MRI and Dose Selection in a Phase II Trial of Baricitinib with Conventional Synthetic Disease-modifying Antirheumatic Drugs in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: Magnetic resonance imaging (MRI) was used in a phase IIb study of baricitinib in patients with RA to support dose selection for the phase III program. METHODS: Three hundred one patients with active RA who were taking stable methotrexate were randomized 2:1:1:1:1 to placebo or once-daily baricitinib (1, 2, 4, or 8 mg) for up to 24 weeks. One hundred fifty-four patients with definitive radiographic erosion had MRI of the hand/wrist at baseline and at weeks 12 and 24. Two expert radiologists, blinded to treatment and visit order, scored images for synovitis, osteitis, bone erosion, and cartilage loss. Combined inflammation (osteitis + 3× synovitis score) and total joint damage (erosion + 2.5× cartilage loss score) scores were calculated. Treatment groups were compared using ANCOVA adjusting for baseline scores. RESULTS: Mean changes from baseline to Week 12 for synovitis were -0.10, -1.50, and -1.60 for patients treated with placebo, baricitinib 4 mg, and baricitinib 8 mg, respectively (p = 0.003 vs placebo for baricitinib 4 and 8 mg). Mean changes for osteitis were 0.00, -3.20, and -2.10 (p = 0.001 vs placebo for baricitinib 4 mg and p = 0.037 for 8 mg), respectively. Mean changes for bone erosion were 0.90, 0.10, and 0.40 (p = 0.089 for 4 mg and p = 0.275 for 8 mg), respectively, in these treatment groups. CONCLUSION: MRI findings in this subgroup of patients suggest suppression of synovitis, osteitis, and combined inflammation by baricitinib 4 and 8 mg. This corroborates previously demonstrated clinical efficacy of baricitinib and increases confidence that baricitinib 4 mg could reduce the radiographic progression in phase III studies. [Clinical trial registration number (www.ClinicalTrials.gov): NCT01185353].
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".