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Abstract Details

Activity Number: 618
Type: Contributed
Date/Time: Thursday, August 2, 2012 : 8:30 AM to 10:20 AM
Sponsor: ENAR
Abstract - #306738
Title: The Summary Predictive Curve: A Novel Method for Evaluating Prediction Performance of Biomarkers and Tests
Author(s): Zheng Zhang*+
Companies: Brown University
Address: 121 South Main Street, Providence, RI, 02912, United States
Keywords: Prediction ; Biomarkers ; PPV ; NPV ; AUC ; ROC curve

Almost all the current methods for evaluating prediction performance of biomarkers are extensions of marker's sensitivity, specificity or AUC. But those measures are more suitable for evaluating marker's diagnostic accuracy than predictive accuracy. In that regard, PPV and NPV are better measures, but both are dependent on the disease prevalence. Since a good marker needs to have both high PPV and NPV, a summary measure that incorporates both values are desirable. We define a measure, summary predictive value(SPV), that is less sensitive to prevalence and combines both PPV and NPV to a single value. In addition, we define summary predictive curve by plotting SPV as a function of the positive test threshold. We show the summary predictive curve is capable to distinguish markers with different ability to predict clinical outcomes.

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