Potential of nintedanib in treatment of progressive fibrosing interstitial lung diseases
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A proportion of patients with fibrosing interstitial lung diseases (ILDs) develop a progressive phenotype characterised by decline in lung function, worsening quality of life and early mortality. Other than idiopathic pulmonary fibrosis (IPF), there are no approved drugs for fibrosing ILDs and a poor evidence base to support current treatments. Fibrosing ILDs with a progressive phenotype show commonalities in clinical behaviour and in the pathogenic mechanisms that drive disease worsening. Nintedanib is an intracellular inhibitor of tyrosine kinases that has been approved for treatment of IPF and has recently been shown to reduce the rate of lung function decline in patients with ILD associated with systemic sclerosis (SSc-ILD). In vitro data demonstrate that nintedanib inhibits several steps in the initiation and progression of lung fibrosis, including the release of pro-inflammatory and pro-fibrotic mediators, migration and differentiation of fibrocytes and fibroblasts, and deposition of extracellular matrix. Nintedanib also inhibits the proliferation of vascular cells. Studies in animal models with features of fibrosing ILDs such as IPF, SSc-ILD, rheumatoid arthritis-ILD, hypersensitivity pneumonitis and silicosis demonstrate that nintedanib has anti-fibrotic activity irrespective of the trigger for the lung pathology. This suggests that nintedanib inhibits fundamental processes in the pathogenesis of fibrosis. A trial of nintedanib in patients with progressive fibrosing ILDs other than IPF (INBUILD) will report results in 2019.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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 it