10
This article was downloaded by: [University of California, San Francisco] On: 26 November 2014, At: 20:00 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Journal of Clinical and Experimental Neuropsychology Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/ncen20 Mild cognitive impairment subcategories depend on the source of norms Genevieve Arsenault-Lapierre a , Victor Whitehead a , Sylvie Belleville b c , Fadi Massoud d e , Howard Bergman a f & Howard Chertkow a f g a Bloomfield Centre for Research on Aging , Lady Davis Institute of Medical Research, Sir B. Davis Jewish General Hospital , Montreal, QC, Canada b Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal , Montreal, QC, Canada c Départment de Psychologie , Université de Montréal , Montreal, QC, Canada d Service de Gériatrie, Centre Hospitalier de l'Université de Montréal , Montreal, QC, Canada e Département de Médecine , Université de Montréal , Montreal, QC, Canada f Division of Geriatric Medicine (Department of Medicine) , McGill University and Sir B. Davis Jewish General Hospital , Montreal, QC, Canada g Department of Neurology and Neurosurgery , McGill University , Montreal, QC, Canada Published online: 06 Feb 2011. To cite this article: Genevieve Arsenault-Lapierre , Victor Whitehead , Sylvie Belleville , Fadi Massoud , Howard Bergman & Howard Chertkow (2011) Mild cognitive impairment subcategories depend on the source of norms, Journal of Clinical and Experimental Neuropsychology, 33:5, 596-603, DOI: 10.1080/13803395.2010.547459 To link to this article: http://dx.doi.org/10.1080/13803395.2010.547459 PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution

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Page 1: Mild cognitive impairment subcategories depend on the source of norms

This article was downloaded by: [University of California, San Francisco]On: 26 November 2014, At: 20:00Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: MortimerHouse, 37-41 Mortimer Street, London W1T 3JH, UK

Journal of Clinical and ExperimentalNeuropsychologyPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/ncen20

Mild cognitive impairment subcategories dependon the source of normsGenevieve Arsenault-Lapierre a , Victor Whitehead a , Sylvie Belleville b c , FadiMassoud d e , Howard Bergman a f & Howard Chertkow a f ga Bloomfield Centre for Research on Aging , Lady Davis Institute of MedicalResearch, Sir B. Davis Jewish General Hospital , Montreal, QC, Canadab Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal ,Montreal, QC, Canadac Départment de Psychologie , Université de Montréal , Montreal, QC, Canadad Service de Gériatrie, Centre Hospitalier de l'Université de Montréal , Montreal,QC, Canadae Département de Médecine , Université de Montréal , Montreal, QC, Canadaf Division of Geriatric Medicine (Department of Medicine) , McGill University and SirB. Davis Jewish General Hospital , Montreal, QC, Canadag Department of Neurology and Neurosurgery , McGill University , Montreal, QC,CanadaPublished online: 06 Feb 2011.

To cite this article: Genevieve Arsenault-Lapierre , Victor Whitehead , Sylvie Belleville , Fadi Massoud , HowardBergman & Howard Chertkow (2011) Mild cognitive impairment subcategories depend on the source of norms, Journalof Clinical and Experimental Neuropsychology, 33:5, 596-603, DOI: 10.1080/13803395.2010.547459

To link to this article: http://dx.doi.org/10.1080/13803395.2010.547459

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”)contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensorsmake no representations or warranties whatsoever as to the accuracy, completeness, or suitabilityfor any purpose of the Content. Any opinions and views expressed in this publication are the opinionsand views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy ofthe Content should not be relied upon and should be independently verified with primary sources ofinformation. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands,costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly orindirectly in connection with, in relation to or arising out of the use of the Content.

