Abstract

Alzheimer's disease (AD) and subcortical vascular dementia (SVaD) are among the most prevalent dementias and they often show specific patterns of cognitive dysfunction. This study examined whether differences exist between groups on the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) that could assist with differential diagnosis. The examiners utilized the NINCDS-ADRDA and the NINDS-AIREN criteria to identify 39 probable AD and 29 probable SVaD patients. A battery of neuropsychological tests was performed and neuroimaging was reviewed for all subjects. Analyses revealed that the SVaD group performed significantly better on the Delayed Memory Index (DMI) and its subtests measuring Recognition, Contextual Memory, and Figure Recall. In contrast to previous research, there were no differences between groups on immediate memory tasks, and post hoc analyses revealed no differences on any other index or subtest. The results also suggested that the DMI and its subtests and the Story Memory subtest of the Immediate Memory Index have better sensitivity to AD, better specificity to SVaD, and roughly equivalent positive predictive power compared with other components of the RBANS. Overall, findings suggest that the indices and subtests of the RBANS may be limited in differentiating AD versus SVaD, except for the DMI and its subtests.

Introduction

Without the proper neuropsychological testing tools, accurate identification and diagnosis of pathology become challenging. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) is a useful screen for measuring cognitive functioning (Randolph, 1998). Several elements were considered in the RBANS' development: (a) limiting administration time to 30 min or less; (b) appropriately developing its level of difficulty; (c) producing standard scores that measure cognitive skills typically affected by dementia; and (d) creating an alternate form for reevaluation (Randolph, Tierney, Mohr, & Chase, 1998). The RBANS is currently available in two forms for clinical use and consists of five indices (comprised of 12 subtests) measuring Immediate and Delayed Memory, Visuospatial/Constructional Skills, Language, and Attention. Additional forms are also now available for research purposes.

In terms of clinical and ecological validity, the research findings are variable, but Duff and colleagues (2008) found that the RBANS was able to differentiate between clinical groups and normal controls. Patterns have also been found differentiating Alzheimer's disease (AD) and Huntington's disease (HD; Randolph et al., 1998), inpatient stroke victims (Larson, Kirschner, Bode, Heinemann, & Goodman, 2005), effects of concussion (Moser & Schatz, 2002), and schizophrenia (Gold, Queern, Iannone, & Buchanan, 1999; Hobart, Goldberg, Bartko, & Gold, 1999) according to their associated neurocognitive impairments. Aupperle, Beatty, Shelton, and Gontkovsky (2002) found that the RBANS is sensitive in detecting cognitive impairment in persons with multiple sclerosis (MS), but they also noted that four of the six index scores were less sensitive to the cognitive sequelae of MS than the Mini-Mental Status Exam. Beatty, Mold, and Gontkovsky (2003) reported sensitivity in detecting the cognitive impairments exhibited by Parkinson's disease (PD) when compared with AD. Similarly, the patterns found for PD patients were comparable to what Ryder and colleagues (2002) found. These lines of research suggest that clinicians can utilize patterns of cognitive performance on the RBANS to assist with differential diagnosis. This may help limit incidences of misdiagnosis, poor treatment planning, and inaccurate prognoses, as different neurological disorders have diverse progressions.

Various neurological disorders can also be classified, in general, as being cortical or subcortical in nature. In a preliminary study, Randolph and colleagues (1998) found that HD patients performed significantly better than AD patients on the Language and Delayed Memory indices of the RBANS, but worse on the Visuospatial/Constructional and Attention indices. This led to the development of the Cortical–Subcortical Deviation Index (C-SDI), which utilizes a patient's scores on these indices to calculate a single overall score. They found that the C-SDI was generally positive for the cortical group (i.e., AD) and mostly negative for the subcortical group (i.e., HD) with an overall classification accuracy rate of 84% (Randolph et al., 1998). However, Duff, Schoenberg, Mold, Scott, and Adams (2007) examined C-SDI normative and retest data and found that 37% of neurologically normal adults in their sample were described as “cortical” suggesting that caution be used when making interpretations based off this single score.

