Impact of Initiating Biologics in Patients With Severe Asthma on Long-Term Oral Corticosteroids or Frequent Rescue Steroids (GLITTER): Data From the International Severe Asthma Registry
Bibliographic record
Abstract
BACKGROUND: Effectiveness of biologics has neither been established in patients with high oral corticosteroid exposure (HOCS) nor been compared with effectiveness of continuing with HOCS alone. OBJECTIVE: To examine the effectiveness of initiating biologics in a large, real-world cohort of adult patients with severe asthma and HOCS. METHODS: This was a propensity score-matched, prospective cohort study using data from the International Severe Asthma Registry. Between January 2015 and February 2021, patients with severe asthma and HOCS (long-term OCSs for ≥1 year or ≥4 courses of rescue OCSs within a 12-month period) were identified. Biologic initiators were identified and, using propensity scores, matched 1:1 with noninitiators. The impact of biologic initiation on asthma outcomes was assessed using generalized linear models. RESULTS: We identified 996 matched pairs of patients. Both groups improved over the 12-month follow-up period, but improvement was greater for biologic initiators. Biologic initiation was associated with a 72.9% reduction in the average number of exacerbations per year versus noninitiators (0.64 vs 2.06; rate ratio, 0.27 [95% CI, 0.10-0.71]). Biologic initiators were 2.2 times more likely than noninitiators to take a daily long-term OCS dose of less than 5 mg (risk probability, 49.6% vs 22.5%; P = .002) and had a lower risk of asthma-related emergency department visits (relative risk, 0.35 [95% CI, 0.21-0.58]; rate ratio, 0.26 [0.14-0.48]) and hospitalizations (relative risk, 0.31 [95% CI, 0.18-0.52]; rate ratio, 0.25 [0.13-0.48]). CONCLUSIONS: In a real-world setting, including patients with severe asthma and HOCS from 19 countries, and within an environment of clinical improvement, initiation of biologics was associated with further improvements across multiple asthma outcomes, including exacerbation rate, OCS exposure, and health care resource utilization.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".