ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Cardiovascular Endocrinology
Exploring the Association Between Immune-Inflammation Index and Carotid Plaque Formation: A Cross-Sectional Study in a Large Chinese Health Screening Population
Provisionally accepted
- Guangzhou 11th People's Hospital, Guangzhou, China
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Abstract Purpose: Cardiovascular disease remains a major public health concern closely associated with carotid atherosclerosis, a lipid-driven inflammatory condition. Composite inflammatory indices, including the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI), have shown promise in cardiovascular risk assessment; however, their comparative predictive value for carotid plaque formation has not been adequately validated in large Asian populations. This study investigated associations between these indices and carotid plaque presence in a large Chinese health screening cohort. Patients and Methods: This cross-sectional study analyzed 9,503 adults (mean age 51.6±9.5 years; 50.8% male) who underwent comprehensive health examinations at Guangzhou 11th People’s Hospital between January 2018 and December 2022. Indices were calculated from complete blood counts: SII = (neutrophils × platelets)/lymphocytes, SIRI = (neutrophils × monocytes)/lymphocytes, and AISI = (neutrophils × platelets × monocytes)/lymphocytes. Carotid plaques were identified by standardized ultrasonography using Mannheim Consensus criteria. Best subset regression with 10-fold cross-validation identified optimal prediction models from 4,095 combinations. The cohort was divided into training (70%, n=6,652) and validation (30%, n=2,851) sets. Results: Carotid plaque prevalence was 29.2%. All inflammatory indices were higher in participants with plaques: SIRI (0.78±0.50 vs. 0.63±0.36, P<0.001), AISI (2.04±1.43 vs. 1.57±0.99, P<0.001), and SII (5.28±2.66 vs. 4.32±1.88, P<0.001). Among 89 models without multicollinearity, the optimal four-variable model included age (OR=1.028, 95% CI: 1.020–1.036), fasting glucose (OR=1.799, 95% CI: 1.657–1.952), AISI (OR=2.277, 95% CI: 2.072–2.502), and diabetes mellitus (OR=3.234, 95% CI: 2.727–3.836). This model achieved superior validation (AUC=0.744) compared with models incorporating SIRI (AUC=0.739) or traditional risk factors (AUC=0.731). At the optimal threshold (0.32), the model had 71.5% sensitivity, 68.9% specificity, and 69.4% accuracy. Calibration was excellent (Hosmer–Lemeshow P=0.511; Brier score=0.198). Conclusion: AISI emerged as the most robust inflammatory biomarker for carotid plaque prediction among composite indices, suggesting its superior ability to capture the interplay between neutrophils, monocytes, platelets, and lymphocytes in atherosclerosis. The four-variable model combining AISI with traditional risk factors provides a feasible tool for carotid atherosclerosis risk stratification in Chinese populations, potentially enhancing early detection and prevention.
Keywords: carotid plaque, aggregate index of systemic inflammation, systemic inflammation response index, systemic immune-inflammation index, Atherosclerosis, Cardiovascular Risk Assessment
Received: 26 Oct 2025; Accepted: 20 Nov 2025.
Copyright: © 2025 Sun, Zhang, Yang, Yang and Zeng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Hua Zeng, 41882095@qq.com
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