This article may be used for research, teaching, and private study purposes. Any substantial orsystematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution

Page 2: Mild cognitive impairment subcategories depend on the source of norms

in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found athttp://www.tandfonline.com/page/terms-and-conditions

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Page 3: Mild cognitive impairment subcategories depend on the source of norms

JOURNAL OF CLINICAL AND EXPERIMENTAL NEUROPSYCHOLOGY2011, 33 (5), 596–603

Mild cognitive impairment subcategories depend on thesource of norms

Genevieve Arsenault-Lapierre1, Victor Whitehead1, Sylvie Belleville2,3, Fadi Massoud4,5,Howard Bergman1,6, and Howard Chertkow1,6,7

1Bloomfield Centre for Research on Aging, Lady Davis Institute of Medical Research, Sir B. DavisJewish General Hospital, Montreal, QC, Canada2Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, Montreal, QC, Canada3Départment de Psychologie, Université de Montréal, Montreal, QC, Canada4Service de Gériatrie, Centre Hospitalier de l’Université de Montréal, Montreal, QC, Canada5Département de Médecine, Université de Montréal, Montreal, QC, Canada6Division of Geriatric Medicine (Department of Medicine), McGill University and Sir B. Davis JewishGeneral Hospital, Montreal, QC, Canada7Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada

The diagnosis of mild cognitive impairment (MCI) entails evidence of objective cognitive loss using neuropsycho-logical measures. In this study, we examined whether the presence and degree of objective cognitive impairmentvaried according to the use of published versus local norms. We also varied the cutoff scores at which impair-ment was recognized and examined whether this altered inclusion in MCI subcategories. We found that the useof different comparison normative groups altered the subcategory diagnoses, especially when the cutoff score forimpairment was conservative. In general, local norms were more stringent than published norms. We discuss theimplications of these results for MCI diagnosis and categorization.

Keywords: Mild cognitive impairment; Subcategories; Normative data; Normal aging; Neuropsychological tests.

INTRODUCTION

The label mild cognitive impairment (MCI) was intro-duced to define a group of individuals in a transition zonebetween normal aging and Alzheimer’s disease (AD).These are individuals who have memory complaints,preferably corroborated by informants, and show deficitson neuropsychological testing, but do not meet the crite-ria for dementia and are still able to function in their dailylives (Chertkow, 2002; Petersen et al., 1999). Evidencefrom population and clinic-based studies suggests thatthese individuals are at an increased risk of progressingto dementia. About 15% of them progress to dementia,generally AD, every year compared to only 1% or 2% ofthe general population above 65 years of age (Petersenet al., 2001).

This study was supported in part by operating grants from the Canadian Institutes of Health Research (CIHR) and the Fonds de laRecherche en Santé du Québec (FRSQ) awarded to H.C.

Address correspondence to Howard Chertkow, Bloomfield Centre for Research in Aging, 3755 Chemin de la Côte-Ste-Catherine,Room 8, Montréal, Québec, H3T 2R8, Canada (E-mail: [email protected]).

As research interest has grown, the heterogeneity ofMCI has become apparent, and different subcategoriesof the term MCI have been suggested (Petersen et al.,2001). Distinctions have been proposed between individ-uals who present with memory-only deficits (amnesticMCI), individuals presenting deficits in multiple cognitivespheres, including memory (multiple-domains MCI), andindividuals presenting no memory deficits but showingone (single nonmemory MCI) or many (multiple non-memory MCI) cognitive deficits (Petersen et al., 2001;Winblad et al., 2004). These subcategories have beenpresumed to have different etiologies and prognoses,with amnestic MCI being the most prevalent subgroupand more likely to progress to dementia, especially AD(Lopez et al., 2007; Maioli et al., 2007; Yaffe, Petersen,Lindquist, Kramer, & Miller, 2006). Evidence, however,

© 2011 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business

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MCI SUBCATEGORIES DEPEND ON NORMS 597

is lacking (Busse, Hensel, Guhne, Angermeyer, & Riedel-Heller, 2006; Di Carlo et al., 2007; Fischer et al., 2007;Forlenza et al., 2009; Nordlund, Rolstad, Klang, Edman,Hansen, & Wallin, 2009). As opposed to other subtypesof MCI, however, amnestic MCI individuals show cere-bral atrophy similar to AD (Whitwell, Petersen, Negash,Weigand, Kantarci, Ivnik, et al., 2007) and are morelikely to have the APOe4 (apolipoprotein E4) genotype(Manly et al., 2005). However, these subcategories couldalso be influenced by the severity of the disease, wheremultiple-domain MCI may be closer to dementia thansingle-domain MCI. Interestingly, multiple-domain MCI(with and without memory) showed poorer instrumen-tal activities of daily living scores than did single-domain(memory or not) and no cognitive impairment groups(Burton, Strauss, Bunce, Hunter, & Hultsch, 2009).

