  Background: Immortal time is a period of follow-up during which death or the
study outcome cannot occur by design. Bias from immortal time has been
increasingly recognized in epidemiologic studies. However, the fundamental
causes and structures of bias from immortal time have not been explained
systematically using a structural approach. Methods: We use an example "Do
Nobel Prize winners live longer than less recognized scientists?" for
illustration. We illustrate how immortal time arises and present the structures
of bias from immortal time using time-varying directed acyclic graphs (DAGs).
We further explore the structures of bias with the exclusion of immortal time
and with the presence of competing risks. We discuss how these structures are
shared by different study designs in pharmacoepidemiology and provide
solutions, where possible, to address the bias. Results: We illustrate that
immortal time arises from using postbaseline information to define exposure or
eligibility. We use time-varying DAGs to explain the structures of bias from
immortal time are confounding by survival until exposure allocation or
selection bias from selecting on survival until eligibility. We explain that
excluding immortal time from the follow-up does not fully address this
confounding or selection bias, and that the presence of competing risks can
worsen the bias. Bias from immortal time may be avoided by aligning time zero,
exposure allocation and eligibility, and by excluding individuals with prior
exposure. Conclusions: Understanding bias from immortal time in terms of
confounding or selection bias helps researchers identify and thereby avoid or
ameliorate this bias.
