Neuropsychological Measures Predict Decline to Alzheimer’s DementiaFrom Mild Cognitive Impairment

Mathew J. SummersUniversity of Tasmania and Wicking Dementia Research &

Education Centre, Hobart, Tasmania, Australia

Nichole L. J. SaundersUniversity of Tasmania

Objective: Studies of Mild Cognitive Impairment (MCI) show elevated rates of conversion to dementiaat the group level. However, previous studies of the trajectory of MCI identify great heterogeneity ofoutcomes, with a significant proportion of individuals with MCI remaining stable over time, changingMCI subtype classification, or reverting to a normal cognitive state at long-term follow-up. Method: Thepresent study examined individual outcomes at 20 months in a group of older adults classified accordingto MCI subtypes. A total of 106 participants, 81 with different subtypes of MCI and 25 healthy controls,undertook longitudinal neuropsychological assessment of visual and verbal memory, attentional process-ing, executive functions, working memory capacity, and semantic memory. Results: At 20 months 12.3%of the MCI group progressed to dementia, 62.9% continued to meet MCI criteria, and 24.7% reverted tounimpaired levels of function. A discriminant function analysis predicted outcome at 20 months on thebasis of baseline neuropsychological test performance with 86.3% accuracy. The analysis indicated thata pattern of impairments on visual episodic memory, verbal episodic memory, short-term memory,working memory, and attentional processing differentiated between participants who developed demen-tia, recovered from MCI, or remained in stable MCI. Conclusions: The results of the present study raisequestions regarding the specificity of existing criteria for the subtypes of MCI, with these resultsindicating a high degree of instability in classification over time. In addition, the results suggest thatmultidomain MCI is the most reliable precursor stage to the development of AD.

Keywords: mild cognitive impairment, memory, executive function, attention, working memory

The notion of a preclinical stage of Alzheimer’s disease (AD) isnow well accepted (Bäckman, Jones, Berger, Laukka, & Small,2005; Johnson, Storandt, Morris, & Galvin, 2009; Mickes et al.,2007). Some authors suggest that mild cognitive impairment(MCI) is a prodromal transitional period between normal aging(Flicker, Ferris, & Reisberg, 1991; Morris et al., 2001; Petersen,2004, 2005; Petersen et al., 1997), whereas others contend thatMCI is a risk factor for dementia and not a prodromal phase(Bennett et al., 2002; Dawe, Procter, & Philpot, 1992; Fisk, Merry,& Rockwood, 2003; Ganguli, Dodge, Shen, & DeKosky, 2004;Luis, Loewenstein, Acevedo, Barker, & Duara, 2003). Recently,

subtypes of MCI have been proposed (Petersen & Morris, 2005;Winblad et al., 2004): single-domain amnestic-MCI (a-MCI);multiple-domain amnestic-MCI (a-MCI�); single-domainnonamnestic-MCI (na-MCI); and multiple-domain nonamnestic-MCI (na-MCI�). However, evidence for the utility of the revisedMCI classification criteria as predictive of impending dementia inolder adults is limited.

Epidemiological studies indicate that MCI is associated withelevated rates of conversion to dementia. A meta-analysis of thesestudies (A. J. Mitchell & Shiri-Feshki, 2009) determined the fol-lowing corrected annual conversion rates to AD: 11.7% for a-MCI(nine studies; sample size � 646), 12.2% for a-MCI� (eightstudies; samples size � 446), and 4.1% for na-MCI (five studies;sample size � 354). However, at the individual level heterogeneityof outcome is common: although some develop dementia, between40 and 70% of adults classified with a-MCI revert to an unim-paired status or remain stable at follow-up (Ravaglia et al., 2006).Recent research suggests that a-MCI is a rare and unstable classi-fication (Alladi, Arnold, Mitchell, Nestor, & Hodges, 2006; Saun-ders & Summers, 2010), has low predictive value for the devel-opment of dementia (Fischer et al., 2007; Rasquin, Lodder, Visser,Lousberg, & Verhey, 2005; Rountree et al., 2007), and that cog-nitive difficulties in areas other than memory can predicate onsetof AD (Storandt, Grant, Miller, & Morris, 2006). Studies indicatethat both a-MCI and na-MCI display increased risk for conversionto other forms of dementia, such as vascular dementia or dementiawith Lewy bodies (Fischer et al., 2007; Rountree et al., 2007). Asa result of this heterogeneity in outcome, some researchers assertthat MCI is a diagnostic nonentity that fails to predict risk of

This article was published Online First May 21, 2012.Mathew J. Summers, School of Psychology, University of Tasmania,

Tasmania, Australia, and Wicking Dementia Research and Education Cen-tre, Hobart, Tasmania, Australia; Nichole L. J. Saunders, School of Psy-chology, University of Tasmania.

We thank the Alzheimer’s Association of Tasmania as well as variousGeneral Practice Surgeries in Northern Tasmania for their assistance inrecruitment of participants in this study. We also thank the participants andtheir families for their enthusiasm in taking part in this study. Dr Saundersreceived a University of Tasmania Postgraduate scholarship as well as aWicking Dementia Research and Education Centre scholarship during thecourse of this study. Dr Summers received a research fellowship from theWicking Dementia Research and Education Centre during the course ofthis study. There was no other financial support received for this study.

Correspondence concerning this article should be addressed to MathewJ. Summers, School of Psychology, University of Tasmania, Locked Bag1342, Launceston, Tasmania, Australia, 7250. E-mail: mathew.summers@utas.edu.au

Neuropsychology © 2012 American Psychological Association2012, Vol. 26, No. 4, 498–508 0894-4105/12/$12.00 DOI: 10.1037/a0028576

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development of dementia (Gauthier & Touchon, 2005; Ritchie,Artero, & Touchon, 2001; Tabert et al., 2006).

