ArticlePloS one2018
The development of a stochastic mathematical model of Alzheimer's disease to help improve the design of clinical trials of potential treatments.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 34 citations in OpenAlex.
- Spore powder of Ganoderma lucidum for the treatment of Alzheimer disease: A pilot study.Medicine · 2018Trial
- Investigating Modifiable Risk Factors Across Dementia Subtypes: Insights from the UK Biobank.Biomedicines · 2024Article
- Data-driven Stochastic Model for Quantifying the Interplay Between Amyloid-beta and Calcium Levels in Alzheimer's Disease.Statistical analysis and data mining · 2024Article
- Article
- Analysis of fractal-fractional Alzheimer's disease mathematical model in sense of Caputo derivative.AIMS public health · 2024Article
- Understanding Alzheimer's disease in the context of aging: Findings from applications of stochastic process models to the Health and Retirement Study.Mechanisms of ageing and development · 2023Article
- A glance through the effects of CD4Computational and structural biotechnology journal · 2023Review
- Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2022Review
- Stochasticity, Entropy and Neurodegeneration.Brain sciences · 2022Article
- Influence of Subject-Specific Effects in Longitudinal Modelling of Cognitive Decline in Alzheimer's Disease.Journal of Alzheimer's disease : JAD · 2022Article
- Dynamical Modeling as a Tool for Inferring Causation.American journal of epidemiology · 2022Article
- Predicting Progression from Mild Cognitive Impairment to Alzheimer's Disease using MRI-based Cortical Features and a Two-State Markov Model.Proceedings. IEEE International Symposium on Biomedical Imaging · 2021Article
- Heterogeneity in Reports of Dementia Disease Duration and Severity: A Review of the Literature.Journal of Alzheimer's disease : JAD · 2021Review
- The dynamics of biomarkers across the clinical spectrum of Alzheimer's disease.Alzheimer's research & therapy · 2020Article
- Current and Future Treatments in Alzheimer Disease: An Update.Journal of central nervous system disease · 2020Review
- Combining hippocampal volume metrics to better understand Alzheimer's disease progression in at-risk individuals.Scientific reports · 2019Article
- Alzheimer's disease progression and risk factors: A standardized comparison between six large data sets.Alzheimer's & dementia (New York, N. Y.) · 2019Article
- RNA Regulatory Networks as a Control of Stochasticity in Biological Systems.Frontiers in genetics · 2019Review
- Potential Factors Associated with Cognitive Improvement of Individuals Diagnosed with Mild Cognitive Impairment or Dementia in Longitudinal Studies.Journal of Alzheimer's disease : JAD · 2018Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder characterised by a slow progressive 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 discontinued 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 progression of Alzheimer's in a longitudinal cohort study. We show how this modelling framework 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 challenging, 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 measurement of diagnostic markers and endpoints, which consequently results in the misdiagnosis of an individual's disease state.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.