Dose reduction of baricitinib in patients with rheumatoid arthritis achieving sustained disease control: results of a prospective study
Bibliographic record
Abstract
OBJECTIVES: This study investigated the effects of dose step-down in patients with rheumatoid arthritis (RA) who achieved sustained disease control with baricitinib 4 mg once a day. METHODS: Patients who completed a baricitinib phase 3 study could enter a long-term extension (LTE). In the LTE, patients who received baricitinib 4 mg for ≥15 months and maintained CDAI low disease activity (LDA) or remission (REM) were blindly randomised to continue 4 mg or taper to 2 mg. Patients could rescue (to 4 mg) if needed. Efficacy and safety were assessed through 48 weeks. RESULTS: Patients in both groups maintained LDA (80% 4 mg; 67% 2 mg) or REM (40% 4 mg; 33% 2 mg) over 48 weeks. However, dose reduction resulted in small, statistically significant increases in disease activity at 12, 24 and 48 weeks. Dose reduction also produced earlier and more frequent relapse (loss of step-down criteria) over 48 weeks compared with 4 mg maintenance (23% 4 mg vs 37% 2 mg, p=0.001). Rescue rates were 10% for baricitinib 4 mg and 18% for baricitinib 2 mg. Dose reduction was associated with a numerically lower rate of non-serious infections (30.6 for baricitinib 4 mg vs 24.9 for 2 mg). Rates of serious adverse events and adverse events leading to discontinuation were similar across groups. CONCLUSIONS: In a large randomised, blinded phase 3 study, maintenance of RA control following induction of sustained LDA/REM with baricitinib 4 mg was greater with continued 4 mg than after taper to 2 mg. Nonetheless, most patients tapered to 2 mg could maintain LDA/REM or recapture with return to 4 mg if needed.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".