Development of a Prognostic Model for MACE in Atherosclerosis Based on MTHFR and Serum Markers

Abstract

Background and Aims Atherosclerosis (AS) is associated with high residual cardiovascular risk despite standard treatment. Abnormal homocysteine metabolism and MTHFR polymorphisms are involved in AS progression, but few prognostic models integrate genetic and multidimensional biochemical indicators. This study aimed to develop and validate a prognostic model for major adverse cardiovascular events (MACE) in patients with AS. Methods This single-center observational cohort study enrolled 580 patients with AS confirmed by coronary angiography between January 2023 and January 2026. Baseline data included clinical characteristics, imaging indices, serum biochemical markers, and MTHFR/MTRR genotypes. The primary outcome was MACE. Predictors were screened by LASSO regression, and a nomogram was constructed using multivariable Cox regression. Model performance was evaluated by C-index, calibration curves, and decision curve analysis. Results Over a median follow-up of 24.5 months, 135 patients (23.3%) developed MACE. Independent predictors included MTHFR 677TT mutation, elevated Hcy, low serum folate, Gensini score, CIMT, Lp-PLA2, and diabetes. The model achieved a C-index of 0.885, showing excellent discrimination, good calibration, and favorable net clinical benefit. Conclusion This integrated prognostic model demonstrated good internal discrimination and calibration for predicting MACE in patients with AS. The nomogram provides a practical risk-stratification framework for identifying individuals at high residual cardiovascular risk. However, given the lack of external validation and the inherent risk of optimism bias in single-center studies, these findings should be considered preliminary. Rigorous external validation in diverse, multicenter cohorts is strictly required before this tool can be recommended for routine clinical implementation.