INTREPID: single-<i>versus</i>multiple-inhaler triple therapy for COPD in usual clinical practice
Bibliographic record
Abstract
Introduction Real-world trial data comparing single- with multiple-inhaler triple therapy (MITT) in COPD patients are currently lacking. The effectiveness of once-daily single-inhaler fluticasone furoate (FF)/umeclidinium (UMEC)/vilanterol (VI) and MITT were compared in usual clinical care. Methods INTREPID was a multicentre, randomised, open-label, phase IV effectiveness study comparing FF/UMEC/VI 100/62.5/25 µgviathe ELLIPTA inhaler with a clinician's choice of any approved non-ELLIPTA MITT in usual COPD clinical practice in five European countries. Primary end-point was proportion of COPD Assessment Test (CAT) responders (≥2-unit decrease in CAT score from baseline) at week 24. Secondary end-points in a subpopulation included change from baseline in forced expiratory volume in 1 s (FEV1) and percentage of patients making at least one critical error in inhalation technique at week 24. Safety was also assessed. Results 3092 patients were included (FF/UMEC/VI n=1545; MITT n=1547). The proportion of CAT responders at week 24 was significantly greater with FF/UMEC/VIversusnon-ELLIPTA MITT (OR 1.31, 95% CI 1.13–1.51; p<0.001) and mean change from baseline in FEV1was significantly greater with FF/UMEC/VI (77 mLversus28 mL; treatment difference 50 mL, 95% CI 26–73 mL; p<0.001). The percentage of patients with at least one critical error in inhalation technique was low in both groups (FF/UMEC/VI 6%; non-ELLIPTA MITT 3%). Safety profiles, including incidence of pneumonia serious adverse events, were similar between treatments. Conclusions In a usual clinical care setting, treatment with once-daily single-inhaler FF/UMEC/VI resulted in significantly more patients gaining health status improvement and greater lung function improvementversusnon-ELLIPTA MITT.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".