Work

Evaluating COVID-19 Vaccine Masking and Unmasking Methods in Two National Pharmacovigilance Databases

Year: 2026

Type: article

Abstract: BACKGROUND: The COVID-19 mass vaccination led to a substantial increase in spontaneous reports submitted to pharmacovigilance (PV) databases, potentially introducing masking effects that could conceal safety signals. OBJECTIVES: To examine the masking effect of COVID-19 vaccines on disproportionality analyses and to compare two unmasking interventions in the Dutch (Lareb database) and Spanish (Farmacovigilancia Española, Datos de Reacciones Adversas, FEDRA) national PV databases: removal of all drug-event combinations (DEC) involving a COVID-19 vaccine versus excluding influential outliers DECs only. METHODS: The masking effect was explored retrospectively on the basis of the number of signals of disproportionate reporting (SDR). DECs involving a COVID-19 vaccine were excluded using crude and outlier techniques, and reporting odds ratios were recalculated. Subsets of important medical events (IME) were analysed in both databases. RESULTS: Both crude and influential outlier removal methods led to reductions in the number of reports, DECs and SDRs. Both in the Lareb database and FEDRA, crude removal excluded 2.1% of DECs, while the outlier method excluded 0.1%. Crude removal had a greater impact on SDRs, reducing them by 9.8% in the Lareb database and 3.9% in FEDRA, compared with 5.7% and 1.1% with the outlier method. In the Lareb database, 1301 SDRs (20 IME-related) were unmasked using crude removal, and 1942 (95 IME-related) with the outlier method. FEDRA showed 1453 and 1226 SDRs unmasked, including 41 and 70 IME-related. CONCLUSIONS: COVID-19 vaccines caused substantial masking in both databases. Both strategies effectively revealed new SDRs, though their impact varied. The choice of approach should be tailored to the database context.

Source: Drug Safety

DOI: 10.1007/s40264-025-01644-4