Safety and tolerability of nintedanib in patients with fibrosing interstitial lung diseases: pooled data from four trials
Bibliographic record
Abstract
Background: The effects of nintedanib have been investigated in trials across progressive fibrosing ILDs. Aim: To characterise the safety and tolerability of nintedanib in patients with fibrosing ILDs using pooled data from four clinical trials. Methods: Data were pooled from Phase III trials in subjects with idiopathic pulmonary fibrosis (INPULSIS-1 and -2), other progressive fibrosing ILDs (INBUILD), and systemic sclerosis-associated ILD (SENSCIS). Subjects were randomised to receive nintedanib 150 mg bid or placebo. Dose reductions to 100 mg bid and treatment interruptions were allowed to manage adverse events. All adverse events reported by investigators, irrespective of causality, over 52 weeks were analysed. Results: Mean (SD) exposure to nintedanib was 10.3 (3.5) months (n=1258) and to placebo was 11.1 (2.7) months (n=1042). Maximum exposure was 13 months in both groups. In the nintedanib and placebo groups, respectively, adverse events that led to dose reduction occurred in 24.6% and 2.5% of patients, and adverse events that led to permanent treatment discontinuation occurred in 18.7% and 10.9% of patients. In the nintedanib and placebo groups, respectively, diarrhoea was reported in 66.3% and 23.8% of patients, led to dose reduction in 14.7% and 0.6% of patients, and led to permanent treatment discontinuation in 5.4% and 0.3% of patients. Conclusions: In clinical trials, the adverse events associated with nintedanib were manageable for most patients with progressive fibrosing ILDs. Diarrhoea was the most frequent adverse event in patients treated with nintedanib but was managed without treatment discontinuation in most patients.
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 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 | 0.020 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.015 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".