Target trial emulation under nonmutually exclusive assignment: structural pitfalls and methodological remedies

Traditional epidemiologic designs typically assume that the exposed and unexposed groups are mutually exclusive, forming the foundation for causal inference. Target trial emulation (TTE), an increasingly adopted framework for estimating causal effects from observational data, may not always require this assumption. Although often applied in settings with nonmutually exclusive treatment assignment, the implications of such structures for causal estimation are underexplored. In real-world contexts, patients may receive combination or single-agent treatments, or neither, leading to ambiguous group distinctions that challenge effect validity. We conducted a simulation study evaluating multiple TTE implementation strategies under nonmutually exclusive treatment assignment. Treatment overlap and covariate alignment were systematically varied to assess how emulation strategies perform under violations of mutual exclusivity. Our results show that nonmutually exclusive assignment can introduce substantial bias unless treatment overlap and positivity are explicitly addressed during propensity score estimation and outcome modeling. Notably, when covariate overlap is sufficient, nonmutually exclusive assignment can recover marginal effects with performance comparable to or exceeding mutually exclusive assignment. However, when overlap is poor, even advanced strategies fail to recover the true marginal effect. These findings underscore the importance of aligning study design, estimand, and treatment-assignment structure when applying TTE in real-world settings.