The body of research examining MCI and risk for dementiareflects a mismatch between epidemiological studies and the di-agnostic requirements of identifying risk for dementia within anindividual. While epidemiological studies indicate that groups ofindividuals meeting a research classification for MCI display ele-vated rates of developing dementia, studies examining the trajec-tory for individuals identified using the same MCI classificationcriteria are somewhat disappointing in terms of the specificity andsensitivity of the diagnosis. There is therefore a need to reexaminethe concept of MCI as a diagnostic entity so as to develop criteriathat meet diagnostic sensitivity and specificity at the individuallevel. There is also a need to develop valid screening tools that can(1) discriminate between unimpaired individuals and those withMCI and (2) identify those individuals with MCI who are mostlikely to progress to AD (Feldman et al., 2004). The capacity toaccurately determine which individuals with MCI will go on todevelop AD from those who will not offers the benefit of allowingthe commencement of pharmacological, behavioral, and cognitivetherapies at the earliest stages of disease progression, therebymaximizing the potential of slowing disease progression (Griffithet al., 2006).

While variation in the rate of conversion to dementia raisesquestions about the utility of the MCI classification as an indicatorof impending dementia, perhaps more striking are reports that asizable proportion of those classified with MCI fail to demonstratecognitive impairment at subsequent assessment. Such individualsare said to “revert” from MCI to unimpaired or cognitively normalstatus. Rates of reversion have been reported in a number of majorepidemiological samples. Ritchie and colleagues reported a 15%rate of reversion across a 1-year follow-up interval in a Frenchsample (Ritchie et al., 2001). Rates of reversion in a second,independent French sample ranged from 32–41% over two years,depending on the operational definition of MCI (Larrieu et al.,2002). In a German sample, rates of reversion across a one and ahalf year follow up interval ranged from 18–22%, again dependingon the operational definition of MCI (Busse, Hensel, Guhne,Angermeyer, & Riedel-Heller, 2006). In a North American sam-ple, 28% of individuals with MCI reverted to normal after a 2-yearfollow up interval (Ganguli et al., 2004). A study from the Cana-dian Study of Health and Aging (Fisk et al., 2003) examinedprogression to dementia over a 5-year period in four different typesof amnestic MCI (with and without subjective memory impair-ment, with and without intact instrumental activities of dailyliving). Of the individuals characterized as amnestic MCI, 26–32% (depending on amnestic MCI version under consideration)were cognitively normal at 5-year follow-up.

Classification criteria for MCI, the operationalisation of MCIcriteria, the cognitive domains assessed, and the neuropsycholog-ical tests used differ widely and continue to emphasize the pres-ence of verbal memory impairments as diagnostic of AD. Suchcriteria underestimate the importance of examining nonmemorycognitive functions that are compromised in the early stages ofAD. It has been suggested that attention, executive, semanticlanguage, and working memory deficits may be more consistentlyassociated with the later development of AD in individuals withMCI than memory processing deficits (Bäckman et al., 2005).Accordingly, it is important to delineate specific patterns of cog-

nitive impairment within MCI, as there is increasing evidence thatprimary deficits to memory in conjunction with deficits to othercognitive functions have greater predictive reliability of risk forprogression to AD than episodic memory deficits alone (Brandt etal., 2009; Espinosa et al., 2009; Herukka et al., 2007; Lonie,Herrmann, Donaghey, & Ebmeier, 2008; Rasquin et al., 2005;Ritchie et al., 2001; Sacuiu et al., 2009; Tabert et al., 2006).

A review (Twamley, Ropacki, & Bondi, 2006) of 73 neuropsy-chological studies investigating preclinical AD provides partialsupport for the findings of Bäckman et al. (2005), indicating thatthis preclinical stage is characterized by subtle deficits in attention(evident in 71% of studies), learning and memory (57% and 50%respectively), executive functioning (44%), processing speed(43%), and language (33%). Furthermore, this review revealed thatattention, although not as commonly assessed as learning andmemory, is more consistently associated with the later develop-ment of AD than memory deficits. Rapp and Reischies (2005)report that poor initial performance on measures of attention andexecutive function (Trail Making Test part B, Digit Letter, DigitSymbol, and Identical Pictures) were better predictors of thosenondemented participants that were diagnosed with AD two yearslater than were tests of episodic memory (Paired Associates, Mem-ory for Test, and Activity Recall). Grober et al. (2008) examinedthe temporal unfolding of declining memory performance andexecutive function before the diagnosis of AD by aligning subjectson time of AD diagnosis and then examining the cognitive coursepreceding diagnosis. They found that the rate of decline in perfor-mance on tests of episodic memory (Selective Reminding Test)accelerated 7 years before diagnosis and the rate of decline inperformance on tests of executive function (Category Fluency,Letter Fluency, Trail Making Test part B) accelerated 2–3 yearsbefore diagnosis. Johnson et al. (2009) examined global mentalability, verbal memory, working memory, and visuospatial abilityin 134 individuals who developed AD and 310 who remainednon-demented. This study established that the optimal inflectionpoint for all four factors was before a diagnosis of dementia:global, 2 years; verbal and working memory, 1 year; and visu-ospatial, 3 years. Before an inflection point the longitudinal courseof those who did and did not develop AD was the same. Further-more, their results indicate that the greatest rate of preclinicaldecline occurred on the visuospatial factor which comprised tasksalso associated with executive functioning and attention (DigitSymbol, Trail Making Test part A). Recent results from the Alz-heimer’s disease Neuroimaging Initiative (ADNI) indicate that thatexecutive impairments (Trail Making Test B-A difference score,and Digit Symbol Coding) predicted impairments in IADL and inMCI participants who progressed to AD (Marshall et al., 2011).Further, this relationship was independent of other factors includ-ing memory impairment and general cognitive impairment. Re-cently, Clark et al., (2012) found that specific measures of exec-utive function (Color-Word Interference Test, Verbal Fluency)differentiated between MCI participants who displayed cognitivedecline over 12 months from those who did not decline.

