Trends and Regional Differences in the Use of Maintenance Inhaled Medications in COPD: A Population-Based Study
Bibliographic record
Abstract
This was a retrospective cohort study in the Canadian province of British Columbia (BC). We included adults aged \(\ge\) 35 with COPD based on a validated case definition and analyzed trends from 2010 to 2020. We used demographics databases and pharmacy records for all outpatient dispensed medications regardless of the payer. Within this cohort, the “index date” was the first dispensation of any (overall) or specific (each drug class) maintenance inhaled medication and marked the beginning of follow-up. Geographic regions across BC are organized into 16 distinct health services delivery areas for planning, reporting, and implementing provincial health policies. The primary outcome was the proportion of maintenance inhaled medication users among prevalent COPD patients, overall and by medication class across those regions. Single therapies consisted of individual use of ICS, LABA, and LAMA. Combination-therapies included either single-inhalers with multiple ingredients or separate inhalers with ≥ 14 days of overlap. Heterogeneity in medication use across regions over calendar years was visualized using boxplots. To adjust for the contribution of patient characteristics, we fitted negative binomial models (with logarithmic link function) with the total number of users as the outcome and region (dummy-coded), age, sex, urban/rural residence, and socio-economic status (SES, neighborhood income quintiles) as independent variables. We generated rate ratios (RR) and 95% confidence intervals. Heterogeneity across regions was tested using a likelihood ratio test. The study received ethics approval from Human Ethics Board at University of British Columbia (H23-00607). Over 11 years, the number of COPD patients using any medication increased from 77,273 to 83,157; however, the proportion of users declined from 59.1 to 41.7% (average decline 1.7%/year; Fig. 1 A). Among single-inhaler therapies, ICS was used by 33.4% patients and showed the fastest decline (average 9.6%/year). Single-inhaler LABA was used by 2.3% of patients (average decline of 5.7%/year). Single-inhaler LAMA was used by 19% (increased by 1.8%/year). Among combination-therapies, 39.1% of COPD patients used ICS + LABA, followed by triple-therapy (ICS + LAMA + LABA, 14.7%) and LAMA + LABA (6.4%). The proportion of ICS + LABA users declined by 2.9%/year, whereas LAMA + LABA and triple-therapy users rose annually by 43.6% and 4.4%, respectively. Annual proportion of maintenance inhaled medication users ( A ), further classified by single-therapies: LAMA ( B ), LABA ( C ), ICS ( D ), and combination-therapies LAMA + LABA ( E ), ICS + LABA ( F ), and LAMA + LABA + ICS ( G ) among patients with COPD in British Columbia, Canada, from 2010 to 2020, stratified by geographic region (HSDA). Abbreviations: COPD, chronic obstructive pulmonary disease; ICS, inhaled corticosteroids; LABA, long-acting beta2-agonists; LAMA, long-acting muscarinic antagonists; HSDA, Health Services Delivery Area; Q1, quartile 1; Q3, quartile 3. Note: Each dot represents an HSDA. The horizontal line cutting through the plot is the overall provincial average. The median is the line separating the upper (white) and lower (dark gray) boxes. Combination-therapies are based either on single-inhalers containing multiple ingredients or from separate inhalers with 14 days of overlap. Annual percentage change is obtained from a negative binomial regression model. Females, younger patients, and those with either lowest (compared to those in second and third quintiles) or highest (compared to the lowest category) SES were more likely to use maintenance inhaled medications. There was significant regional variability in medication use after controlling for patient characteristics ( p < 0.01). Compared to the reference region, the RR of medication use ranged from 0.80 to 1.20 across regions (Fig. 2 B). Geographic map of the regions (HSDA) ( A ) and forest plots of adjusted RRs and 95% CI of maintenance inhaled medication use ( B ). CI, confidence interval. The negative binominal regression models were adjusted for age group, sex, socio-economic status, and area of residence. Abbreviations: HSDA, Health Services Delivery Area.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".