Origins of Discordant Responses among 3 Rheumatoid Arthritis Improvement Criteria
Bibliographic record
Abstract
OBJECTIVE: We examined agreement between the American College of Rheumatology (ACR), European League Against Rheumatism (EULAR), and Simplified Disease Activity Index (SDAI) response criteria in rheumatoid arthritis (RA) and tested whether discordant responses were associated with patients' baseline characteristics or changes in RA activity encapsulated by the different criteria. METHODS: In a prospective longitudinal study, we examined responses of 243 patients with active RA to escalation of antirheumatic treatment. We computed agreement between pairs of response criteria using κ coefficients and identified patient characteristics associated with unique responses to individual criteria. RESULTS: We found that 110 patients (45.3%) had an ACR 20% improvement (ACR20) response, 135 (55.5%) had a EULAR moderate/good response, and 83 (34.1%) had an SDAI50 response. Agreement was moderate to good (ACR20/EULAR κ 0.57; ACR20/SDAI50 κ 0.64; EULAR/SDAI50 κ 0.59). All who had SDAI50 response also had a EULAR response. Patient characteristics at baseline generally did not distinguish those who responded to both, 1, or neither criterion. Discordance was most often because of improvements in the erythrocyte sedimentation rate or C-reactive protein level among EULAR and SDAI50 responders, which were not as common among ACR20 responders. Based on receiver-operating characteristic curves, SDAI35 response had a better balance of sensitivity and specificity relative to ACR20 and EULAR moderate/good responses than SDAI50. CONCLUSION: Discordant responses to RA improvement criteria are most often because of differences in responses of acute-phase reactants. SDAI35 response had higher sensitivity for improvement, as reflected by other response criteria, than SDAI50 response.
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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 | 0.012 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".