Early Detection of Pharmacovigilance Signals with Automated Methods Based on False Discovery Rates A Comparative Study
Early Detection of Pharmacovigilance Signals with Automated Methods Based on False Discovery Rates A Comparative Study
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DOI：
10.2165/11597180-000000000-00000
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发表时间：
2012-01-01
期刊：
影响因子：
4.2
通讯作者：
Tubert-Bitter, Pascale
中科院分区：
文献类型：
--
作者：
Ahmed, Ismail;Thiessard, Frantz;Tubert-Bitter, Pascale
背景：改进药物安全信号的检测导致一些药物警戒监管机构将自动定量方法纳入其自发报告管理系统。全球三个最大的药物警戒数据库通常采用比例报告比95%置信区间（PRR02.5）、信息成分2.5%分位数（IC02.5）或Gamma Poisson Shrinker 5%分位数（GPS(05)）的下界进行筛选。最近，基于贝叶斯和非贝叶斯错误发现率（FDR）的方法被提出，这些方法解决了阈值的任观性，并允许对FDR进行内置估计。通过模拟研究也表明，这些方法是目前使用的方法的有趣替代方案。目的：这项工作的目的是双重的。基于广泛的回顾性研究，我们将PRR02.5、GPS（05）和IC02.5与两种基于fdr的方法进行了比较，这些方法分别来自Fisher精确检验和GPS模型（GPS(pH0)[由Gamma Poisson Shrinker模型计算的零假设后验概率]）。其次，将分析限制在GPS（pH0）上，我们旨在评估使用自动信号检测工具与“传统”方法（即由药物警戒专家操作的非自动化监测）相比的附加价值。方法：对1996年1月1日至2002年7月1日期间法国整个药物警戒数据库进行逐月回顾性分析。评估是根据同期法国药物警戒技术委员会（PhVTC）开展的调查所对应的243个参考信号（RSs）清单进行的。根据检测RSs的数量和检测时间对检测方法进行比较。结果：5种自动定量方法在真信号检测次数和检测时间上均优于GPS（pH0）。此外，基于5%的FDR阈值，GPS（pH0）检测到87%与超过三份报告相关的RSs，将PhVTC的调查日期平均提前15.8个月。结论：我们的研究结果表明，与传统的药物警戒方法相比，只要有合理的数据支持，自动化信号检测工具是探索大型自发报告系统数据库并快速检测相关信号的强大工具。
Background: Improving the detection of drug safety signals has led several pharmacovigilance regulatory agencies to incorporate automated quantitative methods into their spontaneous reporting management systems. The three largest worldwide pharmacovigilance databases are routinely screened by the lower bound of the 95% confidence interval of proportional reporting ratio (PRR02.5), the 2.5% quantile of the Information Component (IC02.5) or the 5% quantile of the Gamma Poisson Shrinker (GPS(05)). More recently, Bayesian and non-Bayesian False Discovery Rate (FDR)-based methods were proposed that address the arbitrariness of thresholds and allow for a built-in estimate of the FDR. These methods were also shown through simulation studies to be interesting alternatives to the currently used methods.Objective: The objective of this work was twofold. Based on an extensive retrospective study, we compared PRR02.5, GPS(05) and IC02.5 with two FDR-based methods derived from the Fisher's exact test and the GPS model (GPS(pH0) [posterior probability of the null hypothesis Ho calculated from the Gamma Poisson Shrinker model]). Secondly, restricting the analysis to GPS(pH0), we aimed to evaluate the added value of using automated signal detection tools compared with 'traditional' methods, i.e. non-automated surveillance operated by pharmacovigilance experts.Methods: The analysis was performed sequentially, i.e. every month, and retrospectively on the whole French pharmacovigilance database over the period 1 January 1996-1 July 2002. Evaluation was based on a list of 243 reference signals (RSs) corresponding to investigations launched by the French Pharmacovigilance Technical Committee (PhVTC) during the same period. The comparison of detection methods was made on the basis of the number of RSs detected as well as the time to detection.Results: Results comparing the five automated quantitative methods were in favour of GPS(pH0) in terms of both number of detections of true signals and time to detection. Additionally, based on an FDR threshold of 5%, GPS(pH0) detected 87% of the RSs associated with more than three reports, anticipating the date of investigation by the PhVTC by 15.8 months on average.Conclusions: Our results show that as soon as there is reasonable support for the data, automated signal detection tools are powerful tools to explore large spontaneous reporting system databases and detect relevant signals quickly compared with traditional pharmacovigilance methods.