The original general definition of MCI (Petersen,Smith, Waring, Ivnik, Kokmen, & Tangelos, 1997)entailed only a clinical assessment of “objective impair-ment” without support from neuropsychological testscores. In order to determine these MCI subcategories,however, one needs to compare the individuals with anormative group and consider the tests with which tocompare them. Many questions arise in relation to this:(a) What tests should be used, (b) how many tests shouldbe used, (c) what cutoff or threshold should be consideredimpaired, (d) for a normative group, does one use pub-lished norms or a locally constituted normative group,and (e) should the norms be adjusted for age alone or foreducation as well?

To determine MCI subcategories it is necessary to usetests that span a reasonable number of cognitive domainsin addition to memory. Executive functions, language,and visuospatial skills at least should be assessed, asthese domains are now recognized to be affected earlyon in the disease (see Bondi et al., 2008, for review).However, as we increase the number of tests, we increasethe chance of finding random impairments. Indeed, it hasbeen reported that 14% of normal controls were misclas-sified when eight or more tests are used (Loewensteinet al., 2006). Loewenstein et al. further suggest the useof a maximum number of tests or the use of compositescores or the use of more stringent norms. The symp-toms of MCI are by definition more subtle than those inAD and may only be detected with more stringent cut-off scores tests—that is, the harder, the better (Petersen,2004a).

Should a cutoff of 1 standard deviation (SD), 1.5 SDs,or 2 SDs below the mean of a normative group be used,and to what norms should these scores be compared:local or published norms? These three cutoffs are themost often used in the literature. The use of 1.5 SDs asa cutoff comes from the observation that, on average,MCI who progressed to dementia had a mean on neu-ropsychological tests equivalent to 1.5 SDs below that ofnormal healthy controls and has been extensively usedin the literature (Petersen, 2004b). The use of a cutoffof 2 SDs, on the other hand, is closer to the clinicalcriteria for dementia and might be a more useful cut-off to identify individuals who will progress to dementia(Petersen, 2004b). However, in doing so, one has to keep

in mind the variability of the test (the lower the cutoffscore, the less variable a test should be). Finally, the useof a cutoff of 1 SD, possibly detecting smaller decline,was also found to have high positive predictive powerfor the development of dementia (Busse et al., 2006).Using a conservative (2-SD) cutoff has the drawback ofmaking the test less sensitive to small declines observedin MCI, whereas using a liberal cutoff (1 SD) has thedisadvantage of increasing the chance of finding falsepositives.

These various cutoff scores all entail a comparisonnormative group, and there are several ways to estab-lish such a comparison group. Normative groups can beselected locally (local norms) or from literature (pub-lished norms). Published norms have the advantage ofbeing publicly available. However, in some cases stan-dard published norms were established as much as 25years ago and might include individuals who would notbe considered normal today, as our understanding ofnormal aging has grown (De Santi et al., 2008). Someresearchers now go as far as excluding from their nor-mative group any individuals who decline years lateron longitudinal follow-up (De Santi et al., 2008). Such“robust norms,” however, are not as readily available aslocal cross-sectional norms. Increasingly, local norms arepreferred because they allow researchers to control forcultural and other secular biases, which affect neuropsy-chological test results (Acevedo, Loewenstein, Agron, &Duara, 2007). Different culture and age groups have dif-ferent educational systems, with different grading andlevels, which have obvious impact on the performance ofa certain group on a neuropsychological test. With this inmind, it becomes apparent that developing local normsthat are more relevant in terms of age, education, andculture is important in the field of neuropsychology.

