| アブストラクト | Background/Objectives: Post-market surveillance of COVID-19 vaccines is vital. This study analyzed EudraVigilance data (Jan 2021-Dec 2023) to detect potential safety signals linking COVID-19 vaccines and specific neurological adverse events (aseptic meningitis, Guillain-Barre syndrome, polyradiculoneuropathies, multiple sclerosis, transverse myelitis, neuromyelitis optica). It also explored the impact of non-healthcare professional reports on disproportionality analysis. Methods: EudraVigilance reports were analyzed to quantify neurological events for 5 COVID-19 vaccines and 47 comparators. Disproportionality was assessed using the Proportional Reporting Ratio (PRR). Spearman's correlation (SCC) was used to examine the impact of non-healthcare professional reports on PRR. Results: An analysis of 4,159,820 COVID-19 vaccine and 114,025 comparator reports showed a reporting decline over time. A higher proportion of adverse drug event reports were submitted by non-healthcare professionals for COVID-19 vaccines compared to control vaccines, a trend observed consistently across 2021 (57.3% vs. 33%, p < 0.001), 2022 (59.4% vs. 36.5%, p = 0.001), and 2023 (42% vs. 24.36%, p = 0.006). In 2023, significant signals (PRR >/= 2) were found between Jcovden(c) and polyradiculoneuropathy (PRR 5.4, IC 95% 3.98-7.32), multiple sclerosis (PRR 2.72, IC 95% (1.08-6.87), transverse myelitis (PRR 4.68, IC 95% 1.02-21.35) and neuromyelitis optica (PRR 7.79, IC 95% 3.5-17.37). In addition, both Spikevax(c) and Comirnaty(c) showed significant signals with multiple sclerosis (PRR 2.50, IC 95% 1.70-3.68, and PRR 2.33, IC 95% 1.68-3.24) and transverse myelitis (PRR 3.50, IC 95% 1.66-7.50 and PRR 3.58, IC 95% 1.85-6.93). A significant negative correlation between the proportion of reports from non-healthcare professionals and the case/no-case ratio was found (SCC = -0.4683, p = 0.009). Conclusions: While some significant signals emerged in 2023, the combined three-year data showed no vaccine exceeding the PRR threshold of 2. High-quality data and bias mitigation strategies are crucial for accurate PRR estimation in pharmacovigilance and public health. |
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| 投稿者 | Lopez de Las Huertas, Arturo Gomez; Stewart, Stefan; Elizalde, Mikel Urroz; Guijarro-Eguinoa, Javier; Seco-Meseguer, Enrique; Diago-Sempere, Elena; Gonzalez, Maria Jimenez; Carcas-Sansuan, Antonio J; Perez, Alberto M Borobia; Ramirez, Elena |
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| 組織名 | Clinical Pharmacology Department, La Paz University Hospital-IdiPAZ, School of;Medicine, Autonomous University of Madrid, 28046 Madrid, Spain.;Clinical Trials Unit, La Paz University Hospital-IdiPAZ, 28046 Madrid, Spain. |
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