Although the RBANS can be a valuable screening measure, other limitations should also be addressed. For example, no normative data for the individual subtests were included in the RBANS manual in part because the psychometric stability of the composite indices is reportedly greater (Lezak, Howieson, & Loring, 2004). However, in a supplementary packet provided by the RBANS' author, this information is now available (Randolph, 2008) wherein he indicates that certain index scores can be considerably affected by minor changes on subtests, suggesting that it may be useful to examine subtest performance. Duff and colleagues (2003) and Gontkovsky, Mold, and Beatty (2002) researched the need for additional education corrected norms finding that certain indices were susceptible to educational influences. Subsequently, they expanded upon the normative data to include corrections for age and education in a community-dwelling elderly sample. Beatty and colleagues (2003) also found mild sex differences, but a larger effect due to education (up to an 11-point index adjustment) suggesting that adjusting for sex and education effects is warranted. Additionally, confirmatory factor analysis was unable to replicate the current 5-factor structure using the 12 subtests (Carlozzi, Horner, Yang, & Tilley, 2008). Subjected to exploratory factor analysis with a maximum likelihood extraction and orthogonal rotation, Carlozzi and colleagues' (2008) findings supported a two-factor structure that they described generally as Memory and Visuospatial function. Studies performed by Duff and colleagues (2006) and Wilde (2006) came to similar conclusions and did not support the use of the overall indices as diagnostic tools. In a comparable study, Garcia, Leahy, Corradi, and Forchetti (2008) found that only five of the six subtests that yield the Immediate and Delayed Memory indices from the original sample load significantly on a component they labeled Memory (i.e., Story Memory, List Recall, Story Recall, List Recognition, and Figure Recall). These authors also found that the Figure Copy, Line Orientation, and Coding subtests had significant loadings on a component they named Visuomotor Processing since these tests require motor skills and/or visual perception. The remaining subtests (i.e., Semantic Fluency, Picture Naming, List Learning, and Digit Span) loaded highest on a third component they labeled Verbal Processing (Garcia et al., 2008). In sum, all of these authors recommend that clinicians use caution when evaluating cognitive functioning with the RBANS' existing structure. In general, they also emphasized subtest score interpretation as opposed to the indices (Carlozzi et al., 2008).

Neuropathology and Cognitive Deficits in AD and Subcortical Vascular Dementia

Multiple etiologies can account for the manifestation of dementia, but it is widely accepted that AD is the most common form and most of our current knowledge of dementia stems from its study (Roman, 2002). The literature varies, but has shown that AD may account for 50%–70% of all dementia cases, whereas others have shown vascular dementia (VaD) to account for 20%–45% of the cases (Hestad, Ellertsen, & Klove, 1998; Skoog, 2004). Studies have noted differences in their cognitive profiles and some have focused on specifically evaluating the profiles of subcortical VaD (SVaD) versus AD (Fink, McCrea, and Randolph, 1998; Graham, Emery, and Hodges, 2004; Levy & Chelune, 2007; Paul, Garrett, & Cohen, 2003; Randolph, 1997; Tierney et al., 2001; Yuspeh, Vanderploeg, Crowell, & Mullan, 2002), and certain differences are expected given their distinct neuropathological profiles. Lesions primarily located in the grey matter regions are common in AD (Tonkonogy & Puente, 2009). Major changes also associated with AD include cerebral atrophy, neuronal loss, and the presence of neurofibrillary tangles and amyloid plaques (Blumenfeld, 2002) that occur predominantly in the medial temporal lobes, hippocampus, entorhinal cortex, and nucleus basalis (Blumenfeld, 2002; Kaufer & Cummings, 2003), which can impede memory functioning. AD pathology can also affect temporal and parieto-occipital cortex, the anterior cingulate gyrus, and the frontal lobes (Blumenfeld, 2002; Kaufer & Cummings, 2003). SVaD patients, however, often have difficulties related to lesions (e.g., microinfarctions and/or chronic small vessel ischemia) in various subcortical structures such as the basal ganglia, thalamus, and frontal lobes that may cause leukoaraiosis (Blumenfeld, 2002; Kaufer & Cummings, 2003; Tonkonogy & Puente, 2009). These lesions can cause executive dysfunction, as they often disrupt frontal–subcortical pathways or disconnect cortical and subcortical regions (Kaufer & Cummings, 2003). Given the different neuroanatomical areas affected by each disease process, it is not surprising that Graham and colleagues (2004) found that AD patients performed worse on measures of episodic memory, whereas SVaD patients performed worse on tasks measuring executive functioning, attentional skills, and visuospatial abilities. SVaD patients generally exhibited better Immediate and Delayed Memory functioning than AD patients (Fink et al., 1998), especially on verbal memory tests of contextual recall and a variety of list learning tasks (Levy & Chelune, 2007). SVaD patients also demonstrated better performance on tasks of memory recognition and cued recall (Fink et al., 1998; Levy & Chelune, 2007) with few differences noted on nonverbal measures of visual memory such as visuospatial, figural, or facial recognition (Levy & Chelune, 2007). Overall, AD patients typically exhibited more rapid forgetfulness and poorer verbal learning with minimal benefit from cueing or a recognition component (Levy & Chelune, 2007; Randolph, 1998). Although additional research has similarly concluded that patients with SVaD performed better than AD patients on measures of recognition memory (Tierney et al., 2001; Yuspeh et al., 2002), this finding is not universal (Misciagna, Masullo, Giordano, & Silveri, 2005). Matsuda, Saito, and Sugishita (1998) found that AD patients tend to have fewer problems with attention and visuospatial function, but these impairments can be found with SVaD patients who suffered multiple subcortical lacunar infarcts.

