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The California Verbal Learning Test and other standard clinical neuropsychological tests to predict conversion from mild memory impairment to dementia Françoise Lekeu abc; Delphine Magis ab; Patricia Marique ab; Xavier Delbeuck d; Sophie Bechet a; Bénédicte Guillaume a; Stéphane Adam a; Jean Petermans c; Gustave Moonen a; Eric Salmon abc a Memory Centre, Department of Neurology, University Hospital, Liège, Belgium b Cyclotron Research Centre, University of Liège, Liège, Belgium c Geriatric Day Hospital, University Hospital, Liège, Belgium d Memory Clinic, University Hospital, Lille, France First Published on: 20 May 2009

To cite this Article Lekeu, Françoise, Magis, Delphine, Marique, Patricia, Delbeuck, Xavier, Bechet, Sophie, Guillaume, Bénédicte,

Adam, Stéphane, Petermans, Jean, Moonen, Gustave and Salmon, Eric(2009)'The California Verbal Learning Test and other standard clinical neuropsychological tests to predict conversion from mild memory impairment to dementia',Journal of Clinical and Experimental Neuropsychology, To link to this Article: DOI: 10.1080/13803390902889606 URL: http://dx.doi.org/10.1080/13803390902889606

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JOURNAL OF CLINICAL AND EXPERIMENTAL NEUROPSYCHOLOGY 2009, iFirst, 1–12

The California Verbal Learning Test and other standard clinical neuropsychological tests to predict conversion from mild memory impairment to dementia

NCEN

POWER OF CVLT IN DEMENTIA PREDICTION

Françoise Lekeu,1,2,3 Delphine Magis,1,2 Patricia Marique,1,2 Xavier Delbeuck,4 Sophie Bechet,1 Bénédicte Guillaume,1 Stéphane Adam,1 Jean Petermans,3 Gustave Moonen,1 and Eric Salmon1,2,3 1

Memory Centre, Department of Neurology, University Hospital, Liège, Belgium Cyclotron Research Centre, University of Liège, Liège, Belgium 3 Geriatric Day Hospital, University Hospital, Liège, Belgium 4 Memory Clinic, University Hospital, Lille, France Downloaded By: [Lekeu, Françoise] At: 09:48 25 May 2009

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This study describes the neuropsychological assessment of 34 patients with questionable Alzheimer’s disease (QAD) followed up for 3 years. Several measures were selected from the California Verbal Learning Test (CVLT) and compared to other cognitive tasks to assess the best neuropsychological indices for (a) detecting early memory impairment in QAD and (b) predicting conversion to AD. Concerning detection, the results indicated that a recall measure depending on semantic categorization (short-delay cued recall) signaled a memory deficit in stable QAD patients, suggesting that episodic and semantic memory problems are involved in the early cognitive impairments of stable QAD patients. However, the conversion to AD was best predicted by the initial performance at the recency index (score reflecting high reliance on working memory), corroborating the idea that AD patients (even at the questionable stage) essentially rely on preserved phonological loop functioning in memory tasks. Finally, an additional impairment in visuospatial memory (Rey’s figure) provided a good discriminant value to distinguish converters from stable QAD patients, showing that various cognitive disabilities deteriorate in AD. Keywords: Questionable Alzheimer’s disease; Mild cognitive impairment; California Verbal Learning Test; Conversion to dementia; Prediction.

INTRODUCTION Differentiating people with mild memory loss who will remain stable from those destined to develop Alzheimer’s disease (AD) represents a real challenge, in particular from the perspective of early cognitive and/or drug support. To achieve this goal, the number of longitudinal studies of patients with mild cognitive impairment (MCI) or questionable Alzheimer’s disease (QAD) has increased over the last 10 years. In these studies,

patients with isolated memory impairment were tested with a large battery of classical neuropsychological tests to isolate, at the end of a given follow-up period, which of the initial cognitive measures were the most sensitive in distinguishing converters—that is, patients who developed AD—from those patients who remained stable (Fowler, Saling, Conway, Semple, & Louis, 1997; Petersen et al., 1999). A number of these studies have shown that measures of episodic memory performance may be the

This study was conducted on behalf of the Network for Efficiency and Standardization of Dementia Diagnosis (NEST-DD), supported by the European Commission (5th framework), and it was finalized under the auspices of the EC-FP6-project DiMI, LSHB– CT–2005–512146. The work was also supported by grants from the Fonds National de la Recherche Scientifique (FNRS) in Belgium, the IUAP P6/29, the University Hospital of Liège, and the University of Liège. Address correspondence to Françoise Lekeu, Memory Centre and Geriatric Day Hospital–University Hospital of Liège, Quai Godefroid Kurth 45, B-4020 Liège, Belgium (E-mail: [email protected]).

© 2009 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business http://www.psypress.com/jcen DOI: 10.1080/13803390902889606

Downloaded By: [Lekeu, Françoise] At: 09:48 25 May 2009

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LEKEU ET AL.

best indicators for differentiating people who will develop AD from those who will not (Albert, Moss, Tanzi, & Jones, 2001; Artero, Tierney, Touchon, & Ritchie, 2003; Bäckman, Jones, Berger, Laukka, & Small, 2004; Blackwell et al., 2004; Chen et al., 2000). However, to increase the sensitivity and specificity of the predictive measures, memory performance should be considered in combination with other “nonmemory” measures (Albert et al., 2001; Artero et al., 2003; Chen et al., 2000; Tabert et al., 2006). This is not surprising when one considers that pure, isolated memory impairment is rare (Alladi, Arnold, Mitchell, Nestor, & Hodges, 2006) and that cognitive impairment in the predementia stage of AD can be observed in many domains, including episodic memory, semantic memory, executive functions, attention, verbal abilities, visuospatial skills, and perceptual speed (Bäckman et al., 2004; Bäckman, Jones, Berger, Laukka, & Small, 2005). In the same vein, some authors recently proposed revising the diagnostic criteria for MCI to incorporate a change in activity level and impairment in nonmnesic cognitive functions (Artero, Petersen, Touchon, & Ritchie, 2006). According to Petersen et al. (1999), verbal episodic memory is the first cognitive domain impaired in the AD process. Supporting this suggestion, Chen et al. (2000) found that, among a battery of 16 neuropsychological tests, the delayed recall of a word list combined with the Trail Making Test B measure offered the best predictive accuracy for dementia conversion. In the same vein, Artero et al. (2003) entered the data from two prospective studies in a regression analysis to predict participants at risk for AD conversion. They confirmed that delayed verbal recall is an important measure to take into account, but it must be combined with data from construction and categorical fluency tests. Nevertheless, some studies also highlighted the high predictive power of visual memory performance in differentiating converters from nonconverters (Albert et al., 2001; Blackwell et al., 2004; Fowler et al., 1997; Masur, Sliwinski, Lipton, Blau, & Crystal, 1994). The differences between these studies concerning the best predictor of conversion to dementia might be due to various factors, such as the definition of MCI and the population studied (selection of persons with memory problems or individuals selected to represent the general population). Moreover, the tests used in these kinds of studies are quite different, and some of them are only used in experimental settings. However, it is important to challenge the clinical value of well-known standard neuropsychological tasks in making an accurate diagnosis.

