effect of new therapies and screening on chronic HCV infection and associated disease outcomes.

Design: Individual-level state-transition model.

Setting: Existing and anticipated therapies and screening for HCV infection in the United States.

Patients: Total HCV-infected population in the United States.

Measurements: The number of cases of chronic HCV infection and outcomes of advanced-stage HCV infection.

Results: The number of cases of chronic HCV infection decreased from 3.2 million in 2001 to 2.3 million in 2013. One-time birth-cohort screening beginning in 2013 is expected to identify 487,000 cases of HCV infection in the next 10 years. In contrast, 1-time universal screening could identify 933,700 cases. With the availability of highly effective therapies, HCV infection could become a rare disease in the next 22 years. Recently approved therapies for HCV infection and 1-time birth-cohort screening could prevent approximately 124,200 cases of decompensated cirrhosis, 78,800 cases of hepatocellular carcinoma, 126,500 liver-related deaths, and 9900 liver transplantations by 2050. Increasing the treatment capacity would further reduce the burden of HCV disease.

Limitation: Institutionalized patients with HCV infection were excluded, and empirical data on the effectiveness of future therapies and on the future annual incidence and treatment capacity of HCV infection are lacking.

Conclusion: New therapies for HCV infection and widespread implementation of screening and treatment will play an important role in reducing the burden of HCV disease. More aggressive screening recommendations are needed to identify a large pool of infected patients.

Primary funding source: National Institutes of Health.

Figure 1

State-transition diagram showing states of the hepatitis C disease-burden model. At any given time, a patient is represented by one of the health states, which are shown by squares. Arrows between states represent possible transitions based on annual probabilities (Appendix Table 1). Patients who are successfully treated transition to the “SVR” state. Patients who achieve SVR from F0–F3 states are assumed to be cured; however, F4 patients after a successful treatment transition to “F4-SVR” state and they could develop further complications. Patients in HCC, DC, and LT have a higher mortality than the general population, therefore can transition to “Liver-Related Death” state. All other patients have the same mortality risk as the general population. Abbreviations: HCV = hepatitis C virus; F0 = METAVIR stage for no liver fibrosis; F1 = METAVIR stage for portal fibrosis without septa; F2 = METAVIR stage for portal fibrosis with few septa; F3 = METAVIR stage for numerous septa without cirrhosis; F4 = METAVIR stage for cirrhosis; SVR = sustained virologic response; DC = decompensated cirrhosis; HCC = hepatocellular carcinoma; LT = liver transplant. Note: the probability of death from other causes exists in every state, but deaths from other causes are not shown in this figure.

Figure 2

The estimated prevalence of chronic hepatitis C virus cases in the United States from 2001 to 2050 under different simulation scenarios. Note: The rare-disease region is calculated based on the definition of a rare disease, and adjusted to the United States population. Based on the Rare Disease Act of 2002 (53), a rare disease affects about 1 in 1500 people. The rare-disease region is increasing with time because of population growth. Natural history = simulation scenario with no screening and no treatment; Pre-DAA = simulation scenario with risk-based screening and peginterferon and ribavirin treatment; Base case = simulation scenario with risk-based and birth-cohort screening, treatment with peginterferon and ribavirin and/or DAAs before 2014, and newly approved and future therapies starting in 2014, and limited treatment capacity; Ideal = simulation scenario with 1-time universal screening, treatment with peginterferon and ribavirin and/or DAAs before 2014, and newly approved and future therapies starting in 2014, and unlimited treatment capacity; DAA = direct-acting antiviral agent.

Figure 3

Model results according to the base-case scenario (column A) and the ideal scenario (column B) of hepatitis C disease burden in the United States from 2001 to 2050. Row 1: the prevalence of fibrosis stages; Row 2: the prevalence of DC and HCC; Row 3: the incidence of DC, DCC, LRD, and LT. Note: The results of the natural-history and pre-DAA scenarios are presented in Appendix Figure 2. Natural history = simulation scenario with no screening and no treatment; Pre-DAA = simulation scenario with risk-based screening and peginterferon and ribavirin treatment; Base case = simulation scenario with risk-based and birth-cohort screening, treatment with peginterferon and ribavirin and/or DAAs before 2014, and newly approved and future therapies starting in 2014, and limited treatment capacity; Ideal = simulation scenario with universal screening, treatment with peginterferon and ribavirin and/or DAAs before 2014, and newly approved and future therapies starting in 2014, and unlimited treatment capacity. Abbreviations: DC = decompensated cirrhosis; HCC = hepatocellular carcinoma; LRD = liver-related deaths; LT = liver transplants; DAA = direct-acting antiviral agent.