Comorbidities in the idiopathic pulmonary fibrosis and progressive pulmonary fibrosis trial population: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Comorbidities can affect drug tolerability and health outcomes in patients with fibrotic interstitial lung disease. This systematic review and meta-analysis evaluated the types and prevalence of comorbidities amongst participants in pharmaceutical randomised controlled trials (RCTs) of idiopathic pulmonary fibrosis (IPF) and progressive pulmonary fibrosis (PPF). METHODS: Ovid Medline, Embase and CENTRAL databases were searched to identify phase II and III pharmaceutical RCTs of IPF or PPF. Reporting of comorbidities was evaluated, with meta-analyses being performed for the prevalence of different conditions. RESULTS: 34 articles were included, with 23 unique trials for IPF and one for PPF. A mean of 14 (range 1-44) comorbidities per study was reported in the IPF RCTs, with 11 being reported in the PPF RCT. Common comorbidities in the IPF RCT cohorts were systemic hypertension (pooled prevalence 45%, 95% CI 39-50%), hyperlipidaemia (38%, 95% CI 27-49%), gastro-oesophageal reflux disease (45%, 95% CI 36-54%), ischaemic heart disease (18%, 95% CI 13-42%) and diabetes mellitus (16%, 95% CI 13-20%). The PPF trial cohort had similar types and prevalence of comorbidities to those reported in the IPF trial cohorts. CONCLUSIONS: Reporting of comorbidities varied across previous IPF RCTs, with limited data available for PPF. Prevalence of comorbidities reported in the IPF and PPF trial cohorts appear to be lower than those reported in prospective patient registries. There is a need for careful consideration of trial eligibility criteria with detailed reporting of comorbidities in future pharmaceutical RCTs to better understand the applicability of trial findings to real-world patients.
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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 | 0.022 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".