Magnetic Resonance Imaging (MRI) Results Following Discontinuation of Methotrexate in Rheumatoid Arthritis Treated with Subcutaneous Tocilizumab: The COMP-ACT MRI Substudy
Bibliographic record
Abstract
OBJECTIVE: To assess differences in joint damage and inflammation using magnetic resonance imaging (MRI) between patients with rheumatoid arthritis (RA) who achieved low disease activity with tocilizumab (TCZ) + methotrexate (MTX) and subsequently continued or discontinued MTX. METHODS: In the COMP-ACT trial, US patients with RA received subcutaneous TCZ 162 mg + MTX. Those who achieved 28-joint count Disease Activity Score calculated with erythrocyte sedimentation rate (DAS28-ESR) ≤ 3.2 at Week 24 were randomized 1:1 (double-blind) to discontinue MTX (TCZ monotherapy; mono) or continue TCZ + MTX until Week 52. In a subset of patients, 1.5-Tesla MRI was used to obtain images of bilateral hands and wrists at weeks 24 and 40. Outcomes included changes in MRI-assessed synovitis, osteitis, erosion, and cartilage loss from Week 24 to Week 40, and in the proportion of patients with progression of each score. RESULTS: Of 296 patients who achieved DAS28-ESR ≤ 3.2 at Week 24, 79 were enrolled in the pilot MRI substudy and randomized to TCZ mono (n = 38) or TCZ + MTX (n = 41). Treatment with either TCZ mono or TCZ + MTX suppressed erosion progression, synovitis, osteitis, and cartilage loss. The proportion of patients with no progression in each outcome measure was similar between groups (range, TCZ mono: 84.8-97.0%; TCZ + MTX: 92.3-100%). CONCLUSION: In a subset of patients who achieved low disease activity with TCZ + MTX, MRI changes were minimal in intraarticular inflammation and damage measures in patients who discontinued MTX versus those who continued TCZ + MTX.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".