Table 5.

Summary of performance metrics for all the predictive models and comparisons between models

Metrics	Manual selection		LDA		P-value*
	Model 1 (clinical + radiomic features)	Model 2 (clinical + radiomic + genomic features)	Model 1 (clinical + radiomic features)	Model 2 (clinical + radiomic + genomic features)
AIC	35.697	27.309	34.816	27.451
AUC	0.598	0.757	0.891	0.904
Sensitivity	69.6%	95.2%	91.3%	100.0%
Specificity	50.0%	50%	70.0%	80.0%
Balanced accuracy	59.8%	72.6%	80.7%	90.0%
Accuracy	63.6%	80.6%	84.9%	93.9%
Comparisons
Manual selection vs LDA (model 1)					0.6344
Manual selection vs LDA (model 2)					0.2242
Model 1 vs Model 2 (manual selection)					0.2815
Model 1 vs Model 2 (LDA)					0.8305

^*DeLong test of ROC curve of models.

AIC, Akaike Information Criterion; AUC, Area Under the Curve; LDA, Linear Discriminant Analysis.