Skip to main content
Top
Published in: Drug Safety 6/2007

01-06-2007 | Correspondence

‘Extreme Duplication’ in the US FDA Adverse Events Reporting System Database

Authors: Manfred Hauben, Dr Lester Reich, James De Micco, Katherine Kim

Published in: Drug Safety | Issue 6/2007

Login to get access

Excerpt

We recently encountered an example of extreme duplication in the publicly released version of the US FDA Adverse Events Reporting System (AERS) database, which is available through the Freedom of Information (FOI) Act. We use the term ‘extreme duplication’ because the majority of reports of the drug-event pair under study were found to be duplicate reports, and these duplicates resulted in the occurrence of a large signal of disproportionate reporting (SDR)[1] discovered during a data-mining exercise. This occurred during a recent demonstration within our company of a commercial vendor’s data-mining software containing these data. Data mining includes emerging computer-based quantitative tools for screening spontaneous reporting system (SRS) databases to assist in the identification of potential new drug safety issues. Although duplicate reporting is one of the numerous well recognised forms of data corruption and distortion in SRS databases, the finding surprised us nonetheless, given the duplicate detection algorithms and procedures included in the commercial data-mining software we used. …
Literature
1.
go back to reference Hauben M, Reich L. Communication of findings in pharmacovigilance: use of the term “signal” and the need for precision in its use. Eur J Clin Pharmacol 2005; 61: 479–80PubMedCrossRef Hauben M, Reich L. Communication of findings in pharmacovigilance: use of the term “signal” and the need for precision in its use. Eur J Clin Pharmacol 2005; 61: 479–80PubMedCrossRef
3.
go back to reference Preparing FOI Drug Safety Data for WebVDME Data Mining, Lincoln Technologies Inc., 2005 Preparing FOI Drug Safety Data for WebVDME Data Mining, Lincoln Technologies Inc., 2005
4.
go back to reference Norén GN, Orre R, Bate A, et al. Duplicate detection in adverse drug reaction surveillance. Data Min Knowl Disc 2007; 14(3): 305–28CrossRef Norén GN, Orre R, Bate A, et al. Duplicate detection in adverse drug reaction surveillance. Data Min Knowl Disc 2007; 14(3): 305–28CrossRef
5.
go back to reference Strom BL. Evaluation of suspected adverse drug reactions. JAMA 2005; 293(11): 1324–5CrossRef Strom BL. Evaluation of suspected adverse drug reactions. JAMA 2005; 293(11): 1324–5CrossRef
6.
go back to reference Hauben M, Patadia V, Gerrits CM, et al. Data mining in pharmacovigilance: the need for a balanced perspective. Drug Saf 2005; 28(10): 835–42PubMedCrossRef Hauben M, Patadia V, Gerrits CM, et al. Data mining in pharmacovigilance: the need for a balanced perspective. Drug Saf 2005; 28(10): 835–42PubMedCrossRef
7.
go back to reference Bate A, Edwards IR. Data mining in spontaneous reports. Basic Clin Pharmacol Toxicol 2006; 98(3): 324–30PubMedCrossRef Bate A, Edwards IR. Data mining in spontaneous reports. Basic Clin Pharmacol Toxicol 2006; 98(3): 324–30PubMedCrossRef
Metadata
Title
‘Extreme Duplication’ in the US FDA Adverse Events Reporting System Database
Authors
Manfred Hauben
Dr Lester Reich
James De Micco
Katherine Kim
Publication date
01-06-2007
Publisher
Springer International Publishing
Published in
Drug Safety / Issue 6/2007
Print ISSN: 0114-5916
Electronic ISSN: 1179-1942
DOI
https://doi.org/10.2165/00002018-200730060-00009

Other articles of this Issue 6/2007

Drug Safety 6/2007 Go to the issue