COST-EFFECTIVENESS ANALYSIS OF BOCEPREVIR FOR THE TREATMENT OF CHRONIC HEPATITIS C VIRUS GENOTYPE 1 INFECTION IN RUSSIA


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Abstract

Background. The hepatitis C virus (HCV) is associated with a substantial clinical and economic burden in Russia. One of the chief reasons of low treatment rates is the limited efficacy of peginterferon—ribavirin (PR) in treating HCV genotype 1 (G1) infection, the most prevalent genotype in Russia. SPRINT-2 and RESPOnD-2 recently demonstrated that boceprevir (BOC) added to PR significantly increased sustained virologic response rates over PR alone in this patient population. The objective of this study is to evaluate the cost-effectiveness of BOC-based therapy compared with 48 weeks of PR treatment (PR48). Methods. A Markov model was used to estimate the incidence of liver complications, discounted costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs) of the label-based BOC treatment strategies for patients infected with chronic HCV G1 compared with PR48 alone. Data from Russia, clinical trials, and published literature were applied to describe HCV treatment, disease progression, clinical monitoring, and survival. Future costs and QALYs were discounted at 5% and 3%, respectively. Results. Our model predicted that treatment with BOC will result in relative decreases of 29-30% and 47-52% in serious liver diseases and increases of 0,54 and 1,00 in QALYs compared with PR48 alone in treatment naive and treatment experienced patients. Compared to treatment with PR48, the ICERs for boceprevir-based treatment were RUR 973,762/QALY and RUR 650,288/QALY, in treatment naive and treatment experienced patients, respectively. Conclusion. Our modeling study demonstrates that BOC-based treatment strategies is projected to be cost-effective in the treatment of patients infected with HCV G1 in Russia.

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About the authors

Shannon Allen FERRANTE

Merck Research Laboratories

Email: Shannon_ferrante@merck.com

Elamin H. ELBASHA

Merck Research Laboratories

Email: Elamin_elbasha@merck.com

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