A 2-year prognostic assessment of patients with coronary borderline lesions based on three-vessel quantitative flow ratio and the development and internal validation of a risk prediction nomogram

Objective To investigate the prognostic value of three-vessel quantitative flow ratio (3V-QFR) in patients with borderline coronary lesions (QFR 0.75–0.80) over a 2-year period; to identify key variables using LASSO regression; and to construct and internally validate a personalized nomogram model for predicting major adverse cardiovascular events (MACE) over 2 years. Methods This single-center retrospective cohort study included patients with coronary artery disease who were treated at Ordos Central Hospital from January 2021 to December 2024, underwent coronary angiography revealing at least one borderline lesion in a major coronary artery, and received a QFR assessment. Patients were followed for up to 24 months after discharge through outpatient visits, telephone follow-up, and electronic medical-record review. The primary endpoint was defined as the occurrence of MACE during the 2-year follow-up period. Restricted cubic spline (RCS) analysis was used to explore the nonlinear relationship between 3V-QFR and the risk of MACE. Least absolute shrinkage and selection operator (LASSO) penalized regression evaluated 19 prespecified candidate predictors using 10-fold cross-validation and the one-standard-error rule. A nomogram was constructed based on the selected factors, and the model’s discriminatory power, consistency, and clinical net benefit were evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Internal validation used 1,000 bootstrap resamples that repeated the complete preprocessing, variable-selection, and model-refitting pipeline. Results A total of 138 patients with borderline lesions were enrolled (33 in the MACE group and 105 in the non-MACE group). Among 33 first MACE events, 20 were ischemia-driven revascularizations, 9 were non-fatal myocardial infarctions, and 4 were all-cause deaths. RCS analysis showed an overall association between lower 3V-QFR and higher MACE risk, whereas evidence for nonlinearity was not statistically strong; multivariable regression supported 3V-QFR as an independent predictor. LASSO regression identified four optimal predictors of 2-year MACE through 10-fold cross-validation: 3V-QFR, age, diabetes, and NT-proBNP levels. The final model included 3V-QFR, age, diabetes, and NT-proBNP. The apparent AUC was 0.869 (95% CI 0.802–0.936), and the optimism-corrected AUC was 0.842 (95% CI 0.771–0.913); calibration and decision-curve findings were considered exploratory. Conclusion Lower 3V-QFR was associated with higher 2-year MACE risk in this retrospective development cohort. The 3V-QFR-based nomogram showed promising internal performance and may support exploratory risk stratification; independent external and prospective validation is required before clinical use.