A step-by-step algorithm for combining diagnostic tests

Abstract

Combining data of several tests or markers for the classification of patients according to their health status for assigning better treatments is a major issue in the study of diseases such as cancer. In order to tackle this problem, several approaches have been proposed in the literature. In this paper, a step-by-step algorithm for estimating the parameters of a linear classifier that combines several measures is considered. The optimization criterion is to maximize the area under the receiver operating characteristic curve. The algorithm is applied to different simulated data sets and its performance is evaluated. Finally, the method is illustrated with a prostate cancer staging database.

Keywords:

• diagnostic tests
• step-by-step algorithm
• linear model
• classification accuracy
• receiver operating characteristic curve

Acknowledgements

The authors thank the referees for their valuable comments and suggestions which have greatly improved the presentation of the paper. We also gratefully acknowledge the financial support from the MEC project MTM2007-63769. G. Sanz and L.M. Esteban are members of the research group Modelos Estocásticos (D.G.A.).