Table 3.

Performance of the GARSL and ERASL models for prediction of early recurrence

Method	Feature type	Training set (n = 362)		Test set (n = 155)
		AUC	C-index (SE)	AUC	C-index (SE)	p value
GARSL	Preclinical	0.863	0.790 (0.016)	0.679	0.647 (0.034)	<0.001*
GARSL	Radiomics	0.740	0.518 (0.023)	0.566	0.533 (0.035)	<0.001*
GARSL	Preoperative	0.781	0.738 (0.018)	0.739	0.695 (0.032)	REF
GARSL	Postoperative	0.767	0.723 (0.019)	0.741	0.710 (0.031)	<0.001*
ERASL-pre	Preoperative	0.667	0.659 (0.021)	0.687	0.672 (0.017)	<0.001*
ERASL-post	Postoperative	0.672	0.656 (0.022)	0.688	0.666 (0.018)	<0.001†

C-index, concordance index; AUC, area under the receiver operating characteristic curve; SE, standard error; ERASL, early recurrence after surgery for liver tumor; GARSL, genetic algorithm for predicting recurrence after surgery of liver cancer.

^*p value compared to the GARSL preoperative score. † p value compared to the GARSL postoperative score.