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The American Journal of Managed Care Special Issue: HCV
Real-World Outcomes of Ledipasvir/Sofosbuvir in Treatment-Naïve Patients With Hepatitis C
Zobair M. Younossi, MD, MPH, FACG, AGAF, FAASLD; Haesuk Park, PhD; Stuart C. Gordon, MD; John R. Ferguson; Aijaz Ahmed, MD; Douglas Dieterich, MD; and Sammy Saab, MD, MPH
Sofosbuvir Initial Therapy Abandonment and Manufacturer Coupons in a Commercially Insured Population
Taruja D. Karmarkar, MHS; Catherine I. Starner, PharmD; Yang Qiu, MS; Kirsten Tiberg, RPh; and Patrick P. Gleason, PharmD
Improving HCV Cure Rates in HIV-Coinfected Patients - A Real-World Perspective
Seetha Lakshmi, MD; Maria Alcaide, MD; Ana M. Palacio, MD, MPH; Mohammed Shaikhomer, MD; Abigail L. Alexander, MS; Genevieve Gill-Wiehl, BA; Aman Pandey, BS; Kunal Patel, BS; Dushyantha Jayaweera, MD; and Maria Del Pilar Hernandez, MD
Does Patient Cost Sharing for HCV Drugs Make Sense?
Darius N. Lakdawalla, PhD; Mark T. Linthicum, MPP; and Jacqueline Vanderpuye-Orgle, PhD
A Way Out of the Dismal Arithmetic of Hepatitis C Treatment
Jay Bhattacharya, MD, PhD, Center for Primary Care and Outcomes Research, Stanford University School of Medicine; Guest Editor-in-Chief for the HCV special issue of The American Journal of Managed
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Value of Expanding HCV Screening and Treatment Policies in the United States
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
Costs and Spillover Effects of Private Insurers' Coverage of Hepatitis C Treatment
Gigi A. Moreno, PhD; Karen Mulligan, PhD; Caroline Huber, MPH; Mark T. Linthicum, MPP; David Dreyfus, DBA; Timothy Juday, PhD; Steven E. Marx, PharmD; Yuri Sanchez Gonzalez, PhD; Ron Brookmeyer, PhD; and Darius N. Lakdawalla, PhD
Coverage for Hepatitis C Drugs in Medicare Part D
Jeah Kyoungrae Jung, PhD; Roger Feldman, PhD; Chelim Cheong, PhD; Ping Du, MD, PhD; and Douglas Leslie, PhD

Value of Expanding HCV Screening and Treatment Policies in the United States

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
Expanding screening for hepatitis C virus infection may generate substantial benefits for patients and society, but only when paired with expanded treatment policies.
Once infected, individuals progress through disease states according to transition probabilities drawn from the literature (see eAppendix, available at Undiagnosed patients face some probability of screening, which varies across the 3 scenarios described below. Diagnosed patients face a probability of treatment that varies according to 3 treatment policy scenarios. If successfully treated, cured patients return to the pool of susceptible, uninfected individuals and experience the same probability of reinfection as those without a previous infection.
The 3 HCV risk groups were modeled independently, such that individuals do not switch among risk groups and cannot infect individuals in a different risk group. Although patients are infected with only 1 genotype at a time, once cured they can be re-infected with any genotype. HCV transmission in the MSM-HIV and PWID risk groups is based on the number of infected individuals in each risk group and genotype, and is described in detail in the eAppendix.25 Outside of the PWID and MSM-HIV groups, the risk of HCV transmission is low.8,25-27 Therefore, we made the simplifying assumption of no further transmission of HCV in the Other Adults group.
Key model inputs included starting population size, transmission probabilities, and progression rates in each risk group; genotype and disease state at diagnosis; HCV treatment costs; nontreatment medical expenditures; screening costs; quality-adjusted life-year (QALY) utility weights; and mortality rates. Model parameters were obtained from the published literature or computed from National Health and Nutrition Examination Survey (NHANES) data for the years 2003 through 2012.5 All cost estimates were adjusted to 2015 US dollars, and all future costs and QALYs were discounted at 3% per year.
Base drug costs reflect wholesale acquisition costs as of December 2014. However, since treatment duration varies by genotype, this results in different treatment costs by genotype. All treatments considered are currently patent-protected and face price competition from other branded products. To account for branded competition, the model reduced treatment costs by 46% in years 2 to 20 of the simulation.28,29 Screening costs included the cost of an HCV antibody test (enzyme-linked immunoassay) and a level-1 outpatient visit.4 Medical expenditures for diagnosed patients were computed by disease state and diagnosis status.9,10,30
QALY weights were assigned based on disease state and diagnosis status. We assumed that individuals diagnosed with HCV incur associated psychological costs; therefore, patients who are HCV-infected, but undiagnosed, have QALY weights 2% higher than their diagnosed and untreated counterparts.23 For details on model parameters, dynamics, and assumptions, see the eAppendix.
Scenarios Analyzed
HCV screening. The model explores 3 scenarios for the frequency and inclusiveness of screening in clinical practice (see Table 1). We used AASLD/IDSA screening guidelines to define screening practice,3 adjusting for 2 important realities. First, screening can occur only if a patient interacts with a healthcare provider. NHANES data were used to determine the annual rate at which patients received healthcare services. Second, patients might decline offered screening. In all scenarios, we assumed that 91% of those offered screening would accept it.7
Real-world screening rates also depend on physician awareness of, and adherence to, screening guidelines. The baseline scenario (Current Screening) assumes that 58% of clinicians are aware of HCV screening guidelines based on data reported in the literature.22 To assess the effects of expanded screening on costs and patient outcomes, we considered 2 alternative scenarios: Physician Education explores the effect of increasing physician awareness of screening guidelines to 100%, with no change in the guidelines themselves, and Screen All assumes that, in addition to increasing physician awareness of guidelines to 100%, guidelines are expanded to provide one-time HCV screening to all individuals born before 1992. Because data for guideline adherence were not available, we made the simplifying assumption in all scenarios that all physicians aware of screening guidelines also adhere to them. In practice, physician adherence to clinical guidelines is likely to be imperfect31; however, assuming full adherence yields the maximum possible value that could be generated by screening. We examined the sensitivity of screening rates to physician adherence in the eAppendix.
Treatment practices. The effect of HCV screening on patient health depends on whether a diagnosed patient is subsequently treated. To better understand the relationship between screening and treatment access, we varied the fibrosis stages at which treatment would be available to diagnosed individuals in each screening scenario. Using the METAVIR scoring system to categorize liver fibrosis stages from F0 (no fibrosis) to F4 (most severe), we considered 3 levels of treatment access: a) treatment at fibrosis stages F3-F4, which reflects current practice32-34 and serves as the baseline; b) treatment at F2-F4; and c) treatment at F0-F4. We assumed that all screened and diagnosed individuals receive all-oral DAAs if they are insured (see eAppendix).

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