Comparison of Composite Indices Tailored for Psoriatic Arthritis Treated with csDMARD and bDMARD: A Cross-sectional Analysis of a Longitudinal Cohort
Bibliographic record
Abstract
OBJECTIVE: In a complex disease such as psoriatic arthritis (PsA), several methods are available to define remission or low disease activity (LDA), including the assessment of different clinical features. The aim of this study was to compare the composite indices tailored for PsA in patients treated with conventional synthetic disease-modifying antirheumatic drugs (csDMARD) and biological DMARD (bDMARD). METHODS: Patients with PsA classified with the ClASsification criteria for Psoriatic ARthritis criteria and with > 6 months followup treated with first csDMARD and bDMARD were consecutively enrolled. To assess disease activity, composite indices tailored for PsA were used, such as the Disease Activity Index for Psoriatic Arthritis (DAPSA), clinical DAPSA (cDAPSA), Psoriatic Arthritis Disease Activity Score (PASDAS), minimal disease activity (MDA) 5/7, and MDA 7/7. DAPSA and cDAPSA score ≤ 4, MDA 7/7, and PASDAS ≤ 1.9 identified remission. MDA 5/7, DAPSA score ≤ 14, cDAPSA score ≤ 13, and PASDAS < 3.2 identified the MDA and LDA criteria. RESULTS: One hundred nine patients with PsA were enrolled: 79 patients were receiving stable treatment with bDMARD and 30 with csDMARD. Overall, 28 (25.6%), 23 (21.1%), 19 (17.4%), and 13 patients (11.9%) were in cDAPSA remission, DAPSA remission, MDA 7/7, and PASDAS ≤ 1.9, respectively. Moreover, 54 (49.5%), 80 (73.3%), 79 (72.3%), and 38 patients (34.8%) were in MDA 5/7, DAPSA LDA, cDAPSA LDA, and PASDAS LDA. Patients treated with bDMARD had significantly lower median DAPSA, cDAPSA, and PASDAS score than patients treated with csDMARD. CONCLUSION: Patients with PsA receiving bDMARD are more likely to achieve a status of MDA and remission when compared with csDMARD. PASDAS ≤ 1.9 and MDA 7/7 seem to be stringent remission 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 | 0.002 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".