Background: In spontaneous reporting databases, reports of well-established drug-event associations may mask alerts that arise from other drugs (drug competition bias). However, a symmetrical event-competition bias has not yet been explored whereby known events may mask an association with new events for a given drug or drug class.
Objective: The objective of this study was to explore the effects of event-competition bias on safety signals generated from spontaneous reporting databases.
Methods: The drug classes tested included statins, oral anticoagulants, antipsychotics and HIV antiretrovirals. For each, a type A reaction was selected, and its potential competitive effect on the generation of other safety signals for the drug was explored. These were rhabdomyolysis/myopathy for statins, haemorrhage for oral anticoagulants, extrapyramidal syndrome for antipsychotics and lipodystrophy for HIV antiretrovirals. Signals of disproportionate reporting (SDRs) were detected using the case/non-case approach in the French research spontaneous reporting database (which contains reports from 1 January 1986 to 31 December 2001), before and after removing all reports concerning these competitor events. SDRs were considered as potential signals if not reported in the literature before 1 January 2002 but confirmed since.
Results: The whole database included 207,236 reports, 4,355 of which included statins as one of the suspected drugs. The removal of reports of rhabdomyolysis/myopathy concerned 8,425 reports among which 867 involved statins. After this removal, 11 new SDRs appeared for statins that had not been detected initially. Similarly, 15 SDRs were unmasked for oral anticoagulants, six for antipsychotics and nine for HIV antiretrovirals. After literature-based assessment, five of the 41 unmasked SDRs appeared related to potential safety signals confirmed after 2002.
Conclusion: This study demonstrated that a masking phenomenon resulting from an event-competition effect could occur when performing signal detection using disproportionality analyses of spontaneous reporting databases. This should be taken into account when routine signal detection is performed.