Systematic literature review of domains assessed in psoriatic arthritis to inform the update of the psoriatic arthritis core domain set
Bibliographic record
Abstract
The objectives of this systematic literature review (SLR) were to identify domains and outcome measures used in psoriatic arthritis (PsA) studies in the past 5 years, and to compare the measurement of the Outcome Measures in Rheumatology (OMERACT) 2006 PsA Core Domain Set in studies published in 2010-2015 vs those published in 2006-2010. We performed a systematic literature search in two databases, PubMed and Embase, to identify randomised controlled trials (RCTs) in PsA. We also identified PsA longitudinal observational studies (LOS). Three patient research partners provided input into study conception, and data collection and interpretation. We identified 41 studies representing 22 unique RCTs, 27 LOS and 12 registries. Across all studies, we identified 24 domains and 169 outcome measures. In addition to the PsA Core Domain Set (6 domains), the following domains were also assessed in more than 30% of RCTs: acute phase reactants, dactylitis, enthesitis, fatigue and work productivity. We identified a range of 1-15 outcome measures per domain with a mean (SD) of 7 (4.7) per domain. The complete PsA Core Domain Set was assessed in 59% of RCTs in 2010-2015 compared to 23.5% RCTs in 2006-2010. There has been increased measurement of the PsA Core Domain Set in RCTs and LOS in the past 5 years. Numerous additional outcomes were also measured. The PsA Core Domain Set needs an update to standardise PsA outcome assessments. This SLR will inform the development of an updated PsA Core Domain Set with patient research partner input.
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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 | 0.049 | 0.200 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.029 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".