Association of patient, treatment and disease characteristics with patient‐reported outcomes: Results of the ECHO Registry
Bibliographic record
Abstract
Abstract Introduction Patient‐reported outcomes (PROs) in people living with haemophilia A (PLWHA) are often under‐reported. Investigating PROs from a single study with a diverse population of PLWHA is valuable, irrespective of FVIII product or regimen. Aim To report available data from the Expanding Communications on Haemophilia A Outcomes (ECHO) registry investigating the associations of patient, treatment and disease characteristics with PROs and clinical outcomes in PLWHA. Methods ECHO (NCT02396862), a prospective, multinational, observational registry, enrolled participants aged ≥16 years with moderate or severe haemophilia A using any product or treatment regimen. Data collection, including a variety of PRO questionnaires, was planned at baseline and annually for ≥2 years. Associations between PRO scores and patient, treatment and disease characteristics were determined by statistical analyses. Results ECHO was terminated early owing to logistical constraints. Baseline data were available from 269 PLWHA from Europe, the United States and Japan. Most participants received prophylactic treatment (76.2%), with those using extended‐half‐life products (10.0%) reporting higher treatment satisfaction. Older age and body weight >30 kg/m2 (>BMI) were associated with poorer joint health. Older age was associated with poorer physical functioning and work productivity. Health‐related quality of life and pain interference also deteriorated with age and >BMI; >BMI also increased pain severity scores. Conclusion ECHO captured a variety of disease characteristics, treatment patterns, PROs and clinical outcomes obtained in real‐world practice with ≤1 year's follow‐up. Older age, poorer joint health and >BMI adversely affected multiple aspects of participant well‐being.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".