Statistical approaches to longitudinal data analysis in neurodegenerative diseases: Huntington's disease as a model
TP Garcia, K Marder - Current neurology and neuroscience reports, 2017 - Springer
Understanding the overall progression of neurodegenerative diseases is critical to the timing
of therapeutic interventions and design of effective clinical trials. Disease progression can …
of therapeutic interventions and design of effective clinical trials. Disease progression can …
Joint modeling of multivariate longitudinal data and survival data in several observational studies of Huntington's disease
JD Long, JA Mills - BMC medical research methodology, 2018 - Springer
Background Joint modeling is appropriate when one wants to predict the time to an event
with covariates that are measured longitudinally and are related to the event. An underlying …
with covariates that are measured longitudinally and are related to the event. An underlying …
An overview of longitudinal data analysis methods for neurological research
JJ Locascio, A Atri - Dementia and geriatric cognitive disorders extra, 2011 - karger.com
The purpose of this article is to provide a concise, broad and readily accessible overview of
longitudinal data analysis methods, aimed to be a practical guide for clinical investigators in …
longitudinal data analysis methods, aimed to be a practical guide for clinical investigators in …
Bayesian latent time joint mixed effect models for multicohort longitudinal data
Characterization of long-term disease dynamics, from disease-free to end-stage, is integral
to understanding the course of neurodegenerative diseases such as Parkinson's and …
to understanding the course of neurodegenerative diseases such as Parkinson's and …
[HTML][HTML] Dynamics of cortical degeneration over a decade in Huntington's disease
Background Characterizing changing brain structure in neurodegeneration is fundamental
to understanding long-term effects of pathology and ultimately providing therapeutic targets …
to understanding long-term effects of pathology and ultimately providing therapeutic targets …
Data-driven modelling of neurodegenerative disease progression: thinking outside the black box
Data-driven disease progression models are an emerging set of computational tools that
reconstruct disease timelines for long-term chronic diseases, providing unique insights into …
reconstruct disease timelines for long-term chronic diseases, providing unique insights into …
Overlap between age-at-onset and disease-progression determinants in Huntington disease
NA Aziz, JMM van der Burg, SJ Tabrizi… - Neurology, 2018 - AAN Enterprises
Objective A fundamental but still unresolved issue regarding Huntington disease (HD)
pathogenesis is whether the factors that determine age at onset are the same as those that …
pathogenesis is whether the factors that determine age at onset are the same as those that …
A data-driven model of biomarker changes in sporadic Alzheimer's disease
We demonstrate the use of a probabilistic generative model to explore the biomarker
changes occurring as Alzheimer's disease develops and progresses. We enhanced the …
changes occurring as Alzheimer's disease develops and progresses. We enhanced the …
Statistical disease progression modeling in Alzheimer disease
LL Raket - Frontiers in big Data, 2020 - frontiersin.org
Background: The characterizing symptom of Alzheimer disease (AD) is cognitive
deterioration. While much recent work has focused on defining AD as a biological construct …
deterioration. While much recent work has focused on defining AD as a biological construct …
Clinical and biomarker changes in premanifest Huntington disease show trial feasibility: a decade of the PREDICT-HD study
There is growing consensus that intervention and treatment of Huntington disease (HD)
should occur at the earliest stage possible. Various early-intervention methods for this fatal …
should occur at the earliest stage possible. Various early-intervention methods for this fatal …