An Update on Biologics in Pediatric Asthma: A Canadian Perspective
Bibliographic record
Abstract
Asthma is one of the most common chronic diseases in Canada, affecting approximately 11% of Canadians. Severe asthma, estimated to affect 5–10% of patients with asthma, is associated with a significant burden of disease‑related morbidity. In adults, typical management strategies include using combinations of inhaled corticosteroids, long-acting beta agonists, leukotriene receptor antagonists, long-acting muscarinic antagonists, and oral corticosteroids. However, in pediatric cases, particularly young children, our medication options are more limited. Although inhaled corticosteroids are effective for the majority of mild-to-moderate asthma cases, their efficacy in non-atopic asthma is limited. Furthermore, using inhaled corticosteroids at moderate-to-high doses can impair linear growth and lead to adrenal suppression. Given our growing recognition of asthma as a heterogenous disease, with multiple disease endotypes driven by distinct inflammatory pathways, there is an increasing demand for targeted therapies, particularly for patients with ongoing, uncontrolled disease (Figure 1). Type 2 (T2) high inflammation, characterized by elevated levels of IgE, interleukin (IL)-4, IL-5, and IL-13, alongside eosinophilia and atopy, remains the most well-defined endotype in school-age children and youth. With the advent of biologic medications, targeting T2‑high inflammatory pathways has become a critical component for managing uncontrolled, moderate‑to-severe asthma in children. This approach aims to improve treatment response and reduce adverse effects. This review will explore the biologic therapies currently available in Canada for moderate-to-severe pediatric asthma, discuss key considerations in selecting the optimal biologic, and outline future research directions to inform the optimal timing for initiating and discontinuing biologic treatments.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".