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KMID : 1170320100160020057
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Korean Journal of Health Economics and Policy
2010 Volume.16 No. 2 p.57 ~ p.77
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Cost-effectiveness analysis of antidepressants in treatment of major depressive disorder
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Park Jeong-Ae
Choi Sang-Eun
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Abstract
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The economic burden of depression is known to be high and was estimated 2,015.3 billion won in Korea. The purpose of this analysis was to evaluate the cost-effectiveness of first-line therapies (escitalopram, paroxetine, venlafaxine, mirtazapine) for the treatment of major depressive disorder (MDD) in Korea. A decision analytic model with a 6 month treatment goal was used to estimate the effectiveness, cost and cost-effectiveness of antidepressants from the societal perspective. Clinical outcome was measured using quality-adjusted life years(QALY) based on remission rates(HAM-D≤7 or MADRS≤10) and adverse drug reaction(ADR) rates. Sensitivity analysis was conducted to examine the impact of uncertainty upon variation of the major parameters. The expected effectiveness of treatment was 0.3700 QALY for escitalopram, followed by 0.3684 for venlafaxine, 0.3675 QALY for mirtazapine and 0.3557 QALY for paroxetine. The total cost of treatment was 6,621,107 won for escitalopram, 6,799,101 won for venlafaxine, 6,830,130 won for mirtazapine and 7,801,911 won for paroxetine. The most effective and the least expensive alternative, escitalopram was dominant compared with other three antidepressants. Sensitivity analyses indicated that the results of the study were robust to the assumptions underpinning the model. This analysis suggests that first-line treatment of MDD with escitalopram is the most cost-effective alternative compared with mirtazapine, venlafaxine, paroxetine in the Korea National Health Insurance context. The observed dominance reported in the current study stems from better clinical outcomes and cost savings demonstrated by escitalopram over the 3 comparators.
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KEYWORD
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depressive disorder, antidepressants, cost-effectiveness analysis, venlafaxine, parixetine, escitalopram, mirtazapine
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