Applying the wisdom of stepping down inhaled corticosteroids in patients with COPD: a proposed algorithm for clinical practice
Bibliographic record
Abstract
Current guidelines for the management of chronic obstructive pulmonary disease (COPD) recommend limiting the use of inhaled corticosteroids (ICS) to patients with more severe disease and/or increased exacerbation risk. However, there are discrepancies between guidelines and real-life practice, as ICS are being overprescribed. In light of the increasing concerns about the clinical benefit and long-term risks associated with ICS use, therapy needs to be carefully weighed on a case-by-case basis, including in patients already on ICS. Several studies sought out to determine the effects of withdrawing ICS in patients with COPD. Early studies have deterred clinicians from reducing ICS in patients with COPD as they reported that an abrupt withdrawal of ICS precipitates exacerbations, and results in a deterioration in lung function and symptoms. However, these studies were fraught with numerous methodological limitations. Recently, two randomized controlled trials and a real-life prospective study revealed that ICS can be safely withdrawn in certain patients. Of these, the WISDOM (Withdrawal of Inhaled Steroids During Optimized Bronchodilator Management) trial was the largest and first to examine stepwise withdrawal of ICS in patients with COPD receiving maintenance therapy of long-acting bronchodilators (ie, tiotropium and salmeterol). Even with therapy being in line with the current guidelines, the findings of the WISDOM trial indicate that not all patients benefit from including ICS in their treatment regimen. Indeed, only certain COPD phenotypes seem to benefit from ICS therapy, and validated markers that predict ICS response are urgently warranted in clinical practice. Furthermore, we are now better equipped with a larger armamentarium of novel and more effective long-acting β2-agonist/long-acting muscarinic antagonist combinations that can be considered by clinicians to optimize bronchodilation and allow for safer ICS withdrawal. In addition to providing a review of the aforementioned, this perspective article proposes an algorithm for the stepwise withdrawal of ICS in real-life clinical practice.
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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 | 0.040 | 0.066 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.010 | 0.011 |
| Research integrity | 0.014 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".