The aforementioned studies indicate that cognitive functionsother than memory are affected years before a clinical diagnosis ofAD, with difficulties performing tasks involving executive func-tions, such as attention control and working memory, often beingthe first indicators of the disease noticed by families (Storandt,2008). Accordingly, it is important to delineate specific patterns of

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nonmemory test impairment and episodic memory deficits withinMCI, with increasing evidence that memory deficits in conjunctionwith other cognitive deficits are more predictive of progressionthan episodic memory deficits alone (Alexopoulos, Grimmer, Per-neczky, Domes, & Kurz, 2006; Bozoki, Giordani, Heidebrink,Berent, & Foster, 2001; Brandt et al., 2009; Espinosa et al., 2009;Herukka et al., 2007; Lonie et al., 2008; Rasquin et al., 2005;Ritchie et al., 2001; Sacuiu et al., 2009; Tabert et al., 2006). Wehave previously reported the results of a prospective longitudinalstudy of MCI subtypes on a battery of neuropsychological mea-sures of memory, executive function, working memory, and lan-guage processing (Saunders & Summers, 2010, 2011). Recentlywe reported the results of a 20-month longitudinal study mappingthe trajectory of neuropsychological function in a sample of olderadults meeting the criteria for amnestic and nonamnestic MCI(Saunders & Summers, 2011). The present study reexamines thisprospective data, with a view to determining whether the outcomeof individuals in this sample could be predicted by their neuro-psychological performances observed at baseline testing. As Luisand colleagues (Luis et al., 2003) indicate, exploring the outcomesof participants in prospective longitudinal studies is essential tomap the transition from MCI to dementia, as well as to a variety ofother outcomes. It is evident from research to date that individualoutcomes from MCI are highly heterogenous. It is essential forfurther research into MCI to develop accurate and reliable diag-nostic criteria that are specific to the various outcomes. It is onlythrough the examination of data collected from prospective longi-tudinal studies that such specific and accurate diagnostic criteriacan be developed.

Method

Participants

A detailed description of the methodology used in this longitu-dinal study is described elsewhere (Saunders & Summers, 2010,2011). Participants were recruited from the general communitythrough advertising in print and radio media as well as throughlocal general medical practices. A total of 261 adults over 60 yearsof age responded to the recruitment campaign, with a total of 120completing a telephone screening which assessed self- andinformant-corroborated reports of the following: (1) memory prob-lems with a history of decline; (2) preserved cognitive functioning;(3) intact activities of daily living; (4) no history of significantmedical, neurological, or psychiatric condition; (5) no history ofmajor risk factors for vascular disease; and (6) no history ofalcohol abuse, sensory impairment, or impairment to hand mobil-ity (Saunders & Summers, 2010). Participants provided informedconsent before the commencement of the study, in accordance withthe Declaration of Helsinki (International Committee of MedicalJournal Editors, 1991) as well as the requirements of the HumanResearch Ethics Committee (Tasmania) Network and NHMRCHuman Research guidelines.

Of the 120 participants who underwent comprehensive neuro-psychological assessment, three were found to have clinicallysignificant levels of depression and were precluded from partici-pation. The remaining 117 participants were classified into one ofthe following MCI subtypes on the basis of baseline neuropsycho-logical screening (Saunders & Summers, 2010). For the purposes

of classification, mild impairment was quantified as a performance�10th percentile below age-based normative data; absence ofobjective impairment was defined as scores above this cutoffcriteria. We selected the 10th percentile as the impairment cutofffor two reasons: (a) 10th percentile equates to 1.28 SD below themean placing it at the midpoint between commonly used cutoffcriteria in MCI studies of 1.0 SD or 1.5 SD (Palmer, Backman,Winblad, & Fratiglioni, 2008; Petersen et al., 2001; Petersen et al.,1999) below the mean with no clear evidence that one has greatersensitivity or specificity than the other (Busse, Bischkopf, Riedel-Heller, & Angermeyer, 2003); and (b) from a clinical neuropsy-chological perspective the 10th percentile has greater ecologicalvalidity than a seemingly arbitrary cutoff of 1.5 SD or 1.0 SD (fora detailed discussion of the use of statistical cutoffs for definingsubclinical levels of impairment see: Brooks, Iverson, Holdnack,& Feldman, 2008; Brooks, Iverson, & White, 2007; Tuokko &McDowell, 2006). Single domain amnestic-MCI (a-MCI): (1)informant-corroborated subjective complaint of declining memoryfunctioning; (2) objective memory impairment (defined as a testscore on the Rey Auditory Verbal Learning Test (RAVLT) and/orPaired Associates Learning Test (PAL) �10th percentile belowage norms); and (3) no objective attention, working memory orsemantic language impairment. Multiple-domain amnestic-MCI(a-MCI�): (1) informant-corroborated subjective complaint ofdeclining memory functioning; (2) objective memory impairment(defined as a test score on the RAVLT and/or PAL �10th per-centile below age norms); and (3) objective attention, workingmemory or semantic language impairment (defined as a test score�10th percentile below age norms). Nonamnestic-MCI (na-MCI):(1) informant-corroborated subjective complaint of declining cog-nitive functioning; (2) no objective memory impairment; and (3)objective attention, working memory or semantic language impair-ment (defined as a test score �10th percentile below age norms).In addition, classification of MCI was contingent upon there beingno evidence of dementia as assessed by a DRS-2 AEMSS �9(Dementia Rating Scale – 2 age- and education-corrected MOANSscaled score) and intact ADL. A healthy control group consisted ofadults with no cognitive complaints or medical history of signifi-cance and matched the mean age and level of education of the MCIgroups. The inclusion of a healthy control group was deemedessential to provide a direct reference point against which thecognitive function of those MCI participants with recovery offunction could be compared. The resulting sample comprised fourgroups: control (n � 25); multiple-domain amnestic-MCI (a-MCI�; n � 48); single-domain amnestic-MCI (a-MCI; n � 12);and nonamnestic-MCI (na-MCI; n � 32). Of the 32 na-MCIparticipants, 30 had significantly lower scores (�10th percentile)on one nonmemory test (single-domain nonamnestic-MCI) andtwo had multiple nonmemory domain deficits below the 10thpercentile for age (multiple-domain nonamnestic-MCI). Given thesmall numbers in the multiple-domain nonamnestic-MCI categoryit was not feasible to individually examine this subtype, so thesetwo participants were classified with the 30 single-domainnonamnestic-MCI participants as na-MCI.

