Introduction to the Target Trial Emulation (TTE) Framework
The TTE framework has gained prominence as a powerful methodological approach for assessing the comparative effectiveness and safety of healthcare interventions using real world data (RWD). The TTE framework is a structured approach that emulates the design and protocol of an ideal hypothetical randomized trial. Conceptualizing an observational study as an attempt to emulate a hypothetical randomized trial offers a structured approach to prevent, reduce or acknowledge the impact of the main biases affecting observational studies, including confounding, selection, and information biases.
Table 1. Biases of observational studies
| Bias | Type | Description | How does TTE help to address it? |
|---|---|---|---|
| Confounding | Data-induced | Spurious associations due to confounders | Identifies baseline and time-varying confounders; applies methods like regression adjustment, propensity scores, and g-computation to account for measured confounding. |
| Selection | Design-induced | Systematic differences in study populations | Ensures synchronization of eligibility, treatment assignment, and time zero; avoids bias through methods such as sequential emulation and cloning. |
| Information | Data-induced | Errors in measurement or missing data | Encourages robust data collection, quality checks, and sensitivity analyses. |
| Modelling | Data-induced | Hazard ratios do not remain constant over time | Modelling Data-induced Hazard ratios do not remain constant over time Consideration of the modelling assumptions of the statistical methods employed in the study; use of survival analysis methods, such as flexible parametric models and non-parametric techniques, can handle time-varying covariates and non-proportional hazards. |
Application of the TTE framework involves three key steps:
- Select fit-for-purpose datasets
- Specify the target trial protocol
- Emulate the target trial protocol with RWD
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