Abstract
Background
Adverse event reports of glomerular diseases (GDs) following coronavirus disease 2019 (COVID-19) vaccination collected nationally have been shared to VigiBase, the global database of adverse event reports for medicines and vaccines. From literature reports, different GDs following COVID-19 vaccination have different time-to-onsets (TTOs), highlighting the potential value of TTO in suggesting underlying disease mechanisms and supporting its relevance in signal validation prior to in-depth signal assessment.Objective
The aim of this study was to characterise the TTO in reports of GDs in association with COVID-19 vaccines inVigiBase. The analysis focuses on exploring the value of TTO for signal validation, an early step preceding signal assessment.Methods
Reports for four different GDs in association with COVID-19 vaccines were extracted from VigiBase on 3 April, 2023. The reports were de-duplicated and TTO information was manually verified. Demographics and clinical characteristics were summarised per GD. The median TTO was compared between GDs and by disease status (relapse and new onset cases) within each GD.Results
In the extracted data, 245 unique cases shared to VigiBase and containing information about both TTO and disease status for the four selected GDs in association with COVID-19 vaccines were identified. Reports for IgA nephropathy represented the majority (49%). Most of the GD cases concerned messenger RNA COVID-19 vaccines (84%) and most occurred following the second dose (54%). Differences in median TTO between the four GDs as well as between disease status within the GDs were observed. However, except between IgA nephropathy and the other three GDs, these differences were not statistically significant.Conclusions
This study explores TTO differences for four different GDs following COVID-19 vaccination, taking new onset or relapse cases into account. The study demonstrates how review and characterisation of TTO data can complement traditional disproportionality analysis in the early stage of signal validation. The presented hypothesis will require further investigation.