Time-to-first exacerbation, adherence, and medical costs among US patients receiving umeclidinium/vilanterol or tiotropium as initial maintenance therapy for chronic obstructive pulmonary disease: a retrospective cohort study
Bibliographic record
Abstract
Abstract Background Adherence to chronic obstructive pulmonary disease (COPD) maintenance medication is important for managing symptoms and exacerbation risk, and is associated with reduced mortality, hospitalizations, and costs. This study compared on-treatment exacerbations, medical costs, and medication adherence in patients with COPD initiating treatment with umeclidinium/vilanterol (UMEC/VI) or tiotropium (TIO). Methods This retrospective matched cohort study selected patients from Optum’s de-identified Clinformatics Data Mart database who initiated maintenance treatment with UMEC/VI or TIO between 01/01/2014 and 12/31/2017 (index date defined as the first dispensing). Eligible patients were ≥ 40 years of age and had ≥ 12 months continuous health plan coverage pre- and post-index; ≥ 1 medical claim for COPD pre-index or on the index date; no moderate/severe COPD-related exacerbations on the index date; no asthma diagnosis pre- or post-index; no maintenance medication fills containing inhaled corticosteroids, long-acting β2-agonists, or long-acting muscarinic antagonists pre-index or on the index date; and no fills for both UMEC/VI and TIO on the index date. Outcomes included time-to-first (Kaplan–Meier analysis) and rates of on-treatment COPD-related moderate/severe exacerbations, medication adherence (proportion of days covered [PDC] and proportion of adherent patients [PDC ≥ 0.8]), and COPD-related medical costs per patient per month (PPPM). Propensity score matching was used to adjust for potential confounders. Results Each cohort included 3929 matched patients. Kaplan–Meier rates of on-treatment COPD-related exacerbations were similar between cohorts (hazard ratio at 12 months; overall: 0.93, moderate: 0.92, severe: 1.07; all p > 0.05). UMEC/VI versus TIO initiators had significantly higher adherence (mean PDC: 0.44 vs 0.37; p < 0.001; proportion with PDC ≥ 0.8: 22.0% vs 16.4%; p< 0.001) and significantly lower mean on-treatment COPD-related total medical costs ($867 vs $1095 PPPM; p = 0.028), driven by lower outpatient visit costs. Conclusions These findings provide valuable information for physicians considering UMEC/VI or TIO as initial maintenance therapy options for patients with COPD.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".