The assumption has been that these MCI subcategoriesare stable and easily established. Our clinical suspicionafter seeing many MCI individuals, however, has becomethe opposite: subcategories might be very variable andclosely related to norms and cutoff scores used. The goalof this study was therefore to test the stability of MCIsubcategories. We hypothesized that the presence anddegree of objective cognitive loss, and hence the MCI sub-category, varied according to the use of published versuslocal norms and cutoff scores.

METHOD

In order to test the stability of MCI subcategories, indi-viduals meeting clinical criteria for MCI were collectedin a set of eight tertiary care referral memory clin-ics across the province of Quebec, Canada, organizedby the Cognition Division of the Réseau Québécois deRecherches sur le Vieillissement (RQRV; Quebec Networkfor Research on Aging). All subjects were clinically diag-nosed based on an agreed set of criteria adapted fromPetersen (Petersen et al., 1997). Core features included:(a) decline form a previously normal level of functionas determined by complaints from subjects and/or fam-ily, (b) demonstrable abnormality on mental status exam,

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598 ARSENAULT-LAPIERRE ET AL.

(c) preserved day-to-day function, and (d) absence ofdementia. Exclusion criteria included serious healthproblems or evidence of systemic causes or other braindiseases that could account for symptoms or chronicpsychiatric disorders (other than depression).

All subjects completed the Mini-Mental StateExamination (MMSE; Folstein, Folstein, & McHugh,1975), the Geriatric Depression Scale (GDS; Yesavageet al., 1982), the Neuropsychiatric Inventory (NPI;Cummings et al., 1994), the Functional AutonomyQuestionnaire (Mahoney & Barthel, 1965), theFunctional Activities Questionnaire (Pfeffer, Kurosaki,Harrah, Chance, & Filos, 1982), and the MemoryComplaint Questionnaire (Schmand, Jonker, Hooijer,& Lindeboom, 1996). The network group developed abattery of neuropsychological instruments in order toattempt to standardize the evaluation of the participantsentered across the network. This battery assessed mem-ory, language, praxis, visual perception, and executivefunction. Also, given the population being assessed,tests were chosen that were available and comparablein French and English. Memory tests included Letter–Number Sequencing (LN Seq) and Visual Reproduction(VR) I and II subtests of the Wechsler Memory Scale–Third Edition (WMS–III; Wechsler, 1987b). Languagetests included the Boston Naming Test (BN; Mack,Freed, Williams, & Henderson, 1992) and ControlledOral Word Association (word fluency, WF; Ruff, Light,Parker, & Levin, 1996). Praxis tests included VR-Copysubtest of WMS–III and Block Design (Block) of theWechsler Adult Intelligence Scale (WAIS; Wechsler,1987a). Finally, executive function tests included StroopVictoria (Stroop; Stroop, 1935), and the Digit Symbol(Digit) subtest of WAIS (Wechsler, 1987a).

The MCI subjects were further subcategorized usingclassifications proposed by Petersen et al. (Petersen,2004a): amnestic MCI, multiple-domain MCI, sin-gle nonmemory MCI, and multiple nonmemory MCI.Impairments were determined by comparing the MCIsubjects’ scores to two different normative groups: localand published norms. We determined MCI subtypesbased on the tests for which we could compute localnorms, listed in Table 1. The references for the publishednorms used are listed in Table 1 (footnotes).

To compute local norms, we used 34 elderly nor-mal controls (NCs) from a longitudinal cohort study onaging who had been followed over 10 years (described inArsenault-Lapierre, Chertkow, & Lupien, 2010). Subjectswere recruited from family practices or through localadvertisements. In order to be included in the normalcohort, they had to show absence of major depres-sion (score > 12) on the Geriatric Depression Scale(GDS; Yesavage et al., 1982), show no impairment onthe Functional Autonomy Questionnaire (Mahoney &Barthel, 1965) and Functional Activities Questionnaire(Pfeffer et al., 1982), and show minimal subjective com-plaints (score less than 4) on the Memory ComplaintQuestionnaire (Schmand et al., 1996). We included allsubjects meeting these criteria in our normative group,irrespective of their status over the following 10 years.Our goal was not to build robust norms but to compare

easily accessible local versus published norms. Exclusioncriteria were the presence of memory complaints, agebelow 65 years, or deficits in memory or other cogni-tive domains based on neuropsychological tests batteryoperationalized as a score of 1.5 SDs below publishednorms.

