The Hemophilia Gene Therapy Patient Journey: Questions and Answers for Shared Decision-Making
Bibliographic record
Abstract
Purpose: The anticipated emergence of hemophilia gene therapy will present people with hemophilia (PWH) and treating clinicians with increasingly complex treatment options. It will be critical that PWH and their families be empowered to participate fully in decision-making through transparent communication and the development of targeted educational resources. Methods: The Council of Hemophilia Community (CHC) convened across a series of roundtable meetings to define the patient journey for hemophilia gene therapy, and to develop a question-and-answer style resource to guide discussion between healthcare professionals (HCPs) and their patients. Patient groups were also consulted during the development of this tool. Results: The CHC defined 5 key stages in the hemophilia gene therapy patient journey: pre-gene therapy (information-seeking and decision-making), treatment initiation, short- and long-term post-gene therapy follow-up. PWH will have different questions and concerns at each stage of their journey, which should be discussed with their HCP to aid decision-making. The resulting patient journey infographic and Q&A resource (see Supplementary Materials) has been developed for HCPs and PWH to provide a novel and practical roadmap of key issues and considerations throughout all stages. Conclusion: These resources support a collaborative, patient-centric, shared decision-making approach to inform treatment decision discussions between HCPs and PWH. The value of such discussions will be influenced by the language adopted; health literacy is a particularly important consideration, and these discussions should be accessible and tailored to PWH. HCPs and PWH can benefit from awareness of the common questions and uncertainties as they progress together along the patient journey. While the contents of this article are specific to hemophilia gene therapy, the concepts developed here could be adapted to aid patients in other disease states.
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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 | 0.091 | 0.149 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.019 | 0.017 |
| Open science | 0.004 | 0.027 |
| Research integrity | 0.011 | 0.022 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".