The effect of emicizumab prophylaxis on long‐term, self‐reported physical health in persons with haemophilia A without factor VIII inhibitors in the HAVEN 3 and HAVEN 4 studies
Bibliographic record
Abstract
INTRODUCTION: Severe haemophilia A (HA) has a major impact on health-related quality of life (HRQoL). AIM: Assess the impact of emicizumab on HRQoL in persons with severe HA (PwHA) without factor VIII (FVIII) inhibitors in the phase 3 HAVEN 3 and 4 studies. METHODS: This pooled analysis examines the HRQoL of PwHA aged ≥ 18 years treated with emicizumab prophylaxis via Haemophilia-Specific Quality of Life Questionnaire for Adults (Haem-A-QoL) and EuroQoL 5-Dimensions 5-levels (EQ-5D-5L). In particular, changes from baseline in Haem-A-QoL 'Physical Health' (PH) domain and 'Total Score' (TS) are evaluated. RESULTS: Among 176 evaluable participants, 96 (55%) had received prior episodic treatment and 80 (45%) prophylaxis; 70% had ≥ 1 target joint and 51% had experienced ≥ 9 bleeds in the previous 24 weeks. Mean Haem-A-QoL PH and TS improved after emicizumab initiation. Mean (standard deviation) -12.0 (21.26)- and -8.6 (12.57)-point improvements were observed in PH and TS from baseline to Week 73; Week 73 scores were 27.9 (24.54) and 22.0 (14.38), respectively. Fifty-four percent of participants reported a clinically meaningful improvement in PH scores (≥ 10 points) by Week 73. Subgroups with poorer HRQoL prior to starting emicizumab (i.e. receiving episodic treatment, ≥ 9 bleeds, target joints) had the greatest improvements in PH scores, and corresponding reductions in missed workdays; change was not detected among those previously taking prophylaxis. No change over time was detected by the EQ-5D-5L questionnaire. CONCLUSIONS: Emicizumab prophylaxis in PwHA without FVIII inhibitors resulted in persistent and meaningful improvements in Haem-A-QoL PH and less work disruption than previous treatment.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".