The published norms used are referenced in Table 1.These published norms were all adjusted for age, exceptfor the word fluency test, which was adjusted for edu-cation and age. The local norms were not adjusted forage or for education, due to the small sample size. One-way analyses of variance (ANOVAs) were performed tocompare the mean of the MCI individuals and the meanof the local NC group on demographic and neuropsy-chological variables. Chi-square analyses were performedto compare the distribution of memory and nonmemorydeficits in local and published norms.

RESULTS

Forty-five MCI subjects were recruited throughout theRQRV centers, 6 of whom presented insufficient infor-mation to assess their MCI subcategory. These 6 MCIsubjects were not different from the other MCI subjectsin terms of demographic variables (data not shown; allp > .05). Therefore, we computed MCI subcategories fora total of 39 subjects. Demographic information for MCIand NC subjects can be viewed in Table 1.

The 34 NCs were compared, as a group, to the pub-lished norms, to examine how they performed in relationto each other. The neuropsychological scores of the 34NCs were rated as average to high average for each test,except for Visual Reproduction II, a measure of visuallong-term memory, where the local normative groupscored, as a group, in the 84th percentile (Table 1). Twoof the 34 NCs have progressed to MCI diagnosis sincethe beginning of the longitudinal study (average 11.8 ±0.8 years to date). However, they were kept in these anal-yses. The scores of these 2 NCs who progressed to MCIdid not differ from scores of the remaining 32 NCs ondemographic or neuropsychological data (all p > .05).The scores of the remaining 32 NCs who did not progressare shown in Table 1 for comparison.

The 39 MCI subjects, as a group, did not differ fromthe local comparison group on demographic variablesexcept for depression. GDS scores were marginally higherfor the MCI subjects than for the 34 NCs (p = .052).Furthermore, the 39 MCI subjects performed signifi-cantly worse than the 34 NC comparisons group on manyof the neuropsychological tests (see Table 1). Controllingfor the GDS eliminated the Stroop test differences, butmade the Block test significantly different.

The distribution of MCI subtypes per normativegroups and cutoff scores is given in Table 2. Using acutoff score of 1 SD, 33 (85%) MCI subjects were clas-sified in the same subcategory using either local normsor published norms. This proportion drastically droppedto 20 (51%) MCI subjects using a cutoff score of 1.5SDs and 16 (41%) MCI subjects using a cutoff scoreof 2 SDs. Table 3 describes the discordant pairs when

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TAB

LE

1C

hara

cter

istic

sof

MC

Isub

ject

san

dlo

calN

Cs

onde

mog

raph

ican

dne

urop

sych

olog

ical

varia

bles

MC

I(n

=39

;17

M:2

2W)

NC

(ori

gina

l)(n

=34

;16

M:1

8W)

NC

(rem

aini

ng)

(n=

32;

16M

:16W

)N

C(o

rigi

nal;

n=

34)

Loc

alvs

.pub

lishe

dno

rms

MS

DM

SD

MS

DM

SD

Per

cent

ile

Age

(yea

rs)

72.5

8.6

74.6

5.9

75.0

5.9

Edu

cati

on(y

ears

)13

.03.

013

.63.

013

.53.

3M

MSE

28.1

1.5

28.4

1.5

28.4

1.4

GD

S6.

03.

93.

94.

33.

84.

