Effectiveness of Single Versus Multiple Inhaler Triple Therapy on Mortality and Cardiopulmonary Risk Reduction in COPD: The SKOPOS-MAZI Study
Bibliographic record
Abstract
BACKGROUND: Patients with chronic obstructive pulmonary disease (COPD) have elevated cardiopulmonary and mortality risk, particularly following exacerbations. While single inhaler triple therapies (SITTs), such as budesonide/glycopyrrolate/formoterol fumarate (BGF), reduce cardiopulmonary risk versus dual bronchodilator therapy, there is limited evidence comparing outcomes with SITTs versus multiple inhaler triple therapies (MITTs). METHODS: SKOPOS-MAZI was a retrospective comparative effectiveness study in patients with COPD aged ≥40 years using US administrative claims data from Optum's deidentified Clinformatics® Data Mart Database. The primary and secondary endpoints were time to all-cause mortality and time to first severe cardiopulmonary event following initiation of BGF or MITT (identification period: October 1, 2020-June 30, 2023; index date: first prescription fill). Relative hazards of outcomes were assessed until a censoring event using Cox proportional hazards models, with inverse propensity treatment weighting accounting for between-group imbalances (standardized mean difference >0.1) in baseline characteristics. RESULTS: In the primary cohort, risk (hazard ratio [95% confidence intervals]) of all-cause mortality and a first severe cardiopulmonary event were 18% (0.82 [0.75, 0.91]) and 12% (0.88 [0.83, 0.93]) lower in patients initiating BGF versus MITT; results were consistent across censoring definitions, landmark periods, and sensitivity cohorts. CONCLUSION: In this real-world comparative effectiveness study of patients with COPD initiating BGF or MITT, BGF was associated with lower all-cause mortality and severe cardiopulmonary event risk versus MITT after accounting for between-group differences in baseline sociodemographic and clinical characteristics. This study supports the benefits of BGF over MITT and the need to consider proactive use of SITTs in COPD management.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| 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".