Changes in Cost-Effectiveness for Chronic Hepatitis C Virus Pharmacotherapy: The Case for Continuous Cost-Effectiveness Analyses.

Background: Cost-effectiveness evaluations for hepatitis C virus (HCV) treatments have been published frequently, but new products with significant cost and effectiveness differences make these analyses obsolete. How valuable are economic models for a fixed time period in a dynamic market?

Objective: To estimate the cost-effectiveness of the best available HCV treatment at different points in time, using the same comparator to demonstrate how rapid innovation in a disease area influences economic outcomes.

Methods: A Markov model was used to calculate the cost-effectiveness of treatment in 2010, 2012, 2014, 2016, and 2018 compared with a standard comparator (no treatment) from the payer perspective. Expected drug costs and treatment effectiveness estimates for sustained virologic response (SVR) were calculated using recommended regimens for each of the 6 HCV genotypes at each time point and distribution of genotypes in the United States. Patients entered the model with different stages of fibrosis. Utility estimates for each health state were used to calculate quality-adjusted life-years (QALYs) earned at each cycle. Incremental cost-effectiveness ratios were reported for each year to compare the "treatment versus no treatment" decision at that time.

Results: No HCV treatment resulted in a gain of 11.54 QALYs over a 20-year time horizon at a cost of $42,938. Costs for treated groups were $69,075, $123,267, $125,431, $86,782, and $56,470 for the 2010, 2012, 2014, 2016, and 2018 scenarios, respectively. QALYs gained for treated groups were 12.90, 12.97, 13.34, 13.39, and 13.46 for the 2010, 2012, 2014, 2016, and 2018 scenarios, respectively. The incremental cost-effectiveness ratios in each year compared with no treatment were $19,218 per QALY, $56,104 per QALY, $45,829 per QALY, $23,699 per QALY, and $7,048 per QALY.

Conclusions: Treatment effectiveness for HCV has increased steadily, while treatment costs increased substantially from 2010-2014 before decreasing to its lowest point in 2018. Thus, the dynamic nature of innovation creates the need for iterative cost-effectiveness analyses.

Disclosures: No outside funding supported this study. Mattingly reports unrelated consulting from the National Health Council, Bristol Myers Squibb, G&W Laboratories, Allergy and Asthma Foundation of American, and the Massachusetts Health Policy Commission. Love reports an unrelated research grant from the American Cancer Society.