Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, Food and Drug Administration, Rockville, MD 20852, USA.
Pharmacoepidemiol Drug Saf. 2013 Aug;22(8):819-25. doi: 10.1002/pds.3451. Epub 2013 Apr 29.
The assumption that the occurrence of outcome event must not alter subsequent exposure probability is critical for preserving the validity of the self-controlled case series (SCCS) method. This assumption is violated in scenarios in which the event constitutes a contraindication for exposure. In this simulation study, we compared the performance of the standard SCCS approach and two alternative approaches when the event-independent exposure assumption was violated.
Using the 2009 H1N1 and seasonal influenza vaccines and Guillain-Barré syndrome as a model, we simulated a scenario in which an individual may encounter multiple unordered exposures and each exposure may be contraindicated by the occurrence of outcome event. The degree of contraindication was varied at 0%, 50%, and 100%. The first alternative approach used only cases occurring after exposure with follow-up time starting from exposure. The second used a pseudo-likelihood method.
When the event-independent exposure assumption was satisfied, the standard SCCS approach produced nearly unbiased relative incidence estimates. When this assumption was partially or completely violated, two alternative SCCS approaches could be used. While the post-exposure cases only approach could handle only one exposure, the pseudo-likelihood approach was able to correct bias for both exposures.
Violation of the event-independent exposure assumption leads to an overestimation of relative incidence which could be corrected by alternative SCCS approaches. In multiple exposure situations, the pseudo-likelihood approach is optimal; the post-exposure cases only approach is limited in handling a second exposure and may introduce additional bias, thus should be used with caution.
假定结果事件的发生不能改变后续暴露的概率，这对于保持自我对照病例系列（SCCS）方法的有效性至关重要。在结果事件构成暴露禁忌的情况下，这一假设就会被违反。在这项模拟研究中，当事件独立暴露假设被违反时，我们比较了标准 SCCS 方法和两种替代方法的性能。
我们使用 2009 年 H1N1 和季节性流感疫苗和格林-巴利综合征作为模型，模拟了一种个体可能遇到多次无序暴露的情况，并且每次暴露都可能因结果事件的发生而被禁忌。禁忌的程度分别为 0%、50%和 100%。第一种替代方法仅使用在暴露后发生的病例，随访时间从暴露开始。第二种方法使用了伪似然法。
当事件独立暴露假设得到满足时，标准 SCCS 方法产生了几乎无偏的相对发病率估计。当这一假设部分或完全被违反时，可以使用两种替代的 SCCS 方法。虽然仅在暴露后发生的病例方法只能处理一次暴露，但伪似然法能够纠正两种暴露的偏倚。
违反事件独立暴露假设会导致相对发病率的高估，这种高估可以通过替代的 SCCS 方法来纠正。在多次暴露的情况下，伪似然法是最优的；仅在暴露后发生的病例方法在处理第二次暴露时受到限制，并且可能引入额外的偏倚，因此应谨慎使用。
