Table 2. DNA hypermethylation markers evaluated as binary marker (positive or negative) based on two statistical approaches (Youden's J index and fixed specificity) with different threshold setting on learning set (A) and subsequent evaluation on validation set (B).
| AUC | 95% CI | Sensitivity (%) | 95% CI (%) | Specificity (%) | 95% CI | P-values | |
|---|---|---|---|---|---|---|---|
|
A. Learning set | |||||||
| Cutoff based on Youden's J index | |||||||
| RASSF1A | 0.69 | 0.60–0.77 | 42.5 | 31.0–54.6 | 96.5 | 90.1–99.3 | <0.001 |
| APC | 0.64 | 0.55–0.73 | 52.1 | 40.0–63.9 | 70.9 | 60.1–80.2 | 0.003 |
| CYGB | 0.65 | 0.56–0.74 | 56.2 | 44.1–67.8 | 74.4 | 63.9–83.2 | <0.001 |
| 3OST2 | 0.72 | 0.64–0.80 | 50.7 | 38.7–62.6 | 86.0 | 76.9–92.6 | <0.001 |
| PRDM14 | 0.71 | 0.63–0.79 | 60.3 | 48.1–71.5 | 76.7 | 66.4–85.2 | <0.001 |
| FAM19A4 | 0.59 | 0.50–0.68 | 86.3 | 76.2–93.2 | 29.1 | 19.8–39.9 | 0.02 |
| PHACTR3 | 0.69 | 0.61–0.77 | 57.5 | 45.4–69.0 | 77.9 | 67.7–86.1 | <0.001 |
| RASSF1A, 3OST2 and PRDM14 | 82.2 | 71.5–90.2 | 66.3 | 55.3–76.1 | <0.001 | ||
| Cutoff based on fixed specificity of >96% in learning set | |||||||
| RASSF1A | 42.5 | 31.0–54.6 | 96.5 | 90.1–99.3 | <0.001 | ||
| APC | 16.4 | 8.8–27.0 | 96.5 | 90.1–99.3 | 0.005 | ||
| CYGB | 19.2 | 10.9–30.1 | 96.5 | 90.1–99.3 | 0.001 | ||
| 3OST2 | 31.5 | 21.1–43.4 | 96.5 | 90.1–99.3 | <0.001 | ||
| PRDM14 | 17.8 | 9.8–28.5 | 96.5 | 90.1–99.3 | 0.003 | ||
| FAM19A4 | 15.1 | 7.8–25.4 | 96.5 | 90.1–99.3 | 0.01 | ||
| PHACTR3 | 28.8 | 18.8–40.6 | 96.5 | 90.1–99.3 | <0.001 | ||
| RASSF1A, 3OST2 and PHACTR3 | 67.1 | 55.1–77.7 | 89.5 | 90.1–99.3 | <0.001 | ||
|
B. Validation set | |||||||
| Cutoff based on Youden's J index | |||||||
| RASSF1A | 0.67 | 0.61–0.73 | 36.5 | 29.0–44.5 | 88.3 | 82.2–92.9 | <0.001 |
| APC | 0.63 | 0.57–0.69 | 52.2 | 44.1–60.2 | 69.5 | 61.676.6 | <0.001 |
| CYGB | 0.64 | 0.58–0.70 | 49.7 | 41.7–57.7 | 68.2 | 60.2–75.4 | 0.001 |
| 3OST2 | 0.71 | 0.65–0.77 | 49.7 | 41.7–57.7 | 85.1 | 78.4–90.3 | <0.001 |
| PRDM14 | 0.75 | 0.69–0.80 | 64.8 | 56.8–72.2 | 74.0 | 66.4–80.8 | <0.001 |
| FAM19A4 | 0.66 | 0.59–0.72 | 77.4 | 70.1–83.6 | 22.1 | 15.8–29.5 | 0.90 |
| PHACTR3 | 0.67 | 0.61–0.73 | 60.4 | 52.3–68.0 | 62.3 | 54.2–70.0 | <0.001 |
| RASSF1A, 3OST2 and PRDM14 | 79.2 | 72.1–85.3 | 64.3 | 56.2–71.8 | <0.001 | ||
| Cutoff based on fixed specificity of >96% in learning set | |||||||
| RASSF1A | 36.5 | 29.0–44.5 | 88.3 | 82.2–92.9 | <0.001 | ||
| APC | 22.0 | 15.8–29.3 | 96.8 | 92.6–98.9 | <0.001 | ||
| CYGB | 19.5 | 13.6–26.5 | 98.1 | 94.4–99.6 | <0.001 | ||
| 3OST2 | 34.0 | 26.6–41.9 | 96.8 | 92.6–98.9 | <0.001 | ||
| PRDM14 | 27.0 | 20.3–34.7 | 96.8 | 92.6–98.9 | <0.001 | ||
| FAM19A4 | 26.4 | 19.7–34.0 | 97.4 | 93.5–99.3 | <0.001 | ||
| PHACTR3 | 25.2 | 18.6–32.6 | 91.6 | 86.0–95.4 | <0.001 | ||
| RASSF1A, 3OST2 and PHACTR3 | 64.8 | 56.8–72.2 | 80.5 | 73.4–86.5 | <0.001 | ||
Abbreviations: AUC=area under the curve; 95% CI=95% confidence intervals.
AUC and 95% CI were calculated for the learning set. Combination rules were defined using multivariate logistic regression. P-values are given for the statistical difference between cases and controls.