The perpetual need of randomized clinical trials: challenges and uncertainties in emulating the REDUCE-AMI trial.

Abstract

Trial emulations in observational data analyses can complement findings from randomized clinical trials, inform future trial designs, or generate evidence when randomized studies are not feasible due to resource constraints and ethical or practical limitations. Importantly, trial emulation designs facilitate causal inference in observational data analyses by enhancing counterfactual thinking and comparisons of real-world observations (e.g. Mendelian Randomization) to hypothetical interventions. In order to enhance credibility, trial emulations would benefit from prospective registration, publication of statistical analysis plans, and subsequent prospective benchmarking to randomized clinical trials prior to their publication. Confounding by indication, however, is the key challenge to interpreting observed intended effects of an intervention as causal in observational data analyses. We discuss the target trial emulation of the REDUCE-AMI randomized clinical trial (ClinicalTrials.gov ID NCT03278509; beta-blocker use in patients with preserved left ventricular ejection fraction after myocardial infarction) to illustrate the challenges and uncertainties of studying intended effects of interventions without randomization to account for confounding. We furthermore directly compare the findings, statistical power, and clinical interpretation of the results of the REDUCE-AMI target trial emulation to those from the simultaneously published randomized clinical trial. The complexity and subtlety of confounding by indication when studying intended effects of interventions can generally only be addressed by randomization.