The 2010 American College of Rheumatology/European League Against Rheumatism classification criteria for rheumatoid arthritis: Phase 2 methodological report
Bibliographic record
Abstract
OBJECTIVE: The American College of Rheumatology and the European League Against Rheumatism have developed new classification criteria for rheumatoid arthritis (RA). The aim of Phase 2 of the development process was to achieve expert consensus on the clinical and laboratory variables that should contribute to the final criteria set. METHODS: Twenty-four expert RA clinicians (12 from Europe and 12 from North America) participated in Phase 2. A consensus-based decision analysis approach was used to identify factors (and their relative weights) that influence the probability of "developing RA," complemented by data from the Phase 1 study. Patient case scenarios were used to identify and reach consensus on factors important in determining the probability of RA development. Decision analytic software was used to derive the relative weights for each of the factors and their categories, using choice-based conjoint analysis. RESULTS: The expert panel agreed that the new classification criteria should be applied to individuals with undifferentiated inflammatory arthritis in whom at least 1 joint is deemed by an expert assessor to be swollen, indicating definite synovitis. In this clinical setting, they identified 4 additional criteria as being important: number of joints involved and site of involvement, serologic abnormality, acute-phase response, and duration of symptoms in the involved joints. These criteria were consistent with those identified in the Phase 1 data-driven approach. CONCLUSION: The consensus-based, decision analysis approach used in Phase 2 complemented the Phase 1 efforts. The 4 criteria and their relative weights form the basis of the final criteria set.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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; both teacher heads 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".