The OMERACT MRI in Arthritis Working Group — Update on Status and Future Research Priorities
Bibliographic record
Abstract
OBJECTIVE: To provide an update on the status and future research priorities of the Outcome Measures in Rheumatology (OMERACT) magnetic resonance imaging (MRI) in arthritis working group. METHODS: A summary is provided of the activities of the group within rheumatoid arthritis (RA), psoriatic arthritis (PsA), and osteoarthritis (OA), and its research priorities. RESULTS: The OMERACT RA MRI score (RAMRIS) evaluating bone erosion, bone edema (osteitis), and synovitis is now the standard method of quantifying articular pathology in RA trials. Cartilage loss is another important part of joint damage, and at the OMERACT 12 conference, we provided longitudinal data demonstrating reliability and sensitivity to change of the RAMRIS JSN component score, supporting its use in future clinical trials. The MRI group has previously developed a PsA MRI score (PsAMRIS). At OMERACT 12, PsAMRIS was evaluated in a randomized placebo-controlled trial of patients with PsA, demonstrating the responsiveness and discriminatory ability of applying the PsAMRIS to hands and feet. A hand OA MRI score (HOAMRIS) was introduced at OMERACT 11, and has subsequently been further validated. At OMERACT 12, good cross-sectional interreader reliability, but variable reliability of change scores, were reported. Potential future research areas were identified at the MRI session at OMERACT 12 including assessment of tenosynovitis in RA and enthesitis in PsA and focusing on alternative MRI techniques. CONCLUSION: MRI has been further developed and validated as an outcome measure in RA, PsA, and OA. The group will continue its efforts to optimize the value of MRI as a robust biomarker in rheumatology 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 | 0.052 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".