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Immortal Time Bias in Pharmacoepidemiology

机译:药物流行病学中的不朽时间偏差

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摘要

Immortal time is a span of cohort follow-up during which, because of exposure definition, the outcome under study could not occur. Bias from immortal time was first identified in the 1970s in epidemiology in the context of cohort studies of the survival benefit of heart transplantation. It recently resurfaced in pharmacoepidemiology, with several observational studies reporting that various medications can be extremely effective at reducing morbidity and mortality. These studies, while using different cohort designs, all involved some form of immortal time and the corresponding bias. In this paper, the author describes various cohort study designs leading to this bias, quantifies its magnitude under different survival distributions, and illustrates it by using data from a cohort of lung cancer patients. The author shows that for time-based, event-based, and exposure-based cohort definitions, the bias in the rate ratio resulting from misclassified or excluded immortal time increases proportionately to the duration of immortal time. The bias is more pronounced with a decreasing hazard function for the outcome event, as illustrated with the Weibull distribution compared with a constant hazard from the exponential distribution. In conclusion, observational studies of drug benefit in which computerized databases are used must be designed and analyzed properly to avoid immortal time bias.
机译:不朽时间是整个队列的随访时间,在此期间,由于暴露的定义,所研究的结果不会发生。在1970年代流行病学中,从对心脏移植的生存获益的队列研究中首次发现了不朽时代的偏见。它最近在药物流行病学中浮出水面,一些观察性研究报告说,各种药物在降低发病率和死亡率方面可以非常有效。这些研究在使用不同的队列设计时,都涉及某种形式的不朽时间和相应的偏见。在本文中,作者描述了导致这种偏倚的各种队列研究设计,在不同的生存分布下量化了其幅度,并使用来自肺癌患者队列的数据对其进行了说明。作者表明,对于基于时间,基于事件和基于暴露的队列定义,因错误分类或排除的不朽时间而导致的比率比率偏差与不朽时间的长短成正比增加。对于结果事件,偏倚随着危害函数的降低而更加明显,如威布尔分布所示,而指数分布的恒定危害则与之相似。总之,必须适当设计和分析使用计算机数据库的药物获益观察性研究,以避免不朽的时间偏差。

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  • 来源
    《American Journal of Epidemiology》 |2008年第4期|p.492-499|共8页
  • 作者

    Samy Suissa;

  • 作者单位

    From the Department of Epidemiology and Biostatistics, and Department of Medicine, McGill University, Montreal, Canada;

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