Should Anti-citrullinated Protein Antibody and Rheumatoid Factor Status Be Reassessed During the First Year of Followup in Recent-Onset Arthritis? A Longitudinal Study
Bibliographic record
Abstract
OBJECTIVE: Presence and levels of antibodies contribute to the classification of rheumatoid arthritis. We investigated the longitudinal course of anti-citrullinated protein antibodies (ACPA) and immunoglobin M (IgM) rheumatoid factor (RF) during the first year after arthritis onset in patients with very short disease duration. METHODS: Patients (aged 18-75 years) with ≥ 1 swollen joint of ≤ 16 weeks' duration had assessments of ACPA (2nd generation anti-cyclic citrullinated peptide antibodies, anti-CCP2) and IgM RF at inclusion and after 3, 6, and 12 months. Frequencies of seroconversions (negative to positive and vice versa) and changes in antibody levels during followup were determined. RESULTS: A total of 281 early arthritis patients (median duration of joint swelling 32 days, 14.2% ACPA positives, 12.8% IgM RF positives) with 978 longitudinally collected serum samples were included. Only 5 patients (1.8%) negative for both antibodies at baseline turned antibody-positive during followup, while 9 antibody-positive patients (3.2%) turned antibody-negative. ACPA was more stable than RF regarding both status and levels. CONCLUSION: Antibody status (ACPA/RF) is a stable phenotype in very early arthritis, as seroconversion was only found in 5% of patients. Repeated measurement of ACPA or RF during the first year after onset of arthritis does not offer major additional information.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".