Assessing the Economic Value of a New Antidepressant
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abstract
Using the method of willingness to pay (WTP), this study assesses the value of a new antidepressant, moclobemide, relative to that of tricyclic antidepressants (TCAs), which have equivalent efficacy but less favourable adverse effect profiles. From a published meta-analysis of controlled clinical trials, we identified 7 adverse effects, the risk of which differed significantly between moclobemide and TCAs. We obtained risk reduction data and descriptions of adverse effects from interviews with 95 individuals who had mild to moderate depression and who had been taking one or more TCAs in the previous year. Using a visual analogue scale, respondents ranked and rated each adverse effect. Participants were then asked (using the scenario of additional out-of-pocket drug payment) to quantify the maximum amount that they would pay for a new drug that reduced each adverse effect by the specified probability. Blurred vision and tremor were ranked and rated as the most bothersome adverse effects, with dry mouth being the least bothersome. On average, respondents were willing to pay an additional $Can22 per month [95% confidence interval (CI) 16-28] to reduce the risk of blurred vision from 10 to 5%. The lowest WTP value was for reducing the risk of dry mouth from 40 to 15%, at $Can11 per month (95% CI 8-15). Although not measured directly, we derived 2 estimates of WTP for multiple (i.e. all 7) risk reductions. We obtained upper and lower WTP limits of $Can118 and $Can36 per month, respectively, depending upon aggregation assumptions. Compared with the TCAs amitriptyline and imipramine, the net cost of moclobemide is greater, but the overall net benefit (WTP minus cost) is ambiguous given uncertainty about WTP aggregation over adverse effects. However, compared with the TCAs desipramine and clomipramine, the net benefit of moclobemide is unambiguously positive. We conclude that the WTP approach is a potentially valuable tool that requires more development for use in healthcare economic evaluation.
