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A Bayesian perspective on Biogen's aducanumab trial.
Temp, Anna G M; Ly, Alexander; van Doorn, Johnny; Wagenmakers, Eric-Jan; Tang, Yi; Lutz, Michael W; Teipel, Stefan.
Afiliação
  • Temp AGM; German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.
  • Ly A; Translational Neurodegeneration Section "Albrecht Kossel," Department of Neurology, University of Rostock, Rostock, Germany.
  • van Doorn J; Department of Psychological Methods, University of Amsterdam, Amsterdam, the Netherlands.
  • Wagenmakers EJ; Machine Learning Group, Centrum Wiskunde & Informatica, Amsterdam, the Netherlands.
  • Tang Y; Department of Psychological Methods, University of Amsterdam, Amsterdam, the Netherlands.
  • Lutz MW; Department of Psychological Methods, University of Amsterdam, Amsterdam, the Netherlands.
  • Teipel S; Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, China.
Alzheimers Dement ; 18(11): 2341-2351, 2022 11.
Article em En | MEDLINE | ID: mdl-35235700
ABSTRACT
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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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença de Alzheimer Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença de Alzheimer Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article