Early and continued improvements in asthma control in patients with severe, uncontrolled asthma after tezepelumab initiation: real-world ASCENT study
Bibliographic record
Abstract
Background: Tezepelumab has demonstrated efficacy in patients with severe, uncontrolled asthma (SUA) in randomized controlled trials. Objective: To assess real-world symptom control in SUA following tezepelumab treatment. Methods: ASCENT ( NCT05677139 ) is an ongoing, prospective, observational study in patients with SUA from Europe and Canada receiving tezepelumab as routine standard of care. This interim analysis assessed changes from baseline to weeks 4, 12 and 24 in ACQ-6 and SGRQ scores and pre-bronchodilator (BD) FEV1, and the annualized asthma exacerbation rate (AAER) in the 52-week baseline and 24-week follow-up periods. Results: Overall, 211 patients were included. The least-squares mean (LSM) changes from baseline in the ACQ-6 score were −1.03, −1.16 and −1.33 at weeks 4, 12 and 24, respectively, with reductions observed across asthma phenotypes (Figure). ACQ-6 score improvements meeting or exceeding the MCID were seen in 64%, 71% and 78% of patients at weeks 4, 12 and 24, respectively. The LSM change from baseline to week 24 was −19.79 for the SGRQ total score and 0.12 L for pre-BD FEV1. The AAER decreased by 65% (95% CI: 55, 73). Conclusion: Clinically meaningful improvements in asthma control were observed with tezepelumab from week 4 and continued to week 24, across asthma phenotypes, and in health status, lung function and exacerbations. erj;66/suppl_69/PA315/F1 F1 F1
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".