Illustrate and describe the Receiver Operator Curve (ROC) and the information gained
For a good answerthe following areas should have been addressed. Diagnostic tests may be
correct or incorrect. The accuracy of a test is assessed by its sensitivity (true positive rate)
and its specificity (true negative rate). The ROC provides a graphical representation of the
trade-off between sensitivity on the y axis and specificity or 1-specificity (false positive rate)
on the x axis. Any increase in sensitivity will be accompanied by a decrease in specificity. It
accounts for an arbitrary cut off level made for a test or comparing two or more diagnostic
tests. A gradient of 1 (area under the curve of 0.5) suggests that the test has no predictive
ability. A steeper gradient has increased area under the curve (ideally > 0.75) and improved
predictive ability. The best point on the curve is dependent on the consequences of a false
positive compared with a false negative of the test and is usually the L elbow of the curve.
The ROC is not affected by changes in prevalence as sensitivity and specificity are not
dependant on prevalence. An illustration of the ROC, with correctly labelled axis and
features was essential to answer this question. Few candidates scored well in this question,
but of those that did they generally achieved a good score. This area is well covered in the
recommended text Statistical Methods for Anaesthesia and Intensive Care by P Myles and T
Gin pages 98 to 99.
As far as college answers go, this is one of the good ones.
Information gained from the ROC curve:
Hanley, James A., and Barbara J. McNeil. "The meaning and use of the area under a receiver operating characteristic (ROC) curve." Radiology 143.1 (1982): 29-36.
Zweig, Mark H., and Gregory Campbell. "Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine." Clinical chemistry 39.4 (1993): 561-577.
Cook, Nancy R. "Use and misuse of the receiver operating characteristic curve in risk prediction." Circulation 115.7 (2007): 928-935.
Jones, Catherine M., and Thanos Athanasiou. "Summary receiver operating characteristic curve analysis techniques in the evaluation of diagnostic tests."The Annals of thoracic surgery 79.1 (2005): 16-20.
Metz, Charles E. "ROC methodology in radiologic imaging." Investigative radiology 21.9 (1986): 720-733.
Søreide, Kjetil. "Receiver-operating characteristic curve analysis in diagnostic, prognostic and predictive biomarker research." Journal of clinical pathology 62.1 (2009): 1-5.
Lusted, Lee B. "ROC recollected." Medical Decision Making (1984): 131-135.