TIOSPIR®: Large scale trial of tiotropium Respimat® vs HandiHaler® (HH) in patients (pts) with COPD
Bibliographic record
Abstract
Background: Direct comparisons of tiotropium Respimat® and HH in pts with COPD are limited. Prospective long-term data are needed to assess the relative effects on efficacy and safety. Aims and objectives: Compare safety and efficacy (exacerbations) of 5 µg and 2.5 µg once daily tiotropium Respimat® with 18 µg tiotropium HH in a phase IIIb study (TIOSPIR ® ). Methods: Randomized, active-controlled, double-blind, double-dummy, parallel-group, non-inferiority, event-driven, international multicentre (50 countries) trial of pts aged ≥40 y with COPD (postbronchodilator (postBD) FEV 1 ≤70% pred., FEV 1 /FVC ≤70%), smoking history ≥10 pack-y. Primary endpoints: time to death (all-cause; non-inferiority analysis), time to first exacerbation (superiority analysis). Secondary endpoints: no. of: exacerbations, hospitalized exacerbations; time to: first hospitalized exacerbation, major cardiovascular AE. Time-to-event analyzed using Cox proportional hazards; no. of events: negative binomial model. Results: Enrollment completed in April 2011; 17135 pts began treatment (Table). Baseline demographics Treated pts,N 17135 Age,y 65.0±9.1 Male,% 71.5 Current smoker,% 38.1 Smoking history, pack-y 43.8±24.8 FEV 1 ,L* 1.34±0.48 FEV 1 , % pred* 48.3±13.9 FVC,L* 2.71±0.85 FEV 1 /FVC* 0.499±0.114 GOLD stage,% I 0.3 II 48.5 III 40.1 IV 10.8 History of myocardial infarction,% 6.0 Coronary artery disease,% 15.2 Cardiac arrhythmia,% 10.6 Heart failure class,% None 92.1 I 3.1 II 4.1 III 0.6 IV 0.0 *PostBD. Data: mean±SD Conclusion: TIOSPIR® will provide robust data on relative safety and efficacy of tiotropium Respimat® vs HH from moderate to very severe COPD and across comorbidities. Funded by Boehringer Ingelheim.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".