Authors: Vikram Venkatraghavan,Esther E. Bron,Wiro J. Niessen,Stefan Klein,for the Alzheimer's Disease Neuroimaging Initiative
ArXiv: 1808.03604
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Abstract URL: http://arxiv.org/abs/1808.03604v1
Alzheimer's Disease (AD) is characterized by a cascade of biomarkers becoming
abnormal, the pathophysiology of which is very complex and largely unknown.
Event-based modeling (EBM) is a data-driven technique to estimate the sequence
in which biomarkers for a disease become abnormal based on cross-sectional
data. It can help in understanding the dynamics of disease progression and
facilitate early diagnosis and prognosis. In this work we propose a novel
discriminative approach to EBM, which is shown to be more accurate than
existing state-of-the-art EBM methods. The method first estimates for each
subject an approximate ordering of events. Subsequently, the central ordering
over all subjects is estimated by fitting a generalized Mallows model to these
approximate subject-specific orderings. We also introduce the concept of
relative distance between events which helps in creating a disease progression
timeline. Subsequently, we propose a method to stage subjects by placing them
on the estimated disease progression timeline. We evaluated the proposed method
on Alzheimer's Disease Neuroimaging Initiative (ADNI) data and compared the
results with existing state-of-the-art EBM methods. We also performed extensive
experiments on synthetic data simulating the progression of Alzheimer's
disease. The event orderings obtained on ADNI data seem plausible and are in
agreement with the current understanding of progression of AD. The proposed
patient staging algorithm performed consistently better than that of
state-of-the-art EBM methods. Event orderings obtained in simulation
experiments were more accurate than those of other EBM methods and the
estimated disease progression timeline was observed to correlate with the
timeline of actual disease progression. The results of these experiments are
encouraging and suggest that discriminative EBM is a promising approach to
disease progression modeling.