Leveraging the Entire Cohort in Drug Safety Monitoring: Part 1 Methods for Sequential Surveillance that Use Regression Adjustment or Weighting to Control Confounding in a Multi-Site, Rare Event, Distributed Data Setting

Project Title Leveraging the Entire Cohort in Drug Safety Monitoring: Part 1 Methods for Sequential Surveillance that Use Regression Adjustment or Weighting to Control Confounding in a Multi-Site, Rare Event, Distributed Data Setting
Date
Friday, May 17, 2019
Location
Description

Study designs involving self-controlled or exposure-matched samples are commonly used to monitor post market vaccine and drug safety using large healthcare databases, and they use a subset of the information available from the larger cohort. This paper reviews sequential methods designed for observational safety monitoring that use the whole exposed and unexposed cohort by implementing regression or weighting to control confounding.

Corresponding Author

Jennifer C. Nelson, Biostatistics Unit, Kaiser Permanente Health Research Institute 1730 Minor Avenue, Suite 1600; Seattle, WA 98101 US

Authors

Jennifer C. Nelson, Ernesto Ulloa-Pe’rez, Jennifer F. Bobb, Judith C. Maro

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