Advantage Of ROC Curve Analysis And Optimal Cut Off Valuie

Question 1

First advantage of ROC curve analysis?

Answer 1

in contrast to single measures of sensitivity and specificity, the diagnostic accuracy, such as AUC driven from this analysis is not affected by decision criterion and it is also independent of prevalence of disease since it is based on sensitivity and specificity.

Question 2

Second advantge of ROC curve?

Answer 2

several diagnostic tasks on the same subjects can be compared simultaneously in a ROC space and the methods also developed to consider the covariance between two correlated ROC curve.

useita diagnostisia tehtäviä samoista aiheista voidaan verrata samanaikaisesti ROC-tilassa, ja menetelmät on myös kehitetty kahden korreloivan ROC-käyrän välisen kovarianssin huomioon ottamiseksi.

Question 3

Third advantage of ROC

Answer 3

one can easily obtain=get the sensitivity at specific FPF by visualizing the curve.

Question 4

Forth advantage?

Answer 4

the optimal cut- off value can be determined (päättää, set on) using ROC curve analysis

Question 5

determining optimal cut off values, at least three methods have been proposed. What is the
first?

Answer 5

The two methods give equal weight to sensitivity and specificity with no ethical, cost and prevalence constraints (7). The first method uses the square of distance between the point (0, 1) on the upper left hand corner of ROC space and any point on ROC curve ie. d2= (1-TPF)2+ FPF2=(1-sensetivity)2+ (1-specificty)2. In order to obtain the optimal cut off points, the square of this distance is minimized. In other words, one can calculate this distance for each cut off point in order to find the optimal cut- off value.

Optimaalisten rajapisteiden saamiseksi tämän etäisyyden neliö minimoidaan. Toisin sanoen tämä etäisyys voidaan laskea jokaiselle rajapisteelle optimaalisen raja-arvon löytämiseksi.

Question 6

determining optimal cut off values, at least three methods have been proposed. What is the second?

Answer 6

called Youden index uses the maximum of vertical distance of ROC curve from the point (x, y) on diagonal line (chance line). In fact, Youden index maximizes the difference between TPF (sensitivity) and FPF (1-sepicificity): Youden Index=TPF-FPF= Sensitivity+ Specificity -1. Thus, by maximizing Sen + Spec aross various cut-off points, the optimal cut- off point is calculated

Question 7

determining optimal cut off values, at least three methods have been proposed. What is the third?

Answer 7

incorporates the financial costs for correct and false diagnosis and the costs of further work up for diagnosis. In fact, the consequence of each possible test outcome is ascertained to their costs and combining ROC analysis with utility-based decision theory can be used to determine the optimal cut point (26). For example, given a disease with low prevalence and high cost of false positive diagnosis, the cut-point may be chosen at higher value to maximize specificity while for a disease occurring at high prevalence and missing diagnosis has a serious fatal consequences, a lower cut-point value would be selected to maximize sensitivity.