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

Area of Science:

• Epidemiology
• Biostatistics
• Health Research Methods

Background:

• Randomized controlled trials (RCTs) are the gold standard for evidence generation but face logistical, financial, and ethical challenges.
• Real-world data offers an alternative, but requires rigorous methods to ensure causal inference.
• Target trial emulation (TTE) bridges this gap by applying RCT principles to observational data.

Purpose of the Study:

• To describe the methodology of Target Trial Emulation (TTE) as an alternative to RCTs.
• To highlight the steps and statistical approaches involved in TTE.
• To discuss the limitations and advancements in TTE for causal inference.

Main Methods:

• TTE involves formulating a precise causal question, defining a target RCT protocol, and replicating it with observational data.
• Statistical methods like propensity score matching, inverse probability weighting, G-methods, and instrumental variables are used to address confounding.
• Sensitivity analyses and transparent reporting are crucial for validating TTE results.

Main Results:

• TTE enables causal effect estimation when RCTs are infeasible, using real-world data.
• Continuously updated registry data facilitates 'living protocols' for iterative refinement.
• TTE represents an evolution towards hybrid prospective-retrospective designs.

Conclusions:

• Target trial emulation is a valuable tool for causal inference, complementing RCTs.
• It offers a rigorous approach to utilizing real-world data for research.
• TTE maintains causal clarity while addressing evolving clinical questions.