Abstract

We aimed to conduct a cost-utility analysis of available interferon-free treatments for genotype 1 chronic hepatitis C patients at the early disease stage from a Brazilian public health system perspective. We built a Markov model using a cohort of stage F0–F2 patients (non-cirrhotic) treated with the following drug combinations as recommended by the Brazilian national guidelines: sofosbuvir + daclatasvir; elbasvir + grazoprevir; sofosbuvir + ledipasvir; glecaprevir + pibrentasvir (GLE+PIB); and sofosbuvir + velpatasvir (SOF+VEL). Efficacy outcomes are expressed in terms of quality-adjusted life years and only direct costs were considered. The incremental cost-effectiveness ratio was calculated for non-dominated strategies. Probabilistic sensitivity analysis was performed and presented as a scatterplot and a cost-effectiveness acceptability graph. The treatment GLE+PIB dominated all other treatments: it was associated with a lower treatment cost and similar QALY compared to the other strategies, followed by SOF+VEL. This result was also confirmed in probabilistic sensitivity analysis where these two direct-acting antiviral combinations presented a higher number of iterations, proving to be the most cost-effective treatments (56% of interactions for GLE+PIB; 43% for SOF+VEL). Similar results were observed in all other scenarios. The present cost-utility analysis shows that GLE+PIB was the most cost-effective treatment, followed by SOF+VEL, whereas sofosbuvir + daclatasvir was considerate the least cost-effective.

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