Table 5.
Predictive accuracy of risk classification and EDNRB and combination after adjusting for other predictors1 associated with head and neck cancer (n=161)
| Predictor | Cutoff2 | Sensitivity (%, 95% CI) | Specificity (%, 95% CI) | PPV3 (%, 95% CI) | NPV4 (%, 95% CI) | AUC (95% CI) |
|---|---|---|---|---|---|---|
| Risk classification | 0.267590 | 71(56 – 83) | 58(48 – 67) | 41 (31 – 53) | 77 (66 – 86) | 0.65(0.56 – 0.75) |
| EDNRB | 0.274459 | 65(49 – 78) | 51(42 – 61) | 36 (26 – 47) | 82 (72 – 90) | 0.61 (0.51 – 0.71) |
| Risk and EDNRB | 0.2467921 | 75(60 – 86) | 50(41 – 60) | 39 (29 – 50) | 83 (72 – 91) | 0.68(0.58 – 0.77) |
| combined | 0.4501881 | 21 (10 – 35) | 92(85 – 96) | 53 (29 – 76) | 73 (65 – 80) |
Other predictors include age, sex, race, tobacco, and ethanol use;
Based on predicted probability of high grade dysplasia/cancerusing multivariable logistic regression model;
Positive predictive value, depending on the prevalence of the disease (high grade dysplasia/cancer) which was 13% for this study population.
Negative predictive value, depending on the prevalence of the disease (high grade dysplasia/cancer) which was 13% for this study population.
Note: The cutoffs are not EDNRB methylation values but a predicted probability from the logistic regression model that simultaneously includes risk classification and EDNRB.