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Activity Number: 73
Type: Contributed
Date/Time: Sunday, August 2, 2009 : 4:00 PM to 5:50 PM
Sponsor: Section on Risk Analysis
Abstract - #304945
Title: Comparison of Methods to Predict Radiation Dose
Author(s): Sally W. Thurston*+ and Jacqueline P. Williams
Companies: University of Rochester and University of Rochester
Address: 601 Elmwood Ave. # 630, Rochester, NY, 14642,
Keywords: CART ; misclassification ; prediction ; principal components ; radiation
Abstract:

In the event of a terrorist attack involving radiation, it will be important to be able to estimate radiation dose among potentially exposed individuals. Irradiation is known to increase expression of certain cytokines (protein markers) in blood, where exposure profiles over time differ across cytokines. Our goal is to estimate dose received based on measurements of 10 cytokines, when time since irradiation is known precisely or imprecisely. We compare three methods: linear regression, principal components, and classification and regression trees (CART). For each method, we use the parameter estimates or CART classification rules as estimated from one data set to predict dose in two data sets not used in fitting the models. The methods are compared using data from mice exposed to different radiation doses, with cytokines measured at one of four time points after irradiation.

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