Cost-effectiveness of asenapine in the treatment of schizophrenia in Canada
Bibliographic record
Abstract
OBJECTIVE: Asenapine is the first tetracyclic antipsychotic approved in Canada for the treatment of schizophrenia (SCZ). Asenapine has shown a comparable efficacy profile to other atypical antipsychotics and it is associated with a favourable metabolic profile and less weight gain. This study aimed to assess the economic impact of asenapine compared to other atypical antipsychotics in the treatment of SCZ in Canada. METHODS: A decision tree combined with a Markov model was constructed to assess the cost-utility of asenapine compared with other atypical antipsychotics. The decision tree takes into account the occurrence of extrapyramidal symptoms, the probability of switching to a different antipsychotic, and the probability of gaining weight. The Markov model takes into account long-term metabolic complications including diabetes, hypertension, coronary heart diseases, and stroke. In the base-case analysis, asenapine was compared to olanzapine. Asenapine was also compared with other atypical antipsychotics commonly used in Canada in alternative scenarios. Analyses were conducted from both Canadian Ministry of Health (MoH) and societal perspectives over a 5-year time horizon. RESULTS: In the treatment of SCZ, asenapine is a dominant strategy over olanzapine from both MoH and societal perspectives. Compared to quetiapine, asenapine is also a dominant strategy. Furthermore, asenapine has a favorable economic impact compared to ziprasidone and aripiprazole, as these antipsychotics are not cost-effective compared to asenapine from both MoH and societal perspectives. CONCLUSION: Despite the short time horizon, the lack of compliance data and the assumptions made, this economic evaluation demonstrates that asenapine is a cost-effective strategy compared to olanzapine and to most of the atypical antipsychotics frequently used in Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".