4

Mem

ory

VR

I∗60

.116

.371

.018

.571

.818

.850

th

VR

II∗

24.3

24.2

48.5

20.2

48.0

20.9

84th

LN

Seq

8.3

2.5

9.1

2.5

9.1

2.4

75th

Lan

guag

eB

N∗

12.2

1.7

13.6

1.3

13.5

1.3

13.1

1.8

WF

lett

ers∗

35.0

13.2

48.4

16.4

47.7

16.7

42.0

12.1

WF

anim

als∗

13.4

3.3

17.8

5.4

17.7

5.4

18.2

4.2

Exe

cuti

vefu

ncti

ons

Dot

s(s

)16

.54.

815

.65.

915

.96.

115

.05.

1W

ords

(s)∗

22.7

6.2

19.7

5.8

19.9

6.0

19.1

5.1

Col

or(s

)∗38

.710

.232

.812

.233

.112

.639

.613

.3D

igit

∗43

.716

.156

.09.

356

.09.

675

th

Pra

xis

VR

copy

95.4

14.5

98.4

4.1

98.2

4.2

75th

Blo

ck29

.39.

027

.19.

826

.69.

850

th

Not

e.M

CI=

mild

cogn

itiv

eim

pair

men

t;N

C=

norm

alco

ntro

l;M

=m

en;W

=w

omen

;NC

(rem

aini

ng)=

NC

sw

hodi

dno

tpr

ogre

ssto

MC

I);M

MSE

=M

ini-

Men

talS

tate

Exa

min

atio

n(F

olst

ein

etal

.,19

75);

GD

S=

Ger

iatr

icD

epre

ssio

nSc

ale

(Yes

avag

eet

al.,

1982

);V

R=

Vis

ualR

epro

duct

ion

(Wec

hsle

r,19

87b)

;LN

Seq

=L

ette

r–N

umbe

rSe

quen

cing

(Wec

hsle

r,19

87a)

;BN

=15

-ite

mB

osto

nN

amin

g(M

ack

etal

.,19

92);

WF

=w

ord

fluen

cy(S

pree

n&

Stra

uss,

1991

);B

lock

=B

lock

Des

ign

(Wec

hsle

r,19

87a)

;D

ots/

Wor

ds/C

olor

=St

roop

Vic

tori

a(S

pree

n&

Stra

uss,

1991

);D

igit

=D

igit

Sym

bol(

Wec

hsle

r,19

87a)

.∗ S

tati

stic

ally

sign

ifica

ntdi

ffer

ence

sbe

twee

nth

e34

loca

lNC

san

d39

MC

Isu

bjec

ts(p

<.0

5).

599

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600 ARSENAULT-LAPIERRE ET AL.

TABLE 2Distribution of MCI subcategories according to two normative groups and three cutoff scores

Local norms (n = 34) Published norms

1.0 SD 1.5 SD 2.0 SD 1.0 SD 1.5 SD 2.0 SD

A 1 3 4 3 3 5M 23 20 11 23 11 7SNM 4 5 9 5 11 9MNM 10 7 4 6 5 3No 1 4 11 2 9 15

Note. MCI = mild cognitive impairment. Numbers represent the number of MCI subjects classified as amnestic MCI (A), multiple-domains MCI (M), single nonmemory MCI (SNM), multiple nonmemory MCI (MNM), or with no impairment (No) whencompared to local and published norms at cutoff of 1 standard deviation (SD), 1.5 SDs, and 2 SDs.

TABLE 3Discordant subcategories pairs

Published

Local M MNM A SNM No

1 SD M — 2MNM —A 1 —SNM 1 1 —No 1 —

1.5 SDs M — 4 1 2 3MNM — 2A 1 —SNM 2 — 2No 2 —

2 SDs M — 2 2 2MNM 1 — 1 5A 1 — 1SNM 2 —No 3 1 1 —

Note. Numbers represent the number of mild cognitive impair-ment (MCI) subjects classified as discordant when compared tolocal and published norms at cutoff of 1 standard deviation (SD),1.5 SDs, and 2 SDs. M is multiple-domains MCI; MNM is multi-ple nonmemory domains MCI; A is amnestic MCI; SNM is singlenonmemory MCI; and No is no impairment.

local and published norms did not agree and shows thedifferent subcategories attributed to each of these MCIparticipants.

