Nintedanib with Add-on Pirfenidone in Idiopathic Pulmonary Fibrosis. Results of the INJOURNEY Trial
Bibliographic record
Abstract
RATIONALE: Nintedanib and pirfenidone slow the progression of idiopathic pulmonary fibrosis (IPF), but the disease continues to progress. More data are needed on the safety and efficacy of combination therapy with nintedanib and add-on pirfenidone. OBJECTIVES: To investigate safety, tolerability, and pharmacokinetic and exploratory efficacy endpoints in patients treated with nintedanib and add-on pirfenidone versus nintedanib alone. METHODS: Patients with IPF and FVC greater than or equal to 50% predicted at screening who completed a 4- to 5-week run-in with nintedanib 150 mg twice daily without dose reduction or treatment interruption were randomized to receive nintedanib 150 mg twice daily with add-on pirfenidone (titrated to 801 mg three times daily) or nintedanib 150 mg twice daily alone in an open-label manner for 12 weeks. The primary endpoint was the percentage of patients with on-treatment gastrointestinal adverse events from baseline to Week 12. Analyses were descriptive and exploratory. MEASUREMENTS AND MAIN RESULTS: On-treatment gastrointestinal adverse events were reported in 37 of 53 patients (69.8%) treated with nintedanib with add-on pirfenidone and 27 of 51 patients (52.9%) treated with nintedanib alone. Predose plasma trough concentrations of nintedanib were similar when it was administered alone or with add-on pirfenidone. Mean (SE) changes from baseline in FVC at Week 12 were -13.3 (17.4) ml and -40.9 (31.4) ml in patients treated with nintedanib with add-on pirfenidone (n = 48) and nintedanib alone (n = 44), respectively. CONCLUSIONS: Nintedanib with add-on pirfenidone had a manageable safety and tolerability profile in patients with IPF, in line with the adverse event profiles of each drug. These data support further research into combination regimens in the treatment of IPF. Clinical trial registered with www.clinicaltrials.gov (NCT02579603).
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".