Analyzing the subcortical dementia syndrome of Parkinson s disease using the RBANS

Archives of Clinical Neuropsychology 18 (2003) 509 520 Abstract Analyzing the subcortical dementia syndrome of Parkinson s disease using the RBANS William W. Beatty, Katherine A. Ryder, Samuel T. Gontkovsky, James G. Scott, Kelli L. McSwan, Kersi J. Bharucha Departments of Psychiatry and Behavioral Sciences and Neurology, University of Oklahoma Health Sciences Center, P.O. Box 26901, Oklahoma City, OK 73190, USA Accepted 28 February 2002 On mental status examinations, groups of equally impaired patients with subcortical (Huntington s disease, HD; Parkinson s disease, PD) or cortical (Alzheimer s disease, AD) dementias exhibit different patterns of neuropsychological deficits. Using the Repeatable Battery for Assessment of Neuropsychological Status (RBANS), classification accuracies of 90% or greater have been reported for individual patients with AD or HD. To test the generality of the RBANS classification algorithm, we studied patients with dementia (AD and PDD) and without dementia (PDND). Classification accuracies were AD: 87%, PDD: 78%, and PDND: 39%. Comparisons of performance on subtests of the RBANS showed that all groups performed more poorly on tests that require motor skill or rapid information processing and that memory performance by the PD groups was not improved by procedures that enhance encoding and facilitate retrieval. The RBANS is useful for discriminating patterns of cognitive impairment in PD and AD, but only if the diagnosis of dementia is established independent of the RBANS test results. Cognitive slowing is not specific to subcortical dementia and current concepts of memory dysfunction in PD may require re-examination. 2002 National Academy of Neuropsychology. Published by Elsevier Science Ltd. All rights reserved. Keywords: Alzheimer s disease; Cortical dementia; Parkinson s disease; RBANS; Subcortical dementia Corresponding author. Tel.: +1-405-271-2474; fax: +1-405-271-6236. E-mail address: william-beatty@ouhsc.edu (W.W. Beatty). 0887-6177/02/$ see front matter 2002 National Academy of Neuropsychology. PII: S0887-6177(02)00148-8

510 W.W. Beatty et al. / Archives of Clinical Neuropsychology 18 (2003) 509 520 1. Introduction Despite occasional dissent on both conceptual and empirical grounds (Brown & Marsden, 1988; Whitehouse, 1986), it is now generally agreed that the patterns of cognitive and behavioral changes that accompany dementing diseases that primarily affect the cerebral cortex (e.g., Alzheimer s disease, AD) are different from those that are associated with dementing diseases (e.g., Parkinson s disease, PD; Huntington s disease, HD) with mainly subcortical pathology (Cummings & Benson, 1984). During the last two decades, literally hundreds of studies have described differences between patients with cortical and subcortical dementias on a wide range of neuropsychological (NP) tasks. In many studies, as Brown and Marsden (1988) documented, the patient groups differed in average score on a dementia screening examination. Hence, they argued the reported differences in NP profiles might have arisen from differences in dementia severity rather than from differences in the main locus of neuropathology. The force of this argument has been substantially blunted by the demonstration that when groups of patients with cortical or subcortical dementias are equated for overall score on standard screening examinations such as the Mini Mental State Exam (MMSE; Folstein, Folstein, & McHugh, 1975) or the Dementia Rating Scale (DRS; Mattis, 1988), different patterns of NP impairment can be identified. Patients with AD are especially impaired on memory items while patients with PD or HD exhibit relatively greater deficiencies on items that tap initiation and attention (Brandt, Folstein, & Folstein, 1988; Paolo, Tröster, Glatt, Hubble, & Koller, 1995; Salmon, Kwo-on-Yuen, Heindel, Butters, & Thal, 1990; Tröster et al., 1998). However, on these screening tests the magnitude of the differences between cortical and subcortical groups is not sufficiently large to permit accurate classification of individual patients. Randolph, Tierney, Mohr, and Chase (1998) compared the performance of patients with AD or HD on the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Using a simple algorithm that compared an individual patient s performances on visuospatial and attention to language and delayed memory, they reported classification accuracies of 95% for AD and 90% for HD. One purpose of the present study was to conduct a systematic replication of the Randolph et al. (1998) study, comparing patients with AD or PD. Each of the RBANS Indexes is comprised of at least two subtests. The Immediate Memory Index measures acquisition of a story and a list of unrelated words. The Visuospatial/ Construction Index involves copying a complex figure and judging the orientation of lines. The Language Index contains tests of Naming and Semantic Fluency. The Attention Index is comprised of Digit Span and a written Coding test. The Delayed Memory Index is based on four measures: delayed recall of the word list, story and figure as well as yes no recognition of the words. Cummings (1990) summarized the differences in NP test performance by patients with cortical or subcortical dementias. Within the domain of verbal memory, patients with subcortical dementias are supposed to perform relatively better if the information is organized in the form of a story or tested with recognition instead of recall. For patients with cortical dementias, these procedural variations are without consequence. The proposed reason for these differential effects of the test format is that in subcortical dementia the main difficulty is in retrieving information while in cortical dementia encoding or storage (or both) are thought to be defective.

