Real-World mepolizumab outcomes in severe asthma; REALITI-A post hoc analysis by exacerbation history
Bibliographic record
Abstract
Context: In severe asthma (SA), a history of exacerbations is associated with a poorer prognosis. Mepolizumab reduces clinically significant asthma exacerbations (CSEs) and maintenance oral corticosteroid (mOCS) use in SA. Aim: To assess the impact of prior exacerbation history on mepolizumab outcomes in SA. Methods: REALITI-A, a 2-year international, prospective study, enrolled adults with asthma newly prescribed (physician’s discretion) mepolizumab 100 mg subcutaneously (index). Data were collected 12 months pre- and 24 months post-index. This post hoc analysis assessed outcomes grouped by exacerbation history (0–2, 3–4 and ≥5 exacerbations in the year before enrolment) and included the rate of CSEs (requiring systemic corticosteroids and/or an emergency department visit/hospitalisation) pre- and post-index, change from baseline (28 days before index) in daily mOCS dose at Weeks 101–104, and change from baseline (90 days before index) in Asthma Control Questionnaire (ACQ)-5 score at Month 24. This is an encore publication of poster “ PA630: Real-world mepolizumab outcomes in severe asthma: REALITI-A post hoc analysis by exacerbation history” at ERS 09-13 September 2023 in Milan. Fig. 1 Results: All outcomes improved post- vs pre- index, regardless of exacerbation history ( Table ). The rate of CSEs reduced by 59–80%. At Week 101–104, median mOCS dose reduced by 75–100%; 45–72% of patients discontinued mOCS. At Month 24, least squares mean ACQ-5 scores improved by 1.3–1.7 points. Conclusions: Real-world mepolizumab therapy benefits patients with SA, regardless of exacerbation history. Funding: GSK (204710) Publication History Article published online: 01 March 2024 © 2024. Thieme. All rights reserved. Georg Thieme Verlag Rüdigerstraße 14, 70469 Stuttgart, Germany
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".