The development of a stochastic mathematical model of Alzheimer's disease to help improve the design of clinical trials of potential treatments

Title: The development of a stochastic mathematical model of Alzheimer's disease to help improve the design of clinical trials of potential treatments
Author(s): Hadjichrysanthou, C
Ower, AK
De Wolf, F
Anderson, RM
Item Type: Journal Article
Abstract: Alzheimer’s disease (AD) is a neurodegenerativ e disorder characterised by a slow progres- sive deterioration of cognitive capacity. Drugs are urgently needed for the treatment of AD and unfortunately almost all clinical trials of AD drug candidates have failed or been discon- tinued to date. Mathematical, computational and statistical tools can be employed in the construction of clinical trial simulators to assist in the improvement of trial design and enhance the chances of success of potential new therapies. Based on the analysis of a set of clinical data provided by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) we developed a simple stochastic mathematical model to simulate the development and pro- gression of Alzheimer’s in a longitudinal cohort study. We show how this modelling frame- work could be used to assess the effect and the chances of success of hypothetical treatments that are administered at different stages and delay disease development. We demonstrate that the detection of the true efficacy of an AD treatment can be very challeng- ing, even if the treatment is highly effective. An important reason behind the inability to detect signals of efficacy in a clinical trial in this therapy area could be the high between- and within-individual variability in the measuremen t of diagnostic markers and endpoints, which consequently results in the misdiagno sis of an individual’s disease state.
Publication Date: 29-Jan-2018
Date of Acceptance: 18-Dec-2017
URI: http://hdl.handle.net/10044/1/59791
DOI: https://dx.doi.org/10.1371/journal.pone.0190615
ISSN: 1932-6203
Publisher: PUBLIC LIBRARY OF SCIENCE
Journal / Book Title: PLOS ONE
Volume: 13
Issue: 1
Copyright Statement: © 2018 Hadjichry santhou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Copyright Statement: © 2018 Hadjichry santhou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Keywords: Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
MILD COGNITIVE IMPAIRMENT
TRANSITION-PROBABILITIES
BIOMARKER CHANGES
BRAIN RESERVE
MARKOV MODEL
RISK-FACTORS
PROGRESSION
DEMENTIA
PREVALENCE
SIMULATION
Alzheimer Disease
Biomarkers
Biometry
Cohort Studies
Decision Support Techniques
Diagnostic Errors
Disease Progression
Humans
Longitudinal Studies
Mathematical Computing
Models, Theoretical
Probability
Research Design
Stochastic Processes
Alzheimer's Disease Neuroimaging Initiative
Humans
Alzheimer Disease
Disease Progression
Diagnostic Errors
Probability
Stochastic Processes
Cohort Studies
Longitudinal Studies
Biometry
Mathematical Computing
Decision Support Techniques
Models, Theoretical
Research Design
Biomarkers
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
MILD COGNITIVE IMPAIRMENT
TRANSITION-PROBABILITIES
BIOMARKER CHANGES
BRAIN RESERVE
MARKOV MODEL
RISK-FACTORS
PROGRESSION
DEMENTIA
PREVALENCE
SIMULATION
MD Multidisciplinary
General Science & Technology
Publication Status: Published
Article Number: ARTN e0190615
Online Publication Date: 2018-01-29
Appears in Collections:Faculty of Medicine
Epidemiology, Public Health and Primary Care



Items in Spiral are protected by copyright, with all rights reserved, unless otherwise indicated.

Creative Commons