When looking at the memory domain as a function ofthe normative group at a cutoff of 1.5 SDs, the numberof MCI individuals showing memory impairment (withor without other cognitive domain impairments) climbedfrom 36% for published norms to 59% using local com-parison norms. While purely amnestic MCI subjects wereabout 8% using both techniques, the multiple-domainMCI cohort constituted 28% of the MCI using publishednorms, but 51% of the MCI using local norms.

Interestingly, at the lowest cutoff of 1 SD below eachmeans, 1 (3%) and 2 (5%) MCI subjects were classi-fied with no impairment, when compared to local andpublished norms, respectively. Inversely, 11 (28%) and 7

(18%) MCI subjects showed multiple cognitive impair-ments, including memory, at more than a 2-SD cutoffwhen compared to local and published norms, respec-tively. However, from Figure 1, it is possible to observethat MCI participants seem to be more impaired in mem-ory performances when compared to local norms thanwhen compared to published norms, whereas the oppo-site is true for executive functions. At 1.5 SDs, localnorms yielded more memory impairment (23 cases ofsingle or multiple impairment) than nonmemory impair-ment (16 cases of single, multiple, or no impairment)compared to published norms (14 and 25, respectively;χ 2 = 4.16, p = .04).

DISCUSSION

In this study we found that the subcategory diagnosis canbe altered dramatically and significantly by varying thesource of the comparison normative groups, especiallywhen the cutoff score for impairment is strict—that is,at 1.5 SDs or 2 SDs below the mean. At 1.5-SD cut-off, only 51% of MCI subjects remained in the samesubgroup when local instead of published norms wereutilized. This demonstrates that in addition to the cutoffscore, the source of the norms is essential in determin-ing who meets criteria for MCI and what subgroup ofMCI they best fit into. As well, local norms yield morememory impairment than nonmemory impairment com-pared to published norms. This could have importantconsequences, as most studies now use 1.5 SDs belowmean as gold standard.

Many factors could explain the difference foundbetween local and published norms in this study. Thefirst factor, a methodological one, is due to advances inaging research. The field of research on MCI is a relativelynew one in comparison to aging research. Therefore,some of the published norms used in this study aredated (1987 to 2007) and may have included MCI sub-jects because subjects with mild impairments were notexcluded in collecting such normative data. In a majorstudy (Sliwinski, Lipton, Buschke, & Stewart, 1996), itwas demonstrated that unintentional inclusion of sub-tly impaired elderly subjects (who later go on to AD)likely results in an underestimation of mean performance

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Figure 1. Impairment of mild cognitive impairment (MCI) participants as compared to local and published norms. This figure showsthe degree of impairment of 39 MCI participants as a group when compared to (A) local norms or (B) published norms. Each rowis an individual MCI subject, and each column is a cognitive test. VR = Visual Reproduction (Wechsler, 1987b); LN Seq = Letter–Number Sequencing (Wechsler, 1987a); BN = 15-item Boston Naming (Mack et al., 1992); WF = word fluency (Spreen & Strauss,1991); Block = Block Design (Wechsler, 1987a); Dots/Words/Colors = Stroop Victoria (Spreen & Strauss, 1991); Digit = Digit Symbol(Wechsler, 1987a). The symbols +, <1SD, >1SD, >1.5SD, and 2SD indicate, respectively, that the participant scores above, less than 1standard deviation (SD) below the mean, or more than 1 SD, more than 1.5 SDs, or more than 2 SDs below the norms; †indicates thatthe score was adjusted for age; ‡ indicates that the score was adjusted for education.