The California Verbal Learning Test (CVLT) is a widely used neuropsychological test that assesses episodic memory (Delis, Freeland, Kramer, & Kaplan, 1988; Delis, Kramer, Kaplan, & Ober, 1987). The test begins with a 16-item word learning test (List A) presented over five trials. Immediately after the last learning trial, a second list of 16 words (List B) is presented as an interference trial, followed by short (a few minutes) and long (20 minutes) delayed free and cued recall of the List A and a recognition memory trial. Consequently, analysis of results on this test can provide information about the functioning of several cognitive domains, since the CVLT requires the contribution of episodic memory but also, among other things, of semantic memory and executive abilities of categorization. To the best of our knowledge, no follow-up study has described the initial performance of patients with MCI or QAD on the CVLT. The three-year follow-up study done by Albert et al. (2001) only used the CVLT basic measure of total recall and found that this measure had little sensitivity and specificity for an early diagnosis of memory impairment. Moreover, the measure did not have sufficient discriminant power to differentiate converters from stable patients. More recently, Greenaway et al. (2006) used a large number of memory measures from the CVLT to analyze the pattern of memory dysfunction across groups of normal controls (NC), MCI patients, and AD patients. The results showed that, compared to NC, MCI patients displayed reduced learning, rapid forgetting, increased recency recall, more intrusion errors, and poor recognition discriminability. A discriminant function analysis demonstrated that delayed recall and total learning were the best measures for distinguishing among the three groups. Unfortunately, that study did not present followup data for the MCI patients. Based upon these observations, our study could be viewed as an extension of the two studies described above. Patients with “isolated” memory impairment and no significant decrease in daily activities were selected in memory clinics where different neuropsychological tests (but not the CVLT) were used to assess memory performance. Patients were referred to the Cyclotron Research Centre to enter a European multicentre study (Network for Efficiency and Standardization of Dementia Diagnosis, NEST-DD), for which the CVLT was selected as a commonly available test to evaluate verbal episodic memory. Different CVLT scores and other baseline neuropsychological tests were analyzed, searching for the cognitive indices that would prove most useful for (a) the objective


detection of early memory impairment in QAD versus control participants and (b) the early diagnosis of patients converting to AD during a three-year follow-up period.

METHOD


Participants The participants were 34 patients referred by neurologists working in memory clinics to participate in the NEST-DD European multicentre study. They had memory problems confirmed by a relative, but without any significant impairment in daily living activities (assessed by Lawton’s scale; Lawton & Brody, 1969) or global cognitive deterioration. Indeed, all participants demonstrated independent functioning in activities of daily living with minor interference of cognitive impairments, since they all scored 1 at each section of Lawton’s scale. The patients had undergone neurological, neuropsychological, and structural neuroimaging evaluations and were classified as QAD since they had a Clinical Dementia Rating (CDR) score of 0.5 (Morris, 1993), and they did not meet criteria for Alzheimer-type dementia (McKhann et al., 1984). They met the criteria for either amnestic MCI (with at least one memory test performance 1.5 standard deviations below the mean for age-matched controls) or multiple-domain MCI (when cognitive performance was also decreased in another, nonmemory, domain; Petersen et al., 2001; Winblad et al., 2004). Exclusion criteria were dementia, mental retardation, fewer than four years of education, brain trauma, epilepsy, cancer, depression, any major systemic disease, or any substance abuse. At the time of inclusion, all patients were free of medication that could noticeably affect brain function. All QAD patients had Mini-Mental State Examination (MMSE) scores of 21 or over at baseline evaluation (MMSE; Folstein, Folstein, & McHugh, 1975). Note that the exclusion criteria included a CDR score of greater than 0.5, attributed by the referring neurologist, while the MMSE score at entry into the study was taken as an experimental variable. All patients were clinically followed up for 36 months, if they did not convert to AD before the end of this period. At the final follow-up session, diagnoses were reviewed on the basis of a multidisciplinary discussion taking into account neuropsychological, neurological, functional, and behavioral factors. The diagnosis of AD was given according to generally accepted clinical criteria (McKhann et al., 1984). At 36 months, 17 patients (50%) remained

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stable, and 17 patients (50%) had converted to probable Alzheimer’s disease (PrAD). In this latter group, 2 patients converted within 6 months, 4 patients converted within 12 months, 6 patients converted within 18 months, 4 converted within 24 months, and 1 converted in 36 months. The mean follow-up duration for the study was 26.8 months. Normal control participants (NC) were 14 cognitively and neurologically intact elderly adults who lived in the community and were recruited by word of mouth. The exclusion criteria were the same as those used for the patients, and the NC had a CDR score of zero. All control participants completed the experimental neuropsychological testing. All patients and controls gave their informed consent to participate in the study, which was approved by the Ethics Committee of the University Hospital Centre in Liège. Neuropsychological tests At the baseline session, all QAD patients and NC performed a neuropsychological battery that examined verbal and visual episodic memory as well as visuoperceptive processing, working memory, language, and executive functions. For verbal episodic memory, the French adaptation of the California Verbal Learning Test was used (CVLT; Delis et al., 1988; Delis et al., 1987). Performance was carefully examined by using different index and memory scores. Short-delay recall In the CVLT, there are two lists of 16 words (List A and List B) belonging to four semantic categories. The measures for List A were: the total number of correct words produced during Trials 1 to 5; the short-delay free recall, corresponding to the number of correct words freely recalled immediately after the recall of List B; and the short-delay cued recall, which corresponds to the number of correct words recalled (over and above the free recall) in response to semantic cues. Three indices were also calculated: a constancy learning index, which corresponds to [(the number of times an item correctly recalled during Trials 1 to 4 is recalled during Trial 5)/(total free recall for Trials 1 to 4)] × 100; a primacy index, which corresponds to [(cumulative recall of the first four items of List A during Trials 1 to 5)/(total free recall for Trials 1 to 5)] × 100; and a recency index, which corresponds to [(cumulative recall of the last four items of List A during Trials 1 to 5)/(total free recall for Trials 1 to 5)] × 100. The only measure for List B is the total number of correct words freely recalled.

