Integrating traditional Chinese medicine syndromes with clinical variables to predict lower extremity arterial disease in type 2 diabetes

Table 5 Key numerical summary of model performance, calibration, and clinical utility

Metric	XGBoost
Nested 5 × 5 cross-validation AUC	0.746 ± 0.038
Bootstrap optimism-corrected AUC	0.745
Calibration slope	1.176-1.007
Calibration intercept	-0.104 to -0.040
Expected calibration error	0.044 to 0.034
Brier score (validation)	0.186
Split-ratio AUC (6:4/7:3/8:2)	0.758/0.762/0.755
PPV/NPV at threshold 0.5	0.737/0.607
PPV/NPV at threshold 0.7	0.863/0.551

Results pertain to the XGBoost model (area under the receiver operating characteristic curve = 0.763). AUC: Area under the receiver operating characteristic curve; PPV: Positive predictive value; NPV: Negative predictive value.