Measurement properties of the minimal disease activity criteria for psoriatic arthritis
Bibliographic record
Abstract
Objective: To comprehensively assess evidence on the measurement properties of the minimal disease activity (MDA) criteria, a composite measure of the state of disease activity in psoriatic arthritis (PsA). Methods: A targeted literature review was conducted to identify studies that informed the validity and/or ability of the MDA to detect change among patients known to have experienced a change in clinical status. The search was conducted using MEDLINE and Embase databases (published as of October 2017). Pertinent articles provided by investigators and identified from select conference proceedings were also evaluated. Results: A total of 20 publications met the inclusion criteria. The MDA criteria were consistently associated with other indicators of disease activity/severity. The ability of the MDA criteria to detect change was supported in randomised controlled trials (n=10), with a greater percentage of patients randomised to active treatments achieving MDA relative to patients in comparator arms. Long-term observational studies (n=2) provided additional support for the ability of the MDA to detect within-subject change in the real-world settings. Conclusion: Evidence supports the MDA as a valid measure of disease activity in PsA that can detect between-group and within-subject change. The MDA is a comprehensive measure and clinically meaningful endpoint to assess the impact of interventions on PsA disease activity.
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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 | 0.031 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.015 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".