title: What is an ROC curve?
abstract: The paper by Bodyet alis concerned with the evaluation of decision aids, which can be used to identify potential acute coronary syndromes (ACS) in the ED. The authors previously developed the Manchester Acute Coronary Syndromes model (MACS) decision aid, which uses several clinical variables and two biomarkers to 'rule in' and 'rule out' ACS. However, one of the two biomarkers (heart-type fatty acid bindingprotein, H-FABP) is not widely used so a revised decision aid has been developed (Troponin-only Manchester Acute Coronary Syndromes, T-MACS), which include a single biomarker hs-cTnT. In this issue, the authors show how they derive a revised decision aid and describe its performance in a number of independent diagnostic cohort studies. Decision aids (as well as other types of 'diagnostic tests') are often evaluated in terms of diagnostic testing parameters such as the area under the receiver operating characteristic (ROC) curve, sensitivity and specificity. In this article, we explain how the ROC analysis is conducted and why it is an essential step towards developing a test with the desirable levels of sensitivity and specificity.
authors.affiliation: School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK.|Sheffield Adult CF Centre, Northern General Hospital, Sheffield, UK.
authors.forename: Zhe Hui
authors.identifier: http://orcid.org/0000-0002-7067-3783
authors.initials: ZH
authors.lastname: Hoo
authors.affiliation: School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK.
authors.forename: Jane
authors.initials: J
authors.lastname: Candlish
authors.affiliation: School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK.
authors.forename: Dawn
authors.initials: D
authors.lastname: Teare
mesh_terms: D003627:Data Interpretation, Statistical; D003661:Decision Support Techniques; D004636:Emergency Service, Hospital / Q000458:organization & administration; D006801:Humans; D012372:ROC Curve; D012680:Sensitivity and Specificity
keywords: ROC curve; diagnostic accuracy