Patient perspective on remission in rheumatoid arthritis: Validation of patient reported outcome instruments to measure absence of disease activity
Bibliographic record
Abstract
OBJECTIVE: Patients have identified pain, fatigue and independence as the most important domains that need to be improved to define remission in rheumatoid arthritis (RA). This study identified and validated instruments for these domains and evaluated their added value to the ACR/EULAR Boolean remission definition. METHODS: Patients with a 28-joint Disease Activity Score (DAS28) ≤3.2 or in self-perceived remission (declaring their disease activity 'as good as gone') from the Netherlands, Portugal, Australia, and Canada, were assessed at 0, 3 and 6 months for patient-reported outcomes and the WHO-ILAR RA core set. Instrument validity was evaluated cross-sectionally, longitudinally and for the ability to predict future good outcome in terms of physical functioning. Logistic regression quantified the added value to Boolean remission. RESULTS: Of 246 patients, 152 were also assessed at 3, and 142 at 6 months. Most instruments demonstrated construct validity and discriminative capacity. Pain and fatigue were best captured by a simple numerical rating scale (NRS). Measurement of independence proved more complex, but a newly developed independence NRS was preferred. NRS for pain, fatigue and independence, in addition to or instead of patient global assessment did not add enough information to justify modification of the current Boolean definition of remission in RA. CONCLUSION: Key elements of the patient perspective on remission in RA can be captured by NRS pain, fatigue, and independence. Although this study did not find conclusive evidence to improve the current definition of remission in RA, the information from these instruments adds value to the physician's assessment of remission and further bridges the gap between physician and patient.
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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 | 0.021 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".