W.W. Beatty et al. / Archives of Clinical Neuropsychology 18 (2003) 509 520 511 Patients with subcortical dementia exhibit slowed processing of information (especially unfamiliar information) and they have difficulty with tasks that require fine motor skill (e.g., Beatty, Staton, Weir, Monson, & Whitaker, 1989; Cummings, 1990). These deficits are not characteristic of AD, at least in the early stages (Cummings, 1990). The second purpose of the present study was to test these predictions about NP differences in subcortical and cortical dementia by comparing the performances of patients with AD or PD on the various subtests from the RBANS. For reasons elaborated above, we predicted that dementia patients with PD would perform better on: Story Learning than List Learning, Story Recall than List Recall, List Recognition than List Recall, Line Orientation than Figure Copy, Naming than Semantic Fluency, and Digit Span than Coding. Equivalent impairment on these pairs of tests was predicted for patients with AD. To examine the influence of chronic neurological disease without dementia we included a group of PD patients of normal mental status. 2. Method 2.1. Participants The participants were 23 patients with AD (13 males, 10 females) and 50 patients with idiopathic PD (46 males, 4 females). The PD group was divided into two subgroups based on scores on the MMSE. Patients who scored between 27 and 30 (N = 23) comprised the PDND (non-demented PD) group. Patients in the PDD group (PD with dementia, N = 27) scored below 27 on the MMSE and, in addition, met the criteria proposed by Cummings and Benson (1984) for dementia (i.e., impairment in at least three of the following spheres of mental activity including language, memory, visuospatial function, cognitive functions such as abstraction, reasoning, mathematics and executive function, and personality or emotion). Although 24 is the usual cutoff for probable dementia on the MMSE, two recent studies (Monsch et al., 1995; vangorp et al., 1999) reported that increasing the cutoff to 26 or 27 increased sensitivity for detecting dementia without significant loss of specificity. All participants were literate residents of the Oklahoma City area and spoke English as their first language. They were recruited from an academic medical center s movement disorders or memory disorders clinics. All patients underwent extensive medical and neurologic workups. They were excluded if they had any of the following conditions: history of neurologic disease other than PD or AD (e.g., stroke, traumatic brain injury); history of schizophrenia or bipolar disease; history of alcoholism or drug abuse or mental retardation; history or current serious medical illness (e.g., COPD, poorly controlled diabetes); or any neurosurgical procedure involving the brain including neurosurgery to relieve PD symptoms (e.g., pallidotomy, deep brain stimulation). The diagnosis of PD was made by a board certified neurologist based on the presence of bradykinesia and at least one of the following: muscular rigidity, 4 6 Hz resting tremor or postural instability not caused by primary visual, vestibular or cerebellar dysfunction. Patients with parkinsonism due to identifiable causes such as encephalitis, neuroleptic or toxin exposure or those exhibiting a poor response to levodopa therapy were excluded. Patients who had end-of-dose motor fluctuations were examined and tested in the on phase. At testing, patients

512 W.W. Beatty et al. / Archives of Clinical Neuropsychology 18 (2003) 509 520 with PD averaged 9.6 years since diagnosis (range: 2 30). Patients in the PDD group averaged 3.2 ± 0.6ontheHoehn and Yahr (1967) scale of disease severity. Patients in the PDND group averaged 2.7 ± 0.7 on the same scale (t(48) = 2.46, P<.05). Most patients in both groups scored 3 on the Hoehn Yahr scale; none scored above 4. The diagnosis of probable AD was made by an experienced neurologist or geriatrician according to the NINCDS ADRDA (McKhann et al., 1984) criteria. Patients with AD who had extrapyramidal signs were excluded. At testing, patients with AD averaged 2.8 years since diagnosis (range: <1 8). All patients received medications as prescribed by their attending physician with doses adjusted for optimal clinical benefit. Of the 50 patients with PD, 48 received a carbidopa/ levodopa preparation, 37 received a direct DA agonist (most often pramipexole dihydrochloride), 13 received trihexiphenidyl HCl, 9 received amantidine HCl, 5 received selegiline HCl, and 1 received tolcapone. In addition, 19 received antidepressants (usually sertraline HCl or paroxetine HCl), 11 received anxiolytics (benzodiazepines or hydroxyzine HCl), and 9 patients received quetiapine fumarate at bedtime to control visual hallucinations that were presumed to be secondary to the regimen of direct and indirect DA agonists used to alleviate parkinsonism. Of the 23 patients with AD, 5 received donepezil HCl, 9 received antidepressants (usually sertraline HCl), 3 received anxiolytics (benzodiazepines), