Domains to Be Considered for the Core Outcome Set of Axial Spondyloarthritis: Results From a 3-round Delphi Survey
Bibliographic record
Abstract
OBJECTIVE: Advances in the field of axial spondyloarthritis (axSpA) and the methodology to develop core sets have led the Assessment of SpondyloArthritis international Society (ASAS) group to update the ASAS-Outcomes in Rheumatology (OMERACT) core set. An important aspect was to ensure it would be applicable to the entire spectrum of axSpA. The first step was to define the most relevant disease domains. METHODS: A 3-round Delphi survey was conducted to gather opinions of 188 patients and 188 axSpA experts to define the most relevant disease domains to be included in the core set. The Delphi survey evaluated 2 separate research settings: (1) studies assessing symptom-modifying therapies; and (2) studies evaluating disease-modifying therapies. Importance of the domains was rated on a 1-9 Likert scale. A domain was considered for inclusion if, for both stakeholder groups, ≥ 70% of participants scored the domain as critical (7-9) and ≤ 15% scored it as not important (1-3) after 3 rounds. RESULTS: A total of 132 (70%) patients and 135 (72%) experts completed at least 1 round. After 3 rounds, 7 domains (pain, physical function, stiffness, disease activity, mobility, overall functioning and health, peripheral manifestations) were selected for the symptom-modifying therapies setting. For the disease-modifying therapies setting, 6 domains (physical function, disease activity, mobility, structural damage, extramusculoskeletal manifestations, peripheral manifestations) were selected. All domains selected by experts were also selected by patients. Patients selected all offered domains except emotional function. CONCLUSION: This study provides the domains selected by patients and axSpA experts that should be considered for the core set for axSpA.
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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 | 0.060 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".