Change search
ReferencesLink to record
Permanent link

Direct link
Outlier removal to uncover patterns in adverse drug reaction surveillance - a simple unmasking strategy
Stockholm University, Faculty of Science, Department of Mathematics. Third Military Medical University, China.
Stockholm University, Faculty of Science, Department of Mathematics. Uppsala Monitoring Centre.
2013 (English)In: Pharmacoepidemiology and Drug Safety, ISSN 1053-8569, E-ISSN 1099-1557, Vol. 22, no 10, 1119-1129 p.Article in journal (Refereed) Published
Abstract [en]

PurposeThis study aimed to develop an algorithm for uncovering associations masked by extreme reporting rates, characterize the occurrence of masking by influential outliers in two spontaneous reporting databases and evaluate the impact of outlier removal on disproportionality analysis. MethodsWe propose an algorithm that identifies influential outliers and carries out parallel analysis after their omission. It considers masking of drugs as well as of adverse drug reactions (ADRs), uses a direct measure of the masking effect and makes no assumptions regarding the number of outliers per drug or ADR. The occurrence of masking is characterized in the WHO Global Individual Case Safety Report database, VigiBase and a regional collection of reports from Shanghai, China. ResultsFor WHO-ART critical terms such as myocardial infarction, rhabdomyolysis and hypoglycaemia outlier removal led to a 25-50% increase in the number of Statistics of Disproportionate Reporting (SDR) and gains in time to detection of 1-2years, while keeping the rate of spurious SDRs from the parallel analysis at 1%. Twenty-three per cent of VigiBase and 18% of Shanghai SRS reports listed an influential outlier. Twenty-seven per cent of the ADRs and 5% of the drugs in VigiBase, and 2% of the ADRs and 3% of the drugs in Shanghai SRS were involved in an outlier. The overall increase in the number of SDRs for both datasets was 3%. ConclusionMasking by outliers has substantial impact on specific ADRs including, in VigiBase, rhabdomyolysis, myocardial infarction and hypoglycaemia. It is a local phenomenon involving a fair number of reports but yielding a limited number of additional SDRs.

Place, publisher, year, edition, pages
2013. Vol. 22, no 10, 1119-1129 p.
Keyword [en]
adverse drug reactions, disproportionality analysis, outliers, masking, statistical shrinkage, competition bias, pharmacoepidemiology
National Category
Pharmaceutical Sciences Mathematics
URN: urn:nbn:se:su:diva-95764DOI: 10.1002/pds.3474ISI: 000325146100013OAI: diva2:661999


Available from: 2013-11-05 Created: 2013-11-04 Last updated: 2013-11-05Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text
By organisation
Department of Mathematics
In the same journal
Pharmacoepidemiology and Drug Safety
Pharmaceutical SciencesMathematics

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 54 hits
ReferencesLink to record
Permanent link

Direct link