Abstract

Vortioxetine is an innovative antidepressant with a new multimodal mechanism of action as well as the improved Health-related QOL of patients. The objective of this study is to evaluate the cost-utility of vortioxetine versus duloxetine for the treatment of major depression disorders in China. The cost-utility model was composed of a decision tree and Markov model. The decision tree was supplemented by a Markov model to estimate cost and quality-adjusted life years for subsequent treatment lines. The economic evaluation was carried out over a one-year time horizon from a societal perspective. Inputs include risk of suicide, effectiveness parameters, safety parameters, utilities, resource use, probabilities, which were sourced from published literature and clinical expert consultation. Outputs include disease management costs, quality-adjusted life-years and cost-utility. One way deterministic sensitivity analysis and probabilistic sensitivity analysis were conducted to assess the drivers of cost-utility and the robustness of the economic analysis. Vortioxetine induced additional QALY gains(0.6888 vs. 0.6762) and cost (Societal: RMB11,668 vs. RMB10,571; Payer: RMB9,016 vs. RMB7,846) versus duloxetine. The incremental cost-effectiveness ratio was RMB87,164 from a societal perspective and RMB92,987 from a payer perspective, both of which were slightly higher than per capita GDP in China in 2018. One way deterministic sensitivity analysis showed that the cost of vortioxetine is one of the most sensitive factors, while the ICER would still remain lower than three-fold per capita GDP when the cost of vortioxetine was increased by 45%. According to probabilistic sensitivity analysis, there was a 60.6% probability for vortioxetine to be cost-effective over duloxetine at willingness to pay threshold considered to be as three-fold per capita GDP. Vortioxetine is more cost-effective in the treatment of major depression disorders due to the broad efficacy and well-tolerated profile compared to duloxetine in China.

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