利用数据挖掘技术对疫苗不良事件报告系统(VAERS)中的安全信号进行前瞻性早期检测:2010-2011 年季节性流感病毒疫苗接种后发热性惊厥的病例研究。
Data mining for prospective early detection of safety signals in the Vaccine Adverse Event Reporting System (VAERS): a case study of febrile seizures after a 2010-2011 seasonal influenza virus vaccine.
机构信息
Office of Biostatistics and Epidemiology, FDA Center for Biologics Evaluation and Research, WOC1 Building, Room 455S, 1401 Rockville Pike, Rockville, MD, 20852, USA.
出版信息
Drug Saf. 2013 Jul;36(7):547-56. doi: 10.1007/s40264-013-0051-9.
BACKGROUND
Reports of data mining results as an initial indication of a prospectively detected safety signal in the US Vaccine Adverse Event Reporting System (VAERS) have been limited. In April 2010 a vaccine safety signal for febrile seizures after Fluvax(®) and Fluvax(®) Junior was identified in Australia without the aid of data mining. In order to refine Northern Hemisphere influenza vaccine safety surveillance, VAERS data mining analyses based on vaccine brand name were initiated during the 2010-2011 influenza season.
OBJECTIVE
We describe the strategies that led to the finding of a novel safety signal using empirical Bayesian data mining.
METHODS
The primary US VAERS analysis calculated an empirical Bayesian geometric mean (EBGM), which was adjusted for age group, sex and year received. A secondary age-stratified analysis calculated a separate EBGM for 11 pre-defined age subsets. These bi-weekly analyses were generated with database restrictions that separated live and inactivated vaccines as well as with the US VAERS database. A cutoff of 2.0 at the fifth percentile of the confidence interval (CI) for the EBGM, the EB05, was used to identify vaccine adverse event combinations for further evaluation. Examination of potential interactions among concomitantly administered vaccines is based on the Interaction Signal Score (INTSS), which is a relative measure of how much excess disproportionality is present in the three-dimensional combination of two vaccines and one adverse event term. An INTSS >1 indicates that the CI for the three-dimensional analysis is larger than and does not overlap with the CI from the highest two-dimensional analysis. We subsequently examined the possibility of masking by removing all 2,095 Fluzone(®) 2010-2011 reports from the 10 December 2010 version of the VAERS database. In addition, we calculated relative reporting ratios to observe the relative contribution of adjustment and the Multi-Item Gamma Poisson Shrinker (MGPS) algorithm to EBGM values.
RESULTS
On 10 December 2010, US VAERS analyses we found an EB05 >2 for Fluzone(®) 2010-2011 and the Medical Dictionary for Regulatory Activities (MedDRA(®)) term "febrile seizure". MedDRA(®) terminology is the medical terminology developed under the auspices of the International Conference on Harmonization of technical requirements for Registration of Pharmaceuticals for Human Use (ICH). No other vaccine products had independent vaccine-febrile seizure combinations with an EB05 >2. Three-dimensional analyses to examine possible interactions among vaccine products concomitantly administered with Fluzone(®) 2010-2011 yielded Interaction Signal Score values <1. Removal of all Fluzone(®) 2010-2011 reports from the VAERS database failed to demonstrate a previously masked vaccine adverse event pair with an EB05 >2. The inactivated vaccine database restriction resulted in a 41 % reduction in background VAERS reports and a 24 % reduction in foreground VAERS reports.
CONCLUSION
Empirical Bayesian data mining in VAERS prospectively detected the safety signal for febrile seizures after Fluzone(®) 2010-2011 in young children. The EB05 threshold, database restrictions, adjustment and baseline data mining were strategies adopted a priori to enhance the specificity of the 2010-2011 influenza vaccine data mining analyses. A database restriction used to separate live vaccines resulted in a reduced EB05. Adjustment of data mining analyses had a larger effect on estimates of disproportionality than the MGPS algorithm. Masking did not appear to influence our findings. This case study illustrates the value of VAERS data mining for vaccine safety monitoring.
背景
在美国疫苗不良事件报告系统(VAERS)中,数据挖掘结果报告作为前瞻性检测到的安全信号的初步指示,报告一直有限。2010 年 4 月,在没有数据挖掘帮助的情况下,澳大利亚发现 Fluvax(®)和 Fluvax(®) Junior 疫苗接种后发热性惊厥的疫苗安全信号。为了完善北半球流感疫苗安全性监测,在 2010-2011 流感季节,VAERS 数据挖掘分析基于疫苗品牌名称开始进行。
目的
我们描述了使用经验贝叶斯数据挖掘发现新的安全信号的策略。
方法
美国 VAERS 的主要分析计算了经验贝叶斯几何平均值(EBGM),该平均值根据年龄组、性别和接种年份进行了调整。二级年龄分层分析为 11 个预先定义的年龄子集计算了单独的 EBGM。这些每两周进行一次的分析是在数据库限制下生成的,这些限制将活疫苗和灭活疫苗以及美国 VAERS 数据库分开。使用 EBGM 的第五个百分位置信区间(CI)的截断值 2.0(EB05)来识别进一步评估的疫苗不良事件组合。潜在同时给药疫苗之间相互作用的检查是基于交互信号评分(INTSS),这是一种衡量两个疫苗和一个不良事件术语的三维组合中存在多大过量不成比例的相对度量。INTSS>1 表示三维分析的 CI 大于且不与二维分析中最高的 CI 重叠。随后,我们从 2010 年 12 月 10 日的 VAERS 数据库中删除了所有 2,095 份 Fluzone(®)2010-2011 报告,以检查是否存在掩蔽的可能性。此外,我们还计算了相对报告率,以观察调整和多项目伽马泊松收缩器(MGPS)算法对 EBGM 值的相对贡献。
结果
2010 年 12 月 10 日,我们在美国 VAERS 分析中发现 Fluzone(®)2010-2011 年的 EB05>2 以及 MedDRA(®)术语“热性惊厥”。MedDRA(®)术语是在国际人用药品注册技术协调会(ICH)的主持下开发的医疗术语。没有其他疫苗产品具有独立的疫苗-热性惊厥组合,EB05>2。对可能与同时给予 Fluzone(®)2010-2011 年的疫苗产品之间相互作用的三维分析得出的交互信号评分值<1。从 VAERS 数据库中删除所有 Fluzone(®)2010-2011 年的报告未能证明之前有 EB05>2 的被掩盖的疫苗不良事件对。灭活疫苗数据库限制导致 VAERS 背景报告减少 41%,VAERS 前景报告减少 24%。
结论
VAERS 中的经验贝叶斯数据挖掘前瞻性地检测到 Fluzone(®)2010-2011 年在幼儿中发热性惊厥的安全性信号。EB05 阈值、数据库限制、调整和基线数据挖掘是为增强 2010-2011 年流感疫苗数据挖掘分析的特异性而预先采用的策略。用于分离活疫苗的数据库限制导致 EB05 降低。数据挖掘分析的调整对不成比例的估计影响大于 MGPS 算法。掩蔽似乎没有影响我们的发现。本案例研究说明了 VAERS 数据挖掘在疫苗安全性监测中的价值。