Inhibitor development according to concentrate after 50 exposure days in severe hemophilia: data from the European HAemophilia Safety Surveillance (EUHASS)
Bibliographic record
Abstract
Background: Patients with hemophilia have a life-long risk of developing neutralizing antibodies (inhibitors) against clotting factor concentrates. After the first 50 exposure days (EDs), ie, in previously treated patients (PTPs), data on inhibitor development are limited. Objectives: To report inhibitor development according to factor (F)VIII or FIX concentrate use in PTPs with severe hemophilia A and B. Methods: Inhibitor development in PTPs was collected since 2008 from 97 centers participating in European HAemophilia Safety Surveillance. Per concentrate, inhibitors were reported quarterly and the number of PTPs treated annually. Incidence rates (IRs)/1000 treatment years with 95% CIs were compared between concentrate types (plasma derived FVIII/FIX, standard half-life recombinant FVIII/FIX, and extended half-life recombinant (EHL-rFVIII/IX) concentrates using IR ratios with CI. Medians and IQRs were calculated for inhibitor characteristics. Results: < .01).For severe hemophilia B, inhibitor rate was 5/11,160 treatment years and IR was 0.45/1000 years (95% CI, 0.15-1.04), at median 3.7 years (95% CI, 2.1-42.4) and 260 EDs (95% CI, 130 to >1000). Data were insufficient to compare by type of FIX concentrates. Conclusion: Low inhibitor rates were observed for PTPs with severe hemophilia A and B. Data suggested reduced inhibitor development on EHL-rFVIII, but no significant difference between plasma-derived FVIII and standard half-life recombinant FVIII. FIX inhibitor rates were too low for robust statistical analysis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".