Global Safety Surveillance and Epidemiology, Wyeth, Collegeville, Pennsylvania, USA.
Drug Saf. 2010 Feb 1;33(2):139-46. doi: 10.2165/11319000-000000000-00000.
The use of data mining has increased among regulators and pharmaceutical companies. The incremental value of data mining as an adjunct to traditional pharmacovigilance methods has yet to be demonstrated. Specifically, the utility in identifying new safety signals and the resources required to do so have not been elucidated.
To analyse the number and types of disproportionately reported product-event combinations (DRPECs), as well as the final disposition of each, in order to understand the potential utility and resource implications of routinely conducting data mining in the US FDA Adverse Event Reporting System (AERS).
We generated DRPECs from AERS for six of Wyeth's products, prospectively tracked their dispositions and evaluated the appropriate DRPECs in the company's safety database. We chose EB05 (the lower bound of the 90% confidence interval around the Empirical Bayes Geometric Mean) > or =2 as the appropriate metric, employing stratification based on age, sex and year of report.
A total of 861 DRPECs were identified - the average number of DRPECs was 144 per product. The proportion of unique preferred terms (PTs) in AERS for each drug with an EB05 > or =2 was similar across the six products (5.1-8.5%). Overall, 64.0% (551) of the DRPECs were closed after the initial screening (44.8% labelled, 14.3% indication related, 4.9% non-interpretable). An additional 9.9% (85) had been reviewed within the prior year and were not further reviewed. The remaining 26.1% (225) required full case review. After review of all pertinent reports and additional data, it was determined which of the DRPECs necessitated a formal review by the company's ongoing Safety Review Team (SRT) process. In total, 3.6% (31/861) of the DRPECs, yielding 16 medical concepts, were reviewed by the SRT, leading to seven labelling changes. These labelling changes involved 1.9% of all DRPECs generated. Four of the six compounds reviewed as part of this pilot had an identified labelling change. The workload required for this pilot, which was driven primarily by those DRPECs requiring review, was extensive, averaging 184 hours per product.
The number of DRPECs identified for each drug approximately correlated with the number of unique PTs in the database. Over one-half of DRPECs were either labelled as per the company's reference safety information (RSI) or were under review after identification by traditional pharmacovigilance activities, suggesting that for marketed products these methods do identify adverse events detected by traditional pharmacovigilance methods. Approximately three-quarters of the 861 DRPECs identified were closed without case review after triage. Of the approximately one-quarter of DRPECs that required formal case review, seven resulted in an addition to the RSI for the relevant products. While this pilot does not allow us to comment on the utility of routine data mining for all products, it is significant that several new safety concepts were identified through this prospective exercise.
数据挖掘在监管机构和制药公司中的使用有所增加。数据挖掘作为传统药物警戒方法的辅助手段的增量价值尚未得到证明。具体来说，识别新的安全信号的效用以及执行此操作所需的资源尚未阐明。
分析不成比例报告的产品-事件组合（DRPECs）的数量和类型，以及每种组合的最终处置情况，以了解在美国 FDA 不良事件报告系统（AERS）中常规进行数据挖掘的潜在效用和资源影响。
我们针对惠氏的六种产品从 AERS 中生成了 DRPECs，前瞻性地跟踪了它们的处置情况，并在公司的安全数据库中评估了适当的 DRPECs。我们选择 EB05（经验贝叶斯几何平均值的 90%置信区间下限）≥2作为适当的指标，根据年龄、性别和报告年份进行分层。
共确定了 861 个 DRPECs-每个产品的平均 DRPECs 数量为 144 个。在具有 EB05≥2 的六种药物中，每种药物的独特首选术语（PT）在 AERS 中的比例相似（5.1-8.5%）。总体而言，64.0%（551）的 DRPECs 在初始筛选后关闭（44.8%标记，14.3%与指示相关，4.9%不可解释）。另外 9.9%（85）在过去一年中进行了审查，不再进行进一步审查。其余 26.1%（225）需要全面的病例审查。在审查了所有相关报告和其他数据后，确定了哪些 DRPECs需要公司正在进行的安全审查团队（SRT）流程进行正式审查。总共，3.6%（31/861）的 DRPECs，产生了 16 个医疗概念，由 SRT 审查，导致了 7 个标签更改。这些标签更改涉及生成的所有 DRPECs 的 1.9%。作为本试点的一部分审查的六种化合物中的四种有已确定的标签更改。该试点所需的工作量主要由需要审查的 DRPECs 驱动，每个产品平均需要 184 个小时。
每种药物确定的 DRPECs 数量与数据库中唯一的 PT 数量大致相关。超过一半的 DRPECs 要么根据公司的参考安全信息（RSI）进行标记，要么在通过传统药物警戒活动识别后进行审查，这表明对于上市产品，这些方法确实可以识别传统药物警戒方法检测到的不良事件。在分类后，大约 861 个 DRPECs 中有四分之三无需病例审查即可关闭。大约四分之一需要正式病例审查的 DRPECs 中有 7 个导致相关产品的 RSI 增加。虽然本试点不允许我们对所有产品的常规数据挖掘的效用发表评论，但值得注意的是，通过这项前瞻性研究确定了几个新的安全概念。
