The comparative responsiveness of the EQ-5D and SF-6D to change in patients with inflammatory arthritis
Bibliographic record
Abstract
PURPOSE: Comparative evidence regarding the responsiveness of the EQ-5D and SF-6D in arthritis patients is conflicting and insufficient across the range of disease severity. We examined the comparative responsiveness of the EQ-5D and SF-6D in cohorts of patients with early inflammatory disease through to severe rheumatoid arthritis (RA). METHODS: Responsiveness was tested using the effect size (ES) and standardised response mean (SRM). Correlation of change in EQ-5D and SF-6D with disease specific measures was tested using Pearson correlations and the Steiger's Z test. Treatment response and self-reported change were used as anchors of important change. RESULTS: The EQ-5D was more responsive to deterioration (ES ratio (EQ-5D/SF-6D): 1.6-3.0) and the SF-6D more responsive to improvement (ES ratio (SF-6D/EQ-5D): 1.1-1.8) in health. The SF-6D did not respond well to deterioration in patients with established severe RA (ES and SRM 0.08). The EQ-5D provided larger absolute mean change estimates but with greater variance compared to the SF-6D. CONCLUSIONS: The comparative responsiveness of the EQ-5D and SF-6D differs according to the direction of change. The level of mean change of the EQ-5D relative to the SF-6D has implications for cost-effectiveness analysis. Use of the SF-6D in patients with severe progressive disease may be inappropriate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".