Literature DB >> 12450705

The Brighton Collaboration: addressing the need for standardized case definitions of adverse events following immunization (AEFI).

Jan Bonhoeffer1, Katrin Kohl, Robert Chen, Philippe Duclos, Harald Heijbel, Ulrich Heininger, Tom Jefferson, Elisabeth Loupi.   

Abstract

UNLABELLED: To further scientific progress of immunization safety, comparability of data from clinical trials and surveillance systems is essential. Comparability requires the availability of standardized case definitions for adverse events following immunization (AEFI) and guidelines for case determination, recording and data presentation.
METHOD: International collaborative working groups, consisting of professional volunteers from developed and developing countries, conduct systematic literature reviews to develop 50-100 AEFI definitions. Case definitions are finalized after a comment period by a reference group consisting of organizations concerned with immunization safety, and will be disseminated via the world-wide-web and other means for free world-wide use.
RESULTS: Literature reviews yielded substantial diversity in data collection and presentation. We have developed standardized case definitions together with guidelines for use in clinical trials and surveillance systems.
CONCLUSIONS: Diversity in safety methods leads to considerable loss of scientific information. We have built the necessary international network of currently about 300 participants from patient care, public health, scientific, pharmaceutical, regulatory and professional organizations to develop and assess standardized AEFI case definitions and guidelines. Evaluation studies, global implementation, ongoing definition development and a continuously growing network will be essential for the success of the collaboration.

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Year:  2002        PMID: 12450705     DOI: 10.1016/s0264-410x(02)00449-8

Source DB:  PubMed          Journal:  Vaccine        ISSN: 0264-410X            Impact factor:   3.641


  40 in total

1.  Opportunities and challenges for improving the quality of reporting clinical research: CONSORT and beyond.

Authors:  David Moher; Douglas G Altman; Kenneth F Schulz; Diana R Elbourne
Journal:  CMAJ       Date:  2004-08-17       Impact factor: 8.262

2.  Text mining for the Vaccine Adverse Event Reporting System: medical text classification using informative feature selection.

Authors:  Taxiarchis Botsis; Michael D Nguyen; Emily Jane Woo; Marianthi Markatou; Robert Ball
Journal:  J Am Med Inform Assoc       Date:  2011-06-27       Impact factor: 4.497

3.  Safety profile of the meningococcal conjugate vaccine (Menafrivac™) in clinical trials and vaccination campaigns: a review of published studies.

Authors:  Jerome Ateudjieu; Beat Stoll; Anne Cecile Bisseck; Ayok M Tembei; Blaise Genton
Journal:  Hum Vaccin Immunother       Date:  2019-09-05       Impact factor: 3.452

4.  Evaluation of 'SAEFVIC', A Pharmacovigilance Surveillance Scheme for the Spontaneous Reporting of Adverse Events Following Immunisation in Victoria, Australia.

Authors:  Hazel J Clothier; Nigel W Crawford; Melissa Russell; Heath Kelly; Jim P Buttery
Journal:  Drug Saf       Date:  2017-06       Impact factor: 5.606

5.  Overcoming Barriers and Identifying Opportunities for Developing Maternal Immunizations: Recommendations From the National Vaccine Advisory Committee.

Authors: 
Journal:  Public Health Rep       Date:  2017-04-05       Impact factor: 2.792

6.  The contribution of the vaccine adverse event text mining system to the classification of possible Guillain-Barré syndrome reports.

Authors:  T Botsis; E J Woo; R Ball
Journal:  Appl Clin Inform       Date:  2013-02-27       Impact factor: 2.342

7.  Enhancing the work of the Department of Health and Human Services national vaccine program in global immunization: recommendations of the National Vaccine Advisory Committee: approved by the National Vaccine Advisory Committee on September 12, 2013.

Authors: 
Journal:  Public Health Rep       Date:  2014       Impact factor: 2.792

8.  Automating case definitions using literature-based reasoning.

Authors:  T Botsis; R Ball
Journal:  Appl Clin Inform       Date:  2013-10-30       Impact factor: 2.342

9.  Application of information retrieval approaches to case classification in the vaccine adverse event reporting system.

Authors:  Taxiarchis Botsis; Emily Jane Woo; Robert Ball
Journal:  Drug Saf       Date:  2013-07       Impact factor: 5.606

10.  Incidence of adverse events among healthcare workers following H1N1 Mass immunization in Ghana: a prospective study.

Authors:  Daniel N A Ankrah; Aukje K Mantel-Teeuwisse; Marie L De Bruin; Philip K Amoo; Charles N Ofei-Palm; Irene Agyepong; Hubert G M Leufkens
Journal:  Drug Saf       Date:  2013-04       Impact factor: 5.606

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