Target Trial Emulation: A Call for More Widespread Use

Abstract Causal inference methods intended for use with observational data have been widely available for decades, but barriers to their widespread adoption exist. These likely include lack of familiarity with several methodological techniques often used in combination in these investigations, such as inverse probability of treatment weighting and g-estimation, and the intensity of computational effort needed to employ these techniques. Even with these methods, critical design flaws undermine the ability to make valid causal inference in some studies. Identification of the need to explicitly pair study design elements with these causal inference methods led to development of a methodological approach recently termed target trial emulation. This approach requires that investigators define a hypothetical randomized trial, emulate that hypothetical protocol in assembling the cohort and defining study elements, and then conduct an analysis that attempts to mirror random treatment assignment. In the accompanying article by Heindel et al (Am J Epidemiol. 2024;XXX(XX):XXX-XXX), the authors successfully emulate a target trial of systemic heparin during arteriovenous fistula creation on short-term endpoints by utilizing data from 2 existing randomized trials with key confounders available. Target trial emulation provides a framework with which to promote valid inference and generate high-quality contributions to the literature, and its use should be expanded.