Abstract Objective. Metabolic syndrome (MS) and type 2 diabetes mellitus (T2DM) share a chronic low-grade inflammatory milieu driven by adiposity. C-X-C motif chemokine ligand 1 (CXCL1) has been linked to insulin resistance and endothelial dysfunction, but its diagnostic relevance remains unclear. Methods. Our study employed a cross-sectional design and enrolled 104 adults: 52 newly diagnosed treatment-naive T2DM patients and 52 normoglycemic controls matched for age and sex. Serum CXCL1, high-sensitivity C-reactive protein (hs-CRP), and metabolic parameters were measured. Logistic regression models to discriminate MS and T2DM status were constructed (base model: age, sex, BMI) and then expanded by adding hs-CRP, CXCL1, or both. Model performance was assessed for discrimination (AUC), calibration (Integrated Calibration Index ICI, Expected Calibration Error ECE), and clinical utility (decision curve analysis, DCA) in accordance with TRIPOD 2024. Results. CXCL1 correlated with BMI (r=0.33, q=0.004) and hs-CRP (r=0.29, q=0.021), but not glycemic indices. For MS, CXCL1 marginally improved the base model (ΔAUC=+0.003, p=0.81); for T2DM, ΔAUC=+0.007 (p=0.60). hs-CRP performed better (AUC=0.744 for T2DM; 0.743 for MS) and the combined panel achieved the highest discrimination (AUC=0.769 and 0.745, respectively). Conclusions. CXCL1 reflects adiposity-related inflammation but provides only minimal incremental discrimination for metabolic syndrome and T2DM beyond conventional markers such as age, sex, BMI, and hs-CRP. The combined hs-CRP+CXCL1 panel achieved the best overall statistical performance, although its clinical utility remains limited. These findings emphasize the need for integrated multi-marker approaches rather than single-biomarker screening in metabolic risk assessment.
Zeynettin et al. (2026) studied this question.