Abstract

Hepatitis C virus (HCV) is the most common chronic blood-borne infection in the United States and will become an increasing source of morbidity and mortality with aging of the infected population. Our objective was to develop decision analytic models to explore the cost-effectiveness of screening in populations with varying prevalence of HCV and risks for fibrosis progression. We developed a Markov state transition model to examine screening of an asymptomatic community-based population in the United States. The base case was an ethnically and gender-mixed adult population with no prior knowledge of HCV status. Interventions were screening followed by guideline-based treatment, or no screening. Effectiveness was measured in quality-adjusted life-years (QALYs), and costs were measured in 2011 US dollars. In the base case (US population, 49% male, 78% white, 13% African American, and 9% Hispanic, mean age, 46 years), screening followed by guideline-based treatment (using boceprevir as the direct-acting antiviral agent) of those with chronic HCV infection costs $47 276 per QALY. The overall HCV prevalence in the United States is reported to be 1.3%-1.9%, but prevalence varies markedly among patients with different numbers and types of risk factors. The marginal cost-effectiveness ratio (mCER) of screening decreases as prevalence increases. Below a prevalence of 0.84%, the mCER is greater than the generally accepted societal willingness-to-pay threshold of $50 000 per QALY and thus is not considered highly cost-effective. Targeted screening is cost-effective when prevalence of HCV exceeds 0.84%. Prospective evaluation of a screening tool is warranted and should include comparisons with other screening strategies.

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