Comparison of Different Remission and Low Disease Definitions in Psoriatic Arthritis and Evaluation of Their Prognostic Value
Bibliographic record
Abstract
OBJECTIVE: There is no agreement on the optimal definitions for assessing disease state in patients with psoriatic arthritis (PsA), and some of the commonly used definitions do not include assessment of skin lesions. We investigated the performance of various definitions in patients with PsA and psoriasis. METHODS: This was a posthoc analysis of data from the PRESTA study. The remission definitions analyzed were very low disease activity (VLDA) index, defined as 7/7 of the minimal disease activity (MDA) cutoffs; Disease Activity Index for PsA (DAPSA); and clinical (c-) DAPSA. The low disease activity (LDA) definitions analyzed were as follows: MDA defined as 5/7 cutoffs; MDA joint with both the tender joint count (TJC) and swollen joint count (SJC) cutoffs mandated; MDA skin where skin cutoff was mandated; MDA joint + skin where TJC, SJC, and skin cutoffs were mandated; DAPSA LDA; and cDAPSA LDA. RESULTS: At Week 24, the proportions of patients achieving VLDA, DAPSA, and cDAPSA remission were 10%, 35%, and 37%, respectively. Of the patients achieving DAPSA and cDAPSA remission, 55% and 56%, respectively, had Psoriasis Area and Severity Index > 1. The proportions of patients achieving MDA 5/7, MDA skin, MDA joint, and MDA joint + skin were 44%, 19%, 36%, and 14%, respectively, versus 70% achieving DAPSA and cDAPSA LDA. Notable residual levels of psoriasis were observed in patients achieving the definitions that did not require skin disease control. CONCLUSION: VLDA and MDA definitions are more stringent than DAPSA and cDAPSA definitions for the assessment of PsA. The relevance of residual disease to patients, however, remains to be determined. [Clinical Trial registration: ClinicalTrials.gov NCT00245960].
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".