Impact of filgotinib on pain control in the phase 3 FINCH studies
Bibliographic record
Abstract
OBJECTIVE: This post hoc analysis of the FINCH 1-3 (NCT02889796, NCT02873936 and NCT02886728) studies assessed specific effects of filgotinib on pain control and their relationship with other aspects of efficacy in patients with rheumatoid arthritis (RA). METHODS: Assessments included: residual pain responses of ≤10 and ≤20 mm on a 100 mm visual analogue scale (VAS); the proportion of patients who achieved VAS pain responses in addition to remission or low disease activity by Disease Activity Score-28 with C-reactive protein (DAS28-CRP) or Clinical Disease Activity Index (CDAI) criteria. RESULTS: Across studies, filgotinib reduced pain from week 2, with responses sustained throughout the studies. In FINCH 1, at week 24, 35.8%, 25.0%, 24.6% and 11.6% of patients in the filgotinib 200 mg, filgotinib 100 mg, adalimumab and placebo arms (each plus methotrexate) achieved VAS pain ≤20 mm in addition to DAS28-CRP remission; 26.3%, 17.9%, 17.2% and 7.6% achieved VAS pain ≤10 mm in addition to DAS28-CRP remission. A similar pattern was seen for CDAI remission. Time during which VAS pain was ≤10 or ≤20 mm was longest with filgotinib 200 mg and comparable between adalimumab and filgotinib 100 mg. Similar findings were reported for filgotinib in FINCH 2 and 3. CONCLUSION: In all RA populations studied, pain improvements occurred from week 2 and were sustained over time. In FINCH 1, filgotinib 100 mg provided similar pain amelioration to adalimumab, whereas filgotinib 200 mg resulted in greater pain improvement and higher proportion of patients with residual pain ≤10 or ≤20 mm and meeting DAS28-CRP remission criteria.
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 | 0.018 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".