Assessing the extent and impact of the masking effect of disproportionality analyses on two spontaneous reporting systems databases.
BACKGROUND
Masking is a statistical issue by which signals are hidden by the presence of other medicines in the database. In the absence algorithm, the impact of the masking effect has not been fully investigated.


OBJECTIVE
Our study is aimed at assessing the extent and the impact of the masking effect on two large spontaneous reporting databases.


METHODS
Cross sectional study using a set of terms of importance for public health in two spontaneous reporting databases.


METHODS
The analyses were performed on EudraVigilance (EV) and the Pfizer spontaneous reporting database (PfDB).


METHODS
Using the masking ratio, we have identified and removed the products inducing the highest masking effect.


RESULTS
Studying a total of almost 50 000 drug-event combinations masking had an impact on approximately 60% of drug-event combinations were masked by another product with a masking ratio >1 in EV and 84% in PfDB. The prevalence of important masking was quite rare (0.003% of the DECs) and mainly affected events rarely reported in EV. The products involved in the highest masking effects are products known to induce the reaction. The removal of the masking effect of the highest masking product has revealed 974 signals of disproportionate reporting in EV including true signals. The study shows that the original ranking provided by the quantitative methods included in our study is marginally affected by the removal of the masking product.


CONCLUSIONS
Our study suggests that significant masking is rare in large spontaneous databases and mostly affects events rarely reported in EV.
European Medicines Agency, London, UK.
Francois
F
Maignen
Manfred
M
Hauben
Eric
E
Hung
Lionel
L
Van Holle
Jean-Michel
JM
Dogne
D016907:Adverse Drug Reaction Reporting Systems / Q000706:statistics & numerical data*; D000465:Algorithms; D003430:Cross-Sectional Studies; D003627:Data Interpretation, Statistical; D016208:Databases, Factual / Q000706:statistics & numerical data*; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D006801:Humans; D017891:Pharmacoepidemiology / Q000379:methods*; D060735:Pharmacovigilance; D011634:Public Health
EudraVigilance; disproportionality analysis; masking; pharmacoepidemiology; proportional reporting ratio; public health; signal detection