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Long-delay recall After a 20-minute delay, correct words (List A) were measured in both free- and cued-recall conditions. Errors The total number of intrusions produced during the recall trials was measured.


Recognition Recognition was tested after the long-delay recall. The following measures were obtained: total number of false recognitions; false recognitions from List B; a discrimination index, which assesses recognition memory performance more accurately by taking into account hits, false recognitions, and omissions; and finally a response bias, which characterizes the tendency for a participant to respond “yes” or “no” in recognition memory tasks (a neutral response bias = 0). Organization in free recall Concerning organization in free recall, the CVLT also provides two specific measures: semantic clustering and serial order recall. Semantic clustering demonstrates how participants organize the word list during learning (encoding). This measure corresponds to the number of consecutively recalled words from the same semantic category, taking into account the total number of words recalled. Serial order recall is the number of words recalled in the same order as presented. A proportional measure (serial cluster ratio) is obtained by dividing the number of serial order clusters by the maximum number of order clusters, which in turns depends on the total number of words recalled. Details about the formula used for the index calculation have been published by Delis et al. (1988).

Data analysis A one-way analysis of variance (ANOVA), with each cognitive measure as the dependent variable and a factor representing the three groups (NC, stable QAD, converting QAD), was first performed. Planned comparisons were then carried out between groups (NC vs. stable QAD, stable QAD vs. converting QAD, NC vs. converting QAD, whole QAD group vs. NC). Only cognitive measures that were significantly different (using Bonferroni corrections) among groups were entered in forward stepwise regression analyses, which were followed by associated discriminant analyses and the receiver operating characteristic (ROC) curve method. We a priori decided to introduce only neuropsychological variables in the subsequent analyses. Our different regression and discriminant analyses aimed to answer four questions concerning patients referred to memory clinics: (a) The first analysis, contrasting normal control and stable QAD groups, investigated the sensitivity of the CVLT indices for the detection of early memory impairment; (b) the analysis contrasting the stable and converting QAD groups was designed to isolate which neuropsychological measure(s) would be the best predictors of dementia in QAD; (c) the analysis contrasting the normal controls and the converters was designed to identify the most accurate neuropsychological measures for early dementia diagnosis (by comparing the two previous analyses and this third analysis); (d) as is done in the literature, we also contrasted the normal controls and the whole QAD group, in order to highlight the neuropsychological measures that best detect the QAD “syndrome.”

RESULTS Visual episodic memory was assessed by using the 30-minute delayed recall of the Rey complex figure (Rey, Osterrieth, & Taylor, 1991). The other cognitive tests used were: copying of the Rey complex figure for visuoperceptive processing; the forward digit span and block tapping tests for working-memory evaluation; the category (animals: 120 s) and phonemic fluency tests (P, R, V: 120 s each) for language assessment; and the Stroop test for evaluation of executive functions (and specifically inhibition; Lezak, 1983). The MMSE was used to assess global cognitive impairment (Folstein et al., 1975), and the 21-item Hamilton scale evaluated depressive symptoms (Hamilton, 1967).

Distributional and demographic analyses Demographic and clinical features for the NC, stable QAD, and converting groups are presented in Table 1. There were no statistically significant differences between groups with respect to educational level, F(2, 45) = 0.65, ns, or Hamilton Rating Scale for Depression (HAM-D) score of depression, F(2, 45) = 0.25, ns. Sex distribution was statistically independent from final diagnosis, c2(1) = 2.95, p < .08, although there were more women in the converting group (71%) than in the stable QAD group (35%). The mean MMSE score of the whole QAD group was 24.9 (SD 2.2). As expected, the normal

POWER OF CVLT IN DEMENTIA PREDICTION TABLE 1 Demographic variables of study participants

Characteristics No. women (%) Age (in years) Education (in years) Ham-D MMSE

NC (N = 14)

Stable QAD (N = 17)

Converting QAD (N = 17)

8 (57) 66.0 (6.6) 12.0 (3.1)

6 (35) 66.6 (6.9) 12.3 (5.2)

12 (71) 72.0 (5.9)a 10.8 (2.5)

3.2 (3.8) 29.1 (0.9)

2.5 (2.8) 25.7 (2.0)b

2.6 (2.7) 24.1 (2.1)a


Note. NC = normal controls. QAD = questionable Alzheimer’s disease. Ham-D = Hamilton Rating Scale for Depression; MMSE = Mini Mental State Examination. Standard deviations in parentheses. a Significantly different from controls and stable QAD group. b Significantly different from controls.

controls had higher MMSE scores than the patients, F(1, 45) = 53.4, p < .0001. Moreover, the converters had lower MMSE scores at entry than the stable QAD participants, F(1, 45) = 7.43, p < .01. The converting patients were also older at entry than the two other groups, as is well established in the literature. MMSE score was entered as a potential predictive variable in all regression analyses. Since age differed between groups, and more importantly between converters and stable QAD patients, we checked that introducing age in all relevant regression and discriminant analyses did not change our results. Age was never retained as a discriminant variable. Neuropsychological data analysis In the stable QAD group, visual working memory (Block Tapping Test), several results on the CVLT (total free recall, short- and long-delay free recall, short- and long-delay cued recall, free recall of List B, total and List B false recognitions, discrimination and recency indices, constancy learning, and semantic clustering), and fluency scores were impaired compared to those for controls (Table 2). Similar deficits were observed in the converters compared to the controls. Moreover, visual episodic memory and some CVLT indices (total free recall, short- and long-delay free recall, short- and long-delay cued recall, total and List B false recognitions, discrimination and recency indices) were lower in the converters than in the stable group. By using a Bonferroni correction (p < .002), only those variables that differed strongly between groups were entered into the regression equation. Note that the effect sizes were positive for all neuropsychological variables (Table 2).