Participants were assessed at 10-month (baseline, 10 months, 20months) intervals (� 1 month). By the third assessment session,eight a-MCI � participants had withdrawn from the study (twodeceased; one relocated; five health reasons - three cancer, onehydrocephalus, one depression) and three na-MCI had withdrawn

500 SUMMERS AND SAUNDERS

(two relocated interstate; one health reasons - CVA). A total of 106participants aged between 60 and 90 years (46 male and 61female), comprising four subgroups, a-MCI (n � 12), a-MCI�(n � 40), na-MCI (n � 29), and healthy controls (n � 25),completed all three phases of assessment.

Materials

The Wechsler Test of Adult Reading (WTAR; The Psycholog-ical Corporation, 2001) was administered at baseline to estimatepremorbid WAIS-III FSIQ. A battery of clinical and neuropsycho-logical tests was administered at each 10-month assessment phase(see Table 1) tapping episodic memory, language processing,executive function, and working memory.

Several tests of executive function (Simple reaction time (RT),Choice RT, MTS, RVP, IED, SWM Strategy), working memory

(SSP, SWM), and visual episodic memory (PAL) were used fromthe CANTAB (Cambridge Automated Neuropsychological As-sessment Battery). The CANTAB subtests were selected from theCANTAB on the basis of the established sensitivity of thesemeasures to the progressive decline of cognitive functions early inthe course of AD (Fray, Robbins, & Sahakian, 1996; Sahakian &Owen, 1992). DRS-2 scores were converted to age- and education-corrected MOANS scaled scores (AEMSS). Parallel versions ofthe RAVLT and PAL were used at each assessment to reducepotential practice effects with repeat testing.

Procedure

Participants were assessed on three occasions: baseline, 10months, and 20 months. At each test session the clinical andneuropsychological tests were administered, followed by theCANTAB tests, which were administered in the following order:RTI, PAL, MTS, SSP, RVP, SWM, IED. The entire test batterytook approximately 90 minutes to administer. Halfway through thetesting procedure all participants were given a 10-minute break tominimize potential negative effects of fatigue. The CANTABsubtests were administered on a laptop computer attached to aseparate 17-inch touch-sensitive screen and a response pad. Par-ticipants were seated approximately 50 cm from the touch-screenand the response pad was positioned 15 cm from the bottom right(or left for left-handed participants) corner of the touch screen. Astandardized script was used to administer the CANTAB tests.

Results

Statistical computations were performed using SPSS for Win-dows (version 18.0) The neuropsychological tests used in thepresent study are susceptible to variations between groups result-ing from discrepancies in age, gender, premorbid IQ, and dementiaseverity (Strauss, Sherman, & Spreen, 2006).

Participants’ clinical and neuropsychological test results fromthe 20-month assessment were used to individually classify par-ticipants a-MCI, a-MCI�, na-MCI, or cognitively normal by anexperienced neuropsychologist (M.S.) who was blind to eachparticipant’s baseline classification. Participants who displayed adecrease in DRS-2 score (�8) and a clinically significant declinein one or more of the cognitive functions assessed were referred toan independent Geriatrician (specialist medical practitioner in Ge-riatric Medicine) for assessment. Participants were deemed to haveprogressed to AD if they were subsequently diagnosed by thegeriatrician as “possible” or “probable” AD. “Recovered” partic-ipants were those who on retesting scored above the 10th percen-tile on all objective tests of cognitive functioning and received aDRS-2 AEMSS score �9. “Stable MCI” refers to those partici-pants who received the same MCI classification at both the base-line and 20-month assessments. “Unstable MCI” encapsulatesparticipants who still met criteria for MCI but who changed MCIsubtype between the baseline and the 20-month assessments. “Pro-gressed” defines those participants who were classified at baselineas a-MCI or na-MCI but were reclassified as a-MCI � followingthe 20-month assessment.

Overall, of the 81 participants classified as MCI at baseline 10(12%) were subsequently diagnosed with possible (n � 5) orprobable (n � 5) AD after the 20-month assessment (converted),

Table 1Neuropsychological Test Battery

Test Purpose of test

Geriatric DepressionScale (GDS)

to screen for clinical depression(Yesavage, 1983)

Mattis Dementia RatingScale-2 (DRS-2)

to screen for the emergence of dementia(Mattis, 2001)

Boston Naming Test(BNT)

a measure of language retrieval fromsemantic memory (Kaplan,Goodglass, & Weintraub, 1983)

Rey Auditory VerbalLearning Task(RAVLT)

a measure of episodic verbal memory(Lezak, Howieson, & Loring, 2004;Strauss, et al., 2006)

Paired AssociatesLearning test (PAL)

a CANTAB subtest assessing ofepisodic visual memory (CambridgeCognition Ltd, 2004)

Simple RTI test (SimpleRT)

a CANTAB subtest assessing simplesustained attention

Five-choice RTI test(Choice RT)

a CANTAB subtest assessing dividedattention

Match to Sample VisualSearch (MTS)

a CANTAB subtest assessing theparticipant’s accuracy and speed inmatching visual samples

Rapid Visual Processing(RVP)

a CANTAB subtest of sustainedattention (RVP mean latency) andtarget detection (RVP A�), with asmall working memory component.RVP is sensitive to dysfunction in theparietal and frontal lobe areas of thebrain (Sahakian & Coull, 1993)

Intra-Extra DimensionalSet Shifting (IED)

a CANTAB subtest assessing ruleacquisition, flexibility of thinking andattentional set shifting. IED is acomputerised equivalent of theWisconsin Card Sorting Test.

