Hemophilia gene therapy: first, do no harm
Bibliographic record
Abstract
The introduction of adeno-associated virus-mediated, liver-directed gene therapy into the hemophilia treatment landscape brings not only great promise but also considerable uncertainty to a community that has a history punctuated by the devastating effects of HIV and hepatitis C virus. These infections were introduced into people with hemophilia through the innovation of factor concentrates in the 1970s and 1980s. Concentrates, heralded as a major advance in treatment at the time, brought devastation and death to the community already challenged by the complications of bleeding into joints, vital organs, and the brain. Over the past 5 decades, considerable advances in hemophilia treatment have improved the survival, quality of life, and participation of people with hemophilia, although challenges remain and health equity with their unaffected peers has not yet been achieved. The decision to take a gene therapy product is one in which an informed, holistic, and shared decision-making approach must be employed. Bias on the part of health care professionals and people with hemophilia must be addressed and minimized. Here, we review data leading to the regulatory authorization of valoctocogene roxaparvovec, an adeno-associated virus 5 gene therapy, in Europe to treat hemophilia A and etranacogene dezaparvovec-drlb in the United States and Europe to treat hemophilia B. We also provide an overview of the decision-making process and recommend steps that should be taken by the hemophilia community to ensure the safety of and optimal outcomes for people with hemophilia who choose to receive a gene therapy product.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".