Association Between T2-related Comorbidities and Effectiveness of Biologics in Severe Asthma
Bibliographic record
Abstract
Abstract Rationale Previous studies investigating the impact of comorbidities on the effectiveness of biologic agents have been relatively small and of short duration and have not compared classes of biologic agents. Objectives To determine the association between type 2–related comorbidities and biologic agent effectiveness in adults with severe asthma (SA). Methods This cohort study used International Severe Asthma Registry data from 21 countries (2017–2022) to quantify changes in four outcomes before and after biologic therapy—annual asthma exacerbation rate, FEV1% predicted, asthma control, and long-term oral corticosteroid daily dose—in patients with or without allergic rhinitis, chronic rhinosinusitis (CRS) with or without nasal polyps (NPs), NPs, or eczema/atopic dermatitis. Measurements and Main Results Of 1,765 patients, 1,257, 421, and 87 initiated anti–IL-5/5 receptor, anti-IgE, and anti–IL-4/13 therapies, respectively. In general, pre- versus post–biologic therapy improvements were noted in all four asthma outcomes assessed, irrespective of comorbidity status. However, patients with comorbid CRS with or without NPs experienced 23% fewer exacerbations per year (95% CI, 10–35%; P < 0.001) and had 59% higher odds of better post–biologic therapy asthma control (95% CI, 26–102%; P < 0.001) than those without CRS with or without NPs. Similar estimates were noted for those with comorbid NPs: 22% fewer exacerbations and 56% higher odds of better post–biologic therapy control. Patients with SA and CRS with or without NPs had an additional FEV1% predicted improvement of 3.2% (95% CI, 1.0–5.3; P = 0.004), a trend that was also noted in those with comorbid NPs. The presence of allergic rhinitis or atopic dermatitis was not associated with post–biologic therapy effect for any outcome assessed. Conclusions These findings highlight the importance of systematic comorbidity evaluation. The presence of CRS with or without NPs or NPs alone may be considered a predictor of the effectiveness of biologic agents in patients with SA.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".