Defining criteria for rheumatoid arthritis patient-derived disease activity score that correspond to Disease Activity Score 28 and Clinical Disease Activity Index based disease states and response criteria
Bibliographic record
Abstract
OBJECTIVE: Two versions of a patient-based DAS (PDAS) 1 and 2 (with and without ESR) have been developed and validated in RA. The objective of this study was to define PDAS1- and PDAS2-based criteria for remission, low, moderate and high disease activity and responses to treatment. METHOD: Using receiver operating characteristic curves, the optimal thresholds for PDAS1 and PDAS2 that correspond to validated assessor-based DAS (DAS28) and Clinical Disease Activity Index (CDAI) disease statuses were determined. Data from RA patients initiated on disease-modifying drugs were used to determine optimal thresholds for PDAS1 and PDAS2 that corresponded to EULAR good and moderate responses. Agreement with DAS28, CDAI and EULAR response criteria was assessed by Cohen's κ statistic. RESULTS: Threshold for PDAS1 and PDAS2 demonstrated fair to moderate agreement with DAS28 [κ = 0.44 (95% CI: 0.40, 0.50) and 0.31 (95% CI: 0.25, 0.38)] and CDAI [κ = 0.27 (95% CI: 0.22, 0.33) and 0.42 (95% CI: 0.35, 0.49)] disease statuses, respectively, which was similar to agreement between DAS28 and CDAI [κ = 0.54 (95% CI: 0.46, 0.61)] within this group. Agreement of EULAR good and moderate response with PDAS1 and PDAS2 was κ = 0.46 (95% CI: 0.27, 0.64) and 0.38 (95% CI: 0.20, 0.56), respectively. CONCLUSION: Thresholds for disease activity statuses and response to treatment for PDAS1 and PDAS2 have been established. They have comparable agreement to assessor-based criteria.
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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 | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 0.001 |
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".