As previously mentioned, although memory impairment is a central aspect of AD, in particular poor consolidation of information into long-term memory (Yuspeh et al., 2002), several lines of research indicate that executive dysfunction is more characteristic of VaD (Paul et al., 2003), particularly SVaD. Owing to the patterns of cognitive dysfunction found in the literature, there is sufficient evidence to suggest that a cognitive profile analysis approach may be efficacious in diagnosing AD versus SVaD and that utilizing an overall impairment score (e.g., RBANS Total Scale score) may overlook specific deficits that could assist in differential diagnosis.

The research performed by Fink and colleagues (1998) focused specifically on the cognitive differentiation of ischemic VaD versus AD utilizing the RBANS. With no group differences in age, education, gender, or overall impairment, the neurocognitive profiles associated with each group differed significantly. The AD group performed better than the ischemic VaD group on the Visuospatial/Constructional and Attention indices, but worse on the Immediate and Delayed Memory and Language indices. On the basis of these findings, the purpose of the current study was to examine the diagnostic utility of the RBANS with similar clinical samples in an attempt at replication. Considering current lines of research, this study also sought to determine whether statistically significant differences exist between these two groups on the RBANS' subtests. We also sought to examine the efficacy of the C-SDI.

The primary hypothesis of this study was that the performance of SVaD and AD groups would dissociate most clearly on measures that assess the proficiency of memory system function. Because the pathology of AD has a more pronounced impact on cerebral structures associated with memory function than does SVaD, we predicted that the SVaD group would perform significantly better on the Immediate and Delayed Memory indices. Moreover, we expected differences in how memory retrieval in the two groups would benefit from semantic and contextual cues (i.e., story recall and recognition accuracy). As such, we predicted that the AD group would show less improvement in memory performance on the Story Recall and List Recognition subtests compared with the SVaD group. On the basis of clinical observations, we predicted that performance between groups on all other indices and subtests would be equivalent.

Materials and Methods

Participants

This IRB approved archival study included 68 veteran outpatients, ages 50–89 years. Patients were diagnosed with probable AD based on the NINCDS-ADRDA criteria (McKhann et al., 1984) or SVaD based on the NINDS-AIREN criteria (Erkinjuntti et al., 2000). A neurologist or neuropsychologist determined group status. A neuropsychologist did so via medical record review. Each subject completed a comprehensive neuropsychological evaluation and neuroimaging (i.e., MRI or CT scan, or both) was reviewed for all participants. SVaD patients with known cortical strokes were excluded from the sample. Individuals with mixed dementia, severe clinical psychopathology, a history of substance abuse, or major medical illnesses were excluded. Groups were equivalent regarding age and education. Table 1 presents detailed characteristics of the sample.

