Literature DB >> 7893579

False-positives in spontaneous reporting: should we worry about them?

B Begaud1, Y Moride, P Tubert-Bitter, A Chaslerie, F Haramburu.   

Abstract

Spontaneous reporting remains the most used and, undoubtedly, the most cost-effective approach for the identification of adverse drug reactions (ADRs). Most of the limitations of this method are well recognised but the possibility of receiving false-positive reports of coincidental drug-event associations has received little attention. In this paper we propose a method based on the Poisson distribution for computing the maximum number of reports of an ADR that could be expected to be reported coincidentally. Three parameters are required: (i) the background risk of the event in the reference population, (ii) the total number of patients treated with the drug considered and, (iii) the proportion of cases that have been reported to the pharmacovigilance system. For most empirical situations occurring in the post-marketing surveillance setting, the expected number remains low and only a maximum of one to three cases could be accepted as possibly coincidental. For rare adverse events such as agranulocytosis or toxic epidermal necrolysis, coincidental associations are so unlikely that a number of reports greater than three constitutes a strong warning and requires further investigation. These findings suggest that for rare events, reports of coincidental drug-event associations are too unlikely to be considered as an important limitation of spontaneous reporting.

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Year:  1994        PMID: 7893579      PMCID: PMC1364871          DOI: 10.1111/j.1365-2125.1994.tb04373.x

Source DB:  PubMed          Journal:  Br J Clin Pharmacol        ISSN: 0306-5251            Impact factor:   4.335


  7 in total

1.  Spontaneous reporting: how many cases are required to trigger a warning?

Authors:  P Tubert; B Bégaud; F Haramburu; J C Péré
Journal:  Br J Clin Pharmacol       Date:  1991-10       Impact factor: 4.335

2.  Toxic epidermal necrolysis (Lyell syndrome). Incidence and drug etiology in France, 1981-1985.

Authors:  J C Roujeau; J C Guillaume; J P Fabre; D Penso; M L Fléchet; J P Girre
Journal:  Arch Dermatol       Date:  1990-01

3.  Spontaneous reporting of adverse drug reactions. I: the data.

Authors:  M D Rawlins
Journal:  Br J Clin Pharmacol       Date:  1988-07       Impact factor: 4.335

4.  Under-reporting of adverse drug reactions.

Authors:  W H Inman
Journal:  Br Med J (Clin Res Ed)       Date:  1985-05-04

5.  Validity of anecdotal reports of suspected adverse drug reactions: the problem of false alarms.

Authors:  G R Venning
Journal:  Br Med J (Clin Res Ed)       Date:  1982-01-23

6.  Discovery of adverse drug reactions. A comparison of selected phase IV studies with spontaneous reporting methods.

Authors:  A C Rossi; D E Knapp; C Anello; R T O'Neill; C F Graham; P S Mendelis; G R Stanley
Journal:  JAMA       Date:  1983 Apr 22-29       Impact factor: 56.272

7.  Spontaneous adverse drug reaction reporting vs event monitoring: a comparison.

Authors:  A P Fletcher
Journal:  J R Soc Med       Date:  1991-06       Impact factor: 18.000

  7 in total
  25 in total

Review 1.  Intraspinal steroids: history, efficacy, accidentality, and controversy with review of United States Food and Drug Administration reports.

Authors:  D A Nelson; W M Landau
Journal:  J Neurol Neurosurg Psychiatry       Date:  2001-04       Impact factor: 10.154

Review 2.  Quantitative methods in pharmacovigilance: focus on signal detection.

Authors:  Manfred Hauben; Xiaofeng Zhou
Journal:  Drug Saf       Date:  2003       Impact factor: 5.606

3.  Risk of drug-induced agranulocytosis: the case of calcium dobesilate.

Authors:  Pedro Zapater; José Francisco Horga; Antonio García
Journal:  Eur J Clin Pharmacol       Date:  2003-02-19       Impact factor: 2.953

Review 4.  The periodic safety update report as a pharmacovigilance tool.

Authors:  Michael J Klepper
Journal:  Drug Saf       Date:  2004       Impact factor: 5.606

Review 5.  Detection, verification, and quantification of adverse drug reactions.

Authors:  Bruno H Ch Stricker; Bruce M Psaty
Journal:  BMJ       Date:  2004-07-03

6.  Drug-induced pancreatitis: lessons in data mining.

Authors:  Manfred Hauben; Lester Reich
Journal:  Br J Clin Pharmacol       Date:  2004-11       Impact factor: 4.335

Review 7.  Perspectives on the use of data mining in pharmaco-vigilance.

Authors:  June Almenoff; Joseph M Tonning; A Lawrence Gould; Ana Szarfman; Manfred Hauben; Rita Ouellet-Hellstrom; Robert Ball; Ken Hornbuckle; Louisa Walsh; Chuen Yee; Susan T Sacks; Nancy Yuen; Vaishali Patadia; Michael Blum; Mike Johnston; Charles Gerrits; Harry Seifert; Karol Lacroix
Journal:  Drug Saf       Date:  2005       Impact factor: 5.606

8.  Communication of findings in pharmacovigilance: use of the term "signal" and the need for precision in its use.

Authors:  Manfred Hauben; Lester Reich
Journal:  Eur J Clin Pharmacol       Date:  2005-07-01       Impact factor: 2.953

9.  A new Poisson and Bayesian-based method to assign risk and causality in patients with suspected hepatic adverse drug reactions: a report of two new cases of ticlopidine-induced hepatotoxicity.

Authors:  Pedro Zapater; José Such; Miguel Pérez-Mateo; José Francisco Horga
Journal:  Drug Saf       Date:  2002       Impact factor: 5.606

Review 10.  Overview of the First Natural Language Processing Challenge for Extracting Medication, Indication, and Adverse Drug Events from Electronic Health Record Notes (MADE 1.0).

Authors:  Abhyuday Jagannatha; Feifan Liu; Weisong Liu; Hong Yu
Journal:  Drug Saf       Date:  2019-01       Impact factor: 5.606

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