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Activity Number: 216 - Promises and Pitfalls of Making Decisions with Real World Data
Type: Invited
Date/Time: Monday, July 29, 2019 : 2:00 PM to 3:50 PM
Sponsor: ENAR
Abstract #300212 Presentation
Title: A Decision Theoretic Approach to Pre-Emptive Genotyping
Author(s): Jonathan Schildcrout*
Companies: Vanderbilt University Medical Center
Keywords: risk prediction; decision theory; electronic medical records; survival analysis; discrete event simulation

We discuss a decision-theoretic approach to building a panel-based, pre-emptive genotyping program. Pre-emptive genotyping permits seamless genotype guided therapy when such medications are prescribed, and panel-based testing allows providers to reuse previously collected genetic data when a new indication arises. Because it is cost-prohibitive to conduct panel-based genotyping on all patients, we describe a three-step approach identifies patients with the highest expected benefit. This approach first seeks to estimate risk of being put on medications with pharmacogenetic effects by constructing risk prediction models using readily available clinical data. It then uses literature-based estimates of adverse event rates, variant allele frequencies, secular death rates, and costs to construct a discrete event simulation that estimates the expected benefit of having an individuals’ genetic data in the electronic health record after an indication has occurred. Finally, it combines medication prescription risk with expected benefit of genotyping once a medication is indicated to calculate the expected benefit of pre-emptive genotyping.

Authors who are presenting talks have a * after their name.

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