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What is an ROC curve?
  1. Zhe Hui Hoo1,2,
  2. Jane Candlish1,
  3. Dawn Teare1
  1. 1 School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK
  2. 2 Sheffield Adult CF Centre, Northern General Hospital, Sheffield, UK
  1. Correspondence to Dr Zhe Hui Hoo; z.hoo{at}sheffield.ac.uk

Abstract

The paper by Body et al is 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.

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Footnotes

  • Contributors All authors contributed to and approved of the final submitted manuscript.

  • Competing interests None declared.

  • Patient consent This is a concept paper and does not involve patients.

  • Provenance and peer review Not commissioned; internally peer reviewed.

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