Target Trial Emulation Applications in Hypertension Research: A scoping Review
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Objectives
Target Trial Emulation (TTE) has emerged as a rigorous framework for causal inference using observational data, but its application in hypertension research remains underexplored. This scoping review aims to map current TTE applications, identify methodological strengths and weaknesses, and propose future directions in hypertension research.
Study Design and Setting
We performed a scoping review following the Joanna Briggs Institute (JBI) guidance and the PRISMA extension for Scoping Reviews (PRISMA-ScR) checklist. We searched multiple databases, and three independent reviewers conducted screening and extraction using Covidence review management software. Of 1,157 articles identified, 14 met the inclusion criteria.
Results
Most studies used data from electronic health records, claims databases, and registries. Common confounding adjustment methods included inverse probability weighting and the g-formula, complemented by regression-based models. However, time-varying confounders were inconsistently addressed, and loss to follow-up was often managed through simple censoring rather than statistical methods. Residual confounding remained a concern—although several studies acknowledged unobserved confounders, only a few employed negative controls or e-values to assess their impact. While subgroup analyses were common, explicit heterogeneous treatment effect (HTE) estimation was limited. Advanced causal machine learning techniques for bias mitigation or HTE detection were not reported.
Conclusion
TTE shows strong potential to complement randomized controlled trials in hypertension research by providing more generalizable insights. While still in its early stages, current studies highlight its ability to address key challenges such as HTE, long-term outcomes, and dynamic treatment strategies.
