An international survey assessing the effects of the duration of attack-free period on health-related quality of life for patients with hereditary angioedema
Bibliographic record
Abstract
BACKGROUND: Hereditary angioedema (HAE) is characterized by unpredictable and often severe cutaneous and mucosal swelling that affects the extremities, face, larynx, gastrointestinal tract, or genitourinary area. Introduction of novel long-term prophylactic treatment options (lanadelumab, berotralstat, and C1-esterase inhibitor SC [human]) into the treatment armamentarium has substantially reduced HAE attacks, allowing patients to be attack free for longer with improvements to their quality of life. Using data drawn from a wide-ranging survey of patients with HAE, we examined the relationship between duration of time attack free and health-related quality of life (HRQoL), exploring the possibility that there is an association between observed improvement in HRQoL and attack-free duration. METHODS: A survey among patients with HAE on long-term prophylaxis (LTP) in six countries (the US, Australia, Canada, UK, Germany, and Japan) assessed the relationship between attack-free duration and mean Angioedema Quality of Life (AE-QoL) scores, quality of life benefits, and rescue medication used. Analysis of covariance (ANCOVA) was used to assess the roles of LTP and attack-free period (< 1 month, 1- < 6 months, ≥ 6 months) on total AE-QoL scores. Results include descriptive p-values for strength of association, without control for multiplicity. Descriptive statistics were used to show the relationship between time attack free and quality of life benefits. RESULTS: Longer durations of time for which participants reported being attack free at the time of the survey correlated with better AE-QoL scores and less use of rescue medication. The mean total AE-QoL scores were 51.8, 33.2, and 19.9 for those who reported having been attack free for < 1 month, 1- < 6 months, and ≥ 6 months, respectively, with higher scores reflecting more impairment. The ANCOVA results showed a strong association between attack-free duration and AE-QoL total score. CONCLUSION: This study shows that longer attack-free duration has an influential role for better HRQoL in patients receiving LTP. Prolonging the attack-free period is an important goal of therapy and recent advances in LTP have increased attack-free duration. However, opportunities exist for new treatments to further increase attack-free duration and improve HRQoL for all patients with HAE.
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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 | 0.002 | 0.005 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".