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I am not sure whether my question is due to fundamental misunderstanding, but does it make sense to estimate a confidence interval (through bootstrap, DeLong, ...) on the value of a cutpoint obtained from the ROC curve?

Can one estimate and calculate a confidence interval for the value of a cutpoint obtained from the ROC curve?

How to modify the example code in order to specify the best cutpoint to be not youden, but topleft?

rocobj <- plot.roc(aSAH$outcome, 
                   aSAH$s100b,  
                   main="Confidence intervals", 
                   percent=TRUE,  ci=TRUE, print.auc=TRUE) 
# print the AUC (will contain the CI)  
ciobj <- ci.se(rocobj, 
               specificities=seq(0, 100, 5)) 
plot(ciobj, type="shape", col="#1c61b6AA")
plot(ci(rocobj, of="thresholds", thresholds="best")) 

I realised how to specify the best cutpoint to be not youden, but topleft?

rocobj <- plot.roc(aSAH$outcome, 
                   aSAH$s100b,  
                   main="Confidence intervals", 
                   percent=TRUE,  ci=TRUE, print.auc=TRUE) 
# print the AUC (will contain the CI)  
ciobj <- ci.se(rocobj, 
               specificities=seq(0, 100, 5)) 
plot(ciobj, type="shape", col="#1c61b6AA")
plot(ci(rocobj, of="thresholds", thresholds="best", best.method="topleft")) 

UPDATE

How to modify the example code in order to specify the best cutpoint to be not youden, but topleft?

rocobj <- plot.roc(aSAH$outcome, 
                   aSAH$s100b,  
                   main="Confidence intervals", 
                   percent=TRUE,  ci=TRUE, print.auc=TRUE) 
# print the AUC (will contain the CI)  
ciobj <- ci.se(rocobj, 
               specificities=seq(0, 100, 5)) 
plot(ciobj, type="shape", col="#1c61b6AA")
plot(ci(rocobj, of="thresholds", thresholds="best"))