# model1
fit_RSF1_1 <- rfsrc(Surv(tcen,CVD)~SBP+FBG+TC+HDL, data = data_train, ntree=50)
predict_RSF1 <- predict(fit_RSF1_1, data_train)
predict_RSF_sur1 <- predict_RSF1$survival
sur_cen1 <- predict_RSF_sur1[, ncol(predict_RSF_sur1)]
haz_cen1 <- 1-sur_cen1

result1 <- roc(data_train$CVD,as.numeric(haz_cen1),plot=F,smooth = F)
ci1_min<- ci(data_train$CVD,haz_cen1)[1]
ci1_max<- ci(data_train$CVD,haz_cen1)[3]
aucera11<- auc(data_train$CVD,haz_cen1)

Youden_index1<- result1$sensitivities + result1$specificities - 1
cut_off1 <- result1$thresholds[which.max(Youden_index1)]
sen1 <- result1$sensitivities[which.max(Youden_index1)]
spe1<- result1$specificities[which.max(Youden_index1)]
oe1 <- sum(data_train$CVD)/sum(haz_cen1)