Data Mining in the US using the Vaccine Adverse Event Reporting System
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LEADING ARTICLE
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Data Mining in the US using the Vaccine Adverse Event Reporting System John Iskander,1 Vitali Pool,1 Weigong Zhou,2 Roseanne English-Bullard3 and The VAERS Team1 1 2 3
Office of Immunization Safety, Office of the Chief Science Officer, Centers for Disease Control and Prevention, Atlanta, Georgia, USA Division of Viral and Rickettsial Diseases, Influenza Branch, National Center for Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA National Center for Public Health Informatics, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
Abstract
The US Vaccine Adverse Event Reporting System (VAERS), which is charged with vigilance for detecting vaccine-related safety issues, faces an increasingly complex immunisation environment. Since 1990, steady increases in vaccine licensing and distribution have resulted in increasing numbers of reports to VAERS. Prominent features of current reports include more routine vaccine co-administration and frequent reports of new postvaccination clinical syndromes. Data-mining methods, based on disproportionality analyses, are one strategy being pursued by VAERS researchers to increase the utility of its complex database. The types of analyses used include proportional reporting ratios, association rule discovery, and various ‘historic limits’ methods that compare observed versus expected event counts. The use of such strategies in VAERS has been primarily supplemental and retrospective. Signals for inactivated influenza, typhoid and tetanus toxoid-containing vaccines have been successfully identified. Concerns flagged through data mining should always be subject to clinical case review as a first evaluation step. Persistent issues should be subject to formal hypothesis testing in large linked databases or other controlled-study settings. Automated data-mining techniques for prospective use are currently undergoing development and evaluation within VAERS. Their use (as one signal-detection tool among many) by trained medical evaluators who are aware of system limitations is one legitimate approach to improving the ability of VAERS to generate vaccine-safety hypotheses. Such approaches are needed as more new vaccines continue to be licensed.
1. The US Vaccine Adverse Event Reporting System (VAERS) The US Vaccine Adverse Event Reporting System (VAERS), which was established in 1990, is jointly operated by the Centers for Disease Control and Prevention (CDC) and the US FDA. As the
frontline national passive surveillance system for vaccine safety, VAERS is primarily responsible for detecting rare or novel vaccine adverse events (VAEs) that may require further study. Such signals have typically been detected by review of case reports and case series published in the medical litera-
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ture, inquiries from providers and the general public[1] or media attention.[2] Although VAERS is subject to well described limitations common to other passive surveilla
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