Validation of the OMERACT Psoriatic Arthritis Magnetic Resonance Imaging Score (PsAMRIS) for the Hand and Foot in a Randomized Placebo-controlled Trial
Bibliographic record
Abstract
OBJECTIVE: To assess changes following treatment and the reliability and responsiveness to change of the Outcome Measures in Rheumatology (OMERACT) Psoriatic Arthritis Magnetic Resonance Imaging Score (PsAMRIS) in a randomized controlled trial. METHODS: Forty patients with PsA randomized to either placebo or abatacept (ABA) had MRI of either 1 hand (n = 20) or 1 foot (n = 20) at baseline and after 6 months. Images were scored blindly twice by 3 independent readers according to the PsAMRIS (for synovitis, tenosynovitis, periarticular inflammation, bone edema, bone erosion, and bone proliferation). RESULTS: Inflammatory features improved numerically but statistically nonsignificantly in the ABA group but not the placebo group. Baseline intrareader intraclass correlation coefficients (ICC) were good (≥ 0.50) to very good (≥ 0.80) for all features in both hand and foot. Baseline interreader ICC were good (ICC 0.72-0.96) for all features, except periarticular inflammation and bone proliferation in the hand and tenosynovitis in the foot (ICC 0.25-0.44). Intrareader and interreader ICC for change scores varied. Guyatt's responsiveness index (GRI) was high for inflammatory features in the hand and metatarsophalangeal joints (GRI -0.67 to -3.13; bone edema not calculable). Minimal change and low prevalence resulted in low ICC and GRI for bone damage. CONCLUSION: PsAMRIS showed overall good intrareader agreement in the hand and foot, and inflammatory feature scores were responsive to change, suggesting that PsAMRIS may be a valid tool for MRI assessment of hands and feet in PsA 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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".