Table 3 Performance of the new and Korean undiagnosed diabetes screening method in the development and validation datasets.
Model | Screeing method | Feature | AUC (95% CI) | Youden index | Sensitivity (%) | Specificity (%) | PPV | NPV | PLR | NLR | |
|---|---|---|---|---|---|---|---|---|---|---|---|
Train & Internal Validation Set | Lee model* | Risk score | Sex, Age, WC, Family history of diabetes, Hypertension status, Smoking status, Alcohol consumption | 0.750 (0.722 to 0.778) | 36 | 86 | 51 | 0.07 | 0.99 | 1.74 | 0.28 |
Logistic Regression | Logistic Regression | 0.786 (0.761 to 0.811) | 42.1 | 89.50 | 52.60 | 0.08 | 0.99 | 1.88 | 0.2 | ||
Random Forest | Random Forest Classifier | 0.781 (0.756 to 0.806) | 43.5 | 82.70 | 60.80 | 0.08 | 0.98 | 2021 | 0.22 | ||
LGBM | LightGBM Classifier | 0.777 (0.751 to 0.803) | 42.4 | 80.80 | 61.50 | 0.08 | 0.98 | 2.26 | 0.21 | ||
XGB | XGBoost Classifier | 0.786 (0.761 to 0.811) | 42.7 | 82.80 | 61.20 | 0.08 | 0.98 | 2.31 | 0.18 | ||
Ada | AdaBoost Classifier | 0.785 (0.76 to 0.81) | 42.4 | 80.30 | 62.10 | 0.08 | 0.99 | 2.12 | 0.32 | ||
External Validation set | Lee | Risk score | Sex, Age, WC, Family history of diabetes, Hypertension status, Smoking status, Alcohol consumption | 0.759 (0.741 to 0.777) | 36 | 90 | 46 | 0.08 | 0.99 | 1.67 | 0.21 |
Logistic Regression | Logistic Regression | 0.801 (0.786 to 0.816) | 46.4 | 86.40 | 60.00 | 0.1 | 0.99 | 2.16 | 0.23 | ||
Random Forest | Random Forest Classifier | 0.792 (0.776 to 0.808) | 46.1 | 83.00 | 63.10 | 0.11 | 0.99 | 2.25 | 0.27 | ||
LGBM | LightGBM Classifier | 0.795 (0.779 to 0.811) | 45.8 | 81.90 | 64.00 | 0.11 | 0.98 | 2.27 | 0.28 | ||
XGB | XGBoost Classifier | 0.802 (0.787 to 0.817) | 44.4 | 90.00 | 54.50 | 0.1 | 0.99 | 1.98 | 0.18 | ||
Ada | AdaBoost Classifier | 0.784 (0.768 to 0.8) | 42.4 | 82.90 | 59.50 | 0.1 | 0.99 | 2.05 | 0.29 |