Spatial WorkingMemory (SWM)

a CANTAB subtest assessing short-termretention and manipulation of spatialinformation in working memory andis sensitive to frontal (but nottemporal) lobe damage. In addition,SWM strategy assesses heuristicstrategy and is a sensitive measure offrontal lobe and ‘executive’dysfunction (Robbins & Sahakian,1994).

Spatial Span (SSP) a CANTAB subtest of working memorycapacity and is a computerisedequivalent of the Corsi Blocks task.

501PREDICTING DECLINE TO AD FROM MCI

20 (25%) had normal cognitive functioning at the 20-month as-sessment (recovered), the remaining 51 MCI participants contin-ued to meet criteria for MCI, however, 33 (41%) retained theirbaseline MCI classification, 12 (15%) changed MCI subtype clas-sification between baseline and the 20-month assessment, and theremaining six (7%) MCI participants developed additional cogni-tive impairments and were reclassified as a-MCI�. All 25 controlsremained cognitively healthy.

As displayed in Figure 1, of the 81 participants with MCI atbaseline, 10 had progressed to AD at 20 months, with all 10 beingclassified at baseline as a-MCI�. Given the period of follow-up(20 months), this equates to a 15% annual conversion rate froma-MCI�. It is also evident that of the 81 participants classifiedwith one of the MCI subtypes at baseline, a total of 20 (24.7%)reverted to unimpaired levels of function within 20 months ofbaseline assessment. Proportionately, rates of recovery to unim-paired levels of function appeared highest among the a-MCI(41.7%), followed by the na-MCI (34.5%) and a-MCI� (12.5%)groups. Of the 81 participants with MCI at baseline, 51 (62.9%)continued to meet one of the subtypes for MCI at 20 monthfollow-up. However, this figure is somewhat misleading as therewas considerable instability of MCI subtype classification overtime, with 33 of these 51 participants retaining the same MCIsubtype classification. Stability of MCI subtype classification washighest among the na-MCI (55.2%), followed by the a-MCI�(37.5%) with the a-MCI (16.7%) group displaying considerablyless stability of classification.

These results indicate that of the 81 MCI participants at base-line, 12.3% progressed to dementia, 62.9% continued to meet thecriteria for MCI, and 24.7% reverted to unimpaired levels offunctioning within 20 months. Of the 51 (62.9%) of MCI partic-ipants who continued to display MCI, only 33 remained in thesame MCI subtype as at baseline. As Figure 1 demonstrates, thereis considerable instability in the MCI classification across a 20-month period. Although some instability is expected, such asprogressive deterioration in cases of MCI that are a precursor to

dementia, other forms of instability, such as a high rate of rever-sion from MCI to unimpaired levels of function, are of concern.The high rate of recovery of function in this sample (24.7%) mayreflect two different effects: poor sensitivity of MCI “diagnosis”resulting in a high false positive rate, or lack of specificity in MCIclassification criteria resulting in poor discrimination betweensubclinical impairment and normal variation in neuropsychologi-cal function.

The original MCI criteria arose from a conceptual presumptionthat subclinical impairments to episodic memory would be ahallmark risk feature for later development of AD (Petersen et al.,1997). However, episodic memory impairments are not unique toAD; further, subclinical impairments to single cognitive functionsare not uncommon in the normal adult population (Brooks et al.,2008; Brooks et al., 2007) increasing the probability of a falsepositive classification. Finally, while AD is characterized by epi-sodic memory impairment, this is not the only cognitive deficitassociated with AD nor is it necessarily the earliest presentingcognitive impairment in the emergence of AD (Grober et al., 2008;Johnson et al., 2009; Rapp & Reischies, 2005). The above resultsindicate that the existing conceptual approach of defining MCIfrom an expectation of the progression of AD fails to meet therequirements for diagnostic sensitivity and specificity when ap-plied at the level of the individual. However, this does not meanthat one should abandon the MCI concept; rather, there is a needto further develop the MCI concept in terms of enhancing diag-nostic sensitivity and specificity at the individual level. To do this,a prospective longitudinal approach is required whereby adultswith mild cognitive problems are assessed serially over time untilthe emergence of AD is identified. Then examination of theprediagnostic cognitive profile of those who develop AD, com-pared with those who do not, may enable the development ofaccurate criteria for diagnosing MCI as a precursor to AD.

To directly examine this proposition, we explored the capacityof the baseline neuropsychological data in our sample of 81 MCIparticipants and 25 controls to predict the outcome classification of

Figure 1. Participant outcomes at 20-month assessment.

502 SUMMERS AND SAUNDERS

each individual in the study. Outcome for each individual wasdefined as one of four outcomes: control group (n � 25), MCIrecovered (reverted to unimpaired levels of function; n � 20), MCI(remained in MCI classification; n � 51), and progressed to AD(n � 10). The demographic data at baseline for these four outcomegroups are evident in Table 2.

Significant differences between outcome groups were detectedfor WTAR estimated FSIQ, with the control group displaying asignificantly higher score than the MCI group; however the pre-morbid estimated FSIQ for all groups remained at or above aver-age levels.

An assumption of discriminant function analysis (DFA) is thatgroup sizes of the dependent variable are not grossly different;therefore, a subsample of 25 was randomly selected from the MCIsample of 51 participants to reduce the potential effect of unequalsample sizes. An analysis of the demographic data from the MCIsubset indicates that it accurately represents the original set of 51participants (see Table 2).

