期刊
ALZHEIMERS & DEMENTIA
卷 18, 期 11, 页码 2341-2351出版社
WILEY
DOI: 10.1002/alz.12615
关键词
aducanumab; Alzheimer's disease; Bayesian statistics; clinical trials
This article introduces the application of Bayesian analysis in clinical trials, using the data of aducanumab as an example. Bayesian analysis can quantify evidence and assess the strength of the effect, which is different from the binary conclusions provided by frequentist tests.
This perspective is a companion to a recent editorial on the use of Bayesian analysis in clinical research. We aim to introduce and highlight the relevance and advantages that Bayesian inference offers to clinical trials using the data on the amyloid antibody aducanumab presented at a Food and Drug Administration hearing in November 2020 as an applied example. We apply Bayesian analysis of model plausibility and effect sizes based on simulated data of the two phase 3 trials of aducanumab in prodromal and mild dementia stages of Alzheimer's disease (AD). Bayesian analysis can quantify evidence in favor of, or against, the presence of an effect (i.e., provide evidence of absence), as well as assess the strength of the effect. This is in contrast to the binary conclusions provided by frequentist tests.
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