Mepolizumab to benralizumab: A case series of a biologic switch in severe asthma
Bibliographic record
Abstract
BACKGROUND Multiple biologics are approved for severe asthma; however, there is a lack of large head-to-head clinical trials to guide biologic selection. There are no defined criteria for discontinuation of biologics, assessing clinical response or guidance for another biologic selection. This case series aims to evaluate patients at a Canadian center with severe eosinophilic asthma with sub-optimal response to mepolizumab, switched to benralizumab for better asthma control.METHODS Twelve patients were identified who had switched from mepolizumab to benralizumab. Inclusion criteria included patients over 18 years of age, a diagnosis of severe asthma as per Canadian Thoracic Society (CTS) guidelines, and treatment with mepolizumab for at least 3 months, then benralizumab for at least 3 months. Clinical outcomes including the Asthma Control Questionnaire (ACQ), lung function (forced expiratory volume in 1 second [FEV1]), oral corticosteroid use, blood eosinophils and annual exacerbation rate (AER) were evaluated.RESULTS Treatment with mepolizumab then benralizumab demonstrated significant clinical improvement in ACQ, AER and blood eosinophils, when compared to baseline data. Comparison of post-mepolizumab endpoints to post-benralizumab endpoints revealed no significant change in clinical outcomes. Half of the patients discontinued benralizumab due to persistent symptoms.CONCLUSIONS In this small series of 12 patients with a suboptimal response to mepolizumab, a switch to benralizumab showed no significant difference. There was a trend toward improved symptoms and reduced exacerbations. We identified a subset of patients with severe eosinophilic asthma with an incomplete response to anti IL-5/5R therapies. Further work is required to better characterize these patients to guide biologic choice.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".