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Table 2 Performance measures based on cross-validation (Multivariable Models)

From: A comparison of statistical methods for the detection of hepatocellular carcinoma based on serum biomarkers and clinical variables

Method (Model)1

LOOCV AUC (95% CI)2

LOOCV ACC3

3CV AUC (95% CI)4

3CV ACC (SD)5

stepPLR (λ = 0.1) (male only, with age)

0.95(0.93-0.98)

86.63

0.94(0.94-0.95)

86.03(4.78)

stepPLR (λ = 1) (male only, with age)

0.95(0.93-0.98)

87.16

0.95(0.95-0.96)

87.12(4.31)

stepPLR (λ = 10) (male only, with age)

0.94(0.92-0.97)

86.63

0.95(0.94-0.95)

87.49(4.31)

stepPLR (λ = 0.1) (male only, without age)

0.90(0.86-0.94)

80.35

0.90(0.89-0.90)

80.97(5.16)

stepPLR (λ = 1) (male only, without age)

0.89(0.84-0.93)

81.28

0.89(0.89-0.90)

80.71(5.09)

stepPLR (λ = 10) (male only, without age)

0.91(0.87-0.95)

83.96

0.91(0.90-0.91)

82.17(5.37)

stepPLR (λ = 0.1) (gender, with age)

0.95(0.92-0.97)

88.25

0.95(0.94-0.95)

87.96(3.20)

stepPLR (λ = 1) (gender, with age)

0.95(0.92-0.97)

88.25

0.95(0.94-0.95)

88.34(3.51)

stepPLR (λ = 10) (gender, with age)

0.94(0.92-0.97)

88.25

0.95(0.94-0.95)

88.31(3.39)

stepPLR (λ = 0.1) (gender, without age)

0.92(0.88-0.95)

84.84

0.92(0.91-0.92)

84.35(4.23)

stepPLR (λ = 1) (gender, without age)

0.92(0.89-0.95)

84.84

0.92(0.92-0.92)

84.59(4.09)

stepPLR (λ = 10) (gender, without age)

0.92(0.89-0.95)

83.71

0.92(0.91-0.92)

83.72(4.29)

mob(AAT|~.) with age, male only)

0.85(0.79-0.91)

83.43

0.81(0.80-0.82)

76.23(5.71)

mob(GP73|~.) with age, male only)

0.88(0.82-0.93)

83.98

0.87(0.87-0.88)

80.77(4.99)

mob(AFP|~.) with age, male only)

0.86(0.80-0.92)

81.22

0.87(0.87-0.88)

83.66(5.52)

mob(Kin|~.) with age, male only)

0.92(0.88-0.96)

86.19

0.86(0.85-0.86)

79.36(5.08)

mob(AAT|~.) without age, male only)

0.78(0.71-0.85)

75.93

0.82(0.81-0.83)

75.33(5.15)

mob(GP73|~.) without age, male only)

0.83(0.76-0.89)

76.47

0.86(0.85-0.86)

77.81(4.16)

mob(AFP|~.) without age, male only)

0.80(0.74-0.86)

72.72

0.83(0.82-0.84)

76.54(5.42)

mob(Kin|~.) without age, male only)

0.88(0.83-0.93)

85.03

0.86(0.85-0.87)

78.88(4.92)

mob(AAT|~.) with age, gender)

0.87(0.83-0.92)

82.57

0.86(0.78-0.94)

81.19(4.59)

mob(GP73|~.) with age, gender)

0.93(0.89-0.96)

87.50

0.91(0.90-0.91)

84.61(4.03)

mob(AFP|~.) with age, gender)

0.90(0.86-0.94)

83.33

0.89(0.88-0.89)

82.95(4.42)

mob(Kin|~.) with age, gender)

0.89(0.85-0.93)

83.33

0.89(0.88-0.89)

82.81(4.14)

mob(AAT|~.) without age, gender)

0.84(0.79-0.89)

84.46

0.87(0.86-0.87)

80.93(3.71)

mob(GP73|~.) without age, gender)

0.91(0.87-0.94)

83.33

0.89(0.88-0.89)

81.22(4.35)

mob(AFP|~.) without age, gender)

0.87(0.82-0.91)

82.95

0.87(0.87-0.87)

80.60(3.73)

mob(Kin|~.) without age, gender)

0.88(0.84-0.92)

84.85

0.89(0.89-0.90)

83.05(3.97)

  1. 1. Method utilized for analysis, stepPLR stepwise penalized logistic regression with or without age and/or gender, mob model-based CART, classification and regression trees developed with or without age and/or gender; 2) LOOCV AUC, leave one out cross validation area under the curve; 3) LOOCV ACC, leave one out cross validation prediction accuracy; 4) 3CV AUC, three fold cross validation area under the curve; 5) 3CV ACC, three fold cross validation prediction accuracy.
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BMC Medical Genomics

ISSN: 1755-8794

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