To select variables that predict progression to AD (progressed),a stable classification of mild cognitive impairment (MCI), rever-sion to normal cognitive functioning (recovered), and stable nor-mal cognitive functioning (control) at 20 months follow-up, all ofthe baseline neuropsychological scores were entered into multi-variate analysis of variances (MANOVAs) to maintain control ofexperiment-wide Type I error rate across tests from similar cog-nitive domains. Multicollinearity was assessed by examining linearcorrelations between each of the dependent variables. Where asignificant linear correlation was identified between two depen-dent variables, partial correlations were performed between theprimary dependent variable and independent variable (outcomegroup) controlling for the influence of the second dependent vari-able. Significant collinearity was identified between RAVLT totaland RAVLT Trial 5, and between IED Total Errors and IED TotalTrials, resulting in the exclusion of RAVLT Trial 5 and IED

Total Errors from all subsequent analyses. All other dependentvariables displayed significant unique variance after the partialingout of collinearity. The overall MANOVA identified significantgroup effects, Pillai’s F(45,192) � 3.388, p. �.001, �e

2 � .443,power � 1.00. Subsequent one-way ANOVAs identified the fol-lowing tests that discriminated between more than one pair ofoutcome groups: RVP A, PAL (total trials and errors at 6 shapes),RAVLT (total and recall), SSP, SWM (total errors), CRT, BNT,and MTS. The baseline neuropsychological tests that discriminatedbetween outcome groups were then entered into a multiple dis-criminant function analysis (DFA), which revealed three discrim-inant functions (DF). The first, � � .130, �2(30, n � 80) �146.80, p � .001, and second, � � .595, �2(18, n � 80) � 37.36,p � .005, discriminant functions were statistically significant, butthe third was not, � � .911, �2(8, n � 80) � 6.72, p � .58. Thefirst discriminant function (DF1) accounted for 85.0% of thevariance with the second discriminant function (DF2) accountingfor a further 12.6% of variance. As shown in Table 3, high scores onDF 1 were associated with lower scores on RVPA (target detection,sustained attention), higher PAL total errors (visual memory), lowerSSP span length (immediate memory span), a lower RAVLT totalscore (verbal memory), and more errors on PAL 6 shapes. In contrast,high scores on DF2 were associated with higher SWM total errors(working memory) and slowed RT on the Choice Reaction Time task(divided attention). DF1 identifies a pattern of poorer performance onmeasures of episodic verbal memory, episodic visual memory, targetdetection on a sustained attention task, and visual immediate memoryspan. DF2 identifies a pattern of poorer performances on measures ofvisual working memory capacity and divided attention.

The means for the outcome groups on the discriminant func-tions, as well as the group means on each of the neuropsycho-logical and demographic variables, are contained in Table 4.DF1 differentiates the four outcome groups, with the progressedgroup having the highest DF1 score followed by the MCI group,

Table 2Demographic Information

Control Recovered MCI Progressed p value (ANOVA) Post hoc differences

nTotal sample 25 20 51 10DFA subset 25

AgeTotal sample 69.36 (5.8) 70.00 (5.9) 71.04 (7.1) 73.80 (7.9) .326DFA subset 71.60 (6.9) .257

EducationTotal sample 13.64 (3.1) 13.70 (4.1) 12.55 (3.0) 14.60 (3.5) .203DFA subset 12.44 (3.2) .341

WTAR Estimated FSIQTotal sample 112.16 (5.4) 108.45 (7.3) 107.65 (7.7) 115.70 (7.5) .003 C MDFA subset 107.64 (8.9) .013 ns

DRS-2Total sample 11.76 (1.7) 11.35 (1.7) 11.43 (2.0) 10.40 (2.5) .323DFA subset 11.84 (1.7) .177

GDSTotal sample 1.64 (1.8) 1.15 (1.0) 1.61 (1.6) 1.70 (1.5) .666DFA subset 1.72 (1.9) .648

Gender (% M:% F)Total sample 32:68 50:50 43:57 60:40 (�2) .423DFA subset 40:60 (�2) .406

Note. Post hoc differences significant at p � .05.

503PREDICTING DECLINE TO AD FROM MCI

then the recovered group, with the control group having thelowest DF1 score. A different pattern was evident for DF2, withthe progressed group displaying lower score than the controlgroup, with both groups displaying lower DF2 scores than the MCIand recovered groups. DF2 did not differentiate between MCI andrecovered groups. Examination of the tests that constitute DF2indicates that the control group displayed significantly fasterChoice RT than the MCI and recovered groups, with the pro-gressed group displaying a RT speed between the control groupand the MCI and recovered groups. On the SWM total errors task,the control group displayed significantly fewer errors than theprogressed, recovered, and MCI groups, with no other groupdifferences being detected. These results indicate that the compos-ite of tests comprising DF1 (RVPA, PAL total errors, SSP length,RAVLT total recall, and PAL 6 shapes) discriminates between theprogressed, MCI, recovered, and control outcome groups. Al-though DF2 is significant, the tests that comprise DF2 (Choice RT,SWM total errors) do not display a clear differentiation betweenprogressed, MCI, recovered, and control outcome groups.

Univariate analyses of variance (ANOVA) indicate that theoutcome groups differed significantly on DF1, F(3,76) � 114.74,

p � .001, and DF2, F(3,76) � 18.21, p � .001. Further ANOVAswere conducted on the variables loading most heavily on DF1,revealing that the outcome groups differed significantly on RVPA�, F(3,76) � 22.96, p � .001, PAL total errors adjusted, F(3,76) �14.65, p � .001, SSP length, F(3,76) � 13.01, p � .001, RAVLTtotal, F(3,76) � 8.77, p � .001, and PAL 6 shapes errors adjusted,F(3,76) � 9.23, p � .001. The four groups also differed signifi-cantly on the functions loading most heavily on DF2: SWM totalerrors, F(3,76) � 8.18, p � .001, and choice RT, F(3,76) � 3.70, p �.014. Although DF3 was not statistically significant, the fourgroups differed significantly on the factors loading most heavilyon this function: BNT, F(3,76) � 4.93, p � .003, RAVLT recall,F(3,76) � 8.97, p � .001, RAVLT Trial 5, F(3,76) � 8.97, p � .001,and MTS correct latency, F(3,76) � 9.01, p � .001. To ensure thatparticipants removed via the random sampling procedure did notdiffer from those in the random sample (n � 80), univariateANOVAs were also conducted on each of the measures reported inTable 3 for the entire sample (n � 106), with the same significantdifferences being detected.