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Detection of memory deficit (versus normal forgetting) in elderly participants When comparing NC versus stable QAD patients, a total of four variables (MMSE, free recall of List B, short-delay free recall and shortdelay cued recall of List A) were entered into the regression analysis, and only MMSE and shortdelay cued recall were retained as potentially significant explanatory variables, F(2, 30) = 13.08, adjusted R2 = .43, p < .0001. These two variables were subsequently entered into a discriminant analysis. The results showed that the MMSE score correctly classified 87% of participants, with a sensitivity of 93% and a specificity of 81%. The short-delay cued recall score correctly classified 80% of participants, with a sensitivity of 86% and a specificity of 75%. The combination of these two variables allowed us to correctly classify 87% of participants (sensitivity 93% and specificity 81%). By using ROC curves, we plotted the sensitivity against 1-specificity for these two cognitive scores (Figure 1). The figure confirmed that the MMSE had better discriminant validity for the distinction between the NC and stable QAD group (the area under the curve was 0.94; SD = 0.04) than the short-delay cued recall score (the area under the curve was 0.83; SD = 0.08). Discrimination of QAD converters versus nonconverters When comparing stable QAD versus converting QAD patients, a total of four variables (delayed recall of Rey complex figure, total free recall 1 to 5, long-delay free recall, and recency index) were entered in the regression analysis. The status of converters compared with stable QAD participants was best predicted by the visual memory measure of recall of Rey’s figure and the recency index of the CVLT, F(2, 30) = 13.08, adjusted R2 = .43, p < .0001. These two predictive variables allowed us to correctly classify 75% of patients, with a sensitivity of 72% and a specificity of 80%. Taken alone, the recall of Rey’s figure correctly classified 76% of patients, with a sensitivity and specificity of 76%, while the recency index correctly classified 72% of patients, with a sensitivity of 73% and a specificity of 72%. By using ROC curves, we plotted the sensitivity against 1-specificity for these two cognitive scores (Figure 2). The figures showed that the score for the recall of Rey’s figure had only a slightly better discriminant validity for the distinction between the stable and converter QAD groups (area under the curve was 0.84; SD = 0.07) than the recency index (area under the curve was 0.83; SD = 0.07).

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LEKEU ET AL. TABLE 2 Mean performance of the control, stable QAD, and converting QAD groups on the different neuropsychological tests

Control group (N = 14)

Neuropsychological testing


Working memory

Stable QAD (N = 17)

Converting QAD (N = 17)

p value (2-tailed)

Post hoc (p < .05)

Effect size

Digit span Block Tapping Test

6.1 (1.3) 5.9 (1.8)

5.6 (2.1) 4.7 (1.3)

5.5 (1.8) 4.5 (1.7)

.62 .04

— STCV < NC

.021 .131

Visual episodic Delayed recall (/36) memory (Rey’s figure)

18.3 (6.2)

15.9 (6.6)

7.9 (4.5)

.0001

NCST > CV

.383

Verbal episodic memory (CVLT)

(A) Total free recall Trials 1–5 (A) Short-delay free recall (A) Short-delay cued recall (A) Long-delay free recall (A) Long-delay cued recall (B) Free recall Total intrusion errors Total false recognitions False recognitions, List B Discrimination index Response bias Primacy index Recency index Constancy learning Semantic clustering Serial order clustering

54.6 (10.6)

43.3 (12.7)

3.3 (7.4)

.0001

NC > ST > CV .479

11.1 (3.0) 12.3 (2.1) 11.5 (2.7) 12.2 (2.3) 7.7 (3.0) 7.6 (6.8) 0.9 (0.9) 0.4 (0.5) 95.9 (2.8) 0.3 (0.5) 29.2 (7.6) 24.7 (7.3) 85.4 (8.0) 2.6 (0.9) 1.8 (1.0)

7.1 (3.8) 8.3 (3.7) 7.9 (4.1) 9.0 (3.8) 4.7 (2.0) 8.2 (6.6) 3.2 (3.0) 1.7 (1.4) 89.3 (8.0) 0.4 (0.5) 27.5 (6.5) 28.4 (8.5) 74.9 (13.0) 1.7 (1.0) 1.4 (0.8)

3.6 (2.3) 6.0 (2.1) 3.8 (2.6) 6.0 (2.5) 3.6 (2.2) 13.9 (12.6) 5.5 (4.0) 2.6 (1.4) 83.3 (9.3) 0.4 (0.4) 26.3 (12.2) 41.3 (1.3) 73.7 (13.3) 1.5 (.9) 1.2 (1.3)

.0001 .0001 .0001 .0001 .0001 .11 .0006 .00007 .0002 .84 .67 .00001 .05 .05 .31

NC > ST > CV NC > ST > CV NC > ST > CV NC > ST > CV STCV < NC — NC > ST > CV NC > ST > CV NC > ST > CV — — NCST > CV STCV < NC STCV < NC —

.499 .477 .496 .419 .337 .091 .283 .351 .329 .007 .018 .407 .164 .198 .054

Language functions

Semantic fluencya Phonemic fluencya

35.4 (8.6) 18.6 (4.7)

28.2 (8.6) 13.9 (5.0)

24.5 (5.6) 15.5 (4.2)

.0005 .05

STCV < NC NC > ST

.29 .139

Executive functions

Stroop test (interference index)

20.8 (14.4)

25.6 (13.6) 29.7 (5.9)

.13

—

.088

31.7 (5.7)

32.8 (2.9)

.56

—

.027

Visuoperceptive Copy (/36) function (Rey’s figure)

31.5 (3.5)

Note. QAD = questionable Alzheimer’s disease. CVLT = California Verbal Learning Test. NCST > CV = performance in normal control and stable groups is better than that in converting group; NC > ST > CV = performance in normal controls is better than that in stable and converting groups, and performance in stable group is better than that in converting group; STCV < NC = performance in stable and converting groups is worse than that in normal control group; NC > ST = performance in normal control group is better than that in stable group; all p < .05. Standard deviations in parentheses. a Z scores are reported for phonemic and semantic fluency.

