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Activity Number: 246
Type: Contributed
Date/Time: Monday, August 5, 2013 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #309656
Title: Adjusting a Quantitative Trait for Medication Effects When the Medication Received Depends on the Trait
Author(s): Yildiz Yilmaz*+ and Stefan Konigorski and Shelley Bull
Companies: University of Toronto and University of Toronto and University of Toronto
Keywords: Censored regression ; Genetic association ; Likelihood-based method ; Informative censoring ; Observational studies ; Response-dependent
Abstract:

In some observational study settings, the prescription of medication depends on a quantitative trait value. For example, use of antihypertensive medication to lower blood pressure (BP) depends on the individual's pre-treatment BP measure, and in fact, the higher the BP measure, the higher the probability of receiving medication. In genetic association analysis of BP, adjusting BPs for the effect of medication is crucial when the objective is to identify genes associated with variation in BP. A naïve analysis based on modeling BP with the treatment as a covariate leads to biased estimates of genetic effects. We propose a likelihood-based method based on censored regression model, assuming that the true "underlying" BP of a treated individual is higher than the observed. The method does not require an assumption of non-informative censoring, and it allows the medication effect to depend on genetic and non-genetic covariates and the probability of receiving medication to depend on the pre-treatment BP measure and covariates. The results of simulation study suggest that the method outperforms the currently available adjustment methods for medication effects.


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