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药物效应观察性研究中的不朽时间偏倚。

Immortal time bias in observational studies of drug effects.

作者信息

Suissa Samy

机构信息

McGill Pharmacoepidemiology Research Unit, McGill University Health Centre, Montreal, Canada.

出版信息

Pharmacoepidemiol Drug Saf. 2007 Mar;16(3):241-9. doi: 10.1002/pds.1357.

Abstract

PURPOSE

Recent observational studies suggest that various drugs are remarkably effective at reducing morbidity and mortality. These cohort studies used a flawed approach to design and data analysis which can lead to immortal time bias. We describe the bias from 20 of these studies and illustrate it by showing that unrelated drugs can be made to appear effective at treating cardiovascular disease (CVD).

METHODS

The illustration used a cohort of 3315 patients, with chronic obstructive pulmonary disease (COPD), identified from the Saskatchewan Health databases, hospitalised for CVD and followed for up to a year. We used the biased approach to assess the effect of two medications, namely gastrointestinal drugs (GID) and inhaled beta-agonists (IBA), both unknown to be effective in CVD, on the risk of all-cause mortality. We also estimated these effects using the proper person-time approach.

RESULTS

Using the inappropriate approach, the rates ratios of all-cause death were 0.73 (95%CI: 0.57-0.93), with IBA and 0.78 (95%CI: 0.61-0.99), with GID. These rate ratios became 0.98 (95%CI: 0.77-1.25) and 0.94 (95%CI: 0.73-1.20), respectively, with the proper person-time analysis.

CONCLUSIONS

Several recent observational studies used a flawed approach to design and data analysis, leading to immortal time bias, which can generate an illusion of treatment effectiveness. Observational studies, with surprising beneficial drug effects should be re-assessed to account for this source of bias.

摘要

目的

近期的观察性研究表明,各种药物在降低发病率和死亡率方面具有显著效果。这些队列研究在设计和数据分析上采用了有缺陷的方法,可能导致不朽时间偏倚。我们描述了其中20项研究中的这种偏倚,并通过表明不相关的药物可以显示出对心血管疾病(CVD)有效的方式来加以说明。

方法

该例证使用了从萨斯喀彻温省健康数据库中识别出的3315例患有慢性阻塞性肺疾病(COPD)且因心血管疾病住院并随访长达一年的患者队列。我们采用有偏倚的方法来评估两种药物,即胃肠道药物(GID)和吸入性β受体激动剂(IBA)(两者均未知对心血管疾病有效)对全因死亡率风险的影响。我们还使用适当的人时方法估计了这些影响。

结果

采用不恰当的方法时,IBA的全因死亡发生率比值为0.73(95%置信区间:0.57 - 0.93),GID为0.78(95%置信区间:0.61 - 0.99)。通过适当的人时分析,这些发生率比值分别变为0.98(95%置信区间:0.77 - 1.25)和0.94(95%置信区间:0.73 - 1.20)。

结论

近期的几项观察性研究在设计和数据分析上采用了有缺陷的方法,导致不朽时间偏倚,这可能产生治疗有效性的错觉。对于具有令人惊讶的有益药物效果的观察性研究,应重新评估以考虑这种偏倚来源。

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