Effect of statins on disease-related outcomes in patients with idiopathic pulmonary fibrosis
Bibliographic record
Abstract
BACKGROUND: Data are conflicting regarding the possible effects of statins in patients with idiopathic pulmonary fibrosis (IPF). This post hoc analysis assessed the effects of statin therapy on disease-related outcomes in IPF. METHODS: Patients randomised to placebo (n=624) in three controlled trials of pirfenidone in IPF (CAPACITY 004 and 006, ASCEND) were categorised by baseline statin use. Outcomes assessed during the 1-year follow-up included disease progression, mortality, hospitalisation and composite outcomes of death or ≥10% absolute decline in FVC and death or ≥50 m decline in 6-minute walk distance (6MWD). RESULTS: At baseline, 276 (44%) patients were statin users versus 348 (56%) non-users. Baseline characteristics were similar between groups, except statin users were older and had higher prevalence of cardiovascular disease and risk factors. In multivariate analyses adjusting for differences in baseline characteristics, statin users had lower risks of death or 6MWD decline (HR 0.69; 95% CI 0.48 to 0.99, p=0.0465), all-cause hospitalisation (HR 0.58; 95% CI 0.35 to 0.94, p=0.0289), respiratory-related hospitalisation (HR 0.44; 95% CI 0.25 to 0.80, p=0.0063) and IPF-related mortality (HR 0.36; 95% CI 0.14 to 0.95, p=0.0393) versus non-users. Non-significant treatment effects favouring statin use were observed for disease progression (HR 0.75; 95% CI 0.52 to 1.07, p=0.1135), all-cause mortality (HR 0.54; 95% CI 0.24 to 1.21, p=0.1369) and death or FVC decline (HR 0.71; 95% CI 0.48 to 1.07, p=0.1032). CONCLUSIONS: This post hoc analysis supports the hypothesis that statins may have a beneficial effect on clinical outcomes in IPF. Prospective clinical trials are required to validate these observations. TRIAL REGISTRATION NUMBERS: NCT01366209, NCT00287729 and NCT00287716.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".