on cognitive tests, overestimating the variance and theeffect of age. The fact that our 34 NCs collected locally,taken as a group, qualified as high average when com-pared to published norms in terms of long-term memoryscores supports this argument. The local norms in thisstudy included few preclinical AD patients (only 2 haddeclined to MCI diagnosis after 10 years of follow-up)and better overall long-term-memory scores than thepublished norms. At the same time, there was no evi-dence that they were surpassing the published norms,suggesting they were not “super agers” who would notbe suitable as a control group. One could argue that onlyrobust norms, where the normative group is followed overthe years to insure the exclusion of preclinical subjects,allow total exclusion of preclinical subjects who mightbe in the earliest stages of prodromal AD. Indeed, DeSanti and de Leon and their colleagues found that suchrobust norms were better at predicting progression todementia in their sample of MCI individuals (De Santiet al., 2008). Such robust norms, however, are less avail-able than a normative group selected in a cross-sectionaldesign. Establishing such norms in every locale would bea daunting task.

A second factor, a demographic one, pertains to thefact that recent aging cohorts are different from previousones. For example, people are increasingly educated com-pared with earlier generations, and cohort factors are notalways considered in published norms for all neuropsy-chological tests. Indeed, the proportion of Canadians 15years old and over with a university degree went from2% in 1951 to 13% in 1996, while the proportion ofCanadians 15 years old and over with fewer than 9 yearsof education went from over 50% in 1951 to 12% in 1996(Clark, 2001). Another demographic factor is the cultural

differences between the two normative groups used inthis study (see Loewenstein, Arguelles, Arguelles, & Linn-Fuentes, 1994, for review). A large proportion of the localnormative group included in this study are immigrants(32%), polyglots living in a multicultural environment, towhich they have had to adapt. All of this makes the groupdifferent from other published normative groups. Onecould raise the question as to whether such a group can orshould be used as a normative one. Our local normativegroup did not differ from the MCI subjects included inthis study on any demographic variables, which makes itrelatively suitable. By selecting individuals that resemblethe experimental group with regard to not only age buteducation and cultural background, local norms shouldbe a more reliable comparison group. One can argue thata more accurate picture of the extent and degree of anysubject’s cognitive impairment is produced when localnorms are applied, and that future research should favorthe use of a local normative group.

An issue that should be considered with caution is thefact that using a 1-SD cutoff, a number of MCI individu-als were classified with no impairment when comparedto the local and published norms. This occurred for 1individual using local norms and 2 individuals using pub-lished norms. This seems at odds with the fact that allMCI individuals were seen by specialists who diagnosedthem. In 2006, a group of researchers found that a major-ity of patients with a Clinical Dementia Rating (CDR)score of 0.5 had no neuropsychological deficit (Storandt,Grant, Miller, & Morris, 2006). Similarly, 11 and 7 MCIindividuals were classified as having multiple-domainsimpairments at 2 SDs or more below the mean of localor published norms, respectively. One might argue thatthese individuals were impaired to the point of dementia

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602 ARSENAULT-LAPIERRE ET AL.

(Royall, Chiodo, & Polk, 2004), although such a clinicalclassification might require functional impairment, whichwas absent. Other limitations of this study include thesmall sample size of the local normative group and thefact that there was no follow-up of the 39 MCI subjects.

As mentioned in the Introduction, epidemiologicalevidence discriminating different subgroups in terms ofprogression of disease has been ambiguous and contra-dictory (Busse et al., 2006; Di Carlo et al., 2007; Fischeret al., 2007; Forlenza et al., 2009; Lopez et al., 2007;Maioli et al., 2007; Nordlund et al., 2010; Yaffe et al.,2006). The results presented here may help explain thisdiscrepancy: The subgroupings may have been deter-mined using different norms and/or cutoffs. The impli-cation is that we should be wary of the considerableliterature that tries to prognosticate distinctly for “pureamnestic” versus “multiple-domains” MCI subjects (usu-ally using a 1.5-SD cutoff score for normal vs. impairedperformance). One must seriously entertain the possibil-ity that an individual deemed to be “multiple nonmem-ory” MCI with published norms might be reclassified as“multiple-domains MCI” if appropriate local norms wereutilized.

Original manuscript received 29 July 2010Revised manuscript accepted 3 December 2010

First published online 6 February 2011

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