Converting factor and nonfactor usage into a single metric to facilitate benchmarking the resources consumed for haemophilia care across jurisdictions and over time
Bibliographic record
Abstract
INTRODUCTION: The World Federation of Hemophilia started measuring factor utilization at the country level as IU/capita (International Units of factor concentrates used per country population) in 2001 for its Annual Global Survey. IU/capita have been used to benchmark a country's usage over time and for advocacy. The introduction of a common metric usage spanning across standard half-life (SHL), and extended half-life (EHL) clotting factor concentrates (CFCs) and emicizumab would be a valuable simplification for national healthcare policymaking and industrial production planning. AIM: Develop and examine a method of converting IU of SHL or EHL, and milligrams of emicizumab into a single metric. METHODS: We developed conversion factors from manufacturer's recommended dose for prophylaxis with SHL, EHL, and emicizumab as reported on the licensing information for the United States and Europe. We validate the accuracy of these conversion factors against real-world usage data. RESULTS: The prescribing information in the United States and Europe is marginally different. The SHL/EHL conversion factors are higher when calculated based on the prescribing information than on real-world studies, which are considered more representative of clinical practice. The best estimate of the SHL/EHL conversion factors for FVIII and FIX were 1.04 and 1.87. The conversion factor for emicizumab to SHL is 70 IU/mg. CONCLUSION: We have generated robust estimates of conversion factors for currently used treatment options for prophylaxis in haemophilia. Usage of a single, harmonized metric will facilitate benchmarking across different countries or longitudinally irrespective of the case-mix of treatment options.
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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 | 0.016 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".