Prognosis of Seronegative Patients in a Large Prospective Cohort of Patients with Early Inflammatory Arthritis
Bibliographic record
Abstract
OBJECTIVE: Rheumatoid factor (RF) and anticitrullinated protein antibodies (ACPA) are believed to be associated with more severe rheumatoid arthritis; however, studies in early inflammatory arthritis (EIA) have yielded conflicting results. Our study determined the prognosis of baseline ACPA-negative and RF-negative patients. METHODS: Patients enrolled in the Canadian Early Arthritis Cohort had IgM RF and IgG anticyclic citrullinated peptide antibodies 2 (anti-CCP2) measured at baseline. Remission was defined as a Disease Activity Score of 28 joints (DAS28) < 2.6 using logistic regression accounting for confounders at 12-month and 24-month followup. RESULTS: Of the 841 patients, 216 (26%) were negative for both RF and anti-CCP2. Compared to seropositive subjects, seronegative subjects were older (57 ± 15 vs 51 ± 14 yrs), more males proportionately (31% vs 23%), and had shorter length of symptoms (166 ± 87 vs 192 ± 98 days), and at baseline had higher mean swollen joint count (SJC; 8.8 ± 6.8 vs 6.5 ± 5.6), DAS28 (5.0 ± 1.6 vs 4.8 ± 1.5), and erosive disease (32% vs 24%, p < 0.05). Treatment was similar between the 2 groups. At 24-month followup, seronegative compared to seropositive subjects had greater mean change (Δ ± SD) in disease activity measures: ΔSJC counts (-6.9 ± 7.0 vs -5.1 ± 5.9), ΔDAS28 (-2.4 ± 2.0 vs -1.8 ± 1.8), and ΔC-reactive protein (-11.0 ± 17.9 vs -6.4 ± 17.5, p < 0.05). Accounting for confounders, antibody status was not significantly associated with remission. However, at 12-month followup, ACPA-positive subjects were independently more likely to have new erosive disease (OR 2.94, 95% CI 1.45-5.94). CONCLUSION: Although seronegative subjects with EIA have higher baseline DAS28 compared to seropositive subjects, they have a good response to treatment and are less likely to develop erosive disease during followup.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".