The sufficient cause framework has been used for decades to improve our understanding of both basic and more complex causal concepts in epidemiology, such as mediation and interaction. Here, we make use of this framework to provide a description of truncation by death, in which the outcome of interest is undefined for individuals who die before the time of assessment at the end of follow-up. We explain the non-causal nature of the crude estimand that compares outcomes by treatment levels conditional on observed survival by showing that it corresponds to a comparison of distinct risk status types, which are defined based on the susceptibility to sufficient causes. Further, expressions for the crude estimand and for the survivor average causal effect, a causal estimand defined under the principal stratification approach, are provided in terms of population-level joint frequencies of the background factors of sufficient causes. Finally, we also describe conditions, based on background factors of sufficient causes, under which the survivor average causal effect is null. Our description of this problem, which studies truncation by death from a new perspective, might encourage further analyses of principal stratification-based estimands using sufficient causes.

翻译：充分因框架已被用于改进对流行病学中基本及更复杂因果概念（如中介效应和交互作用）的理解达数十年。本文利用该框架对死亡截断现象进行描述，其中感兴趣的结果变量对随访结束前死亡的个体而言无法定义。通过指出粗估计量（基于观察存活状况按治疗水平比较结局）对应于不同类型风险状态的比较（这些状态根据对充分因的易感性定义），我们阐明了该估计量的非因果本质。进一步，本文基于充分因背景因素的人群联合频率，给出了粗估计量和幸存者平均因果效应（主分层方法下定义的因果估计量）的表达式。最后，我们还基于充分因的背景因素描述了幸存者平均因果效应为零的条件。本文从新视角研究死亡截断问题，可能促进利用充分因对基于主分层的估计量进行进一步分析。