Disease Burden and Access to Biologic Therapy in Patients with Severe Asthma, 2017–2022: An Analysis of the International Severe Asthma Registry
Bibliographic record
Abstract
Introduction: Patients with severe asthma may be prescribed biologic therapies to improve disease control. The EVEREST study aimed to characterize the global disease burden of patients with severe asthma without access to biologics and those who have access but do not receive biologics, as well as the remaining unmet need despite use of these therapies. Methods: This was a historical cohort study of patients with severe asthma (aged ≥18 years) in the International Severe Asthma Registry receiving Global Initiative for Asthma (GINA) 2018 step 5 treatment, or with uncontrolled disease at GINA step 4. Prospective data on patient clinical characteristics, healthcare resource utilization, and medication use over a 12-month period between December 2017 and May 2022 were assessed for the following five groups: biologics accessible (omalizumab, mepolizumab, reslizumab, benralizumab, or dupilumab); biologics inaccessible; biologics accessible but not received; biologics accessible and received; and biologic recipients whose asthma remained suboptimally controlled. Results: Overall, 9587 patients from 21 countries were included. Among patients in the biologics accessible (n=5073), biologics inaccessible (n=3041), and biologics accessible but not received (n=382) groups, 41.4%, 18.7%, and 49.6% experienced at least two exacerbations, 11.5%, 10.5%, and 6.2% required at least one hospitalization, 47.9%, 54.6%, and 71.2% had uncontrolled asthma, and 23.9%, 8.6%, and 11.0% received long-term oral corticosteroids (LTOCS), respectively. Following biologic therapy, among patients who received biologics overall (n=2666) and among those whose asthma remained suboptimally controlled (n=1780), 19.1% and 23.0% experienced at least two exacerbations, 2.7% and 2.9% required at least one hospitalization, and 16.7% and 22.0% received LTOCS, respectively. Conclusion: There is a substantial disease burden in both patients without access to biologics and those with access who do not receive these therapies, although specific outcomes may vary between these groups. There also remains a high unmet need among biologic recipients, many of whom have a suboptimal response to treatment.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".