Table 2 Comparison of the predictive ability of the Nomogram model and models constructed in previous studies.

From: Interpretable machine learning-derived nomogram model for early detection of diabetic retinopathy in type 2 diabetes mellitus: a widely targeted metabolomics study

Model

AUC

AUC (95%CI)

Sensitivity (%)

Specificity (%)

Precision (%)

Positive predictive value (%)

Negative predictive value (%)

Youden’s index

Training set

 Nomogram model

0.99

0.97, 1.00

97.96

93.88

95.92

94.12

97.87

0.92

 Rhee et al. model

0.64

0.53, 0.76

87.76

48.98

68.37

63.24

80.00

0.37

 Aspelund et al. model

0.70

0.59, 0.80

83.67

51.02

67.35

63.08

75.76

0.35

 Hippisley-Cox and Coupland model

0.67

0.57, 0.78

61.22

73.47

67.35

69.77

65.45

0.35

 Dagliati et al. model

0.69

0.59, 0.80

55.10

79.59

67.35

72.97

63.93

0.35

Testing set

 Nomogram model

0.99

0.96, 1.00

95.00

100.00

97.50

100.00

95.24

0.95

 Rhee et al. model

0.76

0.61, 0.92

75.00

75.00

75.00

75.00

75.00

0.50

 Aspelund et al. model

0.73

0.57, 0.88

55.00

80.00

67.50

73.33

64.00

0.35

 Hippisley-Cox and Coupland model

0.77

0.62, 0.92

80.00

75.00

77.50

76.19

78.95

0.55

 Dagliati et al. model

0.78

0.63, 0.92

80.00

65.00

72.50

69.57

76.47

0.45

  1. Nomogram model contains thiamine triphosphate, systolic blood pressure, and duration of diabetes; Rhee et al. model contains glutamine/glutamic acid ratio; Aspelund et al. model contains sex, systolic blood pressure, duration of diabetes, and glycated hemoglobin; Hippisley-Cox and Coupland model contains sex, BMI, systolic blood pressure, cholesterol/high-density lipoprotein ratio, and glycated hemoglobin; Dagliati et al. model contains age, sex, duration of diabetes, BMI, glycated hemoglobin, hypertension, and smoking.