Table 1.

Demographic characteristics by group

Characteristic NINCDS-ADRDA probable AD NINDS-AIREN probable SVaD 
N 39 29 
Gender (n [%]) 
 Men 38 (97.4) 28 (96.6) 
 Women 1 (2.6) 1 (3.4) 
Age 75.7 (7.5) 72.7 (8.5) 
Dominant hand (n [%]) 
 Right 32 (82.1) 27 (93.1) 
 Left 7 (17.9) 2 (6.9) 
Education (n [%]) 
 Less than HS 10 (25.7) 8 (27.5) 
 Equal to HS 15 (38.5) 11 (37.9) 
 More than HS 14 (35.8) 10 (34.6) 
Characteristic NINCDS-ADRDA probable AD NINDS-AIREN probable SVaD 
N 39 29 
Gender (n [%]) 
 Men 38 (97.4) 28 (96.6) 
 Women 1 (2.6) 1 (3.4) 
Age 75.7 (7.5) 72.7 (8.5) 
Dominant hand (n [%]) 
 Right 32 (82.1) 27 (93.1) 
 Left 7 (17.9) 2 (6.9) 
Education (n [%]) 
 Less than HS 10 (25.7) 8 (27.5) 
 Equal to HS 15 (38.5) 11 (37.9) 
 More than HS 14 (35.8) 10 (34.6) 

Notes: AD = Alzheimer's disease; SVaD = subcortical vascular dementia; HS = high school.

Statistical Analyses

In order to determine statistically significant differences between groups (defined as .05) on index and subtest scores, multivariate analysis of variance was performed. We also performed discriminant function analysis, and positive predictive power (PPP) was calculated for the significant indices and subtest scores to determine their ability to accurately predict group membership. The C-SDI was calculated for all subjects according to the equation provided by the RBANS' author (Randolph et al., 1998), and classification analysis was conducted to evaluate this scores ability to accurately predict group membership.

Results

Participant characteristic analysis confirmed that the two groups were equivalent with regard to age (AD = 75.7 [SD = 7.5]; SVaD = 72.7 [SD = 8.5], t = 2.512, p = .14) and education (t = 0.68, p = .50).

The multivariate test of differences between groups using Wilk's lambda criteria was statistically significant (p = .021). Follow-up analyses of the indices and subtest scores revealed that, consistent with previous research, AD patients performed worse on the Delayed Memory Index (DMI) (p ≤ .0001) and on almost all of its subtests including Verbal Recognition (p ≤ .0001), Story Recall (p ≤ .0001), and Figure Recall (p = .02). In contrast to previous research, there were no differences found between groups on the Immediate Memory Index (p = .404) or any of its subtests. Analysis of the remaining indices and subtests also found no significant differences between groups including the RBANS Total score (p = .272). Presented in Table 2 are detailed results of the statistical analyses for each of the indices and their respective subtests including effect sizes. Fig. 1 visually presents the mean scaled scores for all of the RBANS indices.

Table 2.

