PMID- 33533072
OWN - NLM
STAT- MEDLINE
DCOM- 20211118
LR  - 20221005
IS  - 1099-1557 (Electronic)
IS  - 1053-8569 (Print)
IS  - 1053-8569 (Linking)
VI  - 30
IP  - 5
DP  - 2021 May
TI  - Prediction of post-vaccination Guillain-Barre syndrome using data from a passive 
      surveillance system.
PG  - 602-609
LID - 10.1002/pds.5196 [doi]
AB  - PURPOSE: Severe adverse events (AEs), such as Guillain-Barre 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.
CI  - (c) 2021 John Wiley & Sons Ltd.
FAU - Luo, Chongliang
AU  - Luo C
AUID- ORCID: 0000-0003-3682-9454
AD  - Department of Biostatistics, Epidemiology and Informatics, University of 
      Pennsylvania, Philadelphia, Pennsylvania, USA.
FAU - Jiang, Ying
AU  - Jiang Y
AD  - Department of Neurology and Multiple Sclerosis Research Center, The Third 
      Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
FAU - Du, Jingcheng
AU  - Du J
AD  - School of Biomedical Informatics, The University of Texas Health Science Center 
      at Houston, Houston, Texas, USA.
FAU - Tong, Jiayi
AU  - Tong J
AD  - Department of Biostatistics, Epidemiology and Informatics, University of 
      Pennsylvania, Philadelphia, Pennsylvania, USA.
FAU - Huang, Jing
AU  - Huang J
AD  - Department of Biostatistics, Epidemiology and Informatics, University of 
      Pennsylvania, Philadelphia, Pennsylvania, USA.
FAU - Lo Re, Vincent 3rd
AU  - Lo Re V 3rd
AD  - Department of Biostatistics, Epidemiology and Informatics, University of 
      Pennsylvania, Philadelphia, Pennsylvania, USA.
FAU - Ellenberg, Susan S
AU  - Ellenberg SS
AD  - Department of Biostatistics, Epidemiology and Informatics, University of 
      Pennsylvania, Philadelphia, Pennsylvania, USA.
FAU - Poland, Gregory A
AU  - Poland GA
AD  - Mayo Clinic Vaccine Research Group, Mayo Clinic, Rochester, Minnesota, USA.
FAU - Tao, Cui
AU  - Tao C
AD  - School of Biomedical Informatics, The University of Texas Health Science Center 
      at Houston, Houston, Texas, USA.
FAU - Chen, Yong
AU  - Chen Y
AD  - Department of Biostatistics, Epidemiology and Informatics, University of 
      Pennsylvania, Philadelphia, Pennsylvania, USA.
LA  - eng
PT  - Journal Article
DEP - 20210223
PL  - England
TA  - Pharmacoepidemiol Drug Saf
JT  - Pharmacoepidemiology and drug safety
JID - 9208369
RN  - 0 (Influenza Vaccines)
SB  - IM
MH  - Adverse Drug Reaction Reporting Systems/*statistics & numerical data
MH  - Female
MH  - *Guillain-Barre Syndrome/chemically induced/diagnosis/epidemiology
MH  - Humans
MH  - Influenza Vaccines/administration & dosage/*adverse effects
MH  - Influenza, Human/*prevention & control
MH  - Male
MH  - United States/epidemiology
MH  - Vaccination/adverse effects
PMC - PMC8014460
OTO - NOTNLM
OT  - Guillain-Barre syndrome
OT  - VAERS
OT  - risk prediction model
OT  - trivalent influenza vaccine
OT  - underreporting
OT  - vaccine pharmacovigilance
COIS- Dr. Poland is the chair of a Safety Evaluation Committee for novel 
      investigational vaccine trials being conducted by Merck Research Laboratories. 
      Dr. Poland offers consultative advice on vaccine development to Merck & Co., 
      Medicago, GlaxoSmithKline, Sanofi Pasteur, Emergent Biosolutions, Dynavax, 
      Genentech, Eli Lilly and Company, Janssen Global Services LLC, Kentucky 
      Bioprocessing, and Genevant Sciences, Inc. Dr. Poland holds patents related to 
      vaccinia, influenza, and measles peptide vaccines. Dr. Poland has received grant 
      funding from ICW Ventures for preclinical studies on a peptide-based COVID-19 
      vaccine. These activities have been reviewed by the Mayo Clinic Conflict of 
      Interest Review Board and are conducted in compliance with Mayo Clinic Conflict 
      of Interest policies.
EDAT- 2021/02/04 06:00
MHDA- 2021/11/19 06:00
PMCR- 2021/02/23
CRDT- 2021/02/03 06:04
PHST- 2020/10/07 00:00 [received]
PHST- 2021/01/11 00:00 [accepted]
PHST- 2021/02/04 06:00 [pubmed]
PHST- 2021/11/19 06:00 [medline]
PHST- 2021/02/03 06:04 [entrez]
PHST- 2021/02/23 00:00 [pmc-release]
AID - PDS5196 [pii]
AID - 10.1002/pds.5196 [doi]
PST - ppublish
SO  - Pharmacoepidemiol Drug Saf. 2021 May;30(5):602-609. doi: 10.1002/pds.5196. Epub 
      2021 Feb 23.