Performance of 3 Composite Measures for Disease Activity in Peripheral Spondyloarthritis
Bibliographic record
Abstract
OBJECTIVE: To investigate concurrent validity and discrimination of the Disease Activity Index for Psoriatic Arthritis (DAPSA) score, Psoriatic Arthritis Disease Activity Score (PASDAS), and Ankylosing Spondylitis Disease Activity Score (ASDAS) in peripheral spondyloarthritis (pSpA) in clinical practice. METHODS: Data from a Dutch registry for SpA (SpA-Net) were used. Predefined hypotheses on concurrent validity of the composite measures with 15 other outcome measures of disease activity, physical function, and health-related quality of life were tested. Concurrent validity was considered acceptable if ≥ 75% of the hypotheses were confirmed. Discrimination was assessed by stratifying patients in DAPSA, PASDAS, and ASDAS predefined disease activity states and studying mean differences in health outcomes by 1-way ANOVA. Further, the concordance in disease activity states was determined. All analyses were repeated in subgroups with and without psoriasis (PsO). RESULTS: DAPSA, PASDAS, and ASDAS scores were available for 191, 139, and 279 patients with pSpA, respectively. The concurrent validity and discrimination of all composite measures were acceptable, as the strength of correlations were as hypothesized in ≥ 75% of the studied correlations. With increasing disease activity states, scores in nearly all outcome measures worsened significantly. The DAPSA, PASDAS, and ASDAS classified 22%, 56%, and 48% of the patients, respectively, in the 2 highest disease activity states. Stratified analyses for concomitant PsO revealed no relevant subgroup differences. CONCLUSION: The performance of DAPSA, PASDAS, and ASDAS in pSpA was acceptable, and independent of concomitant PsO. Due to discrepancy in classification, the validity of existing thresholds for disease activity states warrants further study in pSpA.
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".