A composite score for executive functioning valid

Authors: Laura E Gibbons Adam C Carle R Scott Mackin Danielle Harvey Shubhabrata Mukherjee Philip Insel S McKay Curtis Dan Mungas Paul K Crane for the Alzheimer’s Disease Neuroimaging Initiative

Publish Date: 2012/05/27

Volume: 6, Issue: 4, Pages: 517-527

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Abstract

The Alzheimer’s Disease Neuroimaging Initiative ADNI measures abilities broadly related to executive function EF including WAISR Digit Symbol Substitution Digit Span Backwards Trails A and B Category Fluency and Clock Drawing This study investigates whether a composite executive function measure based on these multiple indicators has better psychometric characteristics than the widely used individual components We applied item response theory methods to 800 ADNI participants to derive an EF composite score ADNIEF from the above measures We then compared ADNIEF with component measures in 390 longitudinallyfollowed participants with mild cognitive impairment MCI with respect to 1 Ability to detect change over time 2 Ability to predict conversion to dementia 3 Strength of crosssectional association with MRIderived measures of structures involved in frontal systems and 4 Strength of baseline association with cerebrospinal fluid CSF levels of amyloid β142 total tau and phosphorylated tau181P ADNIEF showed the greatest change over time followed closely by Category Fluency ADNIEF needed a 40  smaller sample size to detect change ADNIEF was the strongest predictor of AD conversion ADNIEF was the only measure significantly associated with all the MRI regions though other measures were more strongly associated in a few of the regions ADNIEF was associated with all the CSF measures ADNIEF appears to be a useful composite measure of EF in MCI as good as or better than any of its composite parts This study demonstrates an approach to developing a psychometrically sophisticated composite score from commonlyused testsData used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative ADNI database adniloniuclaedu As such the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report A complete listing of ADNI investigators can be found at http//adniloniuclaedu/research/activeinvestigators/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’s Drug Discovery Foundation Amorfix Life Sciences Ltd AstraZeneca Bayer HealthCare BioClinica Inc Biogen Idec Inc BristolMyers Squibb Company Eisai Inc Elan Pharmaceuticals Inc Eli Lilly and Company F HoffmannLa Roche Ltd and its affiliated company Genentech Inc GE Healthcare Innogenetics NV 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 Inc Servier Synarc Inc 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 wwwfnihorg 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 of Neuro Imaging at the University of California Los Angeles This research was also supported by NIH grants P30 AG010129 K01 AG030514 and the Dana Foundation

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