Table 4.

The metrics of the prediction models using all the features (variables) for predicting the primary outcome

	AUROC	Sensitivity	Specificity	PPV	NPV	Accuracy	Brier
Cox	80.18%	0.34	0.94	0.72	0.76	0.75	0.167
LR-L1	80.37%	0.44	0.91	0.69	0.78	0.76	0.162
LR-L2	80.29%	0.44	0.91	0.69	0.78	0.76	0.162
Ensemble	81.23%	0.42	0.92	0.71	0.78	0.76	0.161
NeuralNet	80.45%	0.45	0.90	0.68	0.78	0.76	0.165
RF	78.84%	0.51	0.86	0.63	0.79	0.75	0.177
XgBoost	80.49%	0.46	0.91	0.69	0.78	0.76	0.161

A threshold of 0.5 is used.

AUROC, area under receiver operator curve; NPV, negative predictive value; PPV, positive predictive value.