Economic and clinical comparison of atypical depot antipsychotic drugs for treatment of chronic schizophrenia in the Czech Republic
Bibliographic record
Abstract
PURPOSE: The Czech Republic is faced with making choices between pharmaceutical products, including depot injectable antipsychotics. A pharmacoeconomic analysis was conducted to determine the cost-effectiveness of atypical depots. METHODS: An existing 1-year decision-analytic framework was adapted to model drug use in this healthcare system. The average direct costs to the General Insurance Company of the Czech Republic of using paliperidone palmitate (Xeplion®), risperidone (Risperdal Consta®), and olanzapine pamoate (Zypadhera®) were determined. Literature-derived clinical rates populated the model, with costs adjusted to 2012 Euros using the consumer price index. Outcomes included quality-adjusted life-years (QALYs), days in remission, and proportions hospitalized or visiting emergency rooms. One-way sensitivity analyses were calculated for all important inputs. A multivariate probability analysis was used to examine the stability of results using 10,000 iterations of simulated input over reasonable ranges of all included variables. RESULTS: Expected average costs/per patient treated were €5377 for PP-LAI, €6118 for RIS-LAI, and €6537 for OLZ-LAI. Respective QALYs were 0.817, 0.809, and 0.811; ER visits were 0.127, 0.134, and 0.141; hospitalizations were 0.252, 0.298, and 0.289. Results were generally robust in sensitivity analyses. PP-LAI dominated RIS-LAI and OLZ-LAI in 90.2% and 92.1% of simulations, respectively. Results were insensitive to drug prices but sensitive to adherence and hospitalization rates. CONCLUSIONS: PP-LAI dominated the other two drugs, as it had a lower overall cost and superior clinical outcomes, making it the preferred choice. Using PP-LAI in place of RIS-LAI for chronic relapsing schizophrenia would reduce the overall costs of care for the healthcare system.
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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 | 0.001 | 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".