Table 3.
Performance Metrics of Predictive Classification Models During Testing
| Model | AUCa (95% CI) | Sensitivity | Specificity | BAC |
|---|---|---|---|---|
| Discovery stage | ||||
| N3SMOTE → N3ORIGINAL | 0.69 (0.63–0.75) | 0.65 | 0.68 | 0.66 |
| N3SMOTE → N3SMOTE | 0.85 (0.82–0.87) | 0.76 | 0.80 | 0.78 |
| Validation stage | ||||
| N3SMOTE→ N2ORIGINAL | 0.66 (0.60–0.72) | 0.64 | 0.59 | 0.62 |
| N3SMOTE → N2SMOTE | 0.86 (0.84–0.89) | 0.84 | 0.59 | 0.72 |
Primary validation step of interest is bolded.
aAUC = area under the curve; BAC = balanced accuracy; CI = confidence interval; N2 = NAPLS2/North American Prodrome Longitudinal Study-2; N3 = NAPLS3/North American Prodrome Longitudinal Study-3; SMOTE = synthetic minority oversampling technique.