Treatment Persistence with Leukotriene Receptor Antagonists and Inhaled Corticosteroids
Bibliographic record
Abstract
BACKGROUND: Leukotriene receptor antagonists (LTRAs) and inhaled corticosteroids (ICSs) must be taken continuously to control persistent asthma. We compared the use of LTRAs and ICSs in patients with similar level of asthma control at treatment initiation with particular attention to treatment persistence. METHODS: Two cohorts of 15 to 45 year old patients with asthma were selected from the Quebec Health Insurance Plan Database between January 1, 1998, and December 31, 2000. We first identified new users of LTRAs and from the remaining patients, we selected new users of ICSs. The ICS patients were then one-to-one matched to LTRA patients on the use of short-acting beta2-agonists and oral corticosteroids in the year prior to the date of the first LTRA or ICS dispensation (index date). We compared compliance to initial therapies using Cox proportional hazards models. RESULTS: Each of the LTRA and ICS cohorts included 2200 patients. Multivariate model showed that compliance was significantly better for LTRAs than for ICSs [adjusted rate ratio of treatment discontinuation (aRR), 0.46; 95% confidence interval (CI), 0.42-0.49]. If in both groups all medications filled were taken at the prescribed dose, the annual percent of days on therapy for LTRA users would have been twice that for ICS users (38% vs. 19%; p<0.0001). CONCLUSION: The findings of this observational study indicate a far from optimal persistence to LTRAs and ICSs in asthmatic patients. The superior persistence to LTRAs might result in better effectiveness.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".