ACPA and Future Onset of Rheumatoid Arthritis Among Individuals With Undifferentiated Arthritis and Arthritis Free Individuals: A Systematic Review of Cohort Studies
Bibliographic record
Abstract
Objective : Antibodies against anti-cyclic citrullinated proteins (ACPA) have been suggested as a risk factor for rheumatoid arthritis (RA). A systematic review of the literature was conducted to determine the relationship between ACPA antibodies and future RA development and to identify the methodological limitations in order to guide the design of any future cohort study in this field. Materials and Methods : Web of Science, Pub Med, and EMBASE databases were searched. A data extraction and quality assessment form was developed based on the ACROBAT-NRSI (“A Cochrane Risk of Bias Assessment Tool - for Non-Randomized Studies of Interventions) and STROBE statement. Our initial searches produced 1,396 titles, which were reviewed by title and abstract. Thirty seven studies were selected for full text review and eleven studies fulfilled our inclusion criteria. Results : Qualitative synthesis of the included studies revealed a consistent positive association between ACPA and future RA development. The unadjusted HR comparing ACPA positive and negative groups ranged from 2.46 to 223.1, while the unadjusted OR ranged 1.09 to 46.7. Only one study reported an unadjusted RR of 2.75. Conclusion : The review indicated that the presence of ACPA in patients with undifferentiated arthritis and healthy subjects predicts future onset of 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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 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".