Published Online First: 25 September 2008. doi:10.1136/jcp.2008.061010
Journal of Clinical Pathology 2009;
62:1-5
Copyright © 2009 by the BMJ Publishing Group Ltd & Association of Clinical Pathologists.
LEADING ARTICLE
Receiver-operating characteristic curve analysis in diagnostic, prognostic and predictive biomarker research
Kjetil Søreide
Kjetil Søreide, Department of Surgery, Stavanger University Hospital, P O Box 8100, Armauer Hansens vei 20, N-4068 Stavanger, Norway; ksoreide@mac.com
Accepted 24 August 2008
| The first 150 words of the full text of this article appear below. |
Take-home messages
- Biomarkers serve various clinical functions including diagnosis, prediction and prognosis of disease.
- Biomarker accuracy, including sensitivity and specificity, relies on the chosen discriminatory cut-off on a continuous test scale.
- Receiver operating characteristic (ROC) curve analysis provides an objective statistical method to assess the diagnostic accuracy of a test with a continuous outcome by graphically displaying the trade-offs of the true-positive rate (sensitivity) and false-positive rate (1-specificity).
- ROC analysis is integral to modern biomarker research, as recommended in the REMARK guidelines.
- Clinical vigilance is needed when applying ROC analysis for biomarkers for a time-to-event study.
From a clinical perspective, biomarkers may have a variety of functions, which correspond to different stages (table 1) in disease development, such as in the progression in cancer or cardiovascular disease.1 2 Biomarkers can assist in the care of patients who are asymptomatic (screening biomarkers), those who are suspected to have the disease (diagnostic biomarkers) . . . [Full text of this article]
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