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何时应使用病例对照设计来监测医疗产品的安全性?

When should case-only designs be used for safety monitoring of medical products?

机构信息

Department Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, BC, Canada.

出版信息

Pharmacoepidemiol Drug Saf. 2012 Jan;21 Suppl 1:50-61. doi: 10.1002/pds.2330.

Abstract

PURPOSE

To assess case-only designs for surveillance with administrative databases.

METHODS

We reviewed literature on two designs that are observational analogs to crossover experiments: the self-controlled case series (SCCS) and the case-crossover (CCO) design.

RESULTS

SCCS views the 'experiment' prospectively, comparing outcome risks in windows with different exposures. CCO retrospectively compares exposure frequencies in case and control windows. The main strength of case-only designs is they entail self-controlled analyses that eliminate confounding and selection bias by time-invariant characteristics not recorded in healthcare databases. They also protect privacy and are computationally efficient, as they require fewer subjects and variables. They are better than cohort designs for investigating transient effects of accurately recorded preventive agents, for example, vaccines. They are problematic if timing of self-administration is sporadic and dissociated from dispensing times, for example, analgesics. They tend to have less exposure misclassification bias and time-varying confounding if exposures are brief. Standard SCCS designs are bidirectional (using time both before and after the first exposure event), so they are more susceptible than CCOs to reverse-causality bias, including immortal-time bias. This is true also for sequence symmetry analysis, a simplified SCCS. Unidirectional CCOs use only time before the outcome, so they are less affected by reverse causality but susceptible to exposure-trend bias. Modifications of SCCS and CCO partially deal with these biases. The head-to-head comparison of multiple products helps to control residual biases.

CONCLUSION

The case-only analyses of intermittent users complement the cohort analyses of prolonged users because their different biases compensate for one another.

摘要

目的

评估基于行政数据库的监测病例对照设计。

方法

我们综述了两种与交叉试验类似的观察性设计的文献:自身对照病例系列(SCCS)和病例交叉(CCO)设计。

结果

SCCS 前瞻性地观察“实验”,比较不同暴露窗口的结果风险。CCO 回顾性地比较病例和对照窗口中的暴露频率。病例对照设计的主要优势在于它们进行了自我对照分析,通过时间不变的特征消除了混杂和选择偏倚,这些特征在医疗保健数据库中没有记录。它们还保护隐私,计算效率高,因为它们需要更少的受试者和变量。与队列设计相比,它们更适合研究准确记录的预防性药物(例如疫苗)的短暂效应。如果自我给药的时间是零星的,并且与配药时间无关(例如镇痛药),则存在问题。如果暴露时间很短,它们往往具有更少的暴露分类偏倚和随时间变化的混杂。标准的 SCCS 设计是双向的(使用第一次暴露事件前后的时间),因此它们比 CCO 更容易受到反向因果关系偏差的影响,包括不朽时间偏差。序列对称分析,一种简化的 SCCS,也是如此。单向 CCO 仅使用结果发生之前的时间,因此受反向因果关系的影响较小,但易受暴露趋势偏差的影响。SCCS 和 CCO 的修改部分解决了这些偏差。对多种产品的头对头比较有助于控制残留偏差。

结论

间歇性使用者的病例对照分析补充了长期使用者的队列分析,因为它们的不同偏倚可以相互补偿。

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