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The Changing Burden of Hepatitis C Virus Infection in the United States: Model-Based PredictionsThe Changing Burden of Hepatitis C Virus Infection

Mina Kabiri, MS; Alison B. Jazwinski, MD; Mark S. Roberts, MD; Andrew J. Schaefer, PhD; and Jagpreet Chhatwal, PhD
[+] Article and Author Information

From the University of Pittsburgh and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, and The University of Texas MD Anderson Cancer Center, Houston, Texas.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the views of the National Institutes of Health.

Acknowledgment: The authors thank Elamin Elbasha, PhD, and Katherine Bornschlegel, MPH, for their constructive comments that improved the quality of the manuscript; John Grefenstette, PhD, for technical support on simulation runs; and Jill Delsigne, PhD, and Diane Hackett for editing the manuscript.

Financial Support: By the National Center for Advancing Translational Sciences, National Institutes of Health (award KL2TR000146). Ms. Kabiri is supported by the Department of Health Policy and Management, University of Pittsburgh Graduate School of Public Health.

Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M14-0095.

Reproducible Research Statement:Study protocol: Not applicable. Statistical code and data set: Available from Dr. Chhatwal (e-mail, jchhatwal@mdanderson.org).

Requests for Single Reprints: Jagpreet Chhatwal, PhD, Department of Health Services Research, Unit 1444, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030; e-mail, JChhatwal@mdanderson.org.

Current Author Addresses: Ms. Kabiri and Dr. Roberts: Department of Health Policy and Management, 130 De Soto Street, Pittsburgh, PA 15261.

Dr. Jazwinski: Division of Gastroenterology, Hepatology and Nutrition, Center for Liver Diseases, 3471 Fifth Avenue, 900 Kaufmann Building, Pittsburgh, PA 15213.

Dr. Schaefer: Department of Industrial Engineering, 1048 Benedum Hall, University of Pittsburgh, Pittsburgh, PA 15261.

Dr. Chhatwal: Department of Health Services Research, Unit 1444, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030.

Author Contributions: Conception and design: M. Kabiri, A.B. Jazwinski, M.S. Roberts, J. Chhatwal.

Analysis and interpretation of the data: M. Kabiri, M.S. Roberts, A.J. Schaefer, J. Chhatwal.

Drafting of the article: M. Kabiri, A.B. Jazwinski, J. Chhatwal.

Critical revision of the article for important intellectual content: M. Kabiri, A.B. Jazwinski, M.S. Roberts, A.J. Schaefer, J. Chhatwal.

Final approval of the article: M. Kabiri, A.B. Jazwinski, M.S. Roberts, A.J. Schaefer, J. Chhatwal.

Statistical expertise: M. Kabiri, J. Chhatwal.

Obtaining of funding: A.J. Schaefer, J. Chhatwal.

Administrative, technical, or logistic support: M. Kabiri.

Collection and assembly of data: M. Kabiri.


Ann Intern Med. 2014;161(3):170-180. doi:10.7326/M14-0095
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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.

Figures

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Figure 1.

State-transition diagram showing the states of the simulation 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 (Table 1 of the Supplement). Patients whose disease is successfully treated transition to the SVR state. Patients who achieve SVR from F0 to F3 states are assumed to be cured; however, patients in an F4 state who are successfully treated transition to an F4-SVR state and may develop further complications. Patients in HCC, DC, and LT states have a higher mortality rate than the general population and therefore may transition to an LRD state. All other patients have the same risk for death as the general population. The probability of death from other causes exists in every state, but deaths from other causes are not shown. According to the Meta-analysis of Histologic Data in Viral Hepatitis (METAVIR) scoring system, F0 indicates no fibrosis of the liver, F1 indicates portal fibrosis without septa, F2 indicates portal fibrosis with few septa, F3 indicates many septa without cirrhosis, and F4 indicates cirrhosis. DC = decompensated cirrhosis; HCC = hepatocellular carcinoma; HCV = hepatitis C virus; LRD = liver-related death; LT = liver transplantation; SVR = sustained virologic response.

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Figure 2.

Estimated prevalence of cases of chronic HCV infection in the United States from 2001 to 2050 under different simulation scenarios.

The rare disease region is calculated on the basis of the definition of a rare disease and adjusted to the U.S. population. On the basis of the Rare Diseases Act of 2002 (51), a rare disease affects approximately 1 in 1500 persons. The rare disease region is increasing with time because of population growth. Natural history indicates a simulation scenario with no screening and no treatment. Pre-DAA indicates a simulation scenario with risk-based screening and PEG-RBV treatment. Base case indicates a simulation scenario with risk-based and birth-cohort screening, treatment with PEG-RBV and/or DAAs before 2014 and newly approved and future therapies starting in 2014, and limited treatment capacity. Ideal indicates a simulation scenario with 1-time universal screening, treatment with PEG-RBV and/or DAAs before 2014 and newly approved and future therapies starting in 2014, and unlimited treatment capacity. DAA = direct-acting antiviral; HCV = hepatitis C virus; PEG-RBV = peginterferon and ribavirin.

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Figure 3.

Model results according to the base-case and ideal scenarios of the burden of HCV infection in the United States from 2001 to 2050.

Base case indicates a simulation scenario with risk-based and birth-cohort screening, treatment with PEG-RBV and/or DAAs before 2014 and newly approved and future therapies starting in 2014, and limited treatment capacity. Ideal indicates a simulation scenario with universal screening, treatment with PEG-RBV and/or DAAs before 2014 and newly approved and future therapies starting in 2014, and unlimited treatment capacity. Figure 2 of the Supplement shows the results of the natural-history and pre-DAA scenarios. DAA = direct-acting antiviral; DC = decompensated cirrhosis; HCC = hepatocellular carcinoma; HCV = hepatitis C virus; LRD = liver-related death; LT = liver transplantation; PEG-RBV = peginterferon and ribavirin. A and B. Prevalence of fibrosis stages. C and D. Prevalence of DC and HCC. E and F. Incidence of DC, HCC, LRD, and LT.

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