Validation studies of rheumatoid arthritis patient-reported outcome measures in populations at risk for inequity: A systematic review and analysis using the OMERACT summary of measurement properties equity table
Bibliographic record
Abstract
BACKGROUND: Existing patient-reported outcome measures (PROMs) in rheumatoid arthritis (RA) may be limited in their applicability to populations that are at risk for inequities. We conducted a systematic review to identify and rate evidence in the validation studies for PROMs in populations at risk for inequity. METHODS: A systematic review of MEDLINE and EMBASE was completed. The search strategy was developed to identify measurement property studies for PROMs of interest (selected pain, disease activity, global evaluation and quality of life scales) in patients with RA. We identified experimental, observational, and qualitative studies reporting analysis of feasibility, construct validity and discriminant ability metrics for populations at risk for inequity by various factors including race, ethnicity, culture or language; employment status; sex and gender identity; education level; socioeconomic status; social support; age; health literacy and disability. These were rated based on the OMERACT Summary of Measurement Properties Equity table. RESULTS: From 19,786 titles and abstracts screened, we identified 14 unique studies reporting validation metrics for pain (n = 3), DAS28-ESR or DAS28-CRP (n = 2), ACR20 (n = 1), patient global assessment (n = 2), EQ5D (n = 4), and PROMIS® (n = 3) by race (n = 10 studies), age (n = 6 studies), sex (n = 5 studies), education level (n = 2 studies), and disability, literacy, employment status, social support level and socioeconomic status (n = 1 study each). Five studies reported on feasibility, 12 reported construct validity metrics, and 4 studies reported on discriminant validity metrics. All studies by culture or language were rated as having good measurement property metrics. There was limited assessment of measurement property metrics for other populations at risk for inequity. CONCLUSION: Our study highlights important gaps in patient representation in rheumatology research for accepted outcome measures. New outcome measures being developed for research purposes and clinical practice should ensure and report representation of patients from populations at risk for inequities in the testing of metrics of feasibility, construct validity and discriminant ability metrics.
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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 | 0.064 | 0.242 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.018 |
| Bibliometrics | 0.030 | 0.025 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".