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. 2017;55(4):1497-1507.
doi: 10.3233/JAD-160842.

Odor Identification Screening Improves Diagnostic Classification in Incipient Alzheimer's Disease

Megan Quarmley  1 , Paul J Moberg  1   2   3 , Dawn Mechanic-Hamilton  2   3 , Sushila Kabadi  1 , Steven E Arnold  4 , David A Wolk  2   3 , David R Roalf  1
Affiliations

Odor Identification Screening Improves Diagnostic Classification in Incipient Alzheimer's Disease

Megan Quarmley et al. J Alzheimers Dis. 2017.

Abstract

Background: Measurements of olfaction may serve as useful biomarkers of incipient dementia. Here we examine the improvement in diagnostic accuracy of Alzheimer's disease (AD) and mild cognitive impairment (MCI) when assessing both cognitive functioning and odor identification.

Objective: To determine the utility of odor identification as a supplementary screening test in incipient AD.

Methods: Sniffin' Sticks Odor Identification Test (SS-OIT) and the Montreal Cognitive Assessment (MoCA) were administered in 262 AD, 174 MCI [150 amnestic (aMCI), and 24 non-amnestic (naMCI)], and 292 healthy older adults (HOA).

Results: Odor identification scores were higher in HOA relative to MCI or AD groups, and MCI outperformed AD. Odor identification scores were higher in aMCI single domain than aMCI multiple domain. Complementing MoCA scores with the SS-OIT significantly improved diagnostic accuracy of individuals with AD and MCI, including within MCI subgroups.

Discussion: Odor identification is a useful supplementary screening tool that provides additional information relevant for clinical categorization of AD and MCI, including those who are at highest risk to convert to AD.

Keywords: Alzheimer’s disease; Montreal Cognitive Assessment; Sniffin’ Sticks Olfactory Identification Test; mild cognitive impairment; odor identification; smell.

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Figures

Fig. 1
Fig. 1
A) Mean SS-OIT scores with standard error bars by diagnosis (HOA, healthy older adults; MCI, mild cognitive impairment; AD, Alzheimer’s disease; *p < 0.0001). B) Mean SS-OIT scores with standard error bars by diagnosis (naMCI, mild cognitive impairment non-amnestic; aMCIsd, mild cognitive impairment amnestic single domain, aMCImd, mild cognitive impairment multiple domain; *p < 0.023).
Fig. 2
Fig. 2
ROC curves for SS-OIT. A-D) Comparison of multinomial AUC (MoCA + SS-OIT) to MoCA only AUC for diagnostic accuracy. The addition of SS-OIT to the MoCA significantly improved overall prediction between MCI and HOA. E) AUC, sensitivity and specificity, Youden index, optimal cut-off score, and diagnostic classification accuracy for the MoCA, SS-OIT, and MoCA + SS-OIT.
Fig. 3
Fig. 3
Classification accuracy of MoCA and SS-OIT scores by diagnosis. The bottom portion of each bar represents the number of individuals correctly classified by the optimal MoCA score (M). The middle portion of each bar indicates the number of individuals that were misidentified by MoCA score, but correctly identified by SS-OIT score (O). The top portion of each bar represents the number of individuals misidentified by both MoCA and SS-OIT score (X).
Fig. 4
Fig. 4
Percentage of HOA individuals with normal MoCA scores falling below the odor identification threshold. Normal MoCA performers were grouped in High (29-30), Middle (27-28), and Low (25-26) performers. Individuals with the lower MoCA scores were more likely to perform poorly on odor identification.
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