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, it remains unclear how immortal time arises and what the structures of bias from immortal time are. Here, we use an example "Do Nobel Prize winners live longer than less recognized scientists?" to illustrate that immortal time arises from using postbaseline information to define exposure or eligibility. We use time-varying directed acyclic graphs (DAGs) to present the structures of bias from immortal time as the key sources of bias, that is confounding and selection bias. We explain that excluding immortal time from the follow-up does not fully address the bias, and that the presence of competing risks can worsen the bias. We also discuss how the structures of bias from immortal time are shared by different study designs in pharmacoepidemiology and provide solutions, where possible, to address the bias.

翻译：永生时间是指随访期间内，因研究设计原因无法发生死亡或研究结局的一段时期。永生时间偏倚在流行病学研究中的受关注度日益增加。然而，永生时间如何产生及其偏倚结构仍不明确。本文以"诺贝尔奖得主是否比未获同等认可的科学家更长寿"为例，阐明永生时间源于使用基线后信息定义暴露或合格标准。我们采用时变有向无环图呈现永生时间偏倚作为关键偏倚来源的结构，即混杂偏倚和选择偏倚。研究指出，仅从随访中排除永生时间并不能完全消除偏倚，且竞争风险的存在会加剧该偏倚。同时探讨不同药物流行病学研究设计中共通的永生时间偏倚结构，并尽可能提供消除此类偏倚的解决方案。