Cost-effectiveness and budget impact of hepatitis C virus treatment with sofosbuvir and ledipasvir in the United States

Abstract

Background: Sofosbuvir and ledipasvir, which have recently been approved for treatment of chronic hepatitis C virus (HCV) infection, are more efficacious and safer than the old standard of care (oSOC) but are substantially more expensive. Whether and in which patients their improved efficacy justifies their increased cost is unclear.

Objective: To evaluate the cost-effectiveness and budget impact of sofosbuvir and ledipasvir.

Design: Microsimulation model of the natural history of HCV infection.

Data sources: Published literature.

Target population: Treatment-naive and treatment-experienced HCV population defined on the basis of HCV genotype, age, and fibrosis distribution in the United States.

Time horizon: Lifetime.

Perspective: Third-party payer.

Intervention: Simulation of sofosbuvir-ledipasvir compared with the oSOC (interferon-based therapies).

Outcome measures: Quality-adjusted life-years (QALYs), incremental cost-effectiveness ratios (ICERs), and 5-year spending on antiviral drugs.

Results of base-case analysis: Sofosbuvir-based therapies added 0.56 QALY relative to the oSOC at an ICER of $55 400 per additional QALY. The ICERs ranged from $9700 to $284 300 per QALY depending on the patient's status with respect to treatment history, HCV genotype, and presence of cirrhosis. At a willingness-to-pay threshold of $100 000 per QALY, sofosbuvir-based therapies were cost-effective in 83% of treatment-naive and 81% of treatment-experienced patients. Compared with the oSOC, treating eligible HCV-infected persons in the United States with the new drugs would cost an additional $65 billion in the next 5 years, whereas the resulting cost offsets would be $16 billion.

Results of sensitivity analysis: Results were sensitive to drug price, drug efficacy, and quality of life after successful treatment.

Limitation: Data on real-world effectiveness of new antivirals are lacking.

Conclusion: Treatment of HCV is cost-effective in most patients, but additional resources and value-based patient prioritization are needed to manage patients with HCV.

Primary funding source: National Institutes of Health.

Figure 1

State-Transition Diagram of Hepatitis C Treatment Model for a Cost-Effectiveness Analysis of Sofosbuvir and Ledipasvir. At any given time, a patient occupies one of the health states represented by circles/ovals. Arrows between states represent possible transitions based on annual probabilities. As time progresses, patients can transition to other states and acquire cost and health-utilities associated with that state. The model stops when all patients transition to death state. Note that a patient could transition to a death state from any of the above states because of background mortality (these transitions are not shown in the figure for clarity) Abbreviations: SVR, sustained virologic response; F0–F4, METAVIR fibrosis score; DC, decompensated cirrhosis; HCC, hepatocellular carcinoma; LT, liver transplant; LRD, liver-related death. *DC and LT states were further divided into first-year and subsequent-year to account of different mortality rates and costs; however, they are collapsed into one state for presentation purpose only.

Figure 2

Total drug spending on sofosbuvir (SOF)- and ledipasvir (LDV)-based therapies to treat all HCV-infected patients in the United States in the next 5 years; A. By HCV genotype (G1–G4), prior treatment history (naïve or experienced), and insurance coverage (military/state/government [govt.], Medicaid/Medicare, and private);

Figure 3

One-way Sensitivity Analysis Showing Top 10 Most Sensitive Parameters. Abbreviations: q: Post SVR, quality of life after achieving sustained virologic response (SVR); SVR Detla: SOF/LDV, Reduction in SVR in sofosbuvir (SOF)- and ledipasvir (LDV)-based therapies; p: F4 to DC, probability of developing decompensated cirrhosis (DC) from fibrosis score F4; q: F4, quality-of-life (QOL) weight associated with F4; p: F4 to HCC, probability of developing hepatocellular carcinoma (HCC) from F4; SVR Delta: oSOC, Reduction in SVR in the old standard of care (oSOC); p: Post SVR to DC, probability of developing DC in F4 patients who achieved SVR; q: F3, QOL weight associated with fibrosis score F3; q: F2, QOL weight associated with fibrosis score F2; q: F1, QOL weight associated with fibrosis score F1.

Figure 4

Probabilistic Sensitivity Analysis of Sofosbuvir- and Ledipasvir-Based Therapies showing the Cost-Effectiveness Probability by Willingness-to-pay Thresholds. Abbreviations: TN, treatment-naïve, TE, treatment-experienced; ICER, incremental-cost-effectiveness ratio.

Figure 5

Incremental Cost-Effectiveness Ratios (ICERs) of Sofosbuvir- and Ledipasvir-Based Therapies by fibrosis score (F0–F4), sex, and age. Abbreviations: F0–F4, METAVIR fibrosis scores. Note that ICERs of males were higher than those of females because of higher background mortality of males than females