Abstract
BACKGROUND: Metabolic inflammatory syndrome (MIS) is a novel concept in integrative healthcare that focuses on addressing metabolic disorders. The systemic immune-inflammatory index (SII) and systemic inflammatory response index (SIRI) are emerging biomarkers derived from blood cell counts. However, their associations with all-cause and cardiovascular mortality remain insufficiently explored. METHODS: This study utilized data from adult participants in the National Health and Nutrition Examination Survey (NHANES) between 2003 and 2018, all of whom had complete MIS-related data. SII and SIRI values were calculated based on blood test results. Kaplan-Meier survival curves and log-rank tests were employed to compare survival rates across quartiles of SII and SIRI. Weighted Cox proportional hazards regression models were used to evaluate the associations of SII and SIRI with all-cause and cardiovascular mortality. Nonlinear relationships and threshold effects were assessed using restricted cubic splines and segmented regression models. Receiver operating characteristic (ROC) and time-dependent ROC curves were generated to assess the predictive performance of SII and SIRI at various timepoints via area under the curve (AUC) analyses. Subgroup and sensitivity analyses were performed to examine these associations within specific populations. RESULTS: A total of 16,972 participants were included in the analysis. After adjusting for potential confounders, individuals in the highest quartile (Q4) of SII exhibited significantly increased risks of all-cause mortality [hazard ratio (HR): 1.28; 95% confidence interval CI 1.09-1.49; P = 0.002] and cardiovascular mortality (HR: 1.64; 95% CI 1.13-2.39; P = 0.009) compared to those in the lowest quartile (Q1). Similarly, participants in the highest quartile of SIRI demonstrated higher risks of all-cause mortality (HR: 1.56; 95% CI 1.26-1.92; P < 0.001) and cardiovascular mortality (HR: 2.14; 95% CI 1.46-3.13; P < 0.001). Both biomarkers emerged as independent predictors of mortality risk. J-shaped dose-response relationships were observed between log-SII and log-SIRI and the risks of all-cause and cardiovascular mortality (all P values for non-linearity were < 0.001). Both ROC and time-dependent ROC curve analyses indicated that log-SIRI had better prognostic performance for all-cause and cardiovascular mortality compared to log-SII. These findings were robust across subgroup and sensitivity analyses. CONCLUSIONS: High levels of SII and SIRI were independently associated with increased risks of all-cause and cardiovascular mortality, with SIRI showing superior predictive performance. This study underscores the prognostic utility of SII and SIRI in patients with MIS and provides valuable insights into their roles in mortality risk assessment.