The LSD procedure was used to make pairwise comparisons onDF1 and DF2. There were significant differences between each groupon DF1, with the progressed group scoring significantly higher thanthe MCI group, which scored significantly higher than the recoveredgroup, which scored significantly higher than the control group.Significant group differences were also identified on DF2, with theprogressed group scoring significantly higher than the MCI and re-covered groups, which scored higher than the control group.

Overall, 86.3% of participants were placed correctly. As shown inTable 5, the relationship between the tests and the group outcomeindicated that 96% of the control group (4% classified as recovered),65% of the improved group (10% classified as control; 25% classifiedas MCI), 88% of the stable MCI group (8% classified as recovered;4% classified as progressed), and 100% of those who progressed toAD were placed in the correct group.

Discussion

Epidemiological studies indicate that individuals classified withMCI show elevated rates of conversion to AD at the group level.

Table 4Mean Scores for the Discriminant Functions and Neuropsychological Variables for Outcome Groups

Variable

Outcome group

Progressed(n � 10)

MCI(n � 25)

Recovered(n � 20)

Control(n � 25)

Discriminant function 1 3.29A 1.23B .354C 2.265D

Discriminant function 2 1.39A .633B .571B .535C

RVP A� .820 (0.05)A .864 (0.04)B .888 (0.05)B 0.939 (0.04)C

PAL total errors adj 56.40 (20.84)A 34.16 (21.77)B 29.45 (13.28)B 19.68 (9.54)C

SSP length 4.70 (0.82)A 4.84 (0.69)A 5.25 (0.55)A 5.84 (0.75)B

RAVLT total 33.40 (5.46)A 39.28 (10.01)A 42.20 (10.27)B 48.44 (6.79)C

PAL6 shapes errors adj 14.30 (10.86)A 9.08 (7.48)B 6.90 (4.42)C 4.36 (3.43)C

SWM total errors 45.90 (9.18)A 50.24 (18.46)A 46.07 (12.22)A 32.92 (12.95)B

Choice RT 364.72 (53.20) 384.47 (44.67)B 380.96 (76.06)B 337.12 (42.79)A

BNT 55.90 (2.13) 55.40 (4.50)A 54.35 (3.18)A 57.48 (1.73)B

RAVLT recall 6.00 (2.54)A 8.28 (3.08)B 8.40 (2.66)B 10.40 (2.47)C

MTS correct latency 3694.05 (1090.77)A 4209.59 (1777.45)A 3333.10 (1414.79)B 2661.63 (665.24)B

Note. Superscript letters A, B, C, D that differ across rows represent statistically significant differences by the LSD procedure (p � .05).

Table 3Structure of the Discriminant Functions (DF)

Variable

Loading

DF 1 DF 2 DF 3

RVP A� .483� .032 .257PAL total errors .348� .270 .249SSP .339� .220 .049RAVLT total .307� .001 .168PAL6 errors .260� .143 .031SWM total errors .222 .393� .155Choice RT .140 .367� .278BNT .110 .321 .711�

RAVLT recall .262 .068 .440�

MTS correct latency .212 .324 .358�

� Largest absolute correlation between each variable and any DF.

504 SUMMERS AND SAUNDERS

However, concerns have been raised regarding the stability of MCIat the individual level, with a substantial proportion of individualswith MCI not exhibiting the specific cognitive deficits that char-acterized their initial cognitive presentation upon longitudinalfollow-up and some reverting to a normal level of cognitivefunctioning (Busse et al., 2006; Gauthier et al., 2006; Jak et al.,2009; Loewenstein, Acevedo, Agron, & Duara, 2007; J. Mitchell,Arnold, Dawson, Nestor, & Hodges, 2009; Tuokko & McDowell,2006). The current study investigated the ability of single time-point neuropsychological measures to predict eventual risk forconversion to dementia, stability of MCI classification, and rever-sion to normal cognitive status. We examined individual outcomesof a group of 81 participants identified at baseline as meetingcriteria for one of three MCI subtypes and 25 age- and education-matched healthy controls. A neuropsychological battery of atten-tion, working memory, executive function, semantic memory, andverbal and visual episodic memory was used to assess theseparticipants at baseline and 20 months later.

At the 20-month follow-up assessment 12.3% of the MCI par-ticipants had developed possible or probable AD (converted), 25%had improved no longer meeting the criteria for MCI (recovered),41% continued to display the same neuropsychological profile asat baseline assessment (stable), 15% displayed a neuropsycholog-ical profile for a different MCI subtype than at baseline assessment(unstable), and the remaining 7% of MCI participants progressedfrom a single domain MCI subtype (a-MCI or na-MCI) to amultidomain MCI subtype (a-MCI�) (progressed). All 25 controlsdisplayed stable neuropsychological performance from baseline tofollow-up. The 20-month conversion rate to AD of 20.83% (12.5%annually) from a-MCI � and 12.3% (7.4% annually) across allforms of MCI in this study falls within the reported annual con-version rates to AD of approximately 1–25% (Dawe et al., 1992).It is of interest, however, that of the participants who had devel-oped AD in the present study, all had met criteria for a-MCI � atinitial assessment, with no participants developing AD directlyfrom single-domain na-MCI or a-MCI subtypes within 20 months.The finding that 25% of the MCI sample reverted to normal levelsof function within 20 months is consistent with previous reportsstudies (Comijs, Dik, Deeg, & Jonker, 2004; Ganguli et al., 2004;Larrieu et al., 2002; Palmer, Wang, Backman, Winblad, &Fratiglioni, 2002) and indicates that current MCI classificationcriteria derived from epidemiological studies have little utilityin the clinical diagnosis of an individual at risk of developingdementia.

