Expanding screening for hepatitis C virus infection may generate substantial benefits for patients and society, but only when paired with expanded treatment policies.
Published Online: May 03, 2016
Mark T. Linthicum, MPP; Yuri Sanchez Gonzalez, PhD; Karen Mulligan, PhD; Gigi A. Moreno, PhD; David Dreyfus, DBA; Timothy Juday, PhD; Steven E. Marx, PharmD; Darius N. Lakdawalla, PhD; Brian R. Edlin, MD; and Ron Brookmeyer, PhD
Objectives: To investigate the value of expanding screening and treatment for hepatitis C virus (HCV) infection in the United States.
Study Design: Discrete-time Markov model.
Methods: We modeled HCV progression and transmission to analyze the costs and benefits of investment in screening and treatment over a 20-year time horizon. Population-level parameters were estimated using National Health and Nutrition Examination Survey data and published literature. We considered 3 screening scenarios that vary in terms of clinical guidelines and physician awareness of guidelines. For each screening scenario, we modeled 3 approaches to treatment, varying the fibrosis stage of treatment initiation. Net social value was the key model outcome, calculated as the value of benefits from improved quality-adjusted survival and reduced transmission minus screening, treatment, and medical costs.
Results: Expanded screening policies generated the largest value to society. However, this value is constrained by the availability of treatment to diagnosed patients. Screening all individuals in the population generates $0.68 billion in social value if diagnosed patients are treated in fibrosis stages F3-F4 compared with $824 billion if all diagnosed patients in stages F0-F4 are treated. Moreover, increased screening generates cumulative net social value by year 8 to 9 under expanded treatment policies compared with 20 years if only patients in stages F3-F4 are treated.
Conclusions: Although increasing screening for HCV may generate some value to society, only when paired with expanded access to treatment at earlier disease stages will it produce considerable value. Such a “test and treat” strategy is likely to entail higher short-term costs but also yield the greatest social benefits.
Am J Manag Care. 2016;22(5 Spec Issue No. 6):SP227-SP235
We developed a discrete-time Markov model to simulate the effects of expanding screening for hepatitis C virus (HCV) infection and initiating treatment at different fibrosis stages. We compare screening and treatment policies in terms of net social value over a 20-year horizon.
Increased screening generates positive social value in 20 years, but this benefit is reduced without concurrent expansion of treatment.
Investments in HCV screening and treatment are expected to “break even” from a social perspective after 20 to 22 years when treatment is limited to fibrosis stages F3-F4 and after only 8 to 9 years when treatment is expanded to include stages F0-F2.
Chronic infection with hepatitis C virus (HCV) is estimated to affect at least 3.5 million individuals in the United States,1
and the incidence is increasing.2
Chronic HCV infection can lead to hepatic damage, including cirrhosis and hepatocellular carcinoma, and is the most common cause of liver transplantation in the United States.3,4
Because symptoms of HCV infection are usually absent or nonspecific until late stages of the disease, an estimated 50% to 75% of infected individuals are unaware of their HCV status and get tested only after significant symptoms develop.5-7
Prior research suggests that earlier identification and treatment of patients infected with HCV generates benefits for patients and society, but the potential social value of increased screening, whether alone or in combination with early treatment, is not well understood.3,8-12
Novel HCV regimens, including direct-acting antivirals (DAAs), have increased cure rates dramatically, which may affect the value of expanded screening.13,14
For example, rates of sustained virologic response (SVR) observed in clinical trials of DAA treatments generally exceed 98% for patients infected with genotype 1 HCV without cirrhosis or prior treatment failure.15-19
Despite rapid innovation in HCV treatment, however, unmet need remains significant. Only 13% to 36% of patients diagnosed with chronic HCV infection have received treatment,3
and even fewer patients completed the treatment regimen and achieved SVR.20
Failures to screen, diagnose, and treat all contribute to this current state of affairs.
Broad consensus exists on the need for inclusive screening. In 2012, the CDC updated its guidelines and recommended expanding screening to include all individuals born between 1945 and 1965 (baby boomers)—a cohort comprising an estimated 75% of existing HCV infections.21
Similarly, the American Association for the Study of Liver Diseases (AASLD) and the Infectious Diseases Society of America (IDSA) updated their guidelines in 2015 to recommend one-time screening for asymptomatic baby boomers.3
Unfortunately, more than 40% of physicians are unaware of current guidelines,21,22
and many individuals infected with HCV may have limited contact with the healthcare system. For these and other reasons, HCV screening rates remain below recommended levels.
It remains unclear whether and to what extent expanded screening benefits society. All-oral DAA regimens present considerable up-front costs23
; yet recent research suggests the value of their long-term health benefits is likely to be even higher.12
Screening can identify potentially treatable patients, with implications for both healthcare costs and health benefits. In this article, we explore whether and to what extent expanded screening policies provide net value to society and assess the net social value of varying levels of access to treatment after diagnosis.
Overview of the Markov Model of HCV Transmission and Progression
In this article, we present results of a discrete-time Markov simulation model (Microsoft Excel 2010/VBA, Microsoft Corporation, Redmond, Washington) that simulates the detection, treatment, and progression of populations susceptible to HCV infection, as well as associated costs and health benefits, under different screening and treatment policies. The model builds on previous work that simulates the effects of treatment policies (without screening) on population-level costs, health benefits, and disease dynamics.12
The model tracks infected and uninfected individuals in 3 groups, stratified by risk of HCV exposure: a) people who inject drugs (PWID), b) HIV-positive men who have sex with men (MSM-HIV), and c) all other adults born before 1992, when systematic testing of the blood supply for HCV began (Other Adults). Of the last group, approximately 39% were baby boomers.5
The model further stratifies the infected population in each risk group by HCV genotypes 1, 2, and 3, which account for 70%, 16%, and 12% of the US population infected with HCV, respectively.24
PDF is available on the last page.