Table 3.
Cohort | Models | AUC (95%CI) | ACC | SEN | SPE | NPV | PPV |
---|---|---|---|---|---|---|---|
Training set | Clinical model | 0.837 (0.754, 0.920) | 0.801 | 0.714 | 0.846 | 0.846 | 0.714 |
Radiomics score | 0.875 (0.797, 0.952) | 0.830 | 0.889 | 0.808 | 0.952 | 0.632 | |
Radiomics nomogram | 0.923 (0.869, 0.977) | 0.877 | 0.741 | 0.918 | 0.905 | 0.769 | |
Validation set | Clinical model | 0.857 (0.741, 0.973) | 0.721 | 1.000 | 0.657 | 1.000 | 0.400 |
Radiomics score | 0.786 (0.592, 0.979) | 0.837 | 0.625 | 0.886 | 0.912 | 0.556 | |
Radiomics nomogram | 0.914 (0.827, 0.998) | 0.839 | 1.000 | 0.771 | 1.000 | 0.500 |
AUC, area under curve; ACC, accuracy; SEN, sensitivity; SPE, specificity; PPV, positive predictive value, NPV, negative predictive value.