Efficacy and safety of treatment with dupilumab for severe asthma: A systematic review of the EAACI guidelines—Recommendations on the use of biologicals in severe asthma
Bibliographic record
Abstract
Abstract Dupilumab, a fully human monoclonal antibody against interleukin‐4 receptor α, is approved as add‐on maintenance treatment for inadequately controlled type 2 severe asthma. This systematic review evaluated the efficacy, safety and economic impact of dupilumab compared to standard of care for uncontrolled severe asthma. PubMed, EMBASE and Cochrane Library were searched for RCTs and health economic evaluations. Critical and important asthma‐related outcomes were evaluated. The risk of bias and the certainty of the evidence were assessed using GRADE. Three RCTs including 2735 subjects >12 years old and 24‐52 weeks of follow‐up were included. Dupilumab reduced with high certainty severe asthma exacerbations (Incidence rate ratio 0.51; 95% CI 0.45‐0.59) and the percentage use of oral corticosteroid use (mean difference (MD) −28.2 mg/d; 95% CI −40.7 to −15.7). Asthma control (ACQ‐5), quality of life (AQLQ) and rescue medication use [puffs/d] improved, without reaching the minimal important clinical difference: ACQ‐5 MD −0.28 (95% CI −0.39 to −0.17); AQLQ MD +0.28 (95% CI 0.20‐0.37); and rescue medication MD −0.35 (95% CI −0.73 to +0.02). FEV1 increased (MD +0.15; 95% CI +0.11 to +0.18) (moderate certainty). There was an increased rate of dupilumab‐related adverse events (AEs) (moderate certainty) and of drug‐related serious AEs (low certainty). The incremental cost‐effectiveness ratio of dupilumab versus standard therapy was 464 000$/QALY (moderate certainty). More data on long‐term safety are needed both for children and for adults, together with more efficacy data in the paediatric population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.028 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.013 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".