RBANS scores and diagnostic group comparisons

Score AD (Mean [SD]) SVaD (Mean [SD]) F (dfp-value d 
RBANS scores 
 Immediate Memory 65.2 (14.5) 68.7 (15.1) 0.707 (1, 61) .40 0.21 
  List Learning 14.9 (5.3) 15.8 (5.7) 0.105 (1, 66) .73 0.08 
  Story Memory 8.9 (4.7) 11.5 (4.6) 2.712 (1, 66) .11 0.40 
 Visuospatial/Cons. 77.0 (19.8) 75.2 (16.3) 0.458 (1, 61) .50 0.17 
  Figure Copy 12.8 (4.9) 12.4 (4.5) 0.130 (1, 66) .77 0.09 
  Line Orientation 12.3 (5.6) 13.1 (5.4) 0.023 (1, 66) .85 0.04 
 Language 82.7 (14.1) 80.9 (13.5) 0.132 (1, 61) .72 0.09 
  Picture Naming 8.6 (1.9) 8.9 (1.9) 0.031 (1, 66) .84 0.04 
  Semantic Fluency 12.8 (4.6) 11.0 (4.2) 2.40 (1, 66) .13 0.38 
 Attention 74.6 (16.2) 68.3 (15.7) 1.145 (1, 61) .29 0.26 
  Digit Span 8.8 (2.2) 8.2 (2.5) 1.04 (1, 66) .33 0.70 
  Coding 16.0 (12.4) 17.1 (10.0) 0.129 (1, 66) .79 0.09 
 Delayed Memory 52.5 (12.2) 69.1 (17.5) 29.02 (1, 61) .0001 1.3 
  List Recall 0.69 (1.1) 1.5 (1.6) 3.31 (1, 66) .07 0.46 
  List Recognition 13.41 (3.7) 16.5 (2.9) 13.91 (1, 66) .0001 0.91 
  Story Recall 1.92 (2.3) 4.4 (2.5) 16.1 (1, 66) .0001 1.0 
  Figure Recall 2.9 (3.3) 5.7 (4.5) 5.72 (1, 66) .02 0.59 
Total Index Score 63.9 (12.3) 66.1 (11.7) 1.23 (1, 61) .27 0.27 
Score AD (Mean [SD]) SVaD (Mean [SD]) F (dfp-value d 
RBANS scores 
 Immediate Memory 65.2 (14.5) 68.7 (15.1) 0.707 (1, 61) .40 0.21 
  List Learning 14.9 (5.3) 15.8 (5.7) 0.105 (1, 66) .73 0.08 
  Story Memory 8.9 (4.7) 11.5 (4.6) 2.712 (1, 66) .11 0.40 
 Visuospatial/Cons. 77.0 (19.8) 75.2 (16.3) 0.458 (1, 61) .50 0.17 
  Figure Copy 12.8 (4.9) 12.4 (4.5) 0.130 (1, 66) .77 0.09 
  Line Orientation 12.3 (5.6) 13.1 (5.4) 0.023 (1, 66) .85 0.04 
 Language 82.7 (14.1) 80.9 (13.5) 0.132 (1, 61) .72 0.09 
  Picture Naming 8.6 (1.9) 8.9 (1.9) 0.031 (1, 66) .84 0.04 
  Semantic Fluency 12.8 (4.6) 11.0 (4.2) 2.40 (1, 66) .13 0.38 
 Attention 74.6 (16.2) 68.3 (15.7) 1.145 (1, 61) .29 0.26 
  Digit Span 8.8 (2.2) 8.2 (2.5) 1.04 (1, 66) .33 0.70 
  Coding 16.0 (12.4) 17.1 (10.0) 0.129 (1, 66) .79 0.09 
 Delayed Memory 52.5 (12.2) 69.1 (17.5) 29.02 (1, 61) .0001 1.3 
  List Recall 0.69 (1.1) 1.5 (1.6) 3.31 (1, 66) .07 0.46 
  List Recognition 13.41 (3.7) 16.5 (2.9) 13.91 (1, 66) .0001 0.91 
  Story Recall 1.92 (2.3) 4.4 (2.5) 16.1 (1, 66) .0001 1.0 
  Figure Recall 2.9 (3.3) 5.7 (4.5) 5.72 (1, 66) .02 0.59 
Total Index Score 63.9 (12.3) 66.1 (11.7) 1.23 (1, 61) .27 0.27 

Notes: AD = Alzheimer's disease; SVaD = subcortical vascular dementia; SD = standard deviation; RBANS = Repeatable Battery for the Assessment of Neuropsychological Status.

Fig. 1.

Mean scores for the index scores. IMI = Immediate Memory Index; Visuo/Con = Visuospatial/Constructional; Lang = Language; Attn = Attention; DMI = Delayed Memory Index. *p ≤ .0001.

