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Pharmacoepidemiol Drug Saf. 2018 Apr;27(4):391-397. doi: 10.1002/pds.4397. Epub 2018 Feb 15.

Meningococcal conjugate vaccine safety surveillance in the Vaccine Safety Datalink using a tree-temporal scan data mining method.

Author information

1
Immunization Safety Office, Centers for Disease Control and Prevention, Atlanta, GA, USA.
2
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA.
3
Kaiser Permanente Vaccine Study Center, Oakland, CA, USA.
4
Group Health Research Institute and University of Washington, Seattle, WA, USA.
5
Institute for Health Research, Kaiser Permanente, Denver, CO, USA.
6
Southern California Kaiser Permanente, Pasadena, CA, USA.

Abstract

PURPOSE:

The objective of our study was to conduct a data mining analysis to identify potential adverse events (AEs) following MENACWY-D using the tree-temporal scan statistic in the Vaccine Safety Datalink population and demonstrate the feasibility of this method in a large distributed safety data setting.

METHODS:

Traditional pharmacovigilance techniques used in vaccine safety are generally geared to detecting AEs based on pre-defined sets of conditions or diagnoses. Using a newly developed tree-temporal scan statistic data mining method, we performed a pilot study to evaluate the safety profile of the meningococcal conjugate vaccine Menactra® (MenACWY-D), screening thousands of potential AE diagnoses and diagnosis groupings. The study cohort included enrolled participants in the Vaccine Safety Datalink aged 11 to 18 years who had received MenACWY-D vaccination(s) between 2005 and 2014. The tree-temporal scan statistic was employed to identify statistical associations (signals) of AEs following MENACWY-D at a 0.05 level of significance, adjusted for multiple testing.

RESULTS:

We detected signals for 2 groups of outcomes: diseases of the skin and subcutaneous tissue, fever, and urticaria. Both groups are known AEs following MENACWY-D vaccination. We also identified a statistical signal for pleurisy, but further examination suggested it was likely a false signal. No new MENACWY-D safety concerns were raised.

CONCLUSIONS:

As a pilot study, we demonstrated that the tree-temporal scan statistic data mining method can be successfully applied to screen broadly for a wide range of vaccine-AE associations within a large health care data network.

KEYWORDS:

Bell's palsy; Menactra; adverse events; pharmacoepidemiology; post-licensure

PMID:
29446176
DOI:
10.1002/pds.4397

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