Unmet Needs, Factor Consumption, and Healthcare Resource Use Among People with Hemophilia a: Real-World Analysis of the Adelphi Hemophilia Disease Specific ProgrammeTM
Bibliographic record
Abstract
Introduction The standard of care for people living with hemophilia A is life-long prophylaxis treatment with factor VIII replacement therapies (standard half-life [SHL], extended half-life [EHL]), or non-factor therapy (NFT), emicizumab. Despite the improvement in disease management and the availability of new therapies in recent years, bleeds still occur, which impact patients' physical health and quality of life (QoL). Aim This study aimed to understand the unmet needs in patients with moderate or severe hemophilia A receiving prophylactic treatment, by evaluating patient- and physician-reported outcomes and bleeds. Methods Data were drawn from the Adelphi Hemophilia Disease Specific Programme™, a real-world cross-sectional survey of hemophilia treating physicians and their patients in the United States, from July 2023 to March 2024. Physicians reported patient demographics, treatment history, FVIII activity levels, annual bleeding rate (ABR), joint problems, therapy use and employment status for their patients. Patients voluntarily reported the impact of hemophilia A on their QoL. Patients included in this study had hemophilia A with no inhibitors (at time of survey), known baseline clotting factor FVIII level, and had received prophylaxis treatment with NFT or prophylactic (plus on-demand) EHL or SHL therapies. ABR is reported only for those who received treatment for >365 days. Analyses were descriptive. Results Data were collected from 47 physicians for 244 patients (mean age ± standard deviation [SD] 27.4 ± 14.7 years, with 10.7% of patients aged 0-11 years, 7.8% aged 12-17 years and 81.6% aged ≥18 years). At the time of survey, 92 patients had FVIII activity levels of 2.0-5.0%; 90 patients had FVIII levels of 1.0-2.0%; and 62 patients had FVIII levels of <1.0%. A total of 113 patients received treatment with SHL therapy (n=39 for >365 days), 40 received EHL therapy (n=23 for >365 days) and 67 received NFT (n=29 for >365 days). Physicians reported that, in the 12 months prior to the survey, the mean (95% confidence interval [CI]) ABR for patients (n=91) was 0.80 (95% CI 0.57, 1.03). For patients who received SHL therapy the mean ABR was 0.77 (95% CI 0.45, 1.15), for patients who received EHL therapy the mean ABR was 1.09 (95% CI 0.46, 1.74), and for patients who received NFT the mean ABR was 0.52 (95% 0.22, 0.78). In the 12 months prior to the survey, a total of 39 patients experienced one or more bleeds. Of the patients who received SHL, EHL and NFT, 41.0%, 52.2% and 37.9% experienced one or more bleeds, respectively. Overall, 25% of patients suffered from joint problems in the 12 months prior to the survey. Physicians reported that 44.3% of all patients utilized therapy to improve their joint health, including physical therapy (26.2%), yoga/pilates (13.9%), or massage (9.4%). Physicians reported that 23.0% of patients used an aid (brace, splints, orthotics, walking stick or crutches) due to joint damage caused by their hemophilia A. Furthermore, physicians also reported that among patients who were not working full time (n=32), 28.1% attributed their inability to work to their hemophilia A. Corresponding patient-reported data were available for 26 patients. Across all treatment groups, 55.0% (n=11) of patients reported nervousness/anxiety and 40.0% (n=8) of patients reported they fear or worry about their hemophilia A. Eighty percent (n=20) of patients reported that they worry about having breakthrough bleeds. A total of 73.7% (n=14) of patients reported they had difficulty taking part in sports and hobbies due to hemophilia A. Additionally, 84.0% (n=21) of patients reported that they avoid physical activities due to hemophilia A, with 12.0% (n=3) stating that they avoided physical activities often. Conclusion Despite receiving regular prophylactic and on-demand treatment, more than one-third of patients with moderate or severe hemophilia A experienced one or more bleeding episodes per year. Both patients and physicians reported that hemophilia A negatively impacted patients' QoL. One-quarter of physicians reported that patients experienced joint problems, with most patients avoiding physical activity due to hemophilia A. These findings indicate that despite recent advances, an unmet need remains for efficacious treatments that may improve QoL in this population.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".