Patients’ perspectives of eosinophilic granulomatosis with polyangiitis within the context of a clinical trial
Bibliographic record
Abstract
Objectives: Eosinophilic granulomatosis with polyangiitis (EGPA) is a complex, multisystem form of vasculitis. MANDARA (NCT04157348) was a phase 3 clinical trial comparing the efficacy and safety of benralizumab versus mepolizumab, in addition to standard of care, for relapsing/refractory EGPA. This qualitative interview substudy explored study participants' experiences with EGPA and their participation in the trial. Methods: Thirty-eight patients from 5 countries participating in MANDARA opted into a longitudinal qualitative substudy, which comprised two 60-minute, semistructured, one-to-one telephone interviews conducted by trained interviewers between December 2019 and June 2023. Topics discussed included motivation to join the trial, time since diagnosis, symptoms, and impacts of EGPA and their degree of 'bothersomeness' and 'disturbance'. Results: The desire to stop or reduce the use of oral glucocorticoids was the most frequently mentioned motivation for, and expectation of, participation in the trial. Comparison of interviews between the 2 time points suggested patients experienced reductions in the number and impact of EGPA-related symptoms and bothersomeness and/or disturbance ratings. Most improved symptoms included difficulty breathing, nasal congestion/discharge, and fatigue, and most improved impacts included ability to exercise, quality/quantity of sleep, and ability to engage in social activities. Conclusions: This study provides insights regarding patients' perspectives of EGPA and their perceptions and experiences associated with receiving an anti-interleukin-5/receptor therapy. These findings highlight the need for effective treatments that allow patients to reduce their use of oral glucocorticoids and the importance of assessing patient experiences when gauging treatment efficacy in EGPA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.031 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".