First analysis of the Severe Paediatric Asthma Collaborative in Europe registry
Bibliographic record
Abstract
New biologics are being continually developed for paediatric asthma, but it is unclear whether there are sufficient numbers of children in Europe with severe asthma and poor control to recruit to trials needed for registration. To address these questions, the European Respiratory Society funded the Severe Paediatric Asthma Collaborative in Europe (SPACE), a severe asthma registry. We report the first analysis of the SPACE registry, which includes data from 10 paediatric respiratory centres across Europe. Data from 80 children with a clinical diagnosis of severe asthma who were receiving both high-dose inhaled corticosteroid and long-acting β2-agonist were entered into the registry between January 2019 and January 2020. Suboptimal control was defined by either asthma control test, or Global Initiative for Asthma criteria, or ≥2 severe exacerbations in the previous 12 months, or a combination. Overall, 62 out of 80 (77%) children had suboptimal asthma control, of whom 29 were not prescribed a biologic. However, in 24 there was an option for starting a licensed biologic. 33 children with suboptimal control were prescribed a biologic (omalizumab (n=24), or mepolizumab (n=7), or dupilumab (n=2)), and for 29 there was an option to switch to a different biologic. We conclude that the SPACE registry provides data that will support the planning of studies of asthma biologics. Not all children on biologics achieve good asthma control, and there is need for new trial designs addressing biologic switching.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.012 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".