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Table 3 Class Prediction Model Results.

From: Proteomic profiling of urine for the detection of colon cancer

Dataset

Sensitivity

Specificity

Misclassification Rate

AUROC

MALDI

65 (52–78)

84 (75–93)

24

0.80

MALDI-DS

68 (55–80)

68 (57–79)

32

0.67

SELDI

51 (38–64)

75 (64–86)

34

0.69

ALL

78 (66–90)

87 (78–96)

17

0.88

  1. Table 3 summarises the logistic regression models tested by leave-one-out cross-validation. Sensitivity, specificity and misclassification rate are presented as percentages (95% confidence intervals). The m/z values of the peaks used in the logistic regressions are, MALDI: 1606, 2254, 5011, MALDI-DS: 2193, SELDI: 1885 and 11960, ALL: 1606, 2251, 4758, 5011. Number of samples in each dataset: MALDI: 123 (55 cancer), MALDI-DS: 119 (53 cancer), SELDI: 116 (55 cancer).