Clinical outcomes in patients switched from adalimumab to baricitinib due to non-response and/or study design: phase III data in patients with rheumatoid arthritis
Bibliographic record
Abstract
OBJECTIVE: To evaluate clinical outcomes in patients who changed treatment from adalimumab to baricitinib, an oral Janus kinase (JAK)1/JAK2 inhibitor, during a phase III programme. METHODS: In phase III RA-BEAM, patients were randomised 3:3:2 to placebo, baricitinib 4 mg once daily, or adalimumab 40 mg biweekly. At week 16 or subsequent visits, non-responders were rescued to open-label baricitinib 4 mg. At week 52, patients could enter a long-term extension (LTE) and continue on baricitinib or switch from adalimumab to baricitinib 4 mg with no adalimumab washout period. Percentage of patients achieving low disease activity and remission were assessed, along with physical function, patient's assessment of pain, and safety. RESULTS: Thirty-five (7%) baricitinib-treated and 40 (12%) adalimumab-treated patients were rescued to baricitinib in RA-BEAM; 78% (381/487) of baricitinib-treated and 72% (238/330) of adalimumab-treated patients who were not rescued in RA-BEAM, entered the LTE and continued/were switched to baricitinib. In both baricitinib-rescued and adalimumab-rescued patients, there were significant improvements in all measures up to 12 weeks after rescue compared with the time of rescue. Patients who switched from adalimumab to baricitinib showed improvements in disease control through 12 weeks in the LTE. Exposure-adjusted incidence rates for treatment-emergent adverse events (TEAEs) and infections, including serious events, were similar for patients who switched from adalimumab to baricitinib and those who continued on baricitinib. CONCLUSIONS: Switching from adalimumab to baricitinib (without adalimumab washout) was associated with improvements in disease control, physical function and pain during the initial 12 weeks postswitch, without an increase in TEAEs, serious adverse events or infections. TRIAL REGISTRATION NUMBERS: NCT01710358, NCT01885078.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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".