Benefits and strengths of the disproportionality analysis for identification of adverse drug reactions in a pharmacovigilance database.

Adverse drug reactions (ADRs) represent an important medical issue: they result in 3–7% of all hospital admissions and are associated with a substantial increase in morbidity and mortality. Numerous methods can be used to investigate ADRs. Each has its strengths and weakness. The insufficiencies of basic (experimental) pharmacology as well as clinical trials for studying ADRs are well known. Animal physiology often differs from that of humans. Clinical trials, although necessary, do not allow definite conclusions, because they are built to evaluate efficacy more than safety. Thus, spontaneous notifications remain the cornerstone for ADRs despite their mandatory limitations (under-reporting, selective reporting, lack of denominator etc.). Intensive studies could allow quantification of a specific problem of drug safety (i.e. drug admission into hospital for ADRs). For some years, several pharmacoepidemiological methods have been used to identify and also to quantify ADRs. Among thesse methods, case–control or cohort studies are most widely used. However, their setting up requires specific organization, delay, money and also use of large databases, which are not often specifically built for evaluation of ADRs. In the present issue of the journal, clinical pharmacologists and pharmacoepidemiologists from Poitiers University Hospital (France) have used another method, working from the French PharmacoVigilance database. They used disproportionality analysis for identification of memory disorders associated with drugs [1]. The present paper discusses the benefits and strengths of this method.