Table 2.

Performance and Comparison of DLR, DLP, DLP-manual and DLRP for distinguish between luminal and non-luminal breast cancers at early stages.

models	AUC	Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)
DLR model
Training set (n = 489)	0.909 (0.879, 0.933)	0.895 (0.862, 0.923)	0.763 (0.634, 0.864)	0.965 (0.942, 0.981)	0.500 (0.392, 0.608)
Validation set (n = 114)	0.830 (0.748, 0.894)	0.770 (0.675, 0.848)	0.786 (0.492, 0.953)	0.962 (0.894, 0.992)	0.324 (0.174, 0.505)
Test set (n = 90)	0.815a (0.719, 0.889)	0.878 (0.782, 0.943)	0.500 (0.247, 0.753)	0.890 (0.795, 0.951)	0.471 (0.230, 0.722)
DLP model
Training set (n = 489)	0.882 (0.850, 0.909)	0.730 (0.686, 0.772)	0.915 (0.813, 0.972)	0.984 (0.964, 0.995)	0.318 (0.248, 0.394)
Validation set (n = 114)	0.827 (0.745, 0.892)	0.660 (0.558, 0.752)	0.857 (0.572, 0.982)	0.971 (0.898, 0.996)	0.261 (0.143, 0.411)
Test set (n = 90)	0.802b,d (0.704, 0.878)	0.419 (0.305, 0.539)	0.875 (0.617, 0.984)	0.939 (0.798, 0.993)	0.246 (0.141, 0.378)
DLP-manual model
Training set (n = 489)	0.889 (0.857, 0.915)	0.754 (0.710, 0.794)	0.881 (0.771, 0.951)	0.979 (0.957, 0.991)	0.329 (0.257, 0.408)
Validation set (n = 114)	0.872 (0.797, 0.927)	0.660 (0.558, 0.752)	0.929 (0.661, 0.998)	0.985 (0.920, 1.000)	0.277 (0.156, 0.426)
Test set (n = 90)	0.834c (0.740, 0.904)	0.405 (0.293, 0.526)	0.937 (0.698, 0.998)	0.968 (0.833, 0.999)	0.254 (0.150, 0.384)
DLRP model
Training set (n = 489)	0.975 (0.956, 0.987)	0.907 (0.875, 0.933)	1.000 (0.939, 1.000)	1.000 (0.991, 1.000)	0.596 (0.493, 0.693)
Validation set (n = 114)	0.929 (0.865, 0.968)	0.940 (0.874, 0.978)	0.643 (0.351, 0.872)	0.949 (0.886, 0.984)	0.600 (0.323, 0.837)
Test set (n = 90)	0.900 (0.819, 0.953)	0.892 (0.798, 0.952)	0.812 (0.544, 0.960)	0.957 (0.878, 0.991)	0.619 (0.384, 0.819)

Note: data in parentheses are 95% confidence intervals. DLR, deep learning radiomics; DLP, deep learning pathomics; DLP-manual, deep learning pathomics trained on manually annotated WSI; DLRP, deep learning radiopathomics; AUC, area under the receiver operating characteristic curve; PPV, positive predictive value; NPV, Negative predictive value.

^aIndicates P = 0.027, Delong et al. in comparison with DLRP model in independent test set.

^bIndicates P = 0.013, Delong et al. in comparison with DLRP model in independent test set.

^cIndicates P = 0.023, Delong et al. in comparison with DLRP model in independent test set.

^dIndicates P = 0.352, Delong et al. in comparison with DLP-manual model in independent test set.