ROC curve analysis: an example showing the relationships among serum lipid and apolipoprotein concentrations in identifying patients with coronary artery disease.
Clinical accuracy, defined as the ability to discriminate between states of health, is the fundamental property of any diagnostic test or system. It is readily expressed as clinical sensitivity and specificity, and elegantly represented by the receiver operating characteristic (ROC) curve. To demonstrate the use of ROC curves, we reexamine a study of the ability of serum lipid and apolipoprotein measures to discriminate among degrees of coronary artery disease in patients undergoing coronary angiography. ROC curve analysis reveals that none of these indexes is highly accurate, but demonstrates a modest increase in the accuracy of apolipoprotein over lipid indexes.
Zweig
M H
MH
Clinical Pathology Department, Warren G. Magnuson Clinical Center, National Institutes of Health, Bethesda, MD 20892.
Broste
S K
SK
Reinhart
R A
RA
D001053:Apolipoproteins / Q000097:blood*; D002784:Cholesterol / Q000097:blood; D008076:Cholesterol, HDL / Q000097:blood; D008078:Cholesterol, LDL / Q000097:blood; D017023:Coronary Angiography; D003327:Coronary Disease / Q000097:blood* / Q000000981:diagnostic imaging; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D008055:Lipids / Q000097:blood*; D008297:Male; D011786:Quality Control; D012372:ROC Curve
D001053:Apolipoproteins; D008076:Cholesterol, HDL; D008078:Cholesterol, LDL; D008055:Lipids; D002784:Cholesterol