Literature DB >> 15317032

The reporting odds ratio versus the proportional reporting ratio: 'deuce'.

Patrick Waller, Eugène van Puijenbroek, Antoine Egberts, Stephen Evans.   

Abstract

Mesh:

Year:  2004        PMID: 15317032     DOI: 10.1002/pds.1002

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


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  21 in total

1.  An Empirical Approach to Explore the Relationship Between Measures of Disproportionate Reporting and Relative Risks from Analytical Studies.

Authors:  Miguel-Angel Maciá-Martínez; Francisco J de Abajo; Gilly Roberts; Jim Slattery; Bharat Thakrar; Antoni F Z Wisniewski
Journal:  Drug Saf       Date:  2016-01       Impact factor: 5.606

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

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

Review 3.  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

Review 4.  Update on Cardiovascular Safety of Tyrosine Kinase Inhibitors: With a Special Focus on QT Interval, Left Ventricular Dysfunction and Overall Risk/Benefit.

Authors:  Rashmi R Shah; Joel Morganroth
Journal:  Drug Saf       Date:  2015-08       Impact factor: 5.606

5.  Detection of signals of abuse and dependence applying disproportionality analysis.

Authors:  V Pauly; M Lapeyre-Mestre; D Braunstein; M Rueter; X Thirion; E Jouanjus; J Micallef
Journal:  Eur J Clin Pharmacol       Date:  2014-11-20       Impact factor: 2.953

6.  A Comparison Study of Algorithms to Detect Drug-Adverse Event Associations: Frequentist, Bayesian, and Machine-Learning Approaches.

Authors:  Minh Pham; Feng Cheng; Kandethody Ramachandran
Journal:  Drug Saf       Date:  2019-06       Impact factor: 5.606

7.  A potential event-competition bias in safety signal detection: results from a spontaneous reporting research database in France.

Authors:  Francesco Salvo; Florent Leborgne; Frantz Thiessard; Nicholas Moore; Bernard Bégaud; Antoine Pariente
Journal:  Drug Saf       Date:  2013-07       Impact factor: 5.606

8.  The past, present and perhaps future of pharmacovigilance: homage to Folke Sjoqvist.

Authors:  Nicholas Moore
Journal:  Eur J Clin Pharmacol       Date:  2013-05-03       Impact factor: 2.953

9.  Performance of pharmacovigilance signal-detection algorithms for the FDA adverse event reporting system.

Authors:  R Harpaz; W DuMouchel; P LePendu; A Bauer-Mehren; P Ryan; N H Shah
Journal:  Clin Pharmacol Ther       Date:  2013-02-11       Impact factor: 6.875

Review 10.  Data mining of the public version of the FDA Adverse Event Reporting System.

Authors:  Toshiyuki Sakaeda; Akiko Tamon; Kaori Kadoyama; Yasushi Okuno
Journal:  Int J Med Sci       Date:  2013-04-25       Impact factor: 3.738

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