Cost-effectiveness of ten commonly used antipsychotics in first-episode schizophrenia in the UK: economic evaluation based on a de novo discrete event simulation model
Zhou J., Millier A., Aballea S., Francois C., Jin H., Williams R., Lennox B., Tsiachristas A., Toumi M.
Background Previous economic evidence about interventions for schizophrenia is outdated, non-transparent and/or limited to a specific clinical context. Aims We developed a de novo discrete event simulation (DES) model for estimating the cost-effectiveness of interventions in schizophrenia in the UK. Method The DES model was developed based on the structure of previous models, populated with demographic, clinical and cost data from the UK, and antipsychotics’ effects from recent network meta-analyses. We simulated treatment pathways for patients with first-episode schizophrenia including events such as relapse, remission, treatment discontinuation, cardiovascular disease and death and estimated costs (2020£) taking the National Health Service perspective and quality-adjusted life years (QALYs) over ten years. Using the model, we ranked ten first-line antipsychotics based on their QALYs and cost-effectiveness. Results Amisulpride was associated with the highest QALYs, followed by risperidone long-acting injection (LAI), aripiprazole-LAI (6.121, 6.084, 6.070, respectively) and others (5.947–6.058). The most cost-effective antipsychotics were amisulpride, olanzapine and risperidone-LAI, with total probability of rankings of 1, ≤2, ≤3, that is, 95%, 89%, 80%, respectively; meanwhile, the least cost-effective were cariprazine, lurasidone and quetiapine, with total probability of rankings of 10, ≥9, ≥8, that is, 96%, 92%, 81%, respectively. Results were robust across sensitivity analyses and influenced primarily by relapse relevant parameters. Conclusions Our findings suggest amisulpride (or risperidone-LAI where oral treatment is inappropriate) as the best overall first-line option based on QALYs and cost-effectiveness. Our ranking may be used to guide decision-making between antipsychotics. Our model is open source and could be applied to the other settings.