Department of Biostatistics and Epidemiology, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, PA, USA.
Department of Neurology, Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA.
Expert Rev Pharmacoecon Outcomes Res. 2021 Aug;21(4):541-551. doi: 10.1080/14737167.2021.1905528. Epub 2021 Apr 29.
Free drug samples are not captured in the pharmacy claims databases used in many pharmacoepidemiologic studies, which could lead to misclassification of drug exposure status and thus bias study results.
We systematically searched the literature in PubMed/MEDLINE, Embase, and Scopus from database inception to August 2020 for studies assessing the magnitude of exposure misclassification in pharmacy claims data associated with uncaptured drug sample utilization. Our review identified five US-based studies with substantially different characteristics, contexts, methods, and results. Taken together, these studies suggest that the risk of sample-related bias may be higher for (1) studies of newly approved, patented brand-only drugs in specific classes and contexts; (2) studies of populations where sample use is common and the unexposed cohort is small; and (3) studies where the outcomes of interest are expected to be early-onset or acute, with non-constant hazards.
In light of declining overall trends in sample use, future research on sample-related exposure misclassification should focus on delineating bias across those modern contexts where sample use remains high and optimizing bias quantification methods to create a more standardized approach. Additionally, further assessment is warranted for other sources of misclassified exposure status in claims-based pharmacoepidemiology research.
在许多药物流行病学研究中使用的药房索赔数据库中,无法捕获免费药物样本,这可能导致药物暴露状态的错误分类,从而偏倚研究结果。
我们系统地在 PubMed/MEDLINE、Embase 和 Scopus 中搜索了从数据库创建到 2020 年 8 月的文献,以评估与未捕获药物样本利用相关的药房索赔数据中暴露错误分类的程度。我们的综述确定了五项具有显著不同特征、背景、方法和结果的基于美国的研究。总的来说,这些研究表明,与未捕获的样本使用相关的偏倚风险可能更高的情况包括:(1)特定类别和背景下新批准的专利品牌药物的研究;(2)样本使用普遍且未暴露队列较小的人群研究;以及(3)感兴趣的结果预计为早期发作或急性发作、风险非恒定的研究。
鉴于整体样本使用趋势的下降,未来关于与样本相关的暴露错误分类的研究应集中在描绘那些样本使用仍然较高的现代背景下的偏差,并优化偏差量化方法,以创建更标准化的方法。此外,还需要进一步评估索赔为基础的药物流行病学研究中其他错误分类的暴露状态的来源。