INTREPID study: Once-daily single-inhaler fluticasone furoate/umeclidinium/vilanterol vs multiple-inhaler triple therapy; sub-analysis by prior medication strata
Bibliographic record
Abstract
Background: The INTREPID study showed improved health status response and lung function in chronic obstructive pulmonary disease (COPD) usual care with single-inhaler fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI) vs multiple-inhaler triple therapy (MITT; inhaled corticosteroid+long-acting muscarinic antagonist+long-acting β2-agonist [ICS+LAMA+LABA]). Aim: Evaluate INTREPID outcomes by prior medication strata. Methods: The open-label, phase IV INTREPID study included 3092 intent-to-treat (ITT) COPD patients who received non-ELLIPTA maintenance therapy for ≥16 weeks, had COPD Assessment Test (CAT) score ≥10 and ≥1 moderate/severe exacerbation in prior 3 years, randomised to FF/UMEC/VI 100/62.5/25µg via ELLIPTA or clinician choice of ICS+LAMA+LABA MITT in non-ELLIPTA devices for 24 weeks. Outcomes were analysed by prior medication strata (ICS+LAMA+LABA, ICS+LABA, LAMA+LABA). Results: Odds of CAT response and lung function improvement at Week 24 were statistically significantly greater for FF/UMEC/VI vs MITT in ICS+LAMA+LABA and ICS+LABA strata, and similar in LAMA+LABA stratum (Table). Adverse event incidence was broadly similar by prior medication strata. Conclusions: In usual care, FF/UMEC/VI significantly improved health status response and lung function vs MITT in patients on prior ICS-containing therapy. Method: GSK (206854/NCT03467425).
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".