From a clinical viewpoint, this distinction is clearly the most important. The cutting score was 11.6 for Rey’s figure recall, and it was 34.6 for the recency index. Detection of very early AD versus elderly controls For the comparison between NC and converters, a total of 12 variables were entered in the analysis (MMSE, delayed recall of Rey complex figure, total free recall 1 to 5, free recall List B, short-delay free and cued recall, long-delay free and cued recall, false recognitions, recency index, discrimination index, semantic fluency). The status of prodromal AD was best predicted by a model composed of the MMSE, the recency index, and the short-delay cued recall measure, F(3, 23) = 49.22,

adjusted R2 = .84, p < .00001. Taken alone, the MMSE score correctly classified 100% of patients, with a sensitivity of 100% but a specificity of 87.5%. Taken alone, the short-delay cued recall measure correctly classified 93% of patients, with a sensitivity of 94% and a specificity of 92%. The recency index alone correctly classified 86% of patients, with a sensitivity of 93% and a specificity of 81%. The combination of the three variables allowed us to correctly classify 100% of participants, with a sensitivity and a specificity of 100%. By using ROC curves, we plotted the sensitivity against 1-specificity for these three cognitive scores (Figure 3). These figures showed that the shortdelay cued recall score (area under the curve was 0.98; SD = 0.02) had a slightly better discriminant validity for the distinction between the NC and converting QAD groups than the MMSE score


ROC Curve

1,00

a 1,00

,75

,75

Sensitivity

Sensitivity

ROC Curve

7

,50

,50

Reference Line ,25

SDCR

,25

MMSE

,25 ,50 ,75 1 - Specificity Diagonal segments are produced by ties.

0,00 0,00

1,00

Figure 1. Receiver-operating characteristic (ROC) curve for Mini-Mental State Examination (MMSE) and short-delay cued recall (SDCR) scores for discrimination between normal controls (NC) and stable questionable Alzheimer’s disease (QAD) groups.

(area under the curve was 0.97; SD = 0.03) or the recency index score (area under the curve was 0.91; SD = 0.05). When converters where compared to normal elderly controls, the cutting score was 27 for the MMSE, 32.4 for the recency index, and 9.1 for the short-delay cued recall. Initial detection of the entire QAD group versus elderly controls To comply with the literature, we finally performed a comparison between the whole QAD group and the controls, and a total of nine variables were entered in the analysis (MMSE, semantic fluency, total free recall 1 to 5, free recall List B, short-delay free and cued recall, long-delay free and cued recall, discrimination index). The status of QAD compared to NC was best predicted by a model composed of the MMSE and the shortdelay cued recall, F(2, 44) = 31.38, adjusted R2 = .56, p < .00001. Taken alone, the MMSE score correctly classified 89% of patients with a sensitivity of 97% but a specificity of 77%. The short-delay cued recall measure alone correctly classified 83% of patients, with a sensitivity of 88% but a specificity of 71%. The combination of both variables allowed us to correctly classify 91% of participants, with a sensitivity of 97% and a specificity of 81%. By using ROC curves, we plotted the sensitivity against 1-specificity for these two cognitive scores (Figure 4). This figure showed that the MMSE had


1,00

ROC Curve b 1,00

,75

Sensitivity


0,00 0,00

,50

,25

0,00 0,00


1,00

Figure 2. Receiver-operating characteristic (ROC) curves for delayed recall of Rey’s figure (a) and recency index (b) for discrimination between stable and converter questionable Alzheimer’s disease (QAD) groups.

a better discriminant validity for the distinction between the whole QAD group and NC (area under the curve was 0.96; SD = 0.02) than did the short-delay cued recall score (area under the curve was 0.90; SD = 0.04). Additionally, we performed the same analyses on QAD patients with a MMSE score of 23 and more, allowing us to equate MMSE score in stable QAD participants (26.1 ± 1.6) and converters (25.1 ± 1.7), and the results were essentially similar (data not shown).

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LEKEU ET AL.

ROC Curve

ROC Curve

,75

,75

Sensitivity

1,00

Sensitivity

a 1,00

,50 Reference Line

Reference Line

SDCR

,25

,50

,25

SDCR

MMSE 0,00 0,00

,25

,50

,75

MMSE

1,00

ROC Curve

,50

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,50

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Figure 4. Receiver-operating characteristic (ROC) curve for Mini-Mental State Examination (MMSE) and short-delay cued recall (SDCR) scores for discrimination between normal controls (NC) and the whole questionable Alzheimer’s disease (QAD) group.

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1 - Specificity Diagonal segments are produced by ties.

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1 - Specificity Diagonal segments are produced by ties.

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Figure 3. Receiver-operating characteristic (ROC) curves for Mini-Mental State Examination (MMSE) and short-delay cued recall (SDCR) scores (a) and recency index (b) for discrimination between normal controls (NC) and converter questionable Alzheimer’s disease (QAD) groups.

DISCUSSION This study showed that patients with a stable syndrome of questionable AD can be distinguished from controls by their MMSE scores and their performance on the short-delay cued recall component of the CVLT. These two scores provided a correct classification rate of 87%, demonstrating their importance for detecting mild cognitive impairments in our population of elderly participants. Converters could be differentiated from

controls using the same tests and the recency index of the CVLT, with an impressive correct classification rate of 100% (corresponding to both sensitivity and specificity of 100%). Finally, converters could be distinguished from stable QAD participants by their delayed recall performance for Rey’s complex figure and the recency index of the CVLT, but the correct classification rate remained modest (75%). The data were obtained in relatively small samples of patients, but they are quite significant. Although replications studies are required before generalizing our observations, the data are congruent with the literature showing that different memory tests are useful for detecting mild cognitive impairments in elderly populations and that direct comparisons are mandatory to know the relative discriminant values of the tests (Ivanoiu et al., 2005). Although combining scores was necessary to achieve optimum discrimination, ROC curves demonstrated that each cognitive test had good discriminant value, and they are discussed individually. Age is one important risk factor for AD, and this was confirmed in our study (as it has been in many previous reports on MCI), since converters were older than the other two groups (Kryscio, Schmitt, Salazar, Mendiondo, & Markesbery, 2006). However, age was not retained as a predictive variable.



