Do Radiographic Joint Damage and Disease Activity Influence Functional Disability Through Different Mechanisms? Direct and Indirect Effects of Disease Activity in Established Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To explore the relationship between rheumatoid arthritis (RA) disease activity and functional disability over time, considering indirect (predictive) and direct (concurrent) associations as well as the influence of radiographic joint damage and treatment strategy. METHODS: Functional disability [Health Assessment Questionnaire (HAQ)], disease activity [28-joint Disease Activity Score (DAS28)], and radiographic joint damage [Sharp/van der Heijde score (SHS)] were measured in 4 consecutive randomized controlled trials with increasingly intensive (tight control) treatment strategies. Average followup time for the 3 cohorts was 97, 53, and 50 months, respectively. Next to current DAS28, the previous DAS28 was used to study the predictive effect of a change in DAS28 on progression of functional disability (HAQ). Finally, it was investigated whether SHS mediated the predictive effect of DAS28. RESULTS: In patients treated with intensive treatment strategies, the progression of HAQ over time was statistically significantly less (p < 0.0001). The predictive influence of DAS28 on HAQ progression increased over the duration of the disease. SHS was not found to influence HAQ progression and did not mediate the predictive effect of DAS28. In the less intensively treated patients, the direct effect of disease activity decreased with disease duration, and contrarily, SHS did influence HAQ progression, but was not found to (fully) mediate the predictive effect of DAS28. CONCLUSION: In patients with RA treated with modern treatment strategies, there is less functional decline over time. Further, disease activity does predict functional decline but joint damage does not. This might indicate that factors associated with cumulative disease activity but not visible on radiographs can influence functional decline in patients with RA. This further underlines the importance of disease activity as a treatment target in early RA and in established RA.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".