Comparison of Composite Measure Remission Targets in Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To identify (1) which composite measure is the most stringent target of remission; and (2) which disease component target proves the most difficult to achieve in the different states of minimal disease activity (MDA), Composite Psoriatic Disease Activity Index (CPDAI), Disease Activity Index for Psoriatic Arthritis (DAPSA), and clinical DAPSA (cDAPSA) in patients with psoriatic arthritis (PsA). METHODS: There were 258 patients with PsA recruited. Disease remission was evaluated comparing 4 different composite measures and using remission cutoffs as previously proposed (very low disease activity [VLDA], CPDAI ≤ 2, DAPSA ≤ 4, cDAPSA ≤ 4). RESULTS: Patients met VLDA criteria (MDA 7/7) in 9.0% of visits, DAPSA remission in 19.8%, cDAPSA remission in 23.4% and CPDAI remission in 30.2%. Of 258 patients, MDA criteria (≥ 5/7) were fulfilled in 46.5%. Of those in MDA, VLDA criteria were reached in 25.0%. Patients met the pain visual analog scale (VAS) target in 57.5% of visits when they were in MDA, 43.3% when in low disease activity (MDA 5-6/7), and 44.8% when in CPDAI remission. Multivariate regression analysis revealed that pain VAS was the least likely target to be achieved. Patients with inflammatory-type back pain had significantly higher pain scores; further, a significant relationship was seen between Bath Ankylosing Spondylitis Disease Activity Index and pain VAS. CONCLUSION: Based on our analysis, VLDA proved the most stringent target of disease remission in PsA compared to CPDAI, DAPSA, and cDAPSA. The pain VAS target of ≤ 1.5 cm was the most difficult component to achieve. CPDAI ≤ 2 was found to be the least stringent remission target; however, measurements of axial involvement, which contributed to the elevated pain VAS score in patients not achieving VLDA, were included as a domain in CPDAI only.
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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 | 0.004 | 0.014 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".