Table 2.

Performance of nomograms from the setting of primary surgery (learning cohort, n = 75)

Nomograms	AUC	Standard error	pa	95% CI of AUC
MSKCC	0.82	0.05	<0.001	0.72–0.92
MDA	0.71	0.06	0.002	0.60–0.83
Mayo	0.71	0.06	0.002	0.60–0.83
Cambridge	0.72	0.06	0.001	0.61–0.84
Tenon	0.75	0.06	<0.001	0.63–0.86
Stanford	0.71	0.06	0.002	0.59–0.82
SENTINAb	0.83	0.05	<0.001	0.74–0.92
Meta nomogram	0.84	0.05	<0.001	0.74–0.93
Full model	0.85	0.04	<0.001	0.76–0.93

^aTesting each nomogram against an AUC of 0.5 (Null hypothesis).

^bIn addition, the SENTINA nomogram was validated in the validation subset (n = 168) with an AUC of 0.83 (95% CI 0.76–0.89, p < 0.001).

AUC = Area under the curve; CI = confidence interval.