We subsequently examined the capacity of a single time-pointneuropsychological examination to accurately predict individualoutcome 20 months later. A discriminant function analysis re-vealed that a combination of measures of visual episodic memory(PAL), verbal episodic memory (RAVLT), visual immediatememory span (SSP), visual working memory capacity (SWM),divided attention (CRT), and sustained attention and target detec-tion (RVP A�) accurately classified outcome at 20 months in86.3% of cases. Of particular interest is the finding that this set ofmeasures accurately identified 100% of the cases that progressedto AD. A total of 65% of the recovered cases were correctlyidentified, with a further 10% having been classified as unimpairedcontrols, resulting in a correct classification of recovery from MCIof 75% of cases. Of those with stable MCI, 88% were correctlyclassified using the same set of measures. The subset of measuresresulted in a false positive rate of 25% for classifying recoveredcases as persistent MCI and 4% of stable MCI as having pro-gressed to AD. These measures also resulting in a false negativerate of 8% for misclassifying stable MCI as recovered to normallevels of function.

From the perspective of the clinician, the results of the presentstudy caution against the diagnosis of MCI based on the presenceof an episodic memory deficit alone. The results of this studyindicate that amnestic impairment alone lacks predictive reliabilityand validity for identifying those at risk of developing dementia inthe short-term. Rather, a pattern of multiple subclinical impair-ments to episodic memory, executive function (attention), short-term memory (STM) span, and working memory capacity hasgreater predictive reliability for the emergence of dementia in theshort term. That multiple domain subclinical impairments predictdevelopment of Alzheimer’s dementia is not surprising given thatthe clinical diagnosis of Alzheimer’s dementia requires the pres-ence of clinically significant impairments in two or more cognitivedomains including memory (McKhann et al., 2011). Thus, thepattern of impairments identified in the present study may repre-sent a clinically identifiable prodromal phase to dementia as dis-tinct to the MCI classification based on a set of epidemiologicallyidentified risk factors for dementia.

One potential source of instability in the predictive reliability ofexisting MCI classification criteria (Winblad et al., 2004) is afailure to account for normal variation in individual performanceacross a range of cognitive measures. Contemporary classificationprocedures for MCI typically require evidence of cognitive im-pairment on only a single test at a single occasion of measurement.

Table 5Outcome Classification Predicted From Baseline Neuropsychological Scores

Outcome classification

Predicted outcome (from baseline scores)

Control Recovered MCI Progressed AD

n (%) n (%) n (%) n (%)

Control (n � 25) 24 (96) 1 (4) — — — —Recovered (n � 20) 2 (10) 13 (65) 5 (25) — —MCI (n � 25) — — 2 (8) 22 (88) 1 (4)Progressed AD (n � 10) — — — — — — 10 (100)

Note. Control � cognitively normal; Recovered � no cognitive impairment at follow-up assessment; MCI � one or more memory or non-memorycognitive domains impaired; Progressed AD � possible or probable Alzheimer’s disease. 86.3% of cases correctly classified.

505PREDICTING DECLINE TO AD FROM MCI

Studies in normative neuropsychology demonstrate that, given amultitest battery of cognitive measures, the probability that acarefully screened, neurologically normal individual will showisolated impairment on a single measure is high (Brooks et al.,2008; Brooks et al., 2007). The lack of precision and reliability ofsingle neuropsychological measures at single time-points mayexplain the reports of high recovery rates among MCI samplestested longitudinally, an effect akin to a false positive diagnosis ofMCI. The results of our study suggest that the rate of recovery washigher among participants classified with a-MCI (41.7%) or na-MCI (34.5%) than those with a-MCI� (12.5%). This may reflectthe difference between the reliability of a classification based onmultiple tests across multiple domains (a-MCI�), as opposed to aclassification based on a single measure on a single domain(a-MCI, na-MCI).

Recent studies hypothesize that preclinical phases of AD may becharacterized by pathological changes in the brain. These patho-logical changes may be detected using various biomarkers, such asCSF, PET imaging, and MRI analysis of brain structure (Sperlinget al., 2011). It is also suggested that these biomarkers may bedetected ahead of changes in cognitive function (Sperling et al.,2011). The results of the present study suggest that the capacity forcognitive measurement to detect prodromal phases of dementia islimited, both by the sensitivity and specificity of existing neuro-psychological measures as well as the instability of single domainsubclinical neuropsychological impairment as a marker of laterdementia. Future research may consider the capacity of biomarkersto enhance the sensitivity and specificity of diagnosis of MCIusing neuropsychological measures. The results of the presentstudy need to be tempered with the limitations of the study. The20-month test–retest interval may have been too short to detectsubstantial changes in neuropsychological function over time. It isprobable that progressive decline in cognitive function in MCI isrelatively slow and that longer time intervals are therefore requiredto detect significant changes.

The present study suggests that existing MCI criteria emergingfrom epidemiological research lack sensitivity and specificity tomeet the standards for diagnosis. A pattern of impairments toepisodic memory, short term memory, working memory, and at-tentional processing were found to differentiate between partici-pants with MCI that would develop AD, recover to normal levelsof function, or remain in stable MCI within 20 months. Thispattern of subclinical impairments may represent clinical symp-toms of a prodromal phase of Alzheimer’s dementia.

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Received September 12, 2011Revision received April 13, 2012

Accepted April 16, 2012 �

508 SUMMERS AND SAUNDERS