Eligibility criteria from pharmaceutical randomised controlled trials of idiopathic pulmonary fibrosis: a registry-based study
Bibliographic record
Abstract
Background Little is known about generalisability of randomised controlled trials (RCTs) for idiopathic pulmonary fibrosis (IPF). We evaluated eligibility criteria for phase III IPF RCTs to determine their representativeness in clinical registries, and calculated forced vital capacity (FVC) changes according to eligibility criteria. Methods Common eligibility criteria used in >60% of IPF RCTs were identified from a literature search and applied to patients with IPF from prospective Australian and Canadian registries. Additional pre-specified criteria of 6-min walk distance (6MWD) and different measures of preceding disease progression were also evaluated. Joint longitudinal-survival modelling was used to compare FVC decline according to eligibility for individual and composite criteria. Results Out of 990 patients with IPF, 527 (53%) met all common RCT eligibility criteria at the first clinic visit, including 343 with definite IPF and 184 with radiological probable usual interstitial pneumonia pattern without histological confirmation (i.e.provisional IPF). The percentages of eligible patients for landmark RCTs of nintedanib and pirfenidone were 19–50%. Adding 6MWD ≥150 m and different measures of preceding disease progression to the composite common criteria reduced the percentages of patients meeting eligibility to 52% (n=516) and 4–18% (n=12–61), respectively. Patients meeting the composite common criteria had less-rapid 1-year FVC decline than those who did not (−90versus−103 mL, p=0.01). Definite IPF generally had more-rapid 1-year FVC decline compared to provisional IPF. Conclusions Eligibility criteria of previous IPF RCTs have limited generalisability to clinical IPF populations, with FVC decline differing between eligible and ineligible populations.
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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 | 0.237 | 0.415 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".