@article{d2d47960bc504f2eaf19b226efd40c4b,
title = "A computational method for computing an Alzheimer's disease progression score; experiments and validation with the ADNI data set",
abstract = "Understanding the time-dependent changes of biomarkers related to Alzheimer's disease (AD) is a key to assessing disease progression and measuring the outcomes of disease-modifying therapies. In this article, we validate an AD progression score model which uses multiple biomarkers to quantify the AD progression of subjects following 3 assumptions: (1) there is a unique disease progression for all subjects; (2) each subject has a different age of onset and rate of progression; and (3) each biomarker is sigmoidal as a function of disease progression. Fitting the parameters of this model is a challenging problem which we approach using an alternating least squares optimization algorithm. To validate this optimization scheme under realistic conditions, we use the Alzheimer's Disease Neuroimaging Initiative cohort. With the help of Monte Carlo simulations, we show that most of the global parameters of the model are tightly estimated, thus enabling an ordering of the biomarkers that fit the model well, ordered as: the Rey auditory verbal learning test with 30minutes delay, the sum of the 2 lateral hippocampal volumes divided by the intracranial volume, followed (by the clinical dementia rating sum of boxes score and the mini-mental state examination score) in no particular order and at last the AD assessment scale-cognitive subscale.",
keywords = "Alzheimer's disease, Biomarkers, Progression score, Sampling from the residuals",
author = "{Alzheimer's Disease Neuroimaging Initiative} and Jedynak, {Bruno M.} and Bo Liu and Andrew Lang and Yulia Gel and Prince, {Jerry L.}",
note = "Funding Information: Personnel costs for this research were partially supported by a grant from Pfizer as well as from an Ossoff scholar award. Other support came from grants numbered P41EB015909 and R01EB012547 from the National Institute of Biomedical Imaging and Bioengineering . Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) ( National Institutes of Health grant U01 AG024904 ). ADNI is funded by the National Institute on Aging , the National Institute of Biomedical Imaging and Bioengineering , and through generous contributions from the following: Abbott ; Alzheimer's Association ; Alzheimer Drug Discovery Foundation ; Amorfix Life Sciences Ltd. ; AstraZeneca ; Bayer HealthCare ; BioClinica, Inc. ; Biogen Idec Inc. ; Bristol-Myers Squibb Foundation ; Eisai ; Elan Pharmaceuticals Inc. ; Eli Lilly and Company ; F. Hoffmann-La Roche Ltd ; and its affiliated company “ Genentech, Inc. ; GE Healthcare ; Innogenetics, N.V. ; IXICO Ltd. ; Janssen Alzheimer Immunotherapy Research & Development, LLC. ; Johnson & Johnson Pharmaceutical Research & Development LLC. ; Medpace, Inc. ; Merck & Co., Inc. ; Meso Scale Diagnostics, LLC. ; Novartis Pharmaceuticals Corporation ; Pfizer .; and Takeda Pharmaceutical Company . The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health ( www.fnih.org ). The grantee organization is the Northern California Institute for Research and Education , and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of California, Los Angeles. This research was also supported by NIH grants P30 AG010129 and K01 AG030514 . Publisher Copyright: {\textcopyright} 2015 Elsevier Inc.",
year = "2015",
month = jan,
day = "1",
doi = "10.1016/j.neurobiolaging.2014.03.043",
language = "English (US)",
volume = "36",
pages = "S178--S184",
journal = "Neurobiology of aging",
issn = "0197-4580",
publisher = "Elsevier Inc.",
number = "S1",
}