Initiating Evaluation of Composite Outcome Measures for Psoriatic Arthritis: 2022 Updates From the GRAPPA-OMERACT Working Group
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-comprising rheumatologists, dermatologists, methodologists, and patient research partners-provided updates at the GRAPPA 2022 annual meeting on its work to evaluate composite outcome measures for PsA. Ten composite outcome measures were considered. Initial steps were to define the population, the purpose of use, and the proposed pros and cons of the 10 candidate composite instruments for PsA. Preliminary Delphi exercises within the working group and GRAPPA stakeholders confirmed high priority for evaluating minimal disease activity (MDA); moderate priority for Disease Activity in PsA (DAPSA), American College of Rheumatology (ACR) response criteria, Psoriatic Arthritis Disease Activity Score (PASDAS), Composite Psoriatic Disease Activity Index (CPDAI), 3 visual analog scale (VAS), and 4VAS; and low priority for Disease Activity Score in 28 joints (DAS28), Psoriatic Arthritis Responder Criteria (PsARC), and Routine Assessment of Patient Index Data 3 (RAPID3). Further appraisal of candidate composite instruments is ongoing.
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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 | 0.255 | 0.167 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".