Fig. 1.

Mean scores for the index scores. IMI = Immediate Memory Index; Visuo/Con = Visuospatial/Constructional; Lang = Language; Attn = Attention; DMI = Delayed Memory Index. *p ≤ .0001.

According to discriminant function analysis, the only index to correctly classify group status at a significant level was the DMI ((1, 67) = 18.03, p ≤ .0001). At the subtest level, five subtests were able to correctly classify group status. Four of these subtests comprise the DMI including Story Recall ((1, 68) = 16, p ≤ .0001), List Recall ((1, 68) = 4.9, p = .026), List Recognition ((1, 68) = 12.5, p ≤ .0001), and Figure Recall ((1, 68) = 8.3, p = .004). Story Memory, a component of the Immediate Memory Index, was the fifth subtest to classify group status at a significant level ((1, 68) = 5.2, p = .023). According to the PPP, the chance that a person receives an abnormal score (1.5 SD below the mean) on the DMI and has AD is 76.6% and 85% for SVaD. Displayed in Table 3 are the PPP, sensitivity, and specificity for each of the indices and subtests that were statistically significant. Overall, these results suggest that the DMI, its subtests, and the Story Memory subtest have better sensitivity to AD, better specificity to SVaD, and roughly equivalent PPP.

Table 3.

Diagnostic classification accuracy on the index and subtest scores of the RBANS

 Sensitivity (%) Specificity (%) PPP (%) 
RBANS score    
AD (N = 39)    
 Immediate Memory    
  Story Memory 84.6 51.7 70.2 
 Delayed Memory 92.3 60.7 76.6 
  List Recall 79.5 48.3 67.4 
  List Recognition 87.2 58.6 73.9 
  Story Recall 76.9 62.1 73.2 
  Figure Recall 76.9 51.7 68.2 
SVaD (N = 29)    
 Immediate Memory    
  Story Memory 51.7 84.6 71.4 
 Delayed Memory 60.7 92.3 85.0 
  List Recall 48.3 79.5 63.6 
  List Recognition 58.6 87.2 77.3 
  Story Recall 62.1 76.9 66.7 
  Figure Recall 51.7 76.9 62.5 
 Sensitivity (%) Specificity (%) PPP (%) 
RBANS score    
AD (N = 39)    
 Immediate Memory    
  Story Memory 84.6 51.7 70.2 
 Delayed Memory 92.3 60.7 76.6 
  List Recall 79.5 48.3 67.4 
  List Recognition 87.2 58.6 73.9 
  Story Recall 76.9 62.1 73.2 
  Figure Recall 76.9 51.7 68.2 
SVaD (N = 29)    
 Immediate Memory    
  Story Memory 51.7 84.6 71.4 
 Delayed Memory 60.7 92.3 85.0 
  List Recall 48.3 79.5 63.6 
  List Recognition 58.6 87.2 77.3 
  Story Recall 62.1 76.9 66.7 
  Figure Recall 51.7 76.9 62.5 

Notes: AD = Alzheimer's disease; SVaD = subcortical vascular dementia; PPP = positive predictive power; RBANS = Repeatable Battery for the Assessment of Neuropsychological Status.

Similar to previous studies, the C-SDI scores for our subjects were, on average, positive for the AD group (mean = 8.3, SD = 15.2) and negative for the SVaD group (mean = −3.2, SD = 14.1). However, there was an overall correct classification rate of only 62% based on this single score, and there was statistically significant overlap between groups (χ2 = 9.1; 1, 66, p < .01) meaning that there was a large number of AD patients with a negative score on this index; the inverse was true for the SVaD group. Moreover, the following ranges attest to the amount of spread observed between groups, as our AD sample's C-SDI scores ranged from −24 to 41 and our SVaD sample's scores ranged from −27.5 to 19. Fig. 2 visually displays these findings.

Fig. 2.

