Cost-effectiveness of asenapine in the treatment of bipolar I disorder patients with mixed episodes

Abstract

Objective:Around one-third of patients with bipolar I disorder (BD-I) experience mixed episodes, characterized by both mania and depression, which tend to be more difficult and costly to treat. Atypical antipsychotics are recommended for the treatment of mixed episodes, although evidence of their efficacy, tolerability, and cost in these patients is limited. This study evaluates, from a UK National Health Service perspective, the cost-effectiveness of asenapine vs olanzapine in BD-I patients with mixed episodes.Methods:Cost-effectiveness was assessed using a Markov model. Efficacy was informed by a post-hoc analysis of two short-term clinical trials, with response measured as a composite Young Mania Rating Score and Montgomery-Åsberg Depression Rating Scale end-point. Probabilities of discontinuation and relapse to manic, mixed, and depressive episodes were sourced from published meta-analyses. Direct costs (2012–2013 values) included drug acquisition, monitoring, and resource use related to bipolar disorder as well as selected adverse events. Benefits were measured as quality-adjusted life years (QALYs).Results:For treating mixed episodes, asenapine generated 0.0187 more QALYs for an additional cost of £24 compared to olanzapine over a 5-year period, corresponding to a £1302 incremental cost-effectiveness ratio. The higher acquisition cost of asenapine was roughly offset by the healthcare savings conferred through its greater efficacy in treating these patients. The model shows that benefits were driven by earlier response to asenapine during acute treatment and were maintained during longer-term follow-up. Results were sensitive to changes in key parameters including short and longer-term efficacy, unit cost, and utilities, but conclusions remained relatively robust.Conclusions:Results suggest that asenapine is a cost-effective alternative to olanzapine in mixed episode BD-I patients, and may have specific advantages in this population, potentially leading to healthcare sector savings and improved outcomes. Limitations of the analysis stem from gaps in clinical and economic evidence for these patients and should be addressed by future clinical trials.