Association between systemic inflammatory response index and cardiovascular disease risk in rheumatoid arthritis patients: a machine learning based on US and Chinese cohorts.

backgroundA high incidence of cardiovascular disease (CVD) is observed among patients with rheumatoid arthritis (RA); although the systemic inflammatory response index (SIRI) has demonstrated predictive utility across inflammatory and cardiovascular disorders, its relationship with CVD risk in RA remains underinvestigated.

methodsThe present study was partitioned into a training set, a temporal validation set, and an external validation set derived from the NHANES database and a Chinese clinical cohort. Between-group differences were characterized, and multivariable logistic regression models were fitted across SIRI tertiles within each dataset. Restricted cubic spline functions were plotted to visualize dose-response associations, and receiver operating characteristic analysis was employed to quantify discrimination and predictive probabilities. Additionally, the incremental value of augmenting the Framingham risk score with SIRI was evaluated across all three datasets. Variable importance derived from an XGBoost algorithm and SHAP summary plots were used to quantify contributor-specific risk, whereas net reclassification improvement and integrated discrimination improvement were computed to corroborate model superiority.

resultsIn training set, CVD prevalence among RA patients was 23.22 % and the mean age was 65.5 years. The cohort comprised 167 male (48.55%) and 177 female (51.45%). Median SIRI values were significantly higher in participants with CVD than in those without (1.19 vs. 0.99, P < 0.001). A positive association between SIRI and CVD risk was detected (P for overall = 0.003, P for nonlinear = 0.022), participants in the highest SIRI tertile exhibited 2-fold increase in CVD risk relative to the lowest tertile (OR = 2.028, 95% CI: 1.343-3.075, P < 0.001). Incorporation of SIRI into the Framingham risk score improved the area under the receiver operating characteristic curve on training set (0.705 vs. 0.688), time validation set (0.693 vs. 0.678) and external validation set (0.793 vs. 0.761) set. Variable importance metrics and SHAP value distributions further indicated that SIRI constitutes a principal determinant of CVD risk in RA.

conclusionSIRI is significantly and positively associated with CVD risk in RA and effectively enhances the predictive performance of the Framingham risk score when applied to this population. Accordingly, SIRI may serve as an inflammatory biomarker for the early identification and management of CVD risk in RA, thereby informing the development of individualized therapeutic strategies. Key Points • SIRI is significantly and positively associated with CVD risk in RA. • SIRI enhances the predictive performance of the Framingham risk score when applied to RA patients.