Low immunogenicity of emicizumab in persons with haemophilia A
Bibliographic record
Abstract
INTRODUCTION: Emicizumab is a humanised, bispecific monoclonal antibody mimicking the cofactor function of activated factor (F)VIII. It is indicated for routine prophylaxis of bleeding episodes in persons with haemophilia A (PwHA) with/without FVIII inhibitors. AIM: To evaluate the development of anti-emicizumab antibodies and their impact on pharmacokinetics (PK), pharmacodynamics (PD), efficacy and safety in PwHA. METHODS: Data from seven completed or ongoing phase 3 studies were pooled. The assessment of the immunogenicity profile of emicizumab included anti-drug antibody (ADA) measurement and the association of ADAs with PK, PD, bleeding events, and adverse events. RESULTS: Of 668 PwHA evaluable for immunogenicity analysis, 34 (5.1%) developed ADAs after exposure to emicizumab. ADAs were transient in 14/34 PwHA (41.2%). ADAs were neutralising in vitro in 18/34 PwHA (52.9%) and associated with decreased emicizumab concentration in 4/668 evaluable PwHA (.6%); of those, one (.1%) discontinued emicizumab due to loss of efficacy. ADAs without decreased exposure did not impact emicizumab efficacy. The proportion of PwHA who had injection-site reactions (ISRs) was higher in ADA-positive PwHA (29.4% vs. 20.8%); however, the safety profile was similar between ADA-positive and ADA-negative PwHA, overall. No cases of anaphylaxis or hypersensitivity were reported in ADA-positive participants. CONCLUSION: The immunogenicity risk of emicizumab in phase 3 studies was low. ADAs, including in vitro neutralising ADAs, were not associated with a change in safety profile. Routine surveillance is, therefore, not warranted; however, in cases where a loss and/or waning of efficacy are observed, prompt evaluation by a healthcare provider should be sought.
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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 | 0.002 | 0.004 |
| 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) | 0.002 | 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".