Effect of Nintedanib in Patients with Progressive Pulmonary Fibrosis in Subgroups with Differing Baseline Characteristics
Bibliographic record
Abstract
INTRODUCTION: In the INBUILD trial in patients with progressive pulmonary fibrosis other than idiopathic pulmonary fibrosis (IPF), nintedanib slowed the rate of decline in forced vital capacity (FVC; mL/year) over 52 weeks compared with placebo. We assessed the efficacy of nintedanib across subgroups in the INBUILD trial by baseline characteristics. METHODS: We assessed the rate of decline in FVC over 52 weeks and time to progression of interstitial lung disease (ILD) (absolute decline from baseline in FVC % predicted > 10%) or death over the whole trial in subgroups based on sex, age, race, body mass index (BMI), time since diagnosis of ILD, FVC % predicted, diffusing capacity of the lungs for carbon monoxide (DLco) % predicted, composite physiologic index (CPI), GAP (gender, age, lung physiology) stage, use of anti-acid therapy and use of disease-modifying antirheumatic drugs (DMARDs) at baseline. RESULTS: The effect of nintedanib versus placebo on reducing the rate of decline in FVC over 52 weeks was consistent across the subgroups by baseline characteristics analysed. Interaction p values did not indicate heterogeneity in the treatment effect between these subgroups (p > 0.05). Over the whole trial (median follow-up time ∼19 months), progression of ILD or death occurred in similar or lower proportions of patients treated with nintedanib than placebo across the subgroups analysed, with no heterogeneity detected between the subgroups. CONCLUSIONS: In the INBUILD trial, no heterogeneity was detected in the effect of nintedanib on reducing the rate of ILD progression across subgroups based on demographics, ILD severity or use of anti-acid therapy or DMARDs. These data support the use of nintedanib as a treatment for progressive pulmonary fibrosis. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Identifier: NCT02999178.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".