Discontinuation of Inhaled Corticosteroids from Triple Therapy in COPD: Effects on Major Outcomes in Real World Clinical Practice
Bibliographic record
Abstract
Recent reports provide evidence-based guidelines for the withdrawal of inhaled corticosteroids (ICS) in COPD, but data on patients treated with ICS-based triple therapy are sparse and contradictory. We assessed the effect of ICS discontinuation on the incidence of severe exacerbation and pneumonia in a real-world population of patients with COPD who initiated triple therapy. We identified a cohort of patients with COPD treated with LAMA-LABA-ICS triple therapy during 2002–2018, age 50 or older, from the UK’s CPRD database. Subjects who discontinued ICS were matched 1:1 on time-conditional propensity scores to those continuing ICS and followed for one year. Hazard ratios (HR) of severe exacerbation and pneumonia were estimated using Cox regression. The cohort included 42,667 patients who discontinued ICS matched to 42,667 who continued ICS treatment. The hazard ratio of a severe exacerbation with ICS discontinuation relative to ICS continuation was 0.86 (95% CI: 0.78–0.95), while for severe pneumonia it was 0.96 (95% CI: 0.88–1.05). The incidence of severe exacerbation after ICS discontinuation was numerically higher than after continuation among patients with two or more exacerbations in the prior year (HR 1.09; 95% CI: 0.94–1.26) and among those with FEV1 <30% predicted (HR 1.29; 95% CI: 1.04–1.59). This large real-world study in the clinical setting of COPD treatment suggests that certain patients on triple therapy can be safely withdrawn from ICS and remain on bronchodilator therapy. As residual confounding cannot be ruled out, ICS discontinuation is not warranted for patients with multiple exacerbations and with very severe airway obstruction.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".