Do inhaled corticosteroids protect against lung cancer in patients with COPD? A systematic review
Bibliographic record
Abstract
Inhaled corticosteroids (ICS) are commonly prescribed to COPD patients, particularly those with more advanced stages of the disease. These patients are also at increased risk of lung cancer. A systematic review was undertaken to identify studies that examined the association between lung cancer risk and ICS therapy in COPD patients. The search strategy was created in MEDLINE and extended to EMBASE as well as other relevant databases. Both randomized controlled trials (RCTs) and observational studies were considered for inclusion. Studies were required to have incident lung cancer or deaths from lung cancer as an outcome in order to be included in the review. Six studies met the inclusion criteria. Two observational studies directly addressed the specific research. Four RCTs presented sufficient data to calculate the relative risk of lung cancer in COPD patients. None of the identified RCTs showed a statistically significant association of ICS use with lung cancer risk. Observational studies showed a protective effect from ICS use, particularly at high doses. Given the observational evidence and the low numbers of lung cancer events in the RCTs, these results may be prone to type II error. The observational studies dealt with very specific patient populations and exposure definitions, which might not have adequately captured the complex relationship between ICS exposure and lung cancer risk. Results from RCTs suggest no effect of ICS on the risk of lung cancer. However, results from observational studies suggest the potential that ICS may confer a protective effect, particularly at high doses.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".