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Optimal linear combinations of multiple diagnostic biomarkers based on Youden index
Author(s) -
Yin Jingjing,
Tian Lili
Publication year - 2013
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6046
Subject(s) - youden's j statistic , computer science , receiver operating characteristic , set (abstract data type) , score , index (typography) , statistics , mathematics , algorithm , data mining , world wide web , programming language
In practice, usually multiple biomarkers are measured on the same subject for disease diagnosis. Combining these biomarkers into a single score could improve diagnostic accuracy. Many researchers have addressed the problem of finding the optimal linear combination based on maximizing the area under ROC curve ( AUC ). Actually, such combined score might have less than optimal property at the diagnostic threshold. In this paper, we propose the idea of using Youden index as an objective function for searching the optimal linear combination. The combined score directly achieves the maximum overall correct classification rate at the diagnostic threshold corresponding to Youden index; in other words, it is the optimal linear combination score for making the disease diagnosis. We present both empirical and numerical searching methods for the optimal linear combination. We carry out extensive simulation study to investigate the performance of the proposed methods. Additionally, we empirically compare the optimal overall classification rates between the proposed combination based on Youden index and the traditional one based on AUC and demonstrate a significant gain in diagnostic accuracy for the proposed combination. In the end, we apply the proposed methods to a real data set. Copyright © 2013 John Wiley & Sons, Ltd.