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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Statistics in Medici...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Statistics in Medicine
Article . 2003 . Peer-reviewed
License: Wiley Online Library User Agreement
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Group sequential design for comparative diagnostic accuracy studies

Authors: Madhu, Mazumdar; Aiyi, Liu;

Group sequential design for comparative diagnostic accuracy studies

Abstract

AbstractIn the field of diagnostic medicine, comparative clinical trials are necessary for assessing the utility of one diagnostic test over another. The area under the receiver operating characteristic (ROC) curve, commonly referred to as AUC, is a general measure of a test's inherent ability to distinguish between patients with and without a condition. Standardized AUC difference is the most frequently used statistic for comparing two diagnostic tests. In therapeutic comparative clinical trials with sequential patient entry, fixed sample design (FSD) is unjustified on ethical and economical grounds and group sequential design (GSD) is frequently used. In this paper, we argue that the same reasoning exists for the comparative clinical trials in diagnostic medicine and hence GSD should be utilized in this field for designing trials. Since computation of the stopping boundaries of GSD and data analysis after a group sequential test rely heavily on Brownian motion approximation, we derive the asymptotic distribution of the standardized AUC difference statistic and point out its resemblance to the Brownian motion. Boundary determination and sample size calculation are then illustrated through an example from a cancer clinical trial. Copyright © 2003 John Wiley & Sons, Ltd.

Related Organizations
Keywords

Diagnostic Imaging, Research Design, Area Under Curve, Liver Neoplasms, Humans, Controlled Clinical Trials as Topic, Monte Carlo Method

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    37
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    Top 10%
    influence
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citations
The total number of citations received by all articles of the researcher of interest.
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
37
Top 10%
Top 10%
Average
Related to Research communities
Cancer Research
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