Clinical characteristics impacting clinical remission attainment in REALITI-A
Bibliographic record
Abstract
Background: Clinical remission (CR) is an ambitious goal of asthma management. Aims and Objectives: This post hoc analysis of REALITI-A data analysed clinical factors that may impact CR in adults with severe asthma. Methods: This 2-year, observational, single-arm, real-world prospective study enrolled adult patients (pts) with severe asthma who were newly prescribed mepolizumab. This analysis defined CR as fulfilment of 3 criteria: no exacerbations throughout the study, no maintenance oral corticosteroid (mOCS) use 28 days before Month 24 and an ACQ-5 score <1 at Month 24. Prediction of CR attainment at Month 24 was evaluated using a single logistic regression model with baseline covariates: mOCS use (yes/no), clinically significant exacerbations (CSEs) pre‑enrolment (≥4/<4), ACQ-5 score (≥2/<2), nasal polyps/depression or anxiety/gastroesophageal reflux disease at screening (yes/no), FEV1 (<60%/≥60%), and BMI (≥30/<25). Results: Of the 822 pts enrolled, 81 had available data, of which 30 (37%) achieved CR at Month 24. Achieving CR was significantly less likely with baseline mOCS usage (odds ratio [OR] [95% CI]: 0.11[0.02,0.51],p=0.0049), occurrence of ≥4 CSEs pre‑enrolment (0.24[0.07,0.87],p=0.0294), ACQ-5 score ≥2 (0.06[0.01,0.39],p=0.0027], and BMI ≥30 (0.11[0.02,0.78],p=0.0275). Conclusions: Despite the small subset of patients yielding a potential limitation as selection bias, CR with mepolizumab was achievable in 1 in 3 pts with severe asthma, but its attainment might significantly decrease with higher disease severity (in line with previous findings), suggesting the potential benefits of initiating treatment before pts reach advanced stages of asthma severity. Funding: GSK (204710)
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".