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. 2026 Apr 28;15(4):246. doi: 10.21037/tcr-2025-aw-2385

Table 3. Comparative performance of optimal machine learning predictors and Cox benchmark for cardiovascular mortality.

Index C-index (95% CI) Optimal model Cox regression benchmark
P value HR 95% CI
TyG-BMI 0.840 (0.802–0.875) RSF 0.194 0.999 0.996–1.001
TyG-WHtR 0.817 (0.763–0.867) CoxNet 0.964 1.003 0.869–1.158
TyG 0.815 (0.770–0.857) CoxPH 0.484 0.929 0.757–1.141
TyG-WC 0.794 (0.744–0.834) SurvivalSVM 0.407 1.000 0.999–1.000

CI, confidence interval; CoxNet, LASSO-Cox regression; CoxPH, Cox proportional hazards; HR, hazard ratio; RSF, random survival forest; survivalSVM, support vector machine for survival analysis; TyG, triglyceride-glucose; TyG-BMI, triglyceride-glucose-body mass index; TyG-WC, triglyceride-glucose-waist circumference; TyG-WHtR, triglyceride-glucose-waist-to-height ratio.