Target trial emulation: bridging observational studies and randomized trials for health decision-making

Randomized controlled trials (RCTs) are the gold standard generating evidence owing to their rigorous methodology. However, their logistical, financial and ethical limitations highlight the need for alternative approaches using real-world data. Target trial emulation (TTE) applies RCT design principles to estimate causal effects when trials are infeasible. TTE involves three steps: formulating a precise causal research question, explicitly specifying the protocol of the target trial, and rigorously replicating each component of the target trial, such as the eligibility criteria, treatment assignment and follow-up period, using available observational data. Statistical methods commonly used include propensity score matching, inverse probability weighting, G-methods and/or instrumental variables to address confounding and align observational data with the target trial design. Nonetheless, residual confounding, missing data and misclassification can bias results. Sensitivity analyses and transparent reporting are recommended. Notably, TTE frameworks utilizing continuously updated registry data enable 'living protocols' that can be iteratively refined as new data accumulate, representing an important evolution toward prospective-retrospective hybrid designs that maintain causal clarity while addressing emerging clinical questions. Though valuable, TTE complements rather than replaces RCTs, as both inform causal inference and clinical decisions.