Cost-effectiveness analysis of atypical long-acting antipsychotics for treating chronic schizophrenia in Finland
Bibliographic record
Abstract
OBJECTIVE: In Finland, regional rates of schizophrenia exceed those in most countries, impacting the healthcare burden. This study determined the cost-effectiveness of long-acting antipsychotic (LAI) drugs paliperidone palmitate (PP-LAI), olanzapine pamoate (OLZ-LAI), and risperidone (RIS-LAI) for chronic schizophrenia. METHOD: This study adapted a decision tree analysis from Norway for the Finnish National Health Service. Country-specific data were sought from the literature and public documents, guided by clinical experts. Costs of health services and products were retrieved from literature sources and current price lists. This simulation study estimated average 1-year costs for treating patients with each LAI, average remission days, rates of hospitalization and emergency room visits and quality-adjusted life-years (QALY). RESULTS: PP-LAI was dominant. Its estimated annual average cost was €10,380/patient and was associated with 0.817 QALY; OLZ-LAI cost €12,145 with 0.810 QALY; RIS-LAI cost €12,074 with 0.809 QALY. PP-LAI had the lowest rates of hospitalization, emergency room visits, and relapse days. This analysis was robust against most variations in input values except adherence rates. PP-LAI was dominant over OLZ-LAI and RIS-LAI in 77.8% and 85.9% of simulations, respectively. Limitations include the 1-year time horizon (as opposed to lifetime costs), omission of the costs of adverse events, and the assumption of universal accessibility. CONCLUSION: In Finland, PP-LAI dominated the other LAIs as it was associated with a lower cost and better clinical outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".