POS0742 THE EFFECT OF DISEASE ACTIVITY ON CARDIOVASCULAR RISK VARIES ACCORDING TO RHEUMATOID FACTOR AND ANTICITRULLINATED PROTEIN ANTIBODY STATUS IN PATIENTS WITH RHEUMATOID ARTHRITIS
Bibliographic record
Abstract
Background: Rheumatoid arthritis (RA) activity associates with cardiovascular (CV) risk. Anticitrullinated protein antibodies (ACPA) were linked to higher disease activity and lower remission rates. Treatment responses to immunomodulatory therapies may, likewise, vary by seropositivity status. We therefore hypothesized that the relationship between disease activity and CV risk may vary among ACPA positive and negative patients. Rheumatoid factor (RF) associated with higher RA activity independently of ACPA status. We hence posited that the effect of RA activity on CV risk may differ among RF positive and negative patients. Variance in disease activity, characteristics and outcomes have been reported in seronegative compared to single or double positive patients. Objectives: We explored whether the relationship between RA activity and CV risk varied according to ACPA and RF status. Methods: We evaluated 3952 patients free of CV disease, enrolled in An InTernation A l Consortium for Cardiovascular disease in RA (ATACC-RA). Main outcome was major adverse cardiovascular events (MACE) defined as non-fatal myocardial infarction, non-fatal stroke, or CV death. Missing data were imputed using multiple imputation by chained equations with 10 iterations. Multivariable Cox models stratified by center risk explored the association of baseline 28-joint disease activity score with C-reactive protein (DAS28CRP), ACPA positivity, RF positivity and the two- and three-way interactions of DAS28CRP with ACPA and/or RF with risk of MACE. All models adjusted for age, gender, hypertension, diabetes, smoking, family history of CV disease, total cholesterol to high-density lipoprotein ratio, and disease duration. Results: Of 3952 patients, 1007 (25.5%) were seronegative, 306 (7.7%) ACPA positive and RF negative, 557 (14.1%) ACPA negative and RF positive, and 2082 (52.7%) double positive at diagnosis. Mean (standard deviation) DAS28CRP was 3.74 (1.28). Over 22,981 patient years, 184 MACE occurred. There was a main effect of DAS28CRP (HR 1.18, 95% CI 1.03-1.36, p=0.016), but not ACPA (HR 1.24, 95% CI 0.84-1.81, p=0.279) or RF (HR 1.27, 95% CI 0.83-1.96, p=0.268) on MACE risk after multivariable adjustment. However, there were main effects of single and double seropositivity; compared to seronegative, single (HR 1.69, 95% CI 1.03-2.75, p=0.036) and double seropositivity (HR 1.72, 95% CI 1.12-2.65, p=0.014) associated with a greater risk of MACE. A significant three-way interaction between DAS28CRP, ACPA and RF positivity was observed (p-interaction=0.034) suggesting that the influence of disease activity on MACE risk varied according to both ACPA and RF status. Among RF negative patients, the ACPA × DAS28CRP interaction was significant (p=0.011) and DAS28CRP associated with MACE in ACPA negative (HR 1.58, 95% CI 1.08-2.33, p=0.020) but not positive patients (HR 1.05, 95% CI 0.67-1.64, p=0.823, Figure 1A). Among RF positive patients, the ACPA × DAS28CRP interaction (p=0.861) and ACPA main effect (HR 1.04, 95% CI 0.70-1.55, p=0.855) were not significant, though the main effect of DAS28CRP was (HR 1.18, 95% CI 1.01-1.38, p=0.044, Figure 1B). Conclusion: Single and double seropositive patients incurred higher risk of MACE compared to seronegatives. Among RF positive patients, RA activity associated with MACE risk irrespective of ACPA status. Among RF negative, disease activity associated with CV risk only in ACPA negative ones. REFERENCES: NIL . Acknowledgements: NIL . Disclosure of Interests: George Karpouzas Scipher, Janssen, Scipher, Pfizer, Virginia Pascual: None declared, Miguel Ángel González-Gay: None declared, Elena Myasoedova: None declared, Alfonso Corrales Martinez: None declared, Solbritt Rantapää Dahlqvist: None declared, Petros P. Sfikakis: None declared, Patrick Dessein: None declared, Carol Hitchon: None declared, Piet van Riel: None declared, Irazú Contreras-Yáñez: None declared, Iris J. Colunga-Pedraza: None declared, Dionicio A. Galarza-Delgado: None declared, Jose R. Azpiri-Lopez: None declared, Anne Grete Semb: None declared, Durga Prasanna Misra: None declared, Patrick Durez: None declared, Brian Bridal-Logstrup: None declared, Ellen-Margrethe Hauge: None declared, George Kitas: None declared, Sarah Ormseth: None declared. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".