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Drug Safety
Published in: Drug Safety 6/2012

01-06-2012 | Original Research Article

Early Detection of Pharmacovigilance Signals with Automated Methods Based on False Discovery Rates

A Comparative Study

Authors: Dr Ismaïl Ahmed, Frantz Thiessard, Ghada Miremont-Salame, Françoise Haramburu, Carmen Kreft-Jais, Bernard Be’gaud, Pascale Tubert-Bitter

Published in: Drug Safety | Issue 6/2012

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Abstract

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 (GPS05). 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, GPS05 and IC02.5 with two FDR-based methods derived from the Fisher’s exact test and the GPS model (GPSpH0 [posterior probability of the null hypothesis H0 calculated from the Gamma Poisson Shrinker model]). Secondly, restricting the analysis to GPSpH0, 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 GPSpH0 in terms of both number of detections of true signals and time to detection. Additionally, based on an FDR threshold of 5%, GPSpH0 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.
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Metadata
Title
Early Detection of Pharmacovigilance Signals with Automated Methods Based on False Discovery Rates
A Comparative Study
Authors
Dr Ismaïl Ahmed
Frantz Thiessard
Ghada Miremont-Salame
Françoise Haramburu
Carmen Kreft-Jais
Bernard Be’gaud
Pascale Tubert-Bitter
Publication date
01-06-2012
Publisher
Springer International Publishing
Published in
Drug Safety / Issue 6/2012
Print ISSN: 0114-5916
Electronic ISSN: 1179-1942
DOI
https://doi.org/10.2165/11597180-000000000-00000

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