Oral non-steroidal anti-inflammatory drug therapy for lung disease in cystic fibrosis
Bibliographic record
Abstract
Background Progressive lung damage causes most deaths in cystic fibrosis. Non‐steroidal anti‐inflammatory drugs (such as ibuprofen) may prevent progressive pulmonary deterioration and morbidity in cystic fibrosis. This is an update of a previously published review. Objectives To assess the effectiveness of treatment with oral non‐steroidal anti‐inflammatory drugs in cystic fibrosis. Search methods We searched the Cochrane Cystic Fibrosis and Genetic Disorders Group Trials Register comprising references identified from comprehensive electronic database searches, hand searches of relevant journals and abstract books of conference proceedings. We contacted manufacturers of non‐steroidal anti‐inflammatory drugs and searched online trials registries. Latest search of the Group's Trials Register: 21 November 2018. Selection criteria Randomized controlled trials comparing oral non‐steroidal anti‐inflammatory drugs, at any dose for at least two months, to placebo in people with cystic fibrosis. Data collection and analysis Two authors independently assessed trials for inclusion the review and their potential risk of bias. Two authors independently rated the quality of the evidence for each outcome using the GRADE guidelines. Main results The searches identified 17 trials; four are included (287 participants aged five to 39 years; maximum follow‐up of four years) and one is currently awaiting classification pending publication of the full trial report and two are ongoing. Three trials compared ibuprofen to placebo (two from the same center with some of the same participants); one trial assessed piroxicam versus placebo. The three ibuprofen trials were deemed to have good or adequate methodological quality, but used various outcomes and summary measures. Reviewers considered measures of lung function, nutritional status, radiological assessment of pulmonary involvement, intravenous antibiotic usage, hospital admissions, survival and adverse effects. Combined data from the two largest ibuprofen trials showed a lower annual rate of decline for lung function, % predicted forced expiratory volume in one second (FEV1), mean difference (MD) 1.32 (95% confidence interval (CI) 0.21 to 2.42) (moderate‐quality evidence); forced vital capacity (FVC), MD 1.27 (95% CI 0.26 to 2.28) (moderate‐quality evidence); forced expiratory flow (FEF25%‐75%), MD 1.80 (95% CI 0.15 to 3.45). The post hoc analysis of data from two trials split by age showed a slower rate of annual decline of FEV1 % predicted and FVC in the ibuprofen group in younger children, MD 1.41% (95% CI 0.03 to 2.80) (moderate‐quality evidence) and MD 1.32% (95% CI 0.04 to 2.60) (moderate‐quality evidence) respectively. Data from four trials demonstrated the proportion of participants with at least one hospitalization may be slightly lower in the ibuprofen group compared to placebo, Peto odds ratio 0.61 (95% CI 0.37 to 1.01) (moderate‐quality evidence). In one trial, long‐term use of high‐dose ibuprofen was associated with reduced intravenous antibiotic usage, improved nutritional and radiological pulmonary status. No major adverse effects were reported, but the power of the trials to identify clinically important differences in the incidence of adverse effects was low. We did not have any concerns with regards to risk of bias for the trial comparing piroxicam to placebo. However, the trial did not report many data in a form that we could analyze in this review. No data were available for the review's primary outcome of lung function; available data for hospital admissions showed no difference between the groups. No analyzable data were available for any other review outcome. Authors' conclusions High‐dose ibuprofen can slow the progression of lung disease in people with cystic fibrosis, especially in children, which suggests that strategies to modulate lung inflammation can be beneficial for people with cystic fibrosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".