Whole-body Magnetic Resonance Imaging in Axial Spondyloarthritis: Reduction of Sacroiliac, Spinal, and Entheseal Inflammation in a Placebo-controlled Trial of Adalimumab
Bibliographic record
Abstract
OBJECTIVE: To investigate whether adalimumab (ADA) reduces whole-body (WB-) magnetic resonance imaging (MRI) indices for inflammation in the entheses, peripheral joints, sacroiliac joints, spine, and the entire body in patients with axial spondyloarthritis (axSpA). METHODS: An investigator-initiated, randomized, placebo-controlled, double-blinded 48-week followup trial included 49 patients with axSpA, who had Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) ≥ 4.0 despite treatment with nonsteroidal antiinflammatory drugs and a clinical indication for tumor necrosis factor inhibitor treatment. Patients were randomized to subcutaneous ADA 40 mg or placebo every other week for 6 weeks; thereafter, all patients received ADA. Conventional MRI and WBMRI were performed at weeks 0, 6, 24, and 48. The primary WBMRI endpoint was the proportion of patients with an improvement in WBMRI total inflammation index above the smallest detectable change (SDC) at Week 6. RESULTS: The primary WBMRI endpoint (improvement of SDC > 2.3) was met in 11 (44%) patients in the ADA group and 3 (13%) patients in the placebo group (p = 0.025, Fisher's exact test). The primary conventional MRI endpoint, the minimally important change in Spondyloarthritis Research Consortium of Canada Spine MRI Inflammation Index at Week 6, was achieved by 9 (36%) patients in the ADA group and 4 (17%) patients in the placebo group (p = 0.20). The primary clinical endpoint, BASDAI reduction > 50% or 2.0 at Week 24, was attained by 32 (65%) patients. CONCLUSION: ADA provided significant reductions in WBMRI indices of peripheral, axial, and whole-body inflammation in patients with axSpA. WBMRI is promising for objective assessment and monitoring of peripheral and axial disease activity in future clinical trials.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".