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Drug Safety
Published in: Drug Safety 5/2003

01-04-2003 | Leading Article

Application of Quantitative Signal Detection in the Dutch Spontaneous Reporting System for Adverse Drug Reactions

Authors: Dr Eugène P. van Puijenbroek, Willem L. Diemont, Kees van Grootheest

Published in: Drug Safety | Issue 5/2003

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Abstract

The primary aim of spontaneous reporting systems (SRSs) is the timely detection of unknown adverse drug reactions (ADRs), or signal detection. Generally this is carried out by a systematic manual review of every report sent to an SRS. Statistical analysis of the data sets of an SRS, or quantitative signal detection, can provide additional information concerning a possible relationship between a drug and an ADR. We describe the role of quantitative signal detection and the way it is applied at the Netherlands Pharmacovigilance Centre Lareb. Results of the statistical analysis are implemented in the traditional case-by-case analysis. In addition, for data-mining purposes, a list of associations of ADRs and suspected drugs that are disproportionally present in the database is periodically generated. Finally, quantitative signal generation can be used to study more complex relationships, such as drug-drug interactions and syndromes. The results of quantitative signal detection should be considered as an additional source of information, complementary to the traditional analysis. Techniques for the detection of drug interactions and syndromes offer a new challenge for pharmacovigilance in the near future.
Literature
1.
Rossi AC, Knapp DE, Anello C, et al. Discovery of adverse drug reactions: a comparison of selected phase IV studies with spontaneous reporting methods. JAMA 1983; 249: 2226–8PubMedCrossRef
2.
3.
Finney DJ. Systemic signalling of adverse reactions to drugs. Methods Inf Med 1974; 13: 1–10PubMed
4.
Finney DJ. Statistical logic in the monitoring of reactions to therapeutic drugs. Methods Inf Med 1971; 10: 237–45PubMed
5.
6.
Evans SJ, Waller PC, Davis S. Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports. Pharmacoepidemiol Drug Saf 2001 Oct-Nov; 10(6): 483–6PubMedCrossRef
7.
Evans SJW, Waller P, Davis S. Proportional reporting ratios: the uses of epidemiological methods for signal generation [abstract]. Pharmacoepidemiol Drug Saf 1998; 7: S102CrossRef
8.
Egberts ACG, Van der Hofstede JW, Meyboom RHB, et al. Transformation of a database of spontaneously reported suspected adverse drug reactions and its use as a tool in signal detection. In: Egberts ACG, editor. Pharmacoepidemiologic approaches to the evaluation of antidepressant drugs [thesis]. Utrecht: 1997: 111–24
9.
Stricker BH, Tijssen JG. Serum sickness-like reactions to cefaclor. J Clin Epidemiol 1992; 45(10): 1177–84PubMedCrossRef
10.
Moore N, Kreft-Jais C, Haramburu F, et al. Reports of hypoglycaemia associated with the use of ACE inhibitors and other drugs: a case/non-case study in the French pharmacovigilance system database. Br J Clin Pharmacol 1997; 44: 513–8PubMedCrossRef
11.
Bate A, Lindquist M, Edwards IR, et al. A Bayesian neural network method for adverse drug reaction signal generation. Eur J Clin Pharmacol 1998; 54: 315–21PubMedCrossRef
12.
Szarfman A, Machado SG, O’Neill RT. Use of screening algorithms and computer systems to efficiently signal higher-than-expected combinations of drugs and events in the US FDA’s spontaneous reports database. Drug Saf 2002; 25(6): 381–92PubMedCrossRef
13.
Egberts AC, Meyboom RH, van Puijenbroek EP. Use of measures of disproportionality in pharmacovigilance: three Dutch examples. Drug Saf 2002; 25(6): 453–8PubMedCrossRef
14.
WHO adverse drug reaction dictionary. Uppsala: WHO Collaborating Centre for International Drug Monitoring, 1995
15.
Farmacotherapeutisch Kompas 2000/2001. Amstelveen: Commissie Farmaceutische Hulp van het College voor zorgverzekeringen, 2000
16.
Informatorium Medicamentorum 2000. ‘s Gravenhage: Wetenschappelijk Instituut Nederlandse Apothekers, 2000
17.
van Puijenbroek EP, Egberts ACG, Meyboom RHB, et al. Association between terbinafine and arthralgia, fever and urticaria: symptoms or syndrome? Pharmacoepidemiol Drug Saf 2001; 10: 135–42PubMedCrossRef
18.
van Puijenbroek EP, Egberts AC, Heerdink ER, et al. Detecting drug-drug interactions using a database for spontaneous adverse drug reactions: an example with diuretics and nonsteroidal anti-inflammatory drugs. Eur J Clin Pharmacol 2000 Dec; 56(9-10): 733–8PubMedCrossRef
19.
van Puijenbroek EP, Egberts AC, Meyboom RH, et al. Signalling possible drug-drug interactions in a spontaneous reporting system: delay of withdrawal bleeding during concomitant use of oral contraceptives and itraconazole. Br J Clin Pharmacol 1999; 47: 689–93PubMedCrossRef
20.
van Puijenbroek EP, Bate A, Leufkens HG, et al. A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions. Pharmacoepidemiol Drug Saf 2002 Jan-Feb; 11(1): 3–10PubMedCrossRef
21.
van Puijenbroek EP, van Grootheest K, Diemont WL, et al. Determinants of signal selection in a spontaneous reporting system for adverse drug reactions. Br J Clin Pharmacol 2001 Nov; 52(5): 579–86PubMedCrossRef
22.
Lindquist M, Stahl M, Bate A, et al. A retrospective evaluation of a data mining approach to aid finding new adverse drug reaction signals in the WHO international database. Drug Saf 2000; 23: 533–42PubMedCrossRef
23.
Moore N, Kreft-Jais C, Haramburu F, et al. Reports of hypoglycaemia associated with the use of ACE inhibitors and other drugs: a case/non-case study in the French pharmacovigilance system database. Br J Clin Pharmacol 1997; 44: 513–8PubMedCrossRef
24.
Metadata
Title
Application of Quantitative Signal Detection in the Dutch Spontaneous Reporting System for Adverse Drug Reactions
Authors
Dr Eugène P. van Puijenbroek
Willem L. Diemont
Kees van Grootheest
Publication date
01-04-2003
Publisher
Springer International Publishing
Published in
Drug Safety / Issue 5/2003
Print ISSN: 0114-5916
Electronic ISSN: 1179-1942
DOI
https://doi.org/10.2165/00002018-200326050-00001

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