Cost-effectiveness analysis of olanzapine and risperidone in Norway

Antipsychotic medications are the mainstay for schizophrenia treatment, and olanzapine and risperidone are popular choices among atypical antipsychotics in Norway. Our aim was to develop a decision analytic model to evaluate the cost-effectiveness of antipsychotics in a Norwegian setting.

The Positive and Negative Symptom Scale (PANSS) score was used to measure effectiveness of the antipsychotics, and costs were analyzed from the payer's perspective. Sensitivity analysis, including Probability Sensitivity Analysis (PSA), was conducted using Monte Carlo simulation to identify uncertain parameters and their effect on the results.

A comprehensive decision model was developed by combining a decision tree model and a Markov model. The model results indicated that olanzapine was a dominant alternative to risperidone (cost per patient in the first year; olanzapine 68,718 vs. risperidone 70,359, PANSS score reductions; olanzapine 112.60 vs. risperidone 111.55, and cost per patient from the second to fifth year; olanzapine 148,732 vs. risperidone 154,632). However, the PSA results indicated that olanzapine and risperidone were not different in terms of cost-effectiveness within a 95% confidence interval. The Incremental Cost-Effectiveness (ICE) scatterplot showed that the chance of olanzapine being an optimal alternative was 67.1% in the model.

Based on the PSA analysis, we could not conclude that olanzapine is an optimal alternative to risperidone in Norway. However, PSA may be a useful tool to examine the results generated by a decision analytic model using uncertain parameters. The model facilitates calculation of the costs per patient treated with antipsychotics, and the model may be useful as a basic frame for modeling patients with schizophrenia in Norway.