Composite Measures for Clinical Trials in Psoriatic Arthritis: Testing Pain and Fatigue Modifications in a UK Multicenter Study
Bibliographic record
Abstract
Objective To test the addition of pain and fatigue to the Composite Psoriatic Arthritis Disease Activity (CPDAI) and the Group for Research and Assessment of Psoriasis and PsA (GRAPPA) Composite Exercise (GRACE) composite measures of psoriatic arthritis (PsA). Methods Clinical and patient-reported outcome measures were assessed in patients with PsA at 3 consecutive follow-up visits over 6 months in a UK multicenter observational study. A pain visual analog scale and Functional Assessment of Chronic Illness Therapy Fatigue scale were added as modifications to the CPDAI and GRACE composite measures. Original and modified versions were tested against the PsA Disease Activity Score (PASDAS) and the Disease Activity Index for PsA (DAPSA). Discrimination between disease states and responsiveness were tested with t-scores, standardized response means (SRMs), and effect sizes. Data were presented to members at the 2020 annual meeting who then voted on the GRAPPArecommended composite and treatment targets for clinical trials. Results One hundred forty-one patients were recruited with a mean PsA disease duration of 6.1 years (range 0–41 yrs). The SRMs for the GRACE and modified GRACE (mGRACE) were 0.67 and 0.64, respectively, and 0.54 and 0.46, respectively, for the CPDAI and modified CPDAI (mCPDAI). The t-scores for the GRACE and mGRACE were unchanged at 7.8 for both, and 6.8 and 7.0 for the CPDAI and mCPDAI, respectively. The PASDAS demonstrated the best responsiveness (SRM 0.84) and discrimination (t-scores 8.3). Most members (82%) agreed the composites should not be modified and 77% voted for the PASDAS as the GRAPPA-recommended composite for clinical trials, with 90% minimal disease activity (MDA) as the target. Conclusion Modifying the CPDAI and GRACE with the addition of pain and fatigue does not enhance responsiveness nor the measures’ ability to detect disease status in terms of requiring treatment escalation. GRAPPA members voted for the PASDAS as the composite measure in clinical trials and MDA as the target.
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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 | 0.105 | 0.190 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".