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Record W4411554707 · doi:10.1016/j.rpth.2025.102948

Why is the uptake of gene therapy in hemophilia less than expected?

2025· editorial· en· W4411554707 on OpenAlexafffund
Glenn F. Pierce, Mark W. Skinner, Brian O’Mahony, Dawn Rotellini, Radosław Kaczmarek

Bibliographic record

VenueResearch and Practice in Thrombosis and Haemostasis · 2025
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsImpactMcMaster UniversityCanadian Hemophilia Society
FundersWorld Federation of Hemophilia
KeywordsGenetic enhancementReimbursementMedicineFactor IXIntensive care medicineVector (molecular biology)GeneSurgeryInternal medicineBiologyGeneticsRecombinant DNAPolitical scienceHealth care

Abstract

fetched live from OpenAlex

Gene therapy has held promise to cure hemophilia since factor (F)VIII and FIX were cloned more than 40 years ago. However, scientific understanding of the adeno-associated virus, the predominant vector used in gene therapy, has been insufficient to overcome many of the hurdles encountered, resulting in failed clinical studies, marginal efficacy, unfavorable benefit/risk, or phase 3 studies that do not sufficiently support wide commercial use. However, a functional cure, defined as permanent factor levels of at least 40%, has seen durable success in some FIX gene therapy recipients. Less success has been seen for FVIII gene therapy. Additional reasons for slow commercial uptake include the need to establish complex reimbursement processes for very high-priced drugs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.022
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.035
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.001
Science and technology studies0.0030.005
Scholarly communication0.0080.008
Open science0.0030.001
Research integrity0.0220.030
Insufficient payload (model declined to judge)0.0060.006

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.

Opus teacher head0.107
GPT teacher head0.434
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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".

Quick stats

Citations6
Published2025
Admission routes2
Has abstractyes

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