Trends in Treatment of Severe Haemophilia and Impact on Inhibitor Assessment by the EUHASS Registry
Bibliographic record
Abstract
BACKGROUND: The last 15 years have seen new extended half-life (EHL) recombinant FVIII/IX concentrates and nonreplacement therapy for haemophilia A (emicizumab) introduced in Europe. These changes affect FVIII/IX exposure in previously untreated patients (PUPs) and previously treated patients (PTPs) with severe haemophilia A and B (SHA and SHB) and may modify inhibitor development and/or detection. AIM: To report trends in treatment for severe haemophilia and concomitant changes in inhibitor incidence. METHODS: Between 2008 and 2022, 97 centres reported inhibitor development against FVIII/IX concentrates to the European Haemophilia Safety Surveillance System (EUHASS). Inhibitors were reported quarterly, and PUPs without inhibitor development annually. Cumulative inhibitor incidences (95% confidence intervals [CI]) were calculated for PUPs and incidence rates/1000 years (CI) for PTPs. RESULTS: By 2022, SHA-PUPs (n = 1574) received emicizumab (44%), SHL-rFVIII (21.5%), pdFVIII (17.5%) and EHL-rFVIII (17%). SHB-PUPs (n = 236) received EHL-rFIX (79%) and SHL-rFIX (21%). SHA-PTPs (68,772 years) received EHL-rFVIII (31%), SHL-rFVIII (28%), emicizumab (25%), and pdFVIII (15%). SHB PTPs (11,185 years) received EHL-rFIX (69%), pdFIX (15%) and SHL-rFIX (15%). Observed Inhibitor incidence in SHA-PUPs decreased from 24% before 2016 to 6% in 2022 (p < 0.001), and potentially in SHB-PUPs too (from 9% to 3%; p = 0.066), but remained stable in SHA/SHB PTPs. CONCLUSION: In 2022, 44% of SHA-PUPs and 25% of SHA-PTPs received emicizumab prophylaxis. Concomitantly, observed inhibitor incidence reduced to 6% in SHA-PUPs. In SHB, EHL-rFIX treatment increased to 79% in SHB-PUPs and 69% in SHB-PTPs. Assessing inhibitor incidence for new concentrates is likely to be hampered by novel treatments causing delayed exposure to FVIII/FIX.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".