Adherence to inhaled corticosteroids and clinical outcomes in mepolizumab therapy for severe asthma
Bibliographic record
Abstract
Introduction Inhaled corticosteroids (ICS) achieve disease control in the majority of asthmatic patients, although adherence to prescribed ICS is often poor. Patients with severe eosinophilic asthma may require treatment with oral corticosteroids (OCS) and/or biologic agents such as mepolizumab. It is unknown if ICS adherence changes on, or alters clinical response to, biologic therapy. Methods We examined ICS adherence and clinical outcomes in OCS-dependent severe eosinophilic asthma patients who completed 1 year of mepolizumab therapy. The ICS medicines possession ratio (MPR) was calculated (the number of doses of ICS issued on prescription/expected number) for the year before and the year after biologic initiation. Good adherence was defined as MPR >0.75, intermediate 0.74–0.51 and poor <0.5. We examined outcomes after 12 months of biologic therapy, including OCS reduction and annualised exacerbation rate (AER), stratified by adherence to ICS on mepolizumab. Results Out of 109 patients commencing mepolizumab, 91 who had completed 12 months of treatment were included in the final analysis. While receiving mepolizumab, 68% had good ICS adherence, with 16 (18%) having poor ICS adherence. ICS use within the cohort remained similar before (MPR 0.81±0.32) and during mepolizumab treatment (0.82±0.32; p=0.78). Patients with good adherence had greater reductions in OCS dose (median (interquartile range) OCS reduction 100 (74–100)% versus 60 (27–100)%; p=0.031) and exacerbations (AER change −2.1±3.1 versus 0.3±2.5; p=0.011) than those with poor adherence. Good ICS adherence predicted the likelihood of stopping maintenance OCS (adjusted OR 3.19, 95% CI 1.02–9.94; p=0.045). Conclusion ICS nonadherence is common in severe eosinophilic asthma patients receiving mepolizumab, and is associated with a lesser reduction in OCS requirements and AER.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".