Pharmacoeconomic analysis of paliperidone palmitate for treating schizophrenia in Greece
Bibliographic record
Abstract
BACKGROUND: Patients having chronic schizophrenia with frequent relapses and hospitalizations represent a great challenge, both clinically and financially. Risperidone long-acting injection (RIS-LAI) has been the main LAI atypical antipsychotic treatment in Greece. Paliperidone palmitate (PP-LAI) has recently been approved. It is dosed monthly, as opposed to biweekly for RIS-LAI, but such advantages have not yet been analysed in terms of economic evaluation. PURPOSE: To compare costs and outcomes of PP-LAI versus RIS-LAI in Greece. METHODS: A cost-utility analysis was performed using a previously validated decision tree to model clinical pathways and costs over 1 year for stable patients started on either medication. Rates were taken from the literature. A local expert panel provided feedback on treatment patterns. All direct costs incurred by the national healthcare system were obtained from the literature and standard price lists; all were inflated to 2011 costs. Patient outcomes analyzed included average days with stable disease, numbers of hospitalizations, emergency room visits, and quality-adjusted life-years (QALYs). RESULTS: The total annual healthcare cost with PP-LAI was €3529; patients experienced 325 days in remission and 0.840 QALY; 28% were hospitalized and 15% received emergency room treatment. With RIS-LAI, the cost was €3695, patients experienced 318.6 days in remission and 0.815 QALY; 33% were hospitalized and 17% received emergency room treatment. Thus, PP-LAI dominated RIS-LAI. Results were generally robust in sensitivity analyses with PP-LAI dominating in 74.6% of simulations. Results were sensitive to the price of PP-LAI. CONCLUSIONS: PP-LAI appears to be a cost-effective option for treating chronic schizophrenia in Greece compared with RIS-LAI since it results in savings to the health care system along with better patient 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".