Dataset Information

Prediction of post-vaccination Guillain-Barre syndrome using data from a passive surveillance system.

ABSTRACT:

Purpose

Severe adverse events (AEs), such as Guillain-Barré syndrome (GBS) occur rarely after influenza vaccination. We identify highly associated AEs with GBS and develop prediction models for GBS using the US Vaccine Adverse Event Reporting System (VAERS) reports following trivalent influenza vaccination (FLU3).

Methods

This study analyzed 80 059 reports from the US VAERS between 1990 and 2017. Several AEs were identified as highly associated with GBS and were used to develop the prediction model. Some common and mild AEs that were suspected to be underreported when GBS occurred simultaneously were removed from the final model. The analyses were validated using European influenza vaccine AEs data from EudraVigilance.

Results

Of the 80 059 reports, 1185 (1.5%) were annotated as GBS related. Twenty-four AEs were identified as having strong association with GBS. The full prediction model, using age, sex, and all 24 AEs achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 85.4% (90% CI: [83.8%, 86.9%]). After excluding the nine (e.g., pruritus, rash, injection site pain) likely underreported AEs, the final AUC became 77.5% (90% CI: [75.5%, 79.6%]). Two hundred and one (0.25%) reports were predicted as of high risk of GBS (predicted probability >25%) and 84 actually developed GBS.

Conclusion

The prediction performance demonstrated the potential of developing risk-prediction models utilizing the VAERS cohort. Excluding the likely underreported AEs sacrificed some prediction power but made the model more interpretable and feasible. The high absolute risk of even a small number of AE combinations suggests the promise of GBS prediction within the VAERS dataset.

SUBMITTER: Luo C

PROVIDER: S-EPMC8014460 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundGuillain-Barré syndrome (GBS) is an acute inflammatory neuropathy with a heterogeneous presentation. Although some evidences support the role of autoantibodies in its pathogenesis, the target antigens remain unknown in a substantial proportion of GBS patients. The objective of this study is to screen for autoantibodies targeting peripheral nerve components in Guillain-Barré syndrome.MethodsAutoantibody screening was performed in serum samples from all GBS patients included in the International GBS Outcome study by 11 different Spanish centres. The screening included testing for anti-ganglioside antibodies, anti-nodo/paranodal antibodies, immunocytochemistry on neuroblastoma-derived human motor neurons and murine dorsal root ganglia (DRG) neurons, and immunohistochemistry on monkey peripheral nerve sections. We analysed the staining patterns of patients and controls. The prognostic value of anti-ganglioside antibodies was also analysed.ResultsNone of the GBS patients (n = 100) reacted against the nodo/paranodal proteins tested, and 61 (61%) were positive for, at least, one anti-ganglioside antibody. GBS sera reacted strongly against DRG neurons more frequently than controls both with IgG (6% vs 0%; p = 0.03) and IgM (11% vs 2.2%; p = 0.02) immunodetection. No differences were observed in the proportion of patients reacting against neuroblastoma-derived human motor neurons. Reactivity against monkey nerve tissue was frequently detected both in patients and controls, but specific patterns were only detected in GBS patients: IgG from 13 (13%) patients reacted strongly against Schwann cells. Finally, we confirmed that IgG anti-GM1 antibodies are associated with poorer outcomes independently of other known prognostic factors.ConclusionOur study confirms that (1) GBS patients display a heterogeneous repertoire of autoantibodies targeting nerve cells and structures; (2) gangliosides are the most frequent antigens in GBS patients and have a prognostic value; (3) further antigen-discovery experiments may elucidate other potential antigens in GBS.