Costs in Relation to Disability, Disease Activity, and Health-related Quality of Life in Rheumatoid Arthritis: Observational Data from Southern Sweden
Bibliographic record
Abstract
OBJECTIVE: To compare how costs relate to disability, disease activity, and health-related quality of life (HRQOL) in rheumatoid arthritis (RA). METHODS: Antitumor necrosis factor (anti-TNF)-treated patients with RA in southern Sweden (n = 2341) were monitored 2005-2010. Health Assessment Questionnaire (HAQ), 28-joint Disease Activity Score (DAS28), and EQ-5D scores were linked to register-derived costs of antirheumatic drugs (excluding anti-TNF agents), patient care, and work loss from 30 days before to 30 days after each visit (n = 13,289). Associations of HAQ/DAS28/EQ-5D to healthcare (patient care and drugs) and work loss costs (patients < 65 yrs) were studied in separate regression models, comparing standardized β coefficients by nonparametric bootstrapping to assess which measure best reflects costs. Analyses were conducted based on both individual means (linear regression, comparing between-patient associations) and by generalized estimating equations (GEE), using all observations to also account for within-patient associations of HAQ/DAS28/EQ-5D to costs. RESULTS: Regardless of the methodology (linear or GEE regression), HAQ was most closely related to both cost types, while work loss costs were also more closely associated with EQ-5D than DAS28. The results of the linear models for healthcare costs were standardized β = 0.21 (95% CI 0.15-0.27), 0.16 (0.11-0.21), and -0.15 (-0.21 to -0.10) for HAQ/DAS28/EQ-5D, respectively (p < 0.05 for HAQ vs DAS28/EQ-5D). For work loss costs, the results were standardized β = 0.43 (95% CI 0.39-0.48), 0.27 (0.23-0.32), and -0.34 (-0.38 to -0.29) for HAQ/DAS28/EQ-5D, respectively (p < 0.05 for HAQ vs DAS28/EQ-5D and for EQ-5D vs DAS28). CONCLUSION: Overall, HAQ disability is a better marker of RA costs than DAS28 or EQ-5D HRQOL.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".