Synovial Tissue Sublining CD68 Expression Is a Biomarker of Therapeutic Response in Rheumatoid Arthritis Clinical Trials: Consistency Across Centers
Bibliographic record
Abstract
OBJECTIVE: To determine whether the correlation between the mean change in disease activity and the mean change in synovial sublining (sl) CD68 expression could be demonstrated across different academic centers. METHODS: Synovial biopsies obtained at arthroscopy from patients with rheumatoid arthritis before and 160 days after rituximab therapy were selected and coded. Paired sections were processed independently at Amsterdam Medical Center (AMC) and at St. Vincent's University Hospital (SVUH), Dublin. Digital image analysis (DIA) was employed at both centers to quantify sublining CD68 expression. RESULTS: After analysis of CD68sl expression at centers in 2 different countries, high levels of intracenter and intercenter agreement were observed. For the pooled sections stained at AMC, the correlation between 2 investigators was R = 0.942, p = 0.000, and for sections stained at SVUH, R = 0.899, p = 0.001. Similarly, the intracenter correlations for DeltaCD68sl expression after treatment were R = 0.998, p = 0.000, for sections stained at AMC and R = 0.880, p = 0.000, for sections stained at SVUH. The intercenter correlation for the pooled scores of sections stained at AMC was R = 0.85, p = 0.000, and for the sections stained at SVUH, R = 0.62, p = 0.001. The consistent correlation between DeltaDAS (Disease Activity Score) and DeltaCD68sl expression across different studies (Pearson correlation = 0.895, p < 0.001) was confirmed. The standardized response mean values for DeltaCD68sl, calculated from analyses at both AMC and SVUH, were consistently 0.5 or greater, indicating a moderate to high potential to detect change. CONCLUSION: The correlation between mean DeltaDAS and mean DeltaCD68sl expression was confirmed across 2 centers. Examination of serial biopsy samples can be used reliably to screen for interesting biological effects at the site of inflammation at an early stage of drug development.
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 | 0.022 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".