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Activity Number: 468 - Blinded Data Reviews Are Necessary in Today's Clinical Trials
Type: Topic Contributed
Date/Time: Wednesday, August 1, 2018 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract #328378
Title: Estimating Event Rate Differences Using Data from Blinded Trials
Author(s): A. Gould* and Bill Wang
Companies: Merck Research Laboratories and Merck
Keywords: Bayesian; parametric; p-value; Fisher

The development of drugs and biologicals whose mechanisms of action may extend beyond their target indications has led to a need to identify unexpected potential toxicities even in ongoing blinded clinical trials. Recently issued FDA rules regarding safety reporting requirements raise the possibility of breaking the blind for serious adverse events that are not the clinical endpoints of a blinded trial. However, unblinding individual cases of frequently occurring adverse events could compromise the overall validity of the trial. The possibility of elevated risk can be addressed without unblinding the trial by using external information about adverse event rates among patients not receiving the test product in populations similar to the trial population. We describe a Bayesian approach to determining the likelihood of elevated risk suitable for binomial or Poisson likelihoods that applies regardless of the metric used to express the difference. The method appears to be particularly appropriate when the adverse events are not 'rare'.

Authors who are presenting talks have a * after their name.

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