HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (3) Citing Articles via Google Scholar Google Scholar Articles by Keller, T. Articles by Jung, K. Search for Related Content PubMed PubMed Citation Articles by Keller, T. Articles by Jung, K. Related Collections Laboratory Management Evidence Based Laboratory Medicine and Test Utilization

Discordance Analysis Characteristics as a New Method to Compare the Diagnostic Accuracy of Tests: Example of Complexed Versus Total Prostate-Specific Antigen

¹ ACOMED Statistik, Leipzig, Germany.
² Bayer Vital GmbH, Leverkusen, Germany.
³ Department of Urology, University Hospital Charité, Humboldt University Berlin, Berlin, Germany.
⁴ Department of Urology, Kantonsspital Aarau, Aarau, Switzerland.
⁵ Department of Urology, University Hospital Münster, Münster, Germany.
⁶ Department of Urology, University of Duisburg-Essen, Essen, Germany.
⁷ Department of Urology, Städtisches Klinikum Braunschweig, Braunschweig, Germany.

^aAddress correspondence to this author at: Department of Urology, University Hospital Charité, Humboldt University Berlin, Schumannstrasse 20/21, D-10098 Berlin, Germany. Fax 49-30-450-515904; e-mail klaus.jung{at}charite.de.

Background: ROC curve analysis is used to compare the overall diagnostic accuracy of tests, but its application to subgroups selected by a concentration range of only one marker may show severe biases. We developed a new approach, which we have named discordance analysis characteristics (DAC).

Methods: The DAC method is based on a generalization of the McNemar test so that for a given pair of cutoff values only those patients are analyzed who are categorized differently by the two tests compared. The analyses are performed for all cutoff pairs that deliver identical sensitivities for both tests. We used data for total (tPSA) and complexed prostate-specific antigen (cPSA) from a recently published multicenter study to demonstrate the DAC method.

Results: The example shows that ROC analyses of subgroups can give contradictory results about the diagnostic accuracy of two markers, depending on the marker used for the selection of subgroups. The DAC method avoids artifacts attributable to questionable selection of subgroups and facilitates overall and local comparisons of the diagnostic accuracy of tests. The DAC results of the analyzed data set suggest that cPSA has higher diagnostic accuracy than does tPSA.

Conclusions: The DAC method is a suitable tool for comparing the clinical usefulness of laboratory markers. The DAC method could be considered as an additional tool to ROC analysis and could replace comparative ROC analyses of diagnostic tests, especially within subgroups defined by only one of the markers.

The following articles in journals at HighWire Press have cited this article:

				C. M. Sturgeon, M. J. Duffy, U.-H. Stenman, H. Lilja, N. Brunner, D. W. Chan, R. Babaian, R. C. Bast Jr., B. Dowell, F. J. Esteva, et al. National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines for Use of Tumor Markers in Testicular, Prostate, Colorectal, Breast, and Ovarian Cancers Clin. Chem., December 1, 2008; 54(12): e11 - e79. [Abstract] [Full Text] [PDF]

eLetters: