A NEW APPROACH TO CAUSAL INFERENCE IN MORTALITY STUDIES WITH A SUSTAINED EXPOSURE PERIOD - APPLICATION TO CONTROL OF THE HEALTHY WORKER SURVIVOR EFFECT
A NEW APPROACH TO CAUSAL INFERENCE IN MORTALITY STUDIES WITH A SUSTAINED EXPOSURE PERIOD - APPLICATION TO CONTROL OF THE HEALTHY WORKER SURVIVOR EFFECT
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DOI：
10.1016/0270-0255(86)90088-6
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发表时间：
1986-01-01
期刊：
影响因子：
--
通讯作者：
ROBINS, J
中科院分区：
文献类型：
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作者：
ROBINS, J
在长期暴露于研究药物的观察性队列死亡率研究中，死亡风险因素成为后续暴露的决定因素并不罕见。例如，在职业死亡率研究中，终止就业的日期既是未来接触的决定因素（因为被终止就业的个人不再接触），也是死亡的独立风险因素（因为残疾人往往离开就业）。当当前的风险因素状态决定了随后的暴露，并由先前的暴露决定时，将年龄特异性死亡率估计为累积暴露函数的标准分析可能会低估暴露对死亡率的真实影响，无论是否在分析中调整风险因素。这一观察结果提出了一个问题，如果有任何人口参数可以在观察性死亡率研究中给出因果解释？在回答中，我们提供了一个图形的方法来识别和计算的因果参数的死亡率研究与持续暴露期。这种方法被证明是等同于一种方法，其中观察性研究是通过假设的双盲随机试验确定的，其中每例受试者分配的治疗方案的数据已从数据文件中删除。因果关系的推断，然后可以通过比较死亡率作为一个功能的治疗protocol，因为，在一个双盲随机试验中的治疗方案缺失的数据，死亡率与治疗protocol的关联仍然可以估计，我们重新分析了一个队列的砷暴露的铜冶炼厂工人的死亡率经验与我们的方法，并比较我们的结果与使用标准方法获得的。我们发现砷暴露对全因死亡率和肺癌死亡率的不利影响，标准方法无法检测到。
In observational cohort mortality studies with prolonged periods of exposure to the agent under study, it is not uncommon for risk factors for death to be determinants of subsequent exposure. For instance, in occupational mortality studies date of termination of employment is both a determinant of future exposure (since terminated individuals receive no further exposure) and an independent risk factor for death (since disabled individuals tend to leave employment). When current risk factor status determines subsequent exposure and is determined by previous exposure, standard analyses that estimate age-specific mortality rates as a function of cumulative exposure may underestimate the true effect of exposure on mortality whether or not one adjusts for the risk factor in the analysis. This observation raises the question, which if any population parameters can be given a causal interpretation in observational mortality studies?In answer, we offer a graphical approach to the identification and computation of causal parameters in mortality studies with sustained exposure periods. This approach is shown to be equivalent to an approach in which the observational study is identified with a hypothetical double-blind randomized trial in which data on each subject's assigned treatment protocol has been erased from the data file. Causal inferences can then be made by comparing mortality as a function of treatment protocol, since, in a double-blind randomized trial missing data on treatment protocol, the association of mortality with treatment protocol can still be estimated.We reanalyze the mortality experience of a cohort of arsenic-exposed copper smelter workers with our method and compare our results with those obtained using standard methods. We find an adverse effect of arsenic exposure on all-cause and lung cancer mortality which standard methods fail to detect.