Once-daily tiotropium Respimat add-on to ICS ± LABA improves control across asthma severities
Bibliographic record
Abstract
Background: Tiotropium Respimat added to ICS±LABA has been investigated across asthma severities. We present ACQ-7 responses from six Phase III randomised, double-blind, placebo-controlled, parallel-group trials in patients with symptomatic asthma. Methods: Two 48-wk trials (PrimoTinA, NCT00772538/6984): 5µg added to ICS (≥800µg budesonide or equivalent [bud or eq])+LABA; two 24-wk trials (MezzoTinA, NCT01172808/2821): 5/2.5µg added to ICS (400 – 800µg bud or eq); 12-wk trial (GraziaTinA, NCT01316380): 5/2.5µg added to ICS (200 – 400µg bud or eq); 52-wk trial (CadenTinA, NCT01340209): 5/2.5µg added to ICS (400 – 800µg bud or eq). ACQ-7 responder rates were pre-specified in MezzoTinA, GraziaTinA and CadenTinA; ACQ-7 change from baseline (response) was pre-specified in PrimoTinA. Results: ACQ-7 responder rate (n/N, (%)): PrimoTinA, wk 48: 5 µg 263/453 (58.1), placebo (pbo) 205/454 (45.2); MezzoTinA, wk 24: 5 µg 330/513 (64.3), 2.5 µg 332/515 (64.5), pbo 299/518 (57.7); GraziaTinA, wk 12: 5 µg 90/155 (58.1), 2.5 µg 91/154 (59.1), pbo 91/155 (58.7); CadenTinA, wk 52: 5 µg 87/114 (76.3), 2.5 µg 81/114 (71.1), pbo 41/56 (73.2). Adjusted mean response difference vs placebo Respimat±SE: PrimoTinA, 5µg –0.132 ± 0.049 (p = 0.007); MezzoTinA, 5µg –0.115 ± 0.043 (p = 0.008), 2.5µg –0.160 ± 0.043 (p < 0.001); GraziaTinA, 5µg 0.014 ± 0.067 (p = 0.835), 2.5µg 0.061 ± 0.067 (p = 0.362). Mean ACQ-7 (SD) in CadenTinA: 0.98 (0.63), 1.09 (0.72) and 0.99 (0.68) for 5µg, 2.5µg and pbo, respectively. Conclusion: Once-daily tiotropium Respimat add-on to at least ICS maintenance therapy was associated with improved asthma control across severities. Funding: Funding for this trial was provided by Boehringer Ingelheim. Editorial assistance was provided by Complete HealthVizion. Presented at ERS congress 2014
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".