The OMERACT Psoriatic Arthritis Magnetic Resonance Imaging Score (PsAMRIS) Is Reliable and Sensitive to Change: Results from an OMERACT Workshop
Bibliographic record
Abstract
OBJECTIVE: The aim of this multireader exercise was to assess the reliability and sensitivity to change of the psoriatic arthritis magnetic resonance imaging score (PsAMRIS) in PsA patients followed for 1 year. METHODS: MRI was acquired from 12 patients with PsA before initiation of treatment and after 12 months. MR images were scored according to PsAMRIS (for synovitis, tenosynovitis, periarticular inflammation, bone marrow edema, bone erosion, and bone proliferation) under standardized conditions, in unknown chronological order. Intraobserver/interobserver reliability was examined by intraclass correlation coefficients (ICC) and sensitivity to change by standardized response means (SRM). RESULTS: The interobserver reliability of PsAMRIS was high for synovitis, tenosynovitis, periarticular inflammation, and bone edema status and change scores (interobserver ICC 0.87-0.97). The intraobserver reliability was moderate to high (ICC 0.60-0.98) for status and change scores, except for change in periarticular inflammation (ICC 0.33). PsAMRIS sensitivity to change was moderate for synovitis, tenosynovitis, and periarticular inflammation (SRM 0.5-0.8), while poor (SRM 0.1-0.3) for bone marrow edema, erosion, and bone proliferation. Rare occurrence and minimal change contributed to poor SRM and change-score ICC for bone parameters. CONCLUSION: This multireader exercise, performed under standardized conditions, confirmed PsAMRIS to have high interobserver and intraobserver reliability for hand PsA. Measures of inflammation were sensitive to change, implying that PsAMRIS may be a valuable tool for monitoring change in inflammation during 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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".