The California Verbal Learning Test and the influence of semantic abilities and working memory Although four neuropsychological scores emerged as being the best at discriminating between groups, other variables also distinguished our populations. Our group of patients with stable cognitive impairment (stable QAD) performed worse than controls on several neuropsychological tests (visual span, CVLT learning score, all recall performances on the CVLT, false recognitions and the related discrimination index, lower constancy in CVLT learning, decreased semantic clustering, and decreased verbal fluency). However, only the MMSE score and three CVLT memory scores were retained when multiple comparisons were done. The CVLT contains many memory retrieval scores, and our study found the short-delay cued recall to be the best at discriminating both stable and converting QAD participants from controls. To the best of our knowledge, no previous study has characterized performance on the different parts of the CVLT in order to detect isolated memory impairment and predict conversion to dementia. Cued recall may particularly well capture the distinction between patients and controls, because the control participants make better use of semantic information to guide cued retrieval, as suggested by their better semantic clustering abilities on the CVLT and better verbal fluency (see Table 2). These results highlight the importance of a semantic recall measure in memory tests to detect early memory impairments (Adam et al., 2007; Bäckman et al., 2005; Blackwell et al., 2004). According to the recent literature, the MCI population is characterized by deficits in cognitive domains beyond episodic memory, and especially in semantic memory (Adlam, Bozeat, Arnold, Watson, & Hodges, 2006; Alladi et al., 2006; Dudas, Clague, Thompson, Graham, & Hodges, 2005; Duong, Whitehead, Hanratty, & Chertkow, 2006; Hodges, Erzinclioglu, & Patterson, 2006; Ribeiro, de Mendonça, & Guerreiro, 2006; Thompson, Graham, Patterson, Sahakian, & Hodges, 2002). The decrease we observed in verbal fluency, and essentially in semantic fluency, in stable QAD (before correction for multiple comparisons) suggests that executive dysfunction (and impaired access to semantic memory) might occur in some of those “stable” patients. Semantic fluency was impaired in the converting QAD group, but it was not retained in the discriminant analyses, suggesting that the fluency deficit was less significant than the memory impairment in our population of converters. In summary, our results suggest that the short-delay cued recall measure of the CVLT is

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good at detecting memory impairment, but would not be the best measure for predicting dementia. Numerous researchers have used the CVLT in the context of AD, and they have consistently found a decline in memory performance on many scores compared to normal control participants (Greenaway et al., 2006; Kohler, 1994). In a previous longitudinal study, the Dementia Rating Scale performance (Mattis, 1973), a score of global cognitive performance, and the long-delay free recall score showed the best classification power between AD patients and controls, but the total learning score for the five free recall trials was also a good indicator of AD (Salmon et al., 2002). In addition to impaired learning and retrieval, heightened recency effects, ineffective use of semantic clustering, and increases in intrusion errors also typified the CVLT performance of patients with mild AD (Greenaway et al., 2006; Simon, Leach, Winocur, & Moscovitch, 1994). In our analysis, the recency index was the only CVLT measure retained to distinguish converters from stable patients with QAD. The tendency to preferentially retrieve the last items of List A during the five learning trials characterizes a strategy based on working memory that is favored by patients with prodromal AD.

The MMSE score The discussion of multiple cognitive impairments in stable QAD is relevant to our results showing that MMSE performance is significantly impaired in our QAD patients. MMSE score was an experimental variable in our study. Although the test was given to patients in memory clinics before their entry into the study, “priming” or “test–retest” effects were somewhat reduced because the environment (the Cyclotron Research Centre) was completely new for all participants. The composite score was lower in the converting QAD group than in the two other groups, but it was also lower in the stable QAD group than in controls. This is not unexpected, since the MMSE comprises different orientation/memory/attentional questions, and MMSE impairment was described in a previous longitudinal study of 82 MCI patients, 54 of whom converted to dementia during a 42-month follow-up period (Huang et al., 2003). The MMSE is a widely used screening test; it has a ceiling effect and thus lacks sensitivity for patients with mild dementia (Tierney, Szalai, Dunn, Geslani, & McDowell, 2000). Three large epidemiological studies have reported good sensitivity, specificity, and likelihood ratio for the positive test of the MMSE in dementia diagnosis (Grut, Fratiglioni, Viitanen, &

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Winblad, 1993; Monsch et al., 1995; Ritchie & Fuhrer, 1992). But our results are closer to those obtained by Benson, Slavin, Tran, Petrella, and Doraiswamy (2005). In this study, the MMSE distinguished MCI patients from control participants (cutoff score of 27), with good specificity (72%) but poor sensitivity (57%), and mild AD patients (cutoff score of 24) from normal controls with high specificity (100%) and modest sensitivity (75%). Our stable QAD patients had a mean MMSE score of 25.7, and thus the MMSE allowed us to distinguish them from normal controls with both good specificity and good sensitivity (81% and 93%, respectively). As in the Benson et al. study, AD patients (converters in our study) were distinguished from normal controls with high specificity (87.5%) and sensitivity (100%). Delayed recall of Rey’s complex figure In our study, delayed recall of Rey’s complex figure (along with the recency index) showed the best discriminant value between converting and stable QAD groups, providing a 75% correct classification. The performance of stable QAD patients on the visual episodic memory test was not significantly different from that of controls, while their performance on the CVLT was decreased for many scores. Visual memory has been reported to be involved in the preclinical phase of Alzheimer’s disease (Kawas et al., 2003). A similar distinction between performance on visual and verbal memory tests was observed in a previous study comparing converting versus stable QAD patients (Albert et al., 2001; Blackwell et al., 2004; Fowler et al., 1997; Masur et al., 1994) and another visual memory test, the CANTAB Paired Associate Learning Test, was shown to differentiate between converter and nonconverter QAD groups (Blackwell et al., 2004; Fowler, Saling, Conway, Semple, & Louis, 2002). In another study, visual recognition memory performance was altered in MCI participants compared to normal controls but MCI participants’ performance was better than that of AD patients (Barbeau et al., 2004). Moreover, MCI patients who failed on this task had lower scores for free recall and received less benefit from cueing on the free and cued Selective Reminding Test. Although the structure of the tests is not the same, those studies suggest that a visual episodic memory impairment might help to distinguish prodromal AD from stable “mild cognitive impairment.” Finally, our results are in agreement with the results of two prospective studies (Borroni et al., 2006; Tierney et al., 1996). In the Tierney’s study,

