Menu Back to Tutorial-1-Signal-Detection-from-Drug-Safety-Databases-using-Likelihood-Ratio-Tests


Tutorials are not included in the meeting registration and require a separate registration fee

Tutorial Registration: 7:30AM-8:30AM

The statistical methods used for data mining or signal detection of drug adverse event combinations from large drug safety databases such as FDA’s Adverse Event Reporting System (FAERS), consisting of spontaneous reports on adverse events for postmarket drugs are called passive surveillance methods. On the other hand, the statistical signal detection methods for longitudinal data, as the data accrues in time, are called active surveillance methods. A review of the most commonly used passive surveillance statistical methods, along with a likelihood ratio test (LRT) based method, developed by the instructors, will be discussed in detail. A live demo of the LRT in OpenFDA tool that uses the FAERS data will be presented. Extensions of LRT, such as the LRT for a drug class (Ext-LRT), the LRT for longitudinal safety data (Long-LRT), used for active surveillance, and the LRT for handling excessive number of zeros (ZIP-LRT) will also be presented in detail. Finally, use of the LRT in meta analysis, when there are several studies, will be given.

The tutorial will consist of three modules:

  • Module-I: a quick review of commonly used Bayesian and Frequentist methods for signal detection in passive surveillance will be given; then the basic LRT method will be discussed in detail and extensions of the LRT methodology to a drug-class and data with excessive zeros, will be presented.
  • Module-II: a live demonstration of the LRT in OpenFDA tool (available for public use) to certain drugs or adverse events (AEs) from the FAERS database will be given. Finally, in
  • Module-III: the LRT for longitudinal clinical database and the use of the LRT in meta-analysis, when there are several studies, will be given.

Who should attend?

Professionals who already have a basic knowledge of statistics

Learning objectives

At the conclusion of this tutorial, participants should be able to:

  • Demonstrate familiarity with data mining in a drug safety database
  • Explain commonly used methods for disproportionality analysis in drug safety databases
  • Apply a new likelihood ratio test (LRT) based method with different extensions for disproportionality analysis that controls false positive and false discovery rates

Contact us

Registration Questions?

Send Email

Agenda Details

Send Email

Event Logistics

Send Email