Table 1.

Summary of predictive accuracy estimates for five models of interest. Lasso-Cox1: censoring weights are estimated from a Cox PH model using the selected variables based on a Lasso-Coxph model. Lasso-Cox2: censoring weights are estimated directly from a Lasso-Cox model.

Model	${\widehat{c}}_s^2(SD)$	${\widehat{c}}_g^2(SD)$	${\widehat{c}}_s^2(SD)$	${\widehat{c}}_g^2(SD)$	${\widehat{c}}_s^2(SD)$	${\widehat{c}}_g^2(SD)$
	tQ25=16(month)		tQ75=68(month)		tMAX=164(month)
	Lasso-Cox1
Model I	0.599(0.053)	0.599(0.054)	0.587(0.049)	0.590(0.052)	0.588(0.050)	0.589(0.056)
Model II	0.561(0.097)	0.561(0.097)	0.540(0.068)	0.541(0.068)	0.539(0.065)	0.543(0.068)
Model III	0.723(0.072)	0.723(0.071)	0.705(0.056)	0.707(0.057)	0.704(0.055)	0.710(0.058)
Model IV	0.683(0.070)	0.680(0.071)	0.666(0.055)	0.672(0.057)	0.666(0.054)	0.668(0.059)
Model V	0.670(0.075)	0.665(0.076)	0.638(0.058)	0.638(0.060)	0.641(0.057)	0.638(0.061)
	Lasso-Cox2
Model I	0.599(0.053)	0.577(0.103)	0.587(0.049)	0.545(0.084)	0.588(0.050)	0.546(0.084)
Model II	0.561(0.097)	0.550(0.124)	0.540(0.068)	0.528(0.098)	0.539(0.065)	0.528(0.098)
Model III	0.723(0.072)	0.726(0.095)	0.705(0.056)	0.715(0.081)	0.704(0.055)	0.715(0.081)
Model IV	0.683(0.070)	0.669(0.101)	0.666(0.055)	0.663(0.080)	0.666(0.054)	0.663(0.080)
Model V	0.670(0.075)	0.600(0.116)	0.638(0.058)	0.579(0.089)	0.641(0.057)	0.580(0.088)

Model I: only PSA and Gleason;

Model II: PSA, Gleason and biomarkers 2,4,8,11,14,16,22,31,46,52,63 based on Long et al. (2011);

Model III: PSA, Gleason and biomarkers 2,3,5,6,7,13,15,26,32,43,56,83 from all 1536 biomarkers;

Model IV: PSA, Gleason and biomarkers 2,5,6,7,10,13,15 from the top 25 biomarkers;

Model V: PSA, Gleason and biomarkers 2,5,6,7,10 from the top 10 biomarkers;