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19 - Statistical Considerations in the Design and Analysis of Alzheimer’s Disease Clinical Trials

from Section 3 - Alzheimer’s Disease Clinical Trials

Published online by Cambridge University Press:  03 March 2022

By
Suzanne B. Hendrix ,
Jessie Nicodemus-Johnson ,
Logan Kowallis ,
Newman Knowlton ,
Sean Hennessey  and
Samuel P. Dickson
Edited by
Jeffrey Cummings ,
Jefferson Kinney  and
Howard Fillit
Jeffrey Cummings
Affiliation:
University of Nevada, Las Vegas
Jefferson Kinney
Affiliation:
University of Nevada, Las Vegas
Howard Fillit
Affiliation:
Alzheimer’s Drug Discovery Foundation
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Summary

Statistical issues are prominent in Alzheimer’s disease (AD) clinical trials due to the enormous challenges in this disease. The complexity of the disease and intervention pathways challenge drug discovery efforts, but measurement and analysis complexities and subjective outcomes also interfere with successful drug development. Variability across disease stage, disease sub-types, comorbidities and concomitant treatments (between-subject), and non-equivalent forms, good and bad days, and rater inconsistencies (within-subject) increase the chance of failure. AD-specific statistical expertise is critical for success, in contrast to most disease areas that require less disease-specific statistical knowledge. Use of global statistical tests and composites, correcting for covariates, and model selection increase the chance of a clearly positive outcome for active treatments and a clearly negative outcome for inactive or harmful treatments.

Keywords

statisticssample sizefutility analysisdisease modificationglobal statistical testsvariabilitystudy designdrug development
Type
Chapter
Information
Alzheimer's Disease Drug Development
Research and Development Ecosystem
 , pp. 232 - 248
Publisher: Cambridge University Press
Print publication year: 2022

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References

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