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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.
Key Model Outputs
The key model output was net social value, defined as the difference between: a) the economic value of clinical benefits from improved quality-adjusted survival and reduced transmission, which is calculated as total QALYs multiplied by $150,00035,36; and b) total healthcare costs, measured as the sum of treatment costs, screening costs, and other medical expenditures. We reported results as changes relative to the baseline scenario (ie, Current Screening with treatment at F3-F4). Therefore, net social value is reported as the difference between a given alternative scenario and the baseline. We also examined the value of expanding screening while treatment remained constant. In this case, Current Screening serves as the baseline for comparing expanded screening scenarios.
In addition to net social value, we reported incremental cost-effectiveness ratios relative to the baseline. Also, since HCV treatment incurs short-term costs but generates long-term benefits, we calculated the break-even point (ie, the years required to switch from negative to positive cumulative net social value) for each screening and treatment combination. Cumulative social value and cost-effectiveness results are presented for a 20-year time horizon. For results at the 10-year time horizon, see the eAppendix.
Sensitivity Analyses
Each parameter in our model is characterized by some degree of uncertainty. For example, estimates for disease and transmission dynamics vary in the literature. Additionally, our model includes a number of important assumptions that affect our results.
To test the sensitivity of our model to disease progression and transmission parameters, we conducted sensitivity tests of key model parameters within each scenario. For each key parameter, we varied the parameter across a range and report how the scenario’s value changes in percentage terms when using the upper and lower bounds of the range. We also examined several key assumptions, including physician adherence to screening guidelines, future reductions in treatment costs, and others. For details, see the eAppendix.
Annual Net Value
Figure 1 reports the annual net value of screening scenarios stratified by treatment scenario. More inclusive screening policies involve net costs in the short term, but generate positive net value after 5 to 7 years. More comprehensive treatment policies cause inclusive screening policies to rise in value more quickly, but also make them more costly in the short run. Relative to Current Screening, annual net values in Screen All are approximately double those in Physician Education.
Cumulative Net Value
Costs and QALY gains used to calculate cumulative net social value over the 20-year time horizon are presented in Table 2. Total cost is driven primarily by medical expenditures and treatment costs. In both expanded screening scenarios, medical expenditures increase under treatment at F3-F4. By contrast, savings from reduced medical expenditures exceed the costs of treatment in all scenarios under treatment at F0-F4.
Over a 20-year time horizon, Screen All generates the greatest cumulative net social value at all levels of treatment access compared with the baseline (see Table 3). In general, however, screening expansion has a relatively small effect on cumulative net social value, unless treatment is similarly expanded. Relative to Current Screening, Screen All generates a net gain of $0.68 billion under the most restrictive access to treatment (F3-F4) and Physician Education generates a net loss in social value of $1.76 billion. The relative gain from increased screening rises with more comprehensive access to treatment. Under treatment at F2-F4, Physician Education generates net social value of $421 billion and Screen All generates net social value of $464 billion over 20 years, relative to baseline. These gains increase to $752 billion (Physician Education) and $824 billion (Screen All) under more comprehensive treatment (F0-F4).
Under any given treatment strategy, Screen All is the highest-value screening strategy (see Figure 2). With treatment at F2-F4, Screen All generates nearly twice the value generated by Physician Education over 20 years. The value of screening approximately doubles when treatment is expanded to F0-F4, under which Physician Education and Screen All generate $83.7 billion and $155.1 billion, respectively, in cumulative discounted social value. Broader treatment increases the costs and benefits by roughly the same proportion. Therefore, even though net social value doubles with wider treatment, incremental cost-effectiveness ratios (ICERs) for screening do not vary ($42,000/QALY for treatment at F2-F4 and $19,000/QALY for F0-F4).

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