Wallis Christopher J D, Saskin Refik, Narod Steven A, Law Calvin, Kulkarni Girish S, Seth Arun, Nam Robert K
Division of Urology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.
BJU Int. 2017 Oct;120(4):584-590. doi: 10.1111/bju.13918. Epub 2017 Jun 18.
To quantify the effect of immortal-time bias in an observational study examining the effect of cumulative testosterone exposure on mortality.
We used a population-based matched cohort study of men aged ≥66 years, newly treated with testosterone-replacement therapy (TRT), and matched-controls from 2007 to 2012 in Ontario, Canada to quantify the effects of immortal-time bias. We used generalised estimating equations to determine the association between cumulative TRT exposure and mortality. Results produced by models using time-fixed and time-varying exposures were compared. Further, we undertook a systematic review of PubMed to identify studies addressing immortal-time bias or time-varying exposures in the urological literature and qualitatively summated these.
Among 10 311 TRT-exposed men and 28 029 controls, the use of a time-varying exposure resulted in the attenuation of treatment effects compared with an analysis that did not account for immortal-time bias. While both analyses showed a decreased risk of death for patients in the highest tertile of TRT exposure, the effect was overestimated when using a time-fixed analysis (adjusted hazard ratio [aHR] 0.56, 95% confidence interval [CI]: 0.52-0.61) when compared to a time-varying analysis (aHR 0.67, 95% CI: 0.62-0.73). Of the 1 241 studies employing survival analysis identified in the literature, nine manuscripts met criteria for inclusion. Of these, five used a time-varying analytical method. Each of these was a large, population-based retrospective cohort study assessing potential harms of pharmacological agents.
Where exposures vary over time, a time-varying exposure is necessary to draw meaningful conclusions. Failure to use a time-varying analysis will result in overestimation of a beneficial effect. However, time-varying exposures are uncommonly utilised among manuscripts published in prominent urological journals.
在一项观察性研究中，量化永生时间偏倚对累积睾酮暴露与死亡率关系研究结果的影响。
我们采用了一项基于人群的匹配队列研究，研究对象为2007年至2012年在加拿大安大略省开始接受睾酮替代疗法（TRT）治疗的66岁及以上男性以及匹配对照，以量化永生时间偏倚的影响。我们使用广义估计方程来确定累积TRT暴露与死亡率之间的关联。比较了使用固定时间暴露和随时间变化暴露的模型所产生的结果。此外，我们对PubMed进行了系统综述，以识别泌尿外科文献中涉及永生时间偏倚或随时间变化暴露的研究，并对这些研究进行定性总结。
在10311名接受TRT治疗的男性和28029名对照中，与未考虑永生时间偏倚的分析相比，使用随时间变化的暴露会导致治疗效果减弱。虽然两种分析均显示TRT暴露处于最高三分位数的患者死亡风险降低，但与随时间变化的分析（调整后风险比[aHR]0.67，95%置信区间[CI]：0.62 - 0.73）相比，使用固定时间分析时效果被高估（aHR 0.56，95% CI：0.52 - 0.61）。在文献中确定的1241项采用生存分析的研究中，有9篇手稿符合纳入标准。其中，5篇使用了随时间变化的分析方法。这些研究均为大型的、基于人群的回顾性队列研究，评估了药物制剂的潜在危害。
当暴露随时间变化时，需要采用随时间变化的暴露分析来得出有意义的结论。未使用随时间变化的分析将导致对有益效果的高估。然而，在著名泌尿外科杂志发表的手稿中，随时间变化的暴露分析很少被采用。
