Literature DB >> 15521907

Drug-induced pancreatitis: lessons in data mining.

Manfred Hauben, Lester Reich.   

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Year:  2004        PMID： 15521907      PMCID： PMC1884633          DOI： 10.1111/j.1365-2125.2004.02203.x

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


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  9 in total

1.  Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports.

Authors:  S J Evans; P C Waller; S Davis
Journal:  Pharmacoepidemiol Drug Saf       Date:  2001 Oct-Nov       Impact factor: 2.890

2.  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.

Authors:  Ana Szarfman; Stella G Machado; Robert T O'Neill
Journal:  Drug Saf       Date:  2002       Impact factor: 5.606

3.  Application of quantitative signal detection in the Dutch spontaneous reporting system for adverse drug reactions.

Authors:  Eugène van Puijenbroek; Willem Diemont; Kees van Grootheest
Journal:  Drug Saf       Date:  2003       Impact factor: 5.606

Review 4.  A brief primer on automated signal detection.

Authors:  Manfred Hauben
Journal:  Ann Pharmacother       Date:  2003 Jul-Aug       Impact factor: 3.154

5.  A Bayesian neural network method for adverse drug reaction signal generation.

Authors:  A Bate; M Lindquist; I R Edwards; S Olsson; R Orre; A Lansner; R M De Freitas
Journal:  Eur J Clin Pharmacol       Date:  1998-06       Impact factor: 2.953

Review 6.  False-positives in spontaneous reporting: should we worry about them?

Authors:  B Begaud; Y Moride; P Tubert-Bitter; A Chaslerie; F Haramburu
Journal:  Br J Clin Pharmacol       Date:  1994-11       Impact factor: 4.335

7.  Spontaneous reports on drug-induced pancreatitis in Denmark from 1968 to 1999.

Authors:  V Andersen; J Sonne; M Andersen
Journal:  Eur J Clin Pharmacol       Date:  2001-09       Impact factor: 2.953

8.  Drug-associated acute pancreatitis: twenty-one years of spontaneous reporting in The Netherlands.

Authors:  I A Eland; E P van Puijenbroek; M J Sturkenboom; J H Wilson; B H Stricker
Journal:  Am J Gastroenterol       Date:  1999-09       Impact factor: 10.864

9.  Discrepancies between population-based data and adverse reaction reports in assessing drugs as causes of acute pancreatitis.

Authors:  R J Lancashire; K Cheng; M J S Langman
Journal:  Aliment Pharmacol Ther       Date:  2003-04-01       Impact factor: 8.171
  9 in total
  18 in total

1.  What Is the Plural of a 'Yellow' Anecdote?

Authors:  Stephen J W Evans
Journal:  Drug Saf       Date:  2016-01       Impact factor: 5.606

2.  A case report of rhabdomyolysis with pentamidine that prompted a retrospective evaluation of a pharmacovigilance tool under investigation.

Authors:  Menfred Hauben; Lester Reich
Journal:  Br J Clin Pharmacol       Date:  2004-12       Impact factor: 4.335

3.  Data mining in pharmacovigilance: the need for a balanced perspective.

Authors:  Manfred Hauben; Vaishali Patadia; Charles Gerrits; Louisa Walsh; Lester Reich
Journal:  Drug Saf       Date:  2005       Impact factor: 5.606

Review 4.  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

5.  Reply: The evaluation of data mining methods for the simultaneous and systematic detection of safety signals in large databases: lessons to be learned.

Authors:  Jonathan G Levine; Joseph M Tonning; Ana Szarfman
Journal:  Br J Clin Pharmacol       Date:  2006-01       Impact factor: 4.335

6.  Potential use of data-mining algorithms for the detection of 'surprise' adverse drug reactions.

Authors:  Manfred Hauben; Sebastian Horn; Lester Reich
Journal:  Drug Saf       Date:  2007       Impact factor: 5.606

7.  Comparative performance of two quantitative safety signalling methods: implications for use in a pharmacovigilance department.

Authors:  June S Almenoff; Karol K LaCroix; Nancy A Yuen; David Fram; William DuMouchel
Journal:  Drug Saf       Date:  2006       Impact factor: 5.606

8.  Gold standards in pharmacovigilance: the use of definitive anecdotal reports of adverse drug reactions as pure gold and high-grade ore.

Authors:  Manfred Hauben; Jeffrey K Aronson
Journal:  Drug Saf       Date:  2007       Impact factor: 5.606

9.  Response to "Comment on: Botulinum Toxin Type A Overdoses: Analysis of the FDA Adverse Event Reporting System Database".

Authors:  Rashid Kazerooni; Edward P Armstrong
Journal:  Clin Drug Investig       Date:  2018-12       Impact factor: 2.859

10.  Safety related drug-labelling changes: findings from two data mining algorithms.

Authors:  Manfred Hauben; Lester Reich
Journal:  Drug Saf       Date:  2004       Impact factor: 5.606
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