<p>Medication adherence and persistence in chronic obstructive pulmonary disease patients receiving triple therapy in a USA commercially insured population</p>
Bibliographic record
Abstract
Introduction: This longitudinal, retrospective cohort study of patients with COPD describes baseline characteristics, adherence, and persistence following initiation of inhaled corticosteroids (ICS)/long-acting β 2 -agonists (LABA)/long-acting muscarinic antagonists (LAMA) from multiple inhaler triple therapy (MITT). Methods: Patients aged ≥40 years receiving MITT between January 2012 and September 2015 were identified from the IQVIA™ Real-world Data Adjudicated Claims–USA database. MITT was defined as subjects with ≥1 overlapping days’ supply of three COPD medications (ICS, LABA, and LAMA). Adherence (proportion of days covered, PDC) and discontinuation (defined as a gap of 1, 30, 60, or 90 days of supply in any of the three components of the triple therapy) were calculated for each patient over 12 months of follow-up. In addition, analyses were stratified by number of inhalers. Results: In total, 14,635 MITT users were identified (mean age, 62 years). Mean PDC for MITT at 12 months was 0.37%. Mean PDC for the ICS/LABA and LAMA component at 12 months was 49% (0.49±0.31; median, 0.47) and 54% (0.54±0.33; 0.56), respectively. The proportion of adherent patients (PDC ≥0.8) at 12 months was 14% for MITT. Allowing for a 30-day gap from last day of therapy, 86% of MITT users discontinued therapy during follow-up. Conclusion: Patients with COPD had low adherence to and persistence with MITT in a real-world setting. Mean PDC for each single inhaler component was higher than the mean PDC observed with MITT. Reducing the number of inhalers may improve overall adherence to intended triple therapy. Keywords: chronic obstructive pulmonary disease, COPD, medication adherence, inhaled corticosteroids, ICS, long-acting β 2 -agonists, LABA, long-acting muscarinic antagonists, LAMA, multiple inhaler triple therapy
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".