Effect of Baricitinib and Adalimumab in Reducing Pain and Improving Function in Patients with Rheumatoid Arthritis in Low Disease Activity: Exploratory Analyses from RA-BEAM
Bibliographic record
Abstract
Patients with rheumatoid arthritis (RA) may experience residual pain and functional impairment despite good control of disease activity. This study compared improvements in pain and physical function in patients with well-controlled RA after 24 weeks’ treatment with baricitinib, adalimumab or placebo in the 52-week RA-BEAM phase III study. Adults with active RA and inadequate response to methotrexate received baricitinib 4 mg once daily, adalimumab 40 mg every two weeks or placebo, with background methotrexate. Patients (N = 1010) were categorised as in remission, in remission or low disease activity, or not in remission or low disease activity at week 24. For patients in remission or low disease activity (n = 310), improvements in mean pain and physical function scores at week 24 were significantly greater with baricitinib than placebo (p < 0.001 and p < 0.01, respectively) and adalimumab (p < 0.05 for both). For both outcomes, differences between adalimumab and placebo were not significant. The proportions of patients in remission or low disease activity with minimal or no pain and with normalised physical function were numerically greater with baricitinib than placebo. Baricitinib 4 mg once daily provided enhanced improvement in pain and physical function in patients with well-controlled RA, suggesting it may produce effects beyond immunomodulation.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".