Product‐dependent anti‐factor <scp>VIII</scp> antibodies
Bibliographic record
Abstract
The development of anti-factor (F)VIII antibodies in haemophilia A (HA) subjects undergoing replacement therapy has been well documented. The correlation between antibody development and the FVIII product used for replacement therapy remains a subject of discussion. The aim of this study was to evaluate the presence of anti-FVIII antibodies towards three commercial rFVIII products in 34 HA subjects' plasmas. Antibodies were quantitated by a Multiplex Fluorescence Immunoassay. All plasmas contained anti-FVIII antibodies at variable concentrations ranging from 50 nm to 570 μm. Eleven of the 20 HA subjects treated with one (r)FVIII product contained inhibitory anti-FVIII antibodies (0.8-3584 BU). The inhibitory antibody titre and the molar concentrations of total antibody were mildly correlated (r(2) = 0.6). Pronounced differences in antibody recognition with the three rFVIII products were observed. For the group treated with Product 'A', the titre towards this product was 2.4-fold higher than that observed with another full-length rFVIII-containing product (Product 'B') and almost four-fold higher than that measured with a B domain-less rFVIII product (Product 'C'). For the group of 14 HA subjects treated with FVIII other than Product 'A', only one showed higher antibody titre when measured with this product. Our data suggest that the development of anti-FVIII antibodies is biased towards the product used for treatment and that a significant fraction of antibodies bind to the B domain of FVIII.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".