Psychometric Properties of Patient Global Assessment in Psoriatic Arthritis: A Systematic Literature Review
Bibliographic record
Abstract
OBJECTIVE: Patient global assessment (PtGA) is a patient-reported outcome (PRO) that reflects a patient's judgment of their health/disease activity (DA). The objective of this systematic literature review was to assess the psychometric properties of PtGA in psoriatic arthritis (PsA). METHODS: Research articles reporting the assessment of psychometric properties of PtGA in PsA, listed in PubMed and extracted according to the Outcome Measures in Rheumatology (OMERACT) Filter 2.1 and the Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) terminology, were selected. Validity was assessed for comprehensiveness (content), correlation with other DA instruments (construct), and with quality of life measurements (criterion). A metaanalysis regarding construct validity was performed. Correlations between PtGA variations and other indices' variations (external responsiveness) and PtGA variations after treatment (internal responsiveness) were collected. Data on the formulation of PtGA and its discordance with physician global assessment (PGA) were also collected. METHODS: Of 60 articles analyzed (comprising 17,453 patients), 44 were observational studies and 16 were trials. PtGA was assessed through 27 different formulations. In all the retrieved studies, PtGA assessed DA, and in 3 studies, PtGA was assessed as a variable of global health status. The correlation between PtGA and PROs was strong (ρ > 0.50), whereas with other DA indices and PGA, it ranged from weak to moderate (ρ 0.20-0.50). Three studies described a positive discordance (PtGA > PGA). Responsiveness, assessed in 24 studies, showed a strong correlation with joint count index variations (ρ 0.51-0.52). CONCLUSION: PtGA is a valid and responsive tool in PsA. Correlations were higher with PROs and weaker with DA composite indices and PGA. PGA was usually scored lower than PtGA. A standardized formulation of PtGA would be useful.
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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 | 0.027 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".