Burden of eosinophilic granulomatosis with polyangiitis by disease phase and steroid-sparing effects of biologics: a real-world retrospective study in Europe
Bibliographic record
Abstract
Objectives The aim of the study was to describe insights into real-world characteristics and clinical outcomes of patients with a history of eosinophilic granulomatosis with polyangiitis (EGPA) across Europe, stratified by disease phase and biologics use. Methods This was a retrospective, physician-panel chart review study in patients with a history of EGPA from five European countries covering the period January 2015–August 2021 (GSK ID: 214661). Outcomes assessed included: baseline characteristics; treatment patterns; clinical outcomes and healthcare resource utilisation (HCRU), which were stratified post hoc by EGPA disease phase and biologics use. Oral corticosteroid (OCS) use was assessed ≤12 months pre- and post-biologics initiation. Results Overall, 407 patients were included: disease phase was identified for 381 patients (36 prodromal; 220 eosinophilic; 125 vasculitic); 185 patients received biologics, and 162 had pre-/post-biologics initiation periods identified. Patients in the vasculitic subgroup had the most comorbidities and clinical manifestations, and the greatest proportion of patients with hospitalisation versus the eosinophilic or prodromal subgroups. All subgroups had high OCS use (97.2–99.1%). The biologics-exposed subgroup had high comorbidity and HCRU burden. Post- versus pre-biologics initiation, OCS use was reduced (0.12 versus 0.69 prescriptions per person-year), the proportion of patients experiencing relapses decreased (3.1% (95% confidence interval: 0.4–5.7) versus 11.7% (6.8–16.7)) and remissions increased (26.5% (19.7–33.3) versus 13.0% (7.8–18.1). Conclusion Although the vasculitic subgroup showed the greatest disease severity, all subgroups demonstrated a substantial disease burden. Results also suggest biologics provide OCS-sparing effects and improve disease control in real-world settings.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 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".