Recommendations for reporting economic evaluations of haemophilia prophylaxis: a nominal groups consensus statement on behalf of the Economics Expert Working Group of The International Prophylaxis Study Group
Bibliographic record
Abstract
BACKGROUND: The need for clearly reported studies evaluating the cost of prophylaxis and its overall outcomes has been recommended from previous literature. OBJECTIVES: To establish minimal ''core standards'' that can be followed when conducting and reporting economic evaluations of hemophilia prophylaxis. METHODS: Ten members of the IPSG Economic Analysis Working Group participated in a consensus process using the Nominal Groups Technique (NGT). The following topics relating to the economic analysis of prophylaxis studies were addressed; Whose perspective should be taken? Which is the best methodological approach? Is micro- or macro-costing the best costing strategy? What information must be presented about costs and outcomes in order to facilitate local and international interpretation? RESULTS: The group suggests studies on the economic impact of prophylaxis should be viewed from a societal perspective and be reported using a Cost Utility Analysis (CUA) (with consideration of also reporting Cost Benefit Analysis [CBA]). All costs that exceed $500 should be used to measure the costs of prophylaxis (macro strategy) including items such as clotting factor costs, hospitalizations, surgical procedures, productivity loss and number of days lost from school or work. Generic and disease specific quality of lífe and utility measures should be used to report the outcomes of the study. CONCLUSIONS: The IPSG has suggested minimal core standards to be applied to the reporting of economic evaluations of hemophilia prophylaxis. Standardized reporting will facilitate the comparison of studies and will allow for more rational policy decisions and treatment choices.
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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 | 0.643 | 0.768 |
| Meta-epidemiology (narrow) | 0.005 | 0.007 |
| Meta-epidemiology (broad) | 0.011 | 0.024 |
| Bibliometrics | 0.026 | 0.026 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.023 | 0.018 |
| Open science | 0.027 | 0.017 |
| Research integrity | 0.031 | 0.037 |
| Insufficient payload (model declined to judge) | 0.011 | 0.011 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".