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Journal ArticleDOI

A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions.

TLDR
The objective of this study is to examine the level of concordance of the various estimates to the measure used by the WHO Collaborating Centre for International ADR monitoring, the information component (IC), when applied to the dataset of the Netherlands Pharmacovigilance Foundation Lareb.
Abstract
SUMMARY Purpose A continuous systematic review of all combinations of drugs and suspected adverse reactions (ADRs) reported to a spontaneous reporting system, is necessary to optimize signal detection. To focus attention of human reviewers, quantitative procedures can be used to sift data in different ways. In various centres, different measures are used to quantify the extent to which an ADR is reported disproportionally to a certain drug compared to the generality of the database. The objective of this study is to examine the level of concordance of the various estimates to the measure used by the WHO Collaborating Centre for International ADR monitoring, the information component (IC), when applied to the dataset of the Netherlands Pharmacovigilance Foundation Lareb. Methods The Reporting Odds Ratio � 1.96 standard errors (SE), proportional reporting ratio � 1.96 SE, Yule’s Q � 1.96 SE, the Poisson probability and Chi-square test of all 17 330 combinations were compared with the IC minus 2 standard deviations. Additionally, the concordance of the various tests, in respect to the number of reports per combination, was examined. Results In general, sensitivity was high in respect to the reference measure when a combination of point- and precision estimate was used. The concordance increased dramatically when the number of reports per combination increased. Conclusion This study shows that the different measures used are broadly comparable when four or more cases per combination have been collected. Copyright # 2002 John Wiley & Sons, Ltd.

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Citations
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Journal ArticleDOI

Quantitative signal detection using spontaneous ADR reporting.

TL;DR: The role of Bayesian shrinkage in screening spontaneous reports, the importance of changes over time in screening the properties of the measures and some suggestions as to where emerging research is likely to lead are given.
Journal ArticleDOI

Data Mining of the Public Version of the FDA Adverse Event Reporting System

TL;DR: The latest information on this area is summarized for future pharmacoepidemiological studies and/or pharmacovigilance analyses.
Journal ArticleDOI

Anti-HERG activity and the risk of drug-induced arrhythmias and sudden death.

TL;DR: Findings are in support of the value of pre-clinical HERG testing to predict pro-arrhythmic effects of medicines.
Journal ArticleDOI

Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs

TL;DR: A machine-learning-based approach for ADR prediction by integrating the phenotypic characteristics of a drug, including indications and other known ADRs, with the drug's chemical structures and biological properties, including protein targets and pathway information is proposed.
Journal ArticleDOI

Assessing the association of pioglitazone use and bladder cancer through drug adverse event reporting

TL;DR: AERS analysis is consistent with an association between pioglitazone and bladder cancer, and this issue needs constant epidemiologic surveillance and urgent definition by more specific studies.
References
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Journal ArticleDOI

The Advanced Theory of Statistics

Maurice G. Kendall, +1 more
- 01 Apr 1963 - 
Journal ArticleDOI

A Bayesian neural network method for adverse drug reaction signal generation

TL;DR: The BCPNN will be an extremely useful adjunct to the expert assessment of very large numbers of spontaneously reported ADRs, and can be used in the detection of significant signals from the data set of the WHO Programme on International Drug Monitoring.
Journal ArticleDOI

Bayesian Data Mining in Large Frequency Tables, with an Application to the FDA Spontaneous Reporting System

TL;DR: Here, a baseline or null hypothesis expected frequency is constructed for each cell, and screening criteria for ranking the cell deviations of observed from expected count are suggested and compared.
Book

Advanced Theory of Statistics

TL;DR: A method for continuously effecting reactions in a liquid phase in the presence of a gas and of a finely divided solid catalyst in a bubble column-cascade reactor with little or no liquid back-mixing.
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