Pretreatment rate of decay in forced vital capacity predicts long-term response to pirfenidone in patients with idiopathic pulmonary fibrosis
Bibliographic record
Abstract
Pirfenidone reduces functional decline in patients with Idiopathic Pulmonary Fibrosis (IPF). However, response to treatment is highly heterogeneous. We sought to evaluate whether response to pirfenidone is influenced by the pretreatment rate of forced vital capacity (FVC) decline. Fifty-six IPF patients were categorized as rapid (RP) or slow progressors (SP) based on whether their FVC decline in the year preceding pirfenidone treatment was > or ≤ 10% predicted. Following pirfenidone treatment patients were followed-up every 6 months and up to 24 months. In the entire population, pirfenidone reduced significantly FVC decline from 231 to 49 ml/year at 6 months (T6) (p = 0.003) and this effect was maintained at the 12-, 18- and 24-month time points (p value for trend n.s.). In RP, the reduction of FVC decline was evident at 6 months (36 vs 706 ml/year pretreatment; p = 0.002) and maintained, though to a lesser degree, at 12 (106 ml/year), 18 (176 ml/year) and 24 months (162 ml/year; p value for trend n.s). Among SP, the reduction in FVC decline was not significant at any of the time points analyzed. In conclusion, pirfenidone reduces FVC decline in IPF patients. However, its beneficial effect is more pronounced in patients with rapidly progressive disease.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".