Current Understanding of Inherited Modifiers of FVIII Pharmacokinetic Variation
Bibliographic record
Abstract
Abstract: The inherited bleeding disorder hemophilia A involves the quantitative deficiency of the coagulation cofactor factor VIII (FVIII). Prophylactic treatment of severe hemophilia A patients with FVIII concentrates aims to reduce the frequency of spontaneous joint bleeding and requires personalized tailoring of dosing regimens to account for the substantial inter-individual variability of FVIII pharmacokinetics. The strong reproducibility of FVIII pharmacokinetic (PK) metrics between repeat analyses in the same individual suggests this trait is genetically regulated. While the influence of plasma von Willebrand factor antigen (VWF:Ag) levels, ABO blood group, and patient age on FVIII PK is well established, estimates suggest these factors account for less than 35% of the overall variability in FVIII PK. More recent studies have identified genetic determinants that modify FVIII clearance or half-life including VWF gene variants that impair VWF-FVIII binding resulting in the accelerated clearance of VWF-free FVIII. Additionally, variants in receptors that regulate the clearance of FVIII or the VWF-FVIII complex have been associated with FVIII PK. The characterization of genetic modifiers of FVIII PK will provide mechanistic insight into a subject of clinical significance and support the development of personalized treatment plans for patients with hemophilia A. Keywords: factor VIII, hemophilia A, von Willebrand factor, pharmacokinetics, clearance receptor
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".