The potential impact of gene therapy on health-related quality of life (HRQoL) domains in haemophilia
Bibliographic record
Abstract
Abstract Introduction Haemophilia is an inherited bleeding disorder characterised by spontaneous bleeding, often leading to impaired health-related quality of life (HRQoL). Commonly used treatments include episodic and prophylactic treatment regimens. Gene therapies could soon become available, potentially creating a paradigm shift in patient management. Aim This paper proposes hypotheses about the potential impact of gene therapy on HRQoL domains in haemophilia, and how these impacts might differ compared with existing treatments. Methods An expert working group with 10 individuals experienced in haemophilia and HRQoL research was established to discuss potential impacts of gene therapy on HRQoL in general and for specific domains in haemophilia. As part of a one-day workshop, domains of three widely used patient-reported outcome (PRO) instruments were explored: the Haemo-QoL-A, the Patient Reported Outcomes, Burden and Experiences (PROBE), and the Haemophilia Activities List (HAL). Results The group expected a greater improvement in HRQoL from gene therapy compared with existing treatments for the following domains: physical/role functioning, worry, and consequences of bleeding (Haemo-QoL-A); haemophilia-related health and EQ-5D-5L (part of the PROBE); leg and arm function, and leisure activities (HAL). In contrast, the experts suggested that no change or potential deterioration might be observed for the emotional impact (HAL) and treatment concerns (Haemo-QoL-A) domains. Conclusions Current PRO instruments in haemophilia have limitations when applied in the context of gene therapy, and no single instrument fully captures the relevant HRQoL domains. However, the PROBE and Haemo-QoL-A were considered as the most suitable existing instruments. As haemophilia treatments evolve, further research should examine the potential effectiveness of existing PRO instruments as compared to the development of novel PRO measures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".