Establishing an Updated Core Domain Set for Studies in Juvenile Idiopathic Arthritis: A Report from the OMERACT 2018 JIA Workshop
Bibliographic record
Abstract
OBJECTIVE: The current Juvenile Idiopathic Arthritis (JIA) Core Set used in randomized controlled trials (RCT) and longitudinal observational studies (LOS) was developed without the input of patients/parents. At the Outcome Measures in Rheumatology (OMERACT) 2016, a special interest group voted to reconsider the core set, incorporating broader input. We describe subsequent work culminating in an OMERACT 2018 plenary and consensus voting. METHODS: Candidate domains were identified through literature review, qualitative surveys, and online discussion boards (ODB) held with patients with JIA and parents in Australia, Italy, and the United States. A Delphi process with parents, patients, healthcare providers, researchers, and regulators served to edit the domain list and prioritize candidate domains. After the presentation of results, OMERACT workshop participants voted, with consensus set at > 70%. RESULTS: Participants in ODB were 53 patients with JIA (ages 15-24 yrs) and 55 parents. Three rounds of Delphi considering 27 domains were completed by 190 (response rate 85%), 201 (84%), and 182 (77%) people, respectively, from 50 countries. There was discordance noted between domains prioritized by patients/parents compared to others. OMERACT conference voting approved domains for JIA RCT and LOS with 83% endorsement. Mandatory domains are pain, joint inflammatory signs, activity limitation/physical function, patient's perception of disease activity (overall well-being), and adverse events. Mandatory in specific circumstances: inflammation/other features relevant to specific JIA categories. CONCLUSION: Following the OMERACT methodology, we developed an updated JIA Core Domain Set. Next steps are to identify and systematically evaluate best outcome measures for these domains.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".