From association to alert—a revised approach to international signal analysis

Lindquist, Marie; Edwards, I. Ralph; Bate, Andrew; Fucik, Helena; Nunes, Ana; Ståhl, Malin

doi:10.1002/(sici)1099-1557(199904)8:1+<s15::aid-pds402>3.3.co;2-2

Cited by 65 publications

(23 citation statements)

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“…The database contains information found in adverse event reports and medication error reports that are submitted to the FDA [7]. Implemented in 2012, FAERS was designed to support the postmarket safety surveillance for drugs and therapeutic products.…”

Section: Faersmentioning

confidence: 99%

Pharmacovigilance, signal detection using statistical data mining methods

Sriramakrishnan¹,

Selvam²,

Mariappan³

et al. 2018

IJET

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Pharmacovigilance programmes monitor and help safeguarding the use of medicines which is grave to the success of public health programmes. Identifying new possible risks and developing risk minimization action plans to prevent or ease these risks is at the heart of all pharmacovigilance activities throughout the product lifecycle. In this paper we examine the use of data mining algorithms to identify signals from adverse events reported. The capabilities include screening, data mining and frequency tabulation for potential signals, including signal estimation using established statistical signal detection methods. We have standard processes, algorithms and follow current requirements for signal detection and risk management activities.

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Section: Faersmentioning

confidence: 99%

Pharmacovigilance, signal detection using statistical data mining methods

Sriramakrishnan¹,

Selvam²,

Mariappan³

et al. 2018

IJET

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“…The term "designated medical events" has been used to describe this type of adverse event in recent years; that is, events that may trigger an alert on the basis of only onr to three cases since they are rare, medically serious, have a high drug-attributable risk, and may occur with drugs from diverse pharmacological/ therapeutic classes (Hauben, 2004). The WHO Programme for International Drug Monitoring has a list of "critical terms" that are adverse event terms based on a similar concept and have been subject to more intense analyses, since the 1970s (Lindquist et al, 1999). "Targeted medical events" are similar but refer to events based on clinical/ pharmacological characteristics specific to a drug, its treatment indication(s), and to such factors as may be monitored in a similar fashion for specific products.…”

Section: "Risk" Estimates From Spontaneous Reportsmentioning

confidence: 99%

“…Even on a national or international level, reporting rates can be useful for signal detection as long as appropriate caveats are emphasized. Other work on quantitative analysis of spontaneous reports on a global level includes estimation of reporting rates using IMS international sales data as a denominator (Lindquist and Edwards, 1997;Lindquist et al, 1999). Several quantitative approaches to look for trends in reporting rates have been proposed, such as by Norwood and Sampson (1988) and Praus et al (1993).…”

Section: How Many Reports Should Trigger a Signal?mentioning

confidence: 99%

Quantitative Signal Detection and Analysis in Pharmacovigilance

Bate

Pariente

Hauben

et al. 2014

Mann's Pharmacovigilance

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“…The presence of a so-called`critical term'. Critical terms are a subset of the WHO preferred terms, being indicative of serious disease states, which can be regarded as important to follow up [10]. For this reason, critical terms may be of particular interest for signal generation.…”

Section: Factorsmentioning

confidence: 99%

Determinants of signal selection in a spontaneous reporting system for adverse drug reactions

Puijenbroek

Grootheest

Diemont

et al. 2001

Brit J Clinical Pharma

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Aims Detection of new adverse drug reactions (ADR) after marketing is often based on a manual review of reports sent to a Spontaneous Reporting System (SRS). Among the many potential signals that are identi®ed, only a limited number are important enough to require further attention. The goal of this study is to gain insight into factors contributing to the selection and dissemination of possible signals originating from the SRS maintained by the Netherlands Pharmacovigilance Foundation. Methods In a case control design, all signals (n=42) disseminated to the Medicines Evaluation Board from the second quarter of 1997 until the third quarter of 2000, which could be expressed as a combination of a single ATC code and a single WHO preferred term, were included. For each case, four controls were matched in time. Logistic regression analysis was used to investigate the in¯uence of various factors, such as the fact whether the ADR or drug is new, the strength of the association, the seriousness of the reaction and the documentation of the reports. Results Multivariate analysis showed that the presence of a`serious report' (Odds Ratio 3.8, 95% CI 1.3, 11.0), a WHO`critical term' (OR 4.7, 95% CI 1.8, 13), the ADR being unlabelled (OR 6.1, 95% CI 2.3, 16) and the presence of a disproportionate association (OR 3.5, 95% CI 1.4,8) were all independently associated with signal selection. The number of reports and the time after marketing of the drug had no in¯uence. Conclusions This study showed that selection of signals is based on both qualitative and quantitative aspects. Knowledge of these factors may improve the ef®ciency of the underlying signal selection process.

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From association to alert—a revised approach to international signal analysis

Cited by 65 publications

References 0 publications

Pharmacovigilance, signal detection using statistical data mining methods

Pharmacovigilance, signal detection using statistical data mining methods

Quantitative Signal Detection and Analysis in Pharmacovigilance

Determinants of signal selection in a spontaneous reporting system for adverse drug reactions

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