Eptacog beta for the management of patients with haemophilia A and B with inhibitors: A European perspective
Bibliographic record
Abstract
Eptacog beta (activated), a recombinant human factor VIIa (rFVIIa), was approved by the US Food and Drug Administration (FDA) in 2020 (SEVENFACT®, LFB & HEMA Biologics) and the European Medicines Agency (EMA) in 2022 (CEVENFACTA®, LFB). In Europe, eptacog beta is indicated for the treatment of bleeds and the prevention of bleeds during surgery or invasive procedures in adults and adolescents (≥12 years old) with congenital haemophilia A or B with high-titre inhibitors (≥5 BU) or with low-titre inhibitors who are expected to have a high anamnestic response to factor VIII or factor IX, or to be refractory to increased dosing of these factors. The efficacy and safety of eptacog beta were evaluated in three Phase III clinical studies, PERSEPT 1, 2 and 3. For the EMA filing dossier, the analysis of data from PERSEPT 1 and 2 differed from the analysis used to support the filing in the US. In this review, we summarise current data regarding the mode of action, clinical efficacy and safety of eptacog beta for the management of haemophilia A and B in patients with inhibitors from a European perspective. In addition to providing a valuable summary of the analyses of the clinical data for eptacog beta conducted for the EMA, our review summarises the potential differentiators for eptacog beta compared with other current bypassing agents.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".