Patadia Vaishali K, Schuemie Martijn J, Coloma Preciosa, Herings Ron, van der Lei Johan, Straus Sabine, Sturkenboom Miriam, Trifirò Gianluca
Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands,
Int J Clin Pharm. 2015 Feb;37(1):94-104. doi: 10.1007/s11096-014-0044-5. Epub 2014 Dec 9.
Electronic reporting and processing of suspected adverse drug reactions (ADRs) is increasing and has facilitated automated screening procedures. It is crucial for healthcare professionals to understand the nature and proper use of data available in pharmacovigilance practice.
To (a) compare performance of EU-ADR [electronic healthcare record (EHR) exemplar] and FAERS [spontaneous reporting system (SRS) exemplar] databases in detecting signals using "positive" and "negative" drug-event reference sets; and (b) evaluate the impact of timing bias on sensitivity thresholds by comparing all data to data restricted to the time before a warning/regulatory action.
Ten events with known positive and negative reference sets were selected. Signals were identified when respective statistics exceeded defined thresholds. Main outcome measure Performance metrics, including sensitivity, specificity, positive predictive value and accuracy were calculated. In addition, the effect of regulatory action on the performance of signal detection in each data source was evaluated.
The sensitivity for detecting signals in EHR data varied depending on the nature of the adverse events and increased substantially if the analyses were restricted to the period preceding the first regulatory action. Across all events, using data from all years, a sensitivity of 45-73 % was observed for EU-ADR and 77 % for FAERS. The specificity was high and similar for EU-ADR (82-96 %) and FAERS (98 %). EU-ADR data showed range of PPV (78-91 %) and accuracy (78-72 %) and FAERS data yielded a PPV of 97 % with 88 % accuracy.
Using all cumulative data, signal detection in SRS data achieved higher specificity and sensitivity than EHR data. However, when data were restricted to time prior to a regulatory action, performance characteristics changed in a manner consistent with both the type of data and nature of the ADR. Further research focusing on prospective validation of is necessary to learn more about the performance and utility of these databases in modern pharmacovigilance practice.
疑似药品不良反应(ADR)的电子报告和处理日益增多,并推动了自动化筛查程序。医疗保健专业人员了解药物警戒实践中可用数据的性质和正确使用方法至关重要。
(a)使用“阳性”和“阴性”药物-事件参考集比较欧盟ADR[电子健康记录(EHR)示例]和FAERS[自发报告系统(SRS)示例]数据库在检测信号方面的性能;(b)通过将所有数据与限于警告/监管行动之前时间的数据进行比较,评估时间偏差对敏感性阈值的影响。
选择了10个具有已知阳性和阴性参考集的事件。当各自的统计数据超过定义的阈值时识别信号。计算主要结局指标性能指标,包括敏感性、特异性、阳性预测值和准确性。此外,评估了监管行动对每个数据源中信号检测性能的影响。
EHR数据中检测信号的敏感性因不良事件的性质而异,如果分析限于首次监管行动之前的时期,则敏感性会大幅提高。在所有事件中,使用所有年份的数据,欧盟ADR的敏感性为45%-73%,FAERS为77%。欧盟ADR和FAERS的特异性都很高且相似(欧盟ADR为82%-96%,FAERS为98%)。欧盟ADR数据显示阳性预测值范围为78%-91%,准确性为78%-72%,FAERS数据的阳性预测值为97%,准确性为88%。
使用所有累积数据时,SRS数据中的信号检测比EHR数据具有更高的特异性和敏感性。然而,当数据限于监管行动之前的时间时,性能特征会根据数据类型和ADR的性质以一致的方式发生变化。有必要进行更多侧重于前瞻性验证的研究,以进一步了解这些数据库在现代药物警戒实践中的性能和效用。