Association Between Patient Perception of Disease Status and Different Components of the Minimal Disease Activity Criteria in Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to evaluate whether meeting minimal disease activity (MDA) as measured by the MDA criteria was perceived as good disease control by patients with psoriatic arthritis (PsA) regardless of which MDA components were not met. METHODS: We analyzed data from the Remission/Flare in PsA (ReFlaP) study (ClinicalTrials.gov: NCT03119805), a cross-sectional international study of adult patients with PsA. Patients self-reported if they felt their PsA was in remission (REM), low disease activity (LDA), or neither. The relationship between patient-reported status and the MDA components met was analyzed using point-biserial correlation, chi-square test, odds ratios, and specificity. RESULTS: Of the study participants who met MDA, 88.4% reported good disease status (REM/LDA). Pain was the most commonly unmet component. A moderate to strong correlation was found between meeting more MDA components and patient-reported good status irrespective of component unmet. On individual component testing, MDA state and patient-reported REM/LDA were significantly associated irrespective of unmet component, with the exception of entheses. Specificity of the MDA score irrespective of the unmet component was > 90%. The odds of MDA patients reporting poor disease status were significant only for when pain visual analog score (VAS) < 1 was the unmet component. This significance was not supported by the sensitivity analysis. CONCLUSION: This study suggests strong agreement between MDA status and patient-reported good status irrespective of unmet component. Pain < 1 or 2 on a 0-10 VAS was the hardest component to meet. The high specificity regardless of the unmet MDA component suggests patients who feel their disease is active are minimally misclassified by the score.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".