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Activity Number: 414 - Advances in Estimation Methods
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 2:00 PM to 3:50 PM
Sponsor: SSC
Abstract #327155 Presentation
Title: A G-Formula Estimator for Performing Causal Mediation Analysis with Survival Outcomes: Investigating the Relationship Between Statins, Cholesterol and Cardiovascular Diseases
Author(s): Denis Talbot* and Joseph A Delaney and Veit Sandfort and David M Herrington and Robyn L McClelland
Companies: Universite Laval and University of Washington School of Public Health and National Institutes of Health and Heart and Vascular Center of Excellence and University of Washington School of Public Health
Keywords: Biostatistics; Causal Inference; Mediation Analysis; Survival Analysis

Statin drugs were initially developed for reducing blood cholesterol as a mean of improving cardiovascular health. However, there is biological evidence that statin treatment yields cardiovascular benefits via other pathways. We developed a semi-parametric g-formula estimator for performing a causal mediation analysis between statin use, cholesterol and cardiovascular events. The analysis was performed on data from the Multi-Ethnic Study of Atherosclerosis, a multi-center population-based prospective cohort study. Our g-formula estimator directly accommodates censored time-to-event outcomes, provides estimates on risk difference and relative risk reduction scales that are easy to interpret and requires relatively few parametric assumptions. We performed a simulation study to investigate the empirical properties of this estimator under four scenarios and modest sample size: 1) ideal circumstances, 2) no indirect effect, 3) mildly misspecified models and 4) lack of adherence for some participants. Small bias and well-calibrated confidence intervals were obtained under all scenarios considered.

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

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