Radiographic joint damage in rheumatoid arthritis is associated with differences in cartilage turnover and can be predicted by serum biomarkers: an evaluation from 1 to 4 years after diagnosis
Bibliographic record
Abstract
INTRODUCTION: The objective of this study was to determine whether serum biomarkers for degradation and synthesis of the extracellular matrix of cartilage are associated with, and can predict, radiographic damage in patients with rheumatoid arthritis (RA). METHODS: Clinical and radiographic data of 87 RA patients were recorded 1 year after disease onset and then annually up to four years. Serum concentrations of four cartilage biomarkers were determined at these time points: a neoepitope formed by collagenase cleavage of type II collagen (C2C), a neoepitope formed by collagenase cleavage of type II collagen as well as type I collagen (C1,2C), a carboxy propeptide of type II procollagen formed during synthesis (CPII), and a cartilage proteoglycan aggrecan turnover epitope (CS846-epitope). Biomarker concentrations between patients with rapid radiographic progression (>7.3 Sharp/van der Heijde units per year) and those with slow radiographic progression (<2.3 units per year) were compared. In addition, we evaluated the long-term and short-term predictive value of each biomarker for progression of radiographic damage. RESULTS: Patients with rapid radiographic progression had higher C2C, higher C1,2C, and higher CS846-epitope levels than slow progressors. CPII levels showed no differences. Most importantly, the long-term radiographic progression for C2C, for C1,2C, and for CS846-epitope can be predicted by the biomarker value at year 1 after disease onset. C2C was also a predictor for joint space narrowing and annual radiographic damage during the subsequent year. CONCLUSION: This study shows that the concentration of serum biomarkers of cartilage collagen breakdown and proteoglycan turnover, but not of collagen synthesis, are related to joint destruction in RA. The use of these biomarkers may be of value when studying progression of joint damage in patients with RA.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".