Monitoring potential adverse event rate differences using data from blinded trials: the canary in the coal mine

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 promptly even while blinded clinical trials are under way. One component of recently issued FDA rules regarding safety reportin...

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Bibliographic Details
Published in:Statistics in medicine 2017-01, Vol.36 (1), p.92-104
Main Authors: Gould, A. Lawrence, Wang, William B.
Format: Article
Language:English
Subjects:
Bayes
Bayes Theorem
Bayesian analysis
binomial
blinded study
Clinical trials
Clinical Trials as Topic
Coal mining
Drug-Related Side Effects and Adverse Reactions
external databases
Humans
Likelihood Functions
observational data
Poisson
Poisson Distribution
Research Design
Side effects
Validity
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Summary: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 promptly even while blinded clinical trials are under way. One component of recently issued FDA rules regarding safety reporting requirements raises the possibility of breaking the blind for pre‐identified serious adverse events that are not the clinical endpoints of a blinded study. Concern has been expressed that unblinding individual cases of frequently occurring adverse events could compromise the overall validity of the study. However, if external information is available about adverse event rates among patients not receiving the test product in populations similar to the study population, then it may be possible to address the potential for elevated risk without unblinding the trial. This article describes a Bayesian approach for determining the likelihood of elevated risk suitable binomial or Poisson likelihoods that applies regardless of the metric used to express the difference. The method appears to be particularly appropriate for routine monitoring of safety information for project development programs that include large blinded trials. Copyright © 2016 John Wiley & Sons, Ltd.
ISSN:0277-6715
1097-0258
DOI:10.1002/sim.7129