Abstract #300479

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JSM 2003 Abstract #300479
Activity Number: 372
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #300479
Title: Quantifying and Comparing the Predictive Accuracy of Prognostic Factors for a Failure Time Outcome
Author(s): Chaya S. Moskowitz*+ and Margaret S. Pepe
Companies: Memorial Sloan-Kettering Cancer Center and University of Washington
Address: Dept. of Epidemiology and Biostatistics, New York, NY, 10021-7701,
Keywords: marginal regression models ; positive predictive values ; prediction ; survival analysis
Abstract:

Ee discuss evaluating the predictive accuracy of one or more prognostic factors that may be used to make a prognosis. In the medical field, for example, an oncologist might have knowledge about two cancer biomarkers that each result in different five-year predicted probabilities of survival for the patient and wish to know which prognosis is the more accurate one. We propose a novel approach to quantifying predictive accuracy that extends the traditional positive and negative predictive values for a binary outcome to the situation when the outcome is a failure time. We will talk about how to use these measures to quantify and test for differences in predictive accuracy. An illustration will be provided where the proposed methodology will be used to quantify and compare the predictive accuracies of a genetic mutation and tumor stage in breast cancer patients.

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