120 memory-impaired patients without dementia were followed for two years The results showed that the neuropsychological measures that best predicted AD conversion at the two-year followup included the delayed recall of Rey’s figure. Similarly, a two-year follow-up study of MCI patients found that results for the delayed recall of Rey’s figure were initially inferior in converter than in nonconverter MCI participants (Borroni et al., 2006). Few CVLT variables did not differ between groups. The number of intrusions was more variable in very early AD (SD = 12) than in stable QAD and in controls (SD = 6), and this probably explains the absence of difference. The response bias for yes and no answers during recognition was similar between groups, as was the recall of the first four words and the trend to repeat the order of the presentation. It is interesting to see that semantic clustering did not differ between stable QAD and converters, consistent with our discussion on the absence of discriminative value of cued recall. In conclusion, the value of the CVLT test is that it provides several scores that depend on specific strategies and different cognitive domains. Numerous scores were found to differ between QAD patients and normal controls, including those that have classically been used in the literature, such as the learning and delayed total recall measures. However, the interest of our study was to highlight the importance of a score depending on prior and spontaneous semantic categorization (cued recall) to objectively demonstrate memory deficits in stable QAD patients. In addition, an increased reliance on working memory (expressed by the recency index) correctly distinguished converter from nonconverter patients. A high recency index should be considered as a risk factor for subsequent development of dementia during the neuropsychological investigation of participants with mild cognitive complaints. Original manuscript received 11 January 2008 Revised manuscript accepted 12 March 2009 First published online day month year

REFERENCES Adam, S., Van der Linden, M., Ivanoiu, A., Juillerat, A.-C., Bechet, S., & Salmon, E. (2007). Optimization of encoding specificity for the diagnosis of early AD: The RI-48 task. Journal of Clinical and Experimental Neuropsychology, 29, 477–487. Adlam, A. L., Bozeat, S., Arnold, R., Watson, P., & Hodges, J. R. (2006). Semantic knowledge in mild cognitive impairment and mild Alzheimer’s disease. Cortex, 42, 675–684.



Albert, M. S., Moss, M. B., Tanzi, R., & Jones, K. (2001). Preclinical prediction of AD using neuropsychological tests. Journal of the International Neuropsychological Society, 7, 631–639. Alladi, S., Arnold, R., Mitchell, J., Nestor, P. J., & Hodges, J. R. (2006). Mild cognitive impairment: Applicability of research criteria in a memory clinic and characterization of cognitive profile. Psychological Medicine, 36, 507–515. Artero, S., Petersen, R., Touchon, J., & Ritchie, K. (2006). Revised criteria for mild cognitive impairment: Validation within a longitudinal population study. Dementia and Geriatric Cognitive Disorders, 22, 465–470. Artero, S., Tierney, M. C., Touchon, J., & Ritchie, K. (2003). Prediction of transition from cognitive impairment to senile dementia: A prospective, longitudinal study. Acta Psychiatrica Scandinavica, 107, 390–393. Bäckman, L., Jones, S., Berger, A. K., Laukka, E. J., & Small, B. J. (2004). Multiple cognitive deficits during the transition to Alzheimer’s disease. Journal of Internal Medicine, 256, 195–204. Bäckman, L., Jones, S., Berger, A.-K., Laukka, E. J., & Small, B. J. (2005). Cognitive impairment in preclinical Alzheimer’s disease: A meta-analysis. Neuropsychology, 19, 520–531. Barbeau, E., Didic, M., Tramoni, E., Felician, O., Joubert, S., Sontheimer, A., et al. (2004). Evaluation of visual recognition memory in MCI patients. Neurology, 62, 1317–1322. Benson, A. D., Slavin, M. J., Tran, T. T., Petrella, J. R., & Doraiswamy, P. M. (2005). Screening for early Alzheimer’s disease: Is there still a role for the MiniMental State Examination? Journal of Clinical Psychiatry, 7, 62–67. Blackwell, A. D., Sahakian, B. J., Vesey, R., Semple, J. M., Robbins, T. W., & Hodges, J. R. (2004). Detecting dementia: Novel neuropsychological markers of preclinical Alzheimer’s disease. Dementia and Geriatric Cognitive Disorders, 17, 42–48. Borroni, B., Anchisi, D., Paghera, B., Vicini, B., Kerrouche, N., Garibotto, V., et al. (2006). Combined 99mTc-ECD SPECT and neuropsychological studies in MCI for the assessment of conversion to AD. Neurobiology of Aging, 27, 24–31. Chen, P., Ratcliff, G., Belle, S. H., Cauley, J. A., DeKosky, S. T., & Ganguli, M. (2000). Cognitive tests that best discriminate between presymptomatic AD and those who remain nondemented. Neurology, 55, 1847–1853. Delis, D. C., Freeland, J., Kramer, J. H., & Kaplan, E. (1988). Integrating clinical assessment with cognitive neuroscience: Construct validation of the California Verbal Learning Test. Journal of Consulting and Clinical Psychology, 56, 123–130. Delis, D. C., Kramer, J. H., Kaplan, E., & Ober, B. A. (1987). California Verbal Learning Test: Adult version manual: Research edition. San Antonio, TX: The Psychological Corporation. Dudas, R. B., Clague, F., Thompson, S. A., Graham, K. S., & Hodges, J. R. (2005). Episodic and semantic memory in mild cognitive impairment. Neuropsychologia, 43, 1266–1276. Duong, A., Whitehead, V., Hanratty, K., & Chertkow, H. (2006). The nature of lexico-semantic processing deficits in mild cognitive impairment. Neuropsychologia, 44, 1928–1935.

