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Activity Number: 428
Type: Contributed
Date/Time: Wednesday, August 9, 2006 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #307495
Title: Evaluating the Predictiveness of a Continuous Marker in Case-Control Design
Author(s): Ying Huang*+ and Margaret S. Pepe
Companies: University of Washington and Fred Hutchinson Cancer Research Center/University of Washington
Address: 13614 NE 11th Street, Bellevue, WA, 98005,
Keywords: predictiveness curve ; ROC ; case-control ; monotone likelihood ratio
Abstract:

To describe the predictive capacity of a continuous biomarker, Pepe and Huang (2006) proposed "predictiveness curve", defined as a plot of risk versus the distribution function of the marker, and proposed estimating a monotone increasing predictiveness curve using a flexible parametric model for cohort data. However, case-control studies are most often performed in the early phases of biomarker development. In this report, we show the relationship between predictiveness curve and ROC curve given disease prevalence. Two strategies for estimating the monotone increasing predictiveness curve are proposed. The first one is to model the monotone likelihood ratio of biomarker. And the second one is to estimate a generalized predictiveness curve, defined as a plot of risk versus its distribution function. Semi-parametric likelihood approach is used for estimating the distribution of risk.

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