Role of Biologics in Asthma
Bibliographic record
Abstract
Patients with severe uncontrolled asthma have disproportionally high morbidity and healthcare utilization as compared with their peers with well-controlled disease. Although treatment options for these patients were previously limited, with unacceptable side effects, the emergence of biologic therapies for the treatment of asthma has provided promising targeted therapy for these patients. Biologic therapies target specific inflammatory pathways involved in the pathogenesis of asthma, particularly in patients with an endotype driven by type 2 (T2) inflammation. In addition to anti-IgE therapy that has improved outcomes in allergic asthma for more than a decade, three anti-IL-5 biologics and one anti-IL-4R biologic have recently emerged as promising treatments for T2 asthma. These targeted therapies have been shown to reduce asthma exacerbations, improve lung function, reduce oral corticosteroid use, and improve quality of life in appropriately selected patients. In addition to the currently approved biologic agents, several biologics targeting upstream inflammatory mediators are in clinical trials, with possible approval on the horizon. This article reviews the mechanism of action, indications, expected benefits, and side effects of each of the currently approved biologics for severe uncontrolled asthma and discusses promising therapeutic targets for the future.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".