The search for markers as potential prognostic factors for different stages of disease is becoming a major task in clinical research. Enormous amounts of information on the effectiveness of tumor markers are being published, and many of these results are conflicting and thus adding confusion to the area. In this paper we discuss the problem of multiplicity that we believe is one of the major statistical reasons for the conflicting results. We further review the ROC curve and the area under it as a popular statistical tool for evaluating the ability of a marker to distinguish between two populations. Finally we provide an extension to the ROC analysis when several markers are available. (C) 2000 Elsevier Science Inc.
|Number of pages||3|
|Journal||Urologic Oncology: Seminars and Original Investigations|
|State||Published - Sep 2000|
- ROC analysis
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