Cough adverse events and FVC decline in the ATLAS study of inhaled pirfenidone (AP01) in Idiopathic Pulmonary Fibrosis
Bibliographic record
Abstract
Introduction: Cough is a common Adverse Event (AE) in Idiopathic Pulmonary Fibrosis (IPF) trials. Pooled trials showed rates of 23.1% on oral pirfenidone and 24% on placebo. Cough may contribute to disease progression. Aim: To examine the relationship between cough AE and disease progression in the open-label ATLAS study of inhaled pirfenidone–AP01 50mg once (qd) or 100mg twice daily (bid) in IPF. Methods: Leicester Cough Monitor (LCM) counts over 24 hours were assessed at baseline, week 12 and week 24. Cough Visual Analogue Score (VAS) and Leicester Cough Questionnaire (LCQ) were recorded every 4 weeks. Forced vital capacity (FVC) change from baseline was modelled by linear slopes. Results: Cough AEs occurred in 11/46 (24%) on 50mg qd & 13/42 (31%) on 100mg bid. LCM counts were similar for both doses, with or without a cough AE, and remained stable over time (Table 1). The same was true for VAS and LCQ (not shown). Estimated slope FVC mL/year overall was -188 for 50mg qd and -34 for 100mg bid with a difference of 154 ml, p = 0.0203. FVC decline was more pronounced in those with an AE of cough (−206, 50mg qd & -129ml, 100mg bid). Conclusion: There was no objective change in cough during the ATLAS study. Disease progression was more marked in subjects with cough as an AE. It is unclear if this is a general feature of IPF and would bear examination in other cohorts. erj;64/suppl_68/PA685/F1 F1 F1
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".