Table 2.
Performance measures of classifiers in different datasets
| Dataset (origin, method of analysis) | Method | Accuracy (%) | PPV (%) | NPV (%) | Sensitivity (%) | Specificity (%) | Prevalence of FTC in dataset (%) |
|---|---|---|---|---|---|---|---|
| B (own, microarray) |
DLDA classification based on the 8 best genes chosen from 99 preselected ones.* |
80 |
82 |
78 |
76 |
83 |
50 |
| DLDA classification based on 45 (optimal number) best genes chosen from 99 preselected ones.* |
84 |
85 |
83 |
83 |
85 |
50 |
|
|
C (own, FFPE qPCR) |
5-gene DLDA classification (cut-off 0.5)** |
72(95% CI: 60–82) |
67(95% CI: 48–82) |
76(95% CI: 60–89) |
71(95% CI: 52–86) |
72(95% CI: 56–85) |
44 |
| 5-gene DLDA classification (cut-off 0.12)** |
70 |
61 |
88 |
90 |
55 |
44 |
|
| D (own, microarray) |
5-gene DLDA classifier trained on dataset B, tested on D |
73 |
77 |
69 |
71 |
75 |
54 |
| E1 (Weber et al. microarray) |
5-gene DLDA classifier.** |
92 |
100 |
86 |
83 |
100 |
50 |
| E2 (Hinsch et al. microarray) | 5-gene DLDA classifier.** | 83 | 100 | 67 | 75 | 100 | 67 |
Accuracy, proportion of all samples that are correctly classified; PPV, positive predictive value; NPV, negative predictive value; SVM, support vector machines; DLDA, diagonal linear discriminant analysis; CI, confidence interval. *Performance assessed by 10-fold cross-validation. **Performance assessed by leave-one-out cross-validation.