Document Detail

Effect of reporting bias in the analysis of spontaneous reporting data.
MedLine Citation:
PMID:  25376637     Owner:  NLM     Status:  Publisher    
It is well-known that a spontaneous reporting system suffers from significant under-reporting of adverse drug reactions from the source population. The existing methods do not adjust for such under-reporting for the calculation of measures of association between a drug and the adverse drug reaction under study. Often there is direct and/or indirect information on the reporting probabilities. This work incorporates the reporting probabilities into existing methodologies, specifically to Bayesian confidence propagation neural network and DuMouchel's empirical Bayesian methods, and shows how the two methods lead to biased results in the presence of under-reporting. Considering all the cases to be reported, the association measure for the source population can be estimated by using only exposure information through a reference sample from the source population. Copyright © 2014 John Wiley & Sons, Ltd.
Palash Ghosh; Anup Dewanji
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2014-11-6
Journal Detail:
Title:  Pharmaceutical statistics     Volume:  -     ISSN:  1539-1612     ISO Abbreviation:  Pharm Stat     Publication Date:  2014 Nov 
Date Detail:
Created Date:  2014-11-7     Completed Date:  -     Revised Date:  2014-11-8    
Medline Journal Info:
Nlm Unique ID:  101201192     Medline TA:  Pharm Stat     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2014 John Wiley & Sons, Ltd.
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