Abstract
BACKGROUND: Chronic inflammation critically influences atherosclerotic progression and plaque destabilization. This investigation assessed and compared six lymphocyte-derived inflammatory indices (neutrophil-to-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), platelet-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), systemic inflammatory response index (SIRI), systemic immune-inflammation response index (SIIRI)) for predicting major adverse cardiovascular events (MACEs) in treatment-naïve acute coronary syndrome (ACS) patients undergoing coronary angiography. METHODS: This study enrolled 1120 patients with newly diagnosed ACS, in which the occurrence of MACEs was monitored. The predictive capacities of the included lymphocyte-derived inflammatory indices were evaluated through receiver operator characteristic (ROC) curve analysis with optimal cutoffs, supplemented by Cox proportional hazards modeling. RESULTS: A total of 265 MACEs (23.66%) were recorded during the 64.20 ± 23.05-month follow-up. Multivariate Cox analyses identified an elevated MLR (hazard ratio (HR) = 2.880, 95% confidence interval (CI) 1.280-6.470; p < 0.001) that was independently associated with the occurrence of MACEs in patients with newly diagnosed ACS. The ROC comparisons revealed a superior discriminative capacity of the MLR versus clinical factors, with an optimal MLR cutoff at 0.304 (sensitivity 61.1%; specificity 78.8%). Patients with a high MLR (≥0.304) exhibited a 3.5-fold increased risk of MACEs compared to those with a low MLR (46.96% vs. 13.29%; risk ratio = 1.635, 95% CI 1.475-1.812; p < 0.001); these data were corroborated by divergent Kaplan-Meier curves (log-rank p < 0.001). Meanwhile, subgroup analyses confirmed the prognostic consistency of the MLR across high-risk populations (age >60 years, diabetes, hypertension), with elevated MLR subgroups demonstrating uniformly higher rates of MACEs (all p < 0.001). CONCLUSIONS: MLR outperformed conventional parameters and five novel lymphocyte-based inflammatory indices in predicting MACEs in ACS patients; thus, the MLR can be established as a robust predictive biomarker. The clinical utility of the MLR extends to risk stratification across key patient subgroups, suggesting potential integration into routine cardiovascular risk assessment protocols.