Core outcome set for gene therapy in haemophilia: Results of the core<scp>HEM</scp> multistakeholder project
Bibliographic record
Abstract
BACKGROUND: Gene therapy trial results show potential to cure haemophilia A and haemophilia B. Securing broad access to a cure for a lifelong chronic disease is anticipated to face barriers at the individual and healthcare system levels, which can be partly mitigated by harmonized planning of clinical research studies. The aim of the coreHEM project was to determine the set of outcome measures required to evaluate efficacy, safety, comparative effectiveness and value of gene therapy for haemophilia. METHODS: Modified Delphi consensus process, based on methods adapted from the COMET Initiative. RESULTS: Forty-nine participants (five patients, five clinicians, five researchers, four regulators, three research agencies, six health technology assessors, nine payers and 12 drug developers) took part in the study, with over 90% participation. The frequency of bleeds, factor activity level, duration of expression, chronic pain, healthcare resource use and mental health were identified as the core outcomes to be measured in addition to regulatory-mandated adverse effects. CONCLUSIONS: For the first time in haemophilia, a core outcome set has been developed, with the involvement of representatives of all relevant stakeholder groups. The core set has been expanded to include outcomes supporting assessment of comparative effectiveness and value, with the goal of streamlining regulatory approval, health technology assessment and market access decisions. Patient involvement ensures that outcomes are meaningful and relevant to those living with haemophilia. Active dialogue among drug developers, regulators and payers throughout the process is expected to facilitate broad uptake of the core outcomes in forthcoming clinical trials.
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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 | 0.187 | 0.186 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".