11

Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). Mini-Mental State: A practical method for grading the state of patients for the clinician. Journal of Psychiatry Research, 12, 189–198. Fowler, K. S., Saling, M. M., Conway, E. L., Semple, J. M., & Louis, W. J. (1997). Computerised neuropsychological tests in the early detection of dementia: Prospective findings. Journal of the International Neuropsychological Society, 3, 139–146. Fowler, K. S., Saling, M. M., Conway, E. L., Semple, J. M., & Louis, W. J. (2002). Paired associate performance in the early detection of DAT. Journal of the International Neuropsychological Society, 8, 58–71. Greenaway, M. C., Lacritz, L. H., Binegar, D., Weiner, M. F., Lipton, A., & Munro Cullum, C. (2006). Patterns of verbal memory performance in mild cognitive impairment, Alzheimer disease, and normal aging. Cognitive and Behavioral Neurology, 19, 79–84. Grut, M., Fratiglioni, L., Viitanen, M., & Winblad, B. (1993). Accuracy of the Mini-Mental Status Examination as a screening test for dementia in a Swedish elderly population. Acta Neurologica Belgica, 87, 312–317. Hamilton, M. (1967). Development of a rating scale for primary depressive illness. British Journal of Social Clinical Psychology, 6, 278–296. Hodges, J. R., Erzinclioglu, S., & Patterson, K. (2006). Evolution of cognitive deficits and conversion to dementia in patients with mild cognitive impairment: A very-long-term follow-up study. Dementia and Geriatric Cognitive Disorders, 21, 380–391. Huang, C., Wahlund, L.-O., Almkvist, O., Elehu, D., Svensson, L., Jonsson,T., et al. (2003). Voxel- and VOI-based analysis of SPECT CBF in relation to clinical and psychological heterogeneity of mild cognitive impairment. NeuroImage, 19, 1137–1144. Ivanoiu, A., Adam, S., Van der Linden, M., Salmon, E., Juillerat, A.-C., Mulligan, R., et al. (2005). Memory evaluation with a new cued recall test in patients with mild cognitive impairment and Alzheimer’s disease. Journal of Neurology, 252, 47–55. Kawas, C. H., Corrada, M. M., Brookmeyer, R., Morrison, A., Resnick, S. M., Zonderman, A. B., et al. (2003). Visual memory predicts Alzheimer’s disease more than a decade before diagnosis. Neurology, 60, 1089–1093. Kohler, S. (1994). Quantitative characterization of verbal learning deficits in patients with Alzheimer’s disease. Journal of Clinical and Experimental Neuropsychology, 16, 749–753. Kryscio, R. J., Schmitt, F. A., Salazar, J. C., Mendiondo, M. S., & Markesbery, M. D. (2006). Risk factors for transitions from normal to mild cognitive impairment and dementia. Neurology, 66, 828–832. Lawton, M. P., & Brody, E. M. (1969). Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist, 9, 179–186. Lezak, M. D. (1983). Neuropsychological assessment (2nd ed.). New York: Oxford University Press. Masur, D. M., Sliwinski, M., Lipton, R. B., Blau, A. D., & Crystal, H. A. (1994). Neuropsychological prediction of dementia and the absence of dementia in healthy elderly persons. Neurology, 44, 1427–1432. Mattis, S. (1973). Dementia Rating Scale: Professional manual. Odessa, FL: Psychological Assessment Resources.


12

LEKEU ET AL.

McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984). Clinical diagnosis of Alzheimer’s disease: Report of NINCDS/ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s disease. Neurology, 34, 939–944. Monsch, A. U., Foldi, N. S., Ermini-Funfschilling, D. E., Berres, M., Taylor, K. I., Stahelin, H. B., et al. (1995). Improving the diagnostic accuracy of the Mini-Mental State Examination. Acta Neurologica Belgica, 92, 145–150. Morris, J. C. (1993). The Clinical Dementia Rating (CDR): Current version and scoring rules. Neurology, 43, 2412–2414. Petersen, R. C., Doody, R., Kurz, A., Mohs, R. C., Morris, J. C., Rabins, P. V., et al. (2001). Current concepts in mild cognitive impairment. Archives of Neurology, 58, 1985–1992. Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G., & Kokmen, E. (1999). Mild cognitive impairment: Clinical characterization and outcome. Archives of Neurology, 56, 303–308. Rey, A., Osterrieth, P. A., & Taylor, L. B. (1991). Rey Osterrieth complex figure test and Taylor version. In O. Spreen & E. Strauss (Eds.), A compendium of neuropsychological tests: Administration, norms, and commentary (pp. 157–167). New York: Oxford University Press. Ribeiro, F., de Mendonça, A., & Guerreiro, M. (2006). Mild cognitive impairment: Deficits in cognitive domains other than memory. Dementia and Geriatric Cognitive Disorders, 21, 284–290. Ritchie, K., & Fuhrer, R. (1992). A comparative study of the performance of screening tests for senile dementia using receiver operating characteristics analysis. Journal of Clinical Epidemiology, 45, 627–637.

Salmon, D. P., Thomas, R. G., Pay, M. M., Booth, A., Hofstetter, B. A., Thal, L. J., et al. (2002). Alzheimer’s disease can be accurately diagnosed in very mildly impaired individuals. Neurology, 59, 1022–1028. Simon, E., Leach, L., Winocur, G., & Moscovitch, M. (1994). Intact primary memory in mild to moderate Alzheimer disease: Indices from the California Verbal Learning Test. Journal of Clinical and Experimental Neuropsychology, 16, 414–422. Tabert, M. H., Manly, J. J., Liu, X., Pelton, G. H., Rosenblum, S., Jacobs, M., et al. (2006). Neuropsychological prediction of conversion to Alzheimer disease in patients with mild cognitive impairment. Archives of General Psychiatry, 63, 916–924. Thompson, S. A., Graham, K. S., Patterson, K., Sahakian, B. J., & Hodges, J. R. (2002). Is knowledge of famous people disproportionately impaired in patients with early and questionable Alzheimer’s disease? Neuropsychology, 16, 344–358. Tierney, M. C., Szalai, J.-P., Dunn, E., Geslani, D., & McDowell, I. (2000). Prediction of probable Alzheimer disease in patients with symptoms suggestive of memory impairment. Value of the Mini-Mental State Examination. Archives of Familial Medicine, 9, 527–532. Tierney, M. C., Szalai, J. P., Snow, W. G., Fisher, R. H., Nores, A., Nadon, G., et al. (1996). Prediction of probable Alzheimer’s disease in memory-impaired patients: Prospective longitudinal study. Neurology, 46, 661–665. Winblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L.-O., et al. (2004). Mild cognitive impairment—beyond controversies, towards a consensus: Report of the International Working Group on Mild Cognitive Impairment. Journal of Internal Medicine, 256, 240–246.