Composite Outcome Measures for Psoriatic Arthritis: Project Updates 2024
Bibliographic record
Abstract
The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA)-Outcome Measures in Rheumatology (OMERACT) psoriatic arthritis (PsA) working group provided updates at the GRAPPA 2024 annual meeting on their assessment of composite outcome measures for PsA. The group presented the progress of a systematic literature review on the psychometric properties of the following candidate composite outcome measures using the OMERACT filter 2.2: (1) minimal disease activity (MDA), (2) Disease Activity for Psoriatic Arthritis (DAPSA), (3) American College of Rheumatology (ACR) response criteria, (4) Psoriatic Arthritis Disease Activity Score (PASDAS), (5) Composite Psoriatic Disease Activity Index (CPDAI), (6) 3-item visual analog scale (3VAS), and (7) 4VAS. A Delphi exercise for patient research partners (PRPs) on domain match and feasibility is ongoing. Following analysis and endorsement of domain match and feasibility by PRPs, the working group will seek endorsement from the GRAPPA community. In addition, the group illustrated a new research proposal for using network metaanalysis to quantitatively compare the responsiveness of these various composite outcome measures.
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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 | 0.133 | 0.145 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 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".