Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Department of Neurology and Multiple Sclerosis Research Center, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Pharmacoepidemiol Drug Saf. 2021 May;30(5):602-609. doi: 10.1002/pds.5196. Epub 2021 Feb 23.
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).
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.
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.
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.
流感疫苗接种后很少发生严重不良事件（AE），如吉兰-巴雷综合征（GBS）。我们使用美国疫苗不良事件报告系统（VAERS）报告，鉴定与 GBS 高度相关的 AE，并开发三价流感疫苗（FLU3）接种后 GBS 的预测模型。
本研究分析了 1990 年至 2017 年美国 VAERS 中的 80059 份报告。确定了一些与 GBS 高度相关的 AE，并用于开发预测模型。一些常见的轻度 AE ，当 GBS 同时发生时，怀疑报告不足，因此从最终模型中删除。使用欧洲流感疫苗 AE 数据在 EudraVigilance 中对分析进行了验证。
在 80059 份报告中，有 1185 份（1.5%）被注释为与 GBS 相关。确定了 24 种与 GBS 有强烈关联的 AE。使用年龄、性别和所有 24 种 AE 的完整预测模型，其接收者操作特征（ROC）曲线下面积（AUC）为 85.4%（90%CI：[83.8%，86.9%]）。排除 9 种（如瘙痒、皮疹、注射部位疼痛）可能报告不足的 AE 后，最终 AUC 为 77.5%（90%CI：[75.5%，79.6%]）。201 份（0.25%）报告被预测为 GBS 高风险（预测概率>25%），84 份实际发生 GBS。
预测性能表明利用 VAERS 队列开发风险预测模型的潜力。排除可能报告不足的 AE 牺牲了一些预测能力，但使模型更具可解释性和可行性。即使是少数 AE 组合的高绝对风险也表明在 VAERS 数据集中进行 GBS 预测的前景。
