Reduced Effectiveness of Anti-IgE Treatment Among Adults with Severe Asthma with Older Age of Asthma Onset: Results from the CHRONICLE Study
Bibliographic record
Abstract
Purpose: Younger age of asthma onset (AAO) has been associated with an allergic phenotype, whereas eosinophilic phenotypes have been associated with older AAO. In randomized trials, biologic efficacy among adults with severe asthma (SA) has varied by age at asthma onset. To determine whether these associations observed in trials apply to real-world outcomes, this study examined biologic effectiveness by AAO and biologic class in a large, real-world cohort. Patients and methods: CHRONICLE is an ongoing, real-world study of US adults with subspecialist-treated SA receiving biologics, maintenance corticosteroids, or who are uncontrolled on high-dosage inhaled corticosteroids with additional controllers. Patients enrolled between February 2018 and February 2022 who initiated a biologic for SA and had complete data for analysis were included. A locally estimated scatterplot smoothing (LOESS) analysis was used to plot the relationship between percentage exacerbation rate reduction and AAO by biologic class. Results: Of 578 patients with complete data, 198, 149, and 231 were diagnosed with asthma at age <18, 18-39, and ≥40 years, respectively. Across subgroups, patients were predominantly White (72-78%), female (67-73%), and commercially insured (54-71%). In the LOESS analysis, exacerbation rate reductions were similar for anti-IgE and anti-IL-5/5R and anti-IL-4R subgroups with younger AAO, but the exacerbation rate reduction diminished for patients with older AAO receiving anti-IgE therapy, particularly with asthma onset age ≥40 years. Conclusion: Clinicians should consider age of onset in biologic treatment decisions, given reduced effectiveness of omalizumab in patients with asthma onset at age ≥40 years. Clinicaltrialsgov Identifier: NCT03373045.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".