Nonparametric comparison of entire ROC curves for computerized ECG left ventricular hypertrophy algorithms using data...

A computer program may be capable of several different statements for left ventricular hypertrophy (eg, possible LVH, probable LVH, consistent with LVH), but such statements resulting from discretized levels of sensitivity/specificity would represent only isolated points on a receiver-operating characteristic (ROC) curve, which is a plot of all levels of sensitivity versus specificity. Even if two algorithms use the same discrete scales, their performances may not readily be compared. The authors present a comparison methodology for ROC curves using ROC area as a nonparametric measure of the ability of the algorithm to separate the two populations; the ROC area ranges from 0.5 (no ability) to 1.0 (perfect separation) and is unbiased if the normal versus abnormal populations have no common values for the measurement. The methodology compares the performance of ECG algorithms on the same population of cases by testing for significant differences of ROC areas and incorporating correlation of the algorithms in a nonparametric way. To illustrate this methodology, they use ECG and echocardiographic data from the Framingham Heart Study.