Mean scores for the Cortical–Subcortical Deviation Index (C-SDI). C-SDI scores were, on average, positive for the AD group (mean = 8.3, SD = 15.2) and negative for the SVaD group (mean = −3.2, SD = 14.1), but there was statistically significant overlap (χ2 = 9.1; 1, 66, p < .01). Moreover, the overall correct classification rate was only 62%, and the scores ranged from −24 to 41 (AD group) and −27.5 to 19 (SVaD group).

Fig. 2.

Mean scores for the Cortical–Subcortical Deviation Index (C-SDI). C-SDI scores were, on average, positive for the AD group (mean = 8.3, SD = 15.2) and negative for the SVaD group (mean = −3.2, SD = 14.1), but there was statistically significant overlap (χ2 = 9.1; 1, 66, p < .01). Moreover, the overall correct classification rate was only 62%, and the scores ranged from −24 to 41 (AD group) and −27.5 to 19 (SVaD group).

Discussion

On the basis of the research performed by Fink and colleagues (1998), the purpose of this study was to examine whether the RBANS indices are sufficient to differentiate AD versus SVaD. The results demonstrated that, in our sample, AD and SVaD patients with similar levels of dementia exhibit comparable neurocognitive patterns across the indices and subtests of the RBANS with the exception of the DMI and three of its four subtests. This suggests that only this index and some of its subtests may aid in differential diagnosis. Analysis also revealed that only this index, its subtests, and the Story Memory subtest of the Immediate Memory Index were able to correctly classify patients at a significant level. In addition, contrary to previous research (Randolph, 1998), the significant overlap found between groups on the C-SDI suggests it is not accurate in discriminating between typical cortical and subcortical dementias. Thus, clinicians should interpret this score with caution.

A possible explanation for the comparable cognitive profile patterns found between groups in this study is that certain subtests of the RBANS involve different levels of information processing. Therefore, if subtests are normed together and are considered to measure aspects of the same cognitive processes, but they actually load higher with tasks from different indices, this may alter an index score's ability to adequately portray a specific cognitive ability. Reviewing the subtest scores individually, however, may still be useful in determining a patient's neurocognitive skills, and practitioners can supplement the RBANS with extra tasks that tap domains that the test battery lacks. For example, the RBANS lacks many tasks measuring executive functioning, a prominent feature of SVaD. It also lacks a measure of manual motor abilities. Administering tests such as letter–word generative fluency, Trail Making Test, and/or grooved pegboard might assist in differential diagnosis without adding a significant amount of time to the screen.

Owing to certain characteristics of our clinical samples, we suggest considering several caveats when interpreting the present results. First, a more comprehensive neuropsychological test battery is generally going to be more sensitive to cognitive impairment. Second, the sample consisted primarily of men, so it is difficult to assess the impact that sex had on our analysis, which is a known influencing factor on RBANS scores (Beatty et al., 2003). Third, although we attempted to exclude all mixed vascular and AD subjects from our sample, we cannot be entirely sure this did not occur, as diagnosis was not autopsy verified. Thus, this could feasibly account for some of the similarities found in the cognitive profiles between groups. In addition, we were unable to utilize an independent classification of dementia severity. Future research with these groups should therefore attempt to obtain equivalent numbers of men and women in their samples and utilize independent classification measures.

Similar to previous studies (Carlozzi et al., 2008; Duff et al., 2006; Garcia et al., 2008; Wilde, 2006), but contrary to another (Fink et al., 1998), these findings do not support using all of the RBANS' indices and subtests for differential diagnosis. However, it is noteworthy that there is no information regarding the reliability of the individual subtests, so interpreting only the subtests should be done with caution. Clinicians may also not want to utilize subtests as stand-alone measures.

In general, the RBANS is a good screening measure and it is useful in many clinical situations. However, although the DMI and some of its subtests may aid in differential diagnosis, the present study does not support utilizing the RBANS when attempting to differentiate AD versus SVaD. Previous research, as aforementioned, has also identified other flaws in the battery that should be considered when using it in clinical practice.

Conflict of Interest

None declared.

Acknowledgements

The authors would like to thank Fiona Hill, Psy.D., Alison J. Donnell, Ph.D., and Joe Elder, Psy.D., for their added assistance on this project.

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