Predicting conversion of patients with Mild Cognitive Impairment to Alzheimer’s disease using bedside cognitive assessments

ABSTRACT

Introduction

Patients diagnosed with Mild Cognitive Impairment (MCI) often go on to develop dementia, however many do not. Although cognitive tests are widely used in the clinic, there is limited research on their potential to help predict which patients may progress to Alzheimer’s disease (AD) from those that do not.

Methods

MCI patients (n = 325) from the longitudinal Alzheimer’s Disease Neuroimaging Initiative (ADNI-2) dataset were tracked across a 5 year period. Upon initial diagnosis, all patients underwent a series of cognitive tests including the Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and Alzheimer’s Disease Assessment Scale-Cognitive (ADAS-Cog 13). Twenty-five percent (n = 83) of those initially diagnosed with MCI subsequently developed AD within 5 years.

Results

We showed that those individuals that progressed to AD had significantly lower scores upon baseline testing on the MMSE and MoCA, and higher scores on the ADAS-13, compared to those that did not convert. However, not all tests were equivalent. We showed that the ADAS-13 offers the best predictability of conversion (Adjusted Odds ratio (AOR) = 3.91). This predictability was higher than that offered by the two primary biomarker Amyloid-beta (Aβ, AOR = 1.99) and phospho-tau (Ptau, AOR = 1.72). Further analysis on the ADAS-13 showed that MCI patients that subsequently converted to AD performed particularly poorly on delayed-recall (AOR = 1.93), word recognition (AOR = 1.66), word finding difficulty (AOR = 1.55) and orientation (1.38) test items.

Conclusions

Cognitive testing using the ADAS-13 may offer a simpler, less invasive, more clinically relevant and a more effective method of determining those that are in danger of converting from MCI to AD.

KEYWORDS:

• Mild cognitive impairment
• Alzheimer’s disease
• Mini Mental State Examination (MMSE)
• Montreal Cognitive Assessment (MoCA)
• Alzheimer’s Disease Assessment scale (ADAS-Cog 13)
• Alzheimer’s Disease Neuroimaging Initiative (ADNI)
• spatial cognition

Acknowledgments

Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. 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 Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.

*Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in the analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgment_List.pdf

Disclosure statement

No potential conflict of interest was reported by the author(s)

Ethical approval

Data analysed was from the ADNI dataset, which is freely available for secondary analysis. Written informed consent was obtained by ADNI according to the Declaration of Helsinki, and procedures were approved by site-specific Institutional Review Boards for the Protection of Human Subjects (see http://adni.loni.usc.edu/wp-content/themes/freshnews-dev-v2/documents/clinical/ADNI-2_Protocol.pdf).

Author contributions

CA, JJ, OR: Analysed data; AC, PH, SC: Analysed data, edited and wrote manuscript; ADNI: provided data.

Additional information

Funding

There is no funding to report in relation to this manuscript.