Evidence map›Paper›PMID 41501319›Full record

ArticleDrug safety2026

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

Oskar Rachwal, Mar Gutiérrez-Lobón, Nuria Sols Cueto, Araceli Nuñez Ventura, Cristina Fernández-Fernández, Florence P A M van Hunsel, Joep H G Scholl, María Gordillo-Marañón, Eugène P van Puijenbroek

Abstract read
In one paragraph

Article in Drug safety, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Oskar RachwalGroningen Research Institute of Pharmacy, PharmacoTherapy, -Epidemiology and -Economics, University of Groningen, Groningen, The Netherlands.ORCID http://orcid.org/0009-0005-9793-4356
Mar Gutiérrez-LobónRisk Identification Unit, Pharmacoepidemiology and Pharmacovigilance Division, Spanish Agency of Medicines and Medical Devices, Madrid, Spain.ORCID http://orcid.org/0009-0001-2905-2475
Nuria Sols CuetoRisk Identification Unit, Pharmacoepidemiology and Pharmacovigilance Division, Spanish Agency of Medicines and Medical Devices, Madrid, Spain.ORCID http://orcid.org/0009-0009-0436-0242
Araceli Nuñez VenturaRisk Identification Unit, Pharmacoepidemiology and Pharmacovigilance Division, Spanish Agency of Medicines and Medical Devices, Madrid, Spain.ORCID http://orcid.org/0009-0006-4998-214X
Cristina Fernández-FernándezRisk Identification Unit, Pharmacoepidemiology and Pharmacovigilance Division, Spanish Agency of Medicines and Medical Devices, Madrid, Spain.ORCID http://orcid.org/0000-0001-7992-8933
Florence P A M van HunselGroningen Research Institute of Pharmacy, PharmacoTherapy, -Epidemiology and -Economics, University of Groningen, Groningen, The Netherlands.ORCID http://orcid.org/0000-0001-8965-3224
Joep H G SchollPharmacovigilance Centre Lareb, 's-Hertogenbosch, The Netherlands.ORCID http://orcid.org/0000-0002-9222-5965
María Gordillo-MarañónRisk Identification Unit, Pharmacoepidemiology and Pharmacovigilance Division, Spanish Agency of Medicines and Medical Devices, Madrid, Spain.ORCID http://orcid.org/0000-0003-2993-6577
Eugène P van PuijenbroekGroningen Research Institute of Pharmacy, PharmacoTherapy, -Epidemiology and -Economics, University of Groningen, Groningen, The Netherlands. e.p.van.puijenbroek@rug.nl.ORCID http://orcid.org/0000-0002-2236-1398

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

objectivesTo 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.

methodsThe 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.

resultsBoth 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.

conclusionsCOVID-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.

Indexed as

Adverse Drug Reaction Reporting SystemsCOVID-19COVID-19 VaccinesDatabases, FactualPharmacovigilanceHumansNetherlandsRetrospective StudiesSpainCOVID-19 Vaccines

Identifiers

PMID41501319
PMCPMC13086669

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.