Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/16218
Title: Novel statistically-derived composite measures for assessing the efficacy of disease-modifying therapies in prodromal Alzheimer’s disease trials: an AIBL study
Austin Authors: Burnham, Samantha C;Raghavan, Nandini;Wilson, William;Baker, David;Ropacki, Michael T;Novak, Gerald;Ames, David;Ellis, Kathryn A;Martins, Ralph N;Maruff, Paul;Masters, Colin L ;Romano, Gary;Rowe, Christopher C ;Savage, Greg;Macaulay, S Lance;Narayan, Vaibhav A
Affiliation: Austin Health, Heidelberg, Victoria, Australia
CSIRO Digital Productivity Flagship, Floreat, Western Australia, Australia
Janssen Research and Development, Raritan, NJ, USA
CSIRO Digital Productivity Flagship, North Ryde, NSW, Australia
Janssen Research and Development, Titusville, NJ, USA
Janssen Research and Development, Fremont, CA, USA
Academic Unit for Psychiatry of Old Age, Department of Psychiatry, University of Melbourne, Parkville, Victoria, Australia
National Ageing Research Institute, Parkville, Victoria, Australia
Centre of Excellence for Alzheimer’s Disease Research & Care, School of Medical Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
Sir James McCusker Alzheimer’s Disease Research Unit (Hollywood Private Hospital), Perth, Western Australia, Australia
Cogstate, Melbourne, Victoria, Australia
Mental Health Research Institute (MHRI), The University of Melbourne, Parkville, Victoria, Australia
Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, Victoria, Australia
ARC Centre of Excellence in Cognition and its Disorders, and Department of Psychology, Macquarie University, Sydney, NSW, Australia
CSIRO Food and Nutrition Flagship, Melbourne, Victoria, Australia
Issue Date: 2015
metadata.dc.date: 2015
Publication information: Journal of Alzheimer's Disease 2015; 46(4): 1079-1089
Abstract: Background: There is a growing consensus that disease-modifying therapies must be given at the prodromal or preclinical stages of Alzheimer’s disease (AD) to be effective. A major unmet need is to develop and validate sensitive measures to track disease progression in these populations. Objective: To generate novel statistically-derived composites from standard scores, which have increased sensitivity in the assessment of change from baseline in prodromal AD. Methods: An empirically based method was employed to generate domain specific, global, and cognitive-functional novel composites. The novel composites were compared and contrasted with each other, as well as standard scores for their ability to track change from baseline. The longitudinal characteristics and power to detect decline of the measures were evaluated. Data from participants in the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study characterized as mild cognitively impaired with high neocortical amyloid-β burden were utilized for the study. Results: The best performing standard scores were CDR Sum-of-Boxes and MMSE. The statistically-derived novel composites performed better than the standard scores from which they were derived. The domain-specific composites generally did not perform as well as the global composites or the cognitive-functional composites. Conclusion: A systematic method was employed to generate novel statistically-derived composite measures from standard scores. Composites comprised of measures including function and multiple cognitive domains appeared to best capture change from baseline. These composites may be useful to assess progression or lack thereof in prodromal AD. However, the results should be replicated and validated using an independent clinical sample before implementation in a clinical trial.
URI: http://ahro.austin.org.au/austinjspui/handle/1/16218
DOI: 10.3233/JAD-143015
ORCID: 0000-0003-3910-2453
PubMed URL: https://pubmed.ncbi.nlm.nih.gov/26402634
Type: Journal Article
Subjects: Alzheimer’s disease
Clinical marker
Mild cognitive impairment
Neuroimaging
Prodromal symptoms
Appears in Collections:Journal articles

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