A systematic review of economic evaluations of orphan medicines for the management of spinal muscular atrophy
Bibliographic record
Abstract
Spinal muscular atrophy (SMA) is a rare inherited autosomal recessive progressive disease of a varying phenotype, with varying clinical symptoms, and as a result the patients suffering from it require multiple types of care. It was deemed useful to conduct a systematic literature review on the pharmacoeconomic evaluations of all currently registered disease-modifying therapies in order to inform policy and highlight research gaps. Pharmacoeconomic analyses written in English and published after 2016 were considered for inclusion. PubMed/Medline, Global Health and Embase were systematically and separately searched between 16 October and 23 October 2023. Hand-searching was also conducted on PubMed based on reference lists of published literature. After the exclusion criteria were applied, 14 studies were included. BMJ checklist was used for quality assessment and the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist was used to assess the quality of reporting of all included studies. Data extraction was performed manually. Regarding evidence synthesis, data were heterogeneous and are thus presented based on comparison. This study confirms the need for pharmacoeconomic analyses (cost-effectiveness or cost-utility) also in cases when the cost of treatment is very high and the incremental cost-effectiveness ratio values exceed the usual, acceptable values for standard therapy. Specific willingness to pay thresholds for orphan medicines are of the utmost importance, to allow patients with SMA to have access to safe and effective treatments. With such economic evaluations, it is possible to compare the value of medications with the same indication, but it should be emphasized that in the interpretation of data and in making decisions about the use of medicines, the impact of new knowledge should be considered.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".