Evidence map›Paper›PMID 16231953›Full record

ReviewDrug safety2005

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

June Almenoff, Joseph M Tonning, A Lawrence Gould, Ana Szarfman, Manfred Hauben, Rita Ouellet-Hellstrom, Robert Ball, Ken Hornbuckle, Louisa Walsh, Chuen Yee and 8 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in Drug safety, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

93 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  20. Social Media Analytics for Pharmacovigilance of Antiepileptic Drugs.Computational and mathematical methods in medicine · 2022
    Article

33 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

June AlmenoffGlaxoSmithKline, Research Triangle Park, North Carolina, USA. june.s.almenoff@gsk.com
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

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last 5 years, regulatory agencies and drug monitoring centres have been developing computerised data-mining methods to better identify reporting relationships in spontaneous reporting databases that could signal possible adverse drug reactions. At present, there are no guidelines or standards for the use of these methods in routine pharmaco-vigilance. In 2003, a group of statisticians, pharmaco-epidemiologists and pharmaco-vigilance professionals from the pharmaceutical industry and the US FDA formed the Pharmaceutical Research and Manufacturers of America-FDA Collaborative Working Group on Safety Evaluation Tools to review best practices for the use of these methods.In this paper, we provide an overview of: (i) the statistical and operational attributes of several currently used methods and their strengths and limitations; (ii) information about the characteristics of various postmarketing safety databases with which these tools can be deployed; (iii) analytical considerations for using safety data-mining methods and interpreting the results; and (iv) points to consider in integration of safety data mining with traditional pharmaco-vigilance methods. Perspectives from both the FDA and the industry are provided. Data mining is a potentially useful adjunct to traditional pharmaco-vigilance methods. The results of data mining should be viewed as hypothesis generating and should be evaluated in the context of other relevant data. The availability of a publicly accessible global safety database, which is updated on a frequent basis, would further enhance detection and communication about safety issues.

Indexed as

Adverse Drug Reaction Reporting SystemsDatabases, FactualData CollectionDrug IndustryHumansInformation Storage and RetrievalProduct Surveillance, PostmarketingTerminology as TopicUnited StatesUnited States Food and Drug Administration

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.