ArticleFrontiers in cardiovascular medicine2026
Underestimation of cardiovascular risk by QRISK3 and RA-adapted SCORE2 in a Chinese rheumatoid arthritis population.
Article in Frontiers in cardiovascular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Patients with rheumatoid arthritis (RA) face a substantially increased risk of cardiovascular disease (CVD), yet existing risk prediction models often perform poorly in this population. QRISK3 and RA-adapted SCORE2 incorporate RA in their frameworks, but their validity in Asian cohorts remains uncertain. Methods: We conducted a retrospective observational study using electronic hospital records from The First People's Hospital of Zhangjiagang City in China (2020-2025). Adults with confirmed RA who subsequently experienced a first major CVD event (coronary heart disease, ischemic stroke, or transient ischemic attack) were included. QRISK3 and RA-adapted SCORE2 were applied to the conventional thresholds of ≥10% and ≥5% respectively, to define high risk. Agreement between tools was assessed with Cohen's kappa and McNemar's test. Adjusted logistic regression examined demographic, RA-related, and traditional risk factors associated with risk underestimation. Results: A total of 249 patients with RA and CVD were included. Both tools substantially underestimated risk, with underestimation more frequent for QRISK3 than RA-adapted SCORE2. Agreement between the two was moderate (κ = 0.44), with discordance most marked across age, glucocorticoid exposure, and disease activity subgroups. Patients with high baseline DAS28 scores were particularly likely to be misclassified as low risk. In adjusted models, diabetes, chronic kidney disease, and systemic steroid use were associated with greater underestimation. Conclusions: QRISK3 and RA-adapted SCORE2substantially underestimated cardiovascular risk in Chinese patients with RA, especially those with active disease. European-derived tools may not be reliable in this setting, underscoring the need for recalibrated or RA-specific models.
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