Target Trial Emulation: A Primer on Improving Observational Research in Neurology

Randomized controlled trials (RCTs) are often considered to be the gold standard for determining treatment effects, but they are often infeasible because of ethical, logistical, or financial constraints. Even when RCTs are possible, they take many years to complete and may not reflect the characteristics or care settings of routine clinical populations. High-quality observational data analyzed rigorously can thus fill important evidence gaps when RCTs are not available. However, analyses of nonrandomized data are susceptible to biases that could have been avoided in a well-designed trial. This review discusses the "target trial" framework to bridge this gap. Target trial emulation involves specifying the protocol for the ideal RCT (i.e., eligibility, interventions, treatment assignment, follow-up, outcomes, and analysis) and then emulating each component using observational data. We describe the concept of target trial emulation, in addition to an overview of the planning and execution of such studies. Although target trial emulation does not overcome data set limitations (e.g., measurement error or residual confounding), it does improve traditional observational analyses in numerous important aspects of study design, such as more precisely defining the research question and avoiding biases related to aligning the start of follow-up with eligibility and treatment assignment. We use examples to familiarize readers with how this methodology can be applied to neurologic conditions.