Simulation Using Target Trial Emulation For Causal Analysis With Applications to RCT Data for AVM

Music City Center 

Target trial emulations are a two-step procedure to help  articulate the causal relationship between a treatment and some health outcome.  A notable limitation is the lack of true randomization and the confounding from noncomparable groups.  However, the closer the baseline data matches a true randomization from homogenous population from potential trial participants, the closer the simulated results should reflect results from an RCT.  This study explores how trial target emulation approach with clinical trial data differs from Individual patient data meta-analysis meta-analysis under settings with increasing heterogenous patient populations.  In this analysis we demonstrate how each approach performs with respect to bias and variability of true treatment affect under various simulated settings which mimic an ideal setting (perfectly harmonized trials) to examples where trials were performed with incomplete or incorrectly applied randomization, which can happen in a poorly run trial.   We explore this in a simulated setting and then apply the methods to a real data of two large trails exploring similar treatments were conducted in order to estimate the true treatment effect.

Simulation

RCT

Causality

Target Trial 

Section on Statistical Computing