Comparing Psoriatic Arthritis Low-field Magnetic Resonance Imaging, Ultrasound, and Clinical Outcomes: Data from the TICOPA Trial
Bibliographic record
Abstract
OBJECTIVE: The Tight Control of inflammation in Psoriatic arthritis (TICOPA; isrctn.com: ISRCTN30147736) trial compared standard care (StdC) and tight control (TC) in early psoriatic arthritis (PsA), demonstrating better outcomes for TC. This substudy evaluated the performance metrics of modern imaging outcomes and compared them to the clinical data. METHODS: Non-contrast 0.2T magnetic resonance imaging (MRI; single hand) was assessed using the Outcomes in Rheumatology (OMERACT) PsA MRI Scoring System (PsAMRIS) with an additional global inflammation score. Ultrasound (US; same hand) was scored for greyscale, power Doppler, and erosions at the metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints and scores summated. RESULTS: Seventy-eight patients had paired (baseline and 48 weeks) US data and 61 paired MRI data; 50 had matched clinical, MR, and US data. Significant within-group changes were seen for the inflammatory PsAMRIS components at MCP level: MRI global inflammation [median difference (range), standardized response mean (SRM)]: 3.25 (-5.0 to 12.0), 0.68; 1.0 (-4.5 to 17.5), 0.45 for TC and StdC, respectively. Similar within-group differences were obtained for US: 1.0 (-13.0 to 23.0), 0.45; 3.0 (-6.0 to 21.0), 0.77 for TC and StdC, respectively. No differences were seen between treatment groups. Significant correlations were found between baseline and change MRI and US scores. A significant correlation was found between baseline PsA disease activity scores and MRI global inflammation scores (Spearman ρ for MCP, PIP: 0.46, 0.63, respectively). No differences in erosion progression were observed. CONCLUSION: The PsAMRIS and US inflammation scores demonstrated good responsiveness. No between-group differences were demonstrated, but this substudy was likely underpowered to determine differences between the 2 treatment strategies.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".