Numbers of spontaneous reports: How to use and interpret?

Abstract

Due to the high intensity of the COVID-19 vaccination campaigns and heightened attention for safety issues, the number of spontaneous reports has surged. In the Netherlands, pharmacovigilance centre Lareb has received more than 100 000 reports on adverse events following immunization (AEFI) associated with Covid-19 vaccination. It is tempting to interpret absolute numbers of reports of AEFIs in signal detection. Signal detection of spontaneously reported adverse drug reactions has its origin in case-by-case analysis, where all case reports are assessed by clinically qualified assessors. The concept of clinical review of cases—even if only a few per country—followed by sharing concerns of suspicions of potential adverse reactions again proved the strength of the system. Disproportionality analysis can be useful in signal identification, and comparing reported cases with expected based on background incidence can be useful to support signal detection. However, they cannot be used without an in-depth analysis of the underlying clinical data and pharmacological mechanism. This in-depth analysis has been performed, and is ongoing, for the signal of vaccine-induced immune thrombotic thrombocytopenia (VITT) in relation to the AstraZeneca and Janssen Covid-19 vaccines. Although not frequency or incidence rates, reporting rates can provide an impression of the occurrence of the event. But the unknown underreporting should also be part of this context. To quantify the incidence rates, follow-up epidemiological studies are needed.