Target Trial Emulation for Non-Pharmaceutical Interventions: Methodological Challenges and Solutions
摘要
Target trial emulation is a methodological framework designed to emulate hypothetical randomized controlled trials using observational data, particularly when conducting actual trials is unethical or infeasible. Non-pharmaceutical interventions, such as dietary patterns, physical activity, and environmental exposures, require unique methodological considerations for target trial emulation compared to pharmaceutical interventions. In this review, we aim to familiarize researchers with the key methodological challenges involved in emulating target trials of non-pharmaceutical interventions and to offer evidence-based recommendations for addressing these challenges.
Recent FindingsWe outline the fundamental assumptions necessary for valid causal inference when emulating a target trial: consistency, exchangeability, and positivity. We examine why these assumptions are particularly challenging to uphold for non-pharmaceutical interventions compared to pharmaceutical exposures. Next, we review recent work on non-pharmaceutical interventions studied using target trial emulation and highlight five methodological challenges that threaten the validity of causal assumptions: ill-defined interventions, intervention heterogeneity, uncommon or infeasible strategies, unclear time zero, and periodic measurement with sustained adherence assumptions. We map each challenge to specific components of the target trial protocol. To demonstrate how these challenges manifest in practice, we present a case study of maternal dairy intake and risk of child allergies and conclude with practical recommendations for mitigating each challenge.
SummaryThe framework and strategies outlined in this review will enable researchers to rigorously apply target trial emulation to non-pharmaceutical interventions, shifting the focus from documenting associations to estimating causal effects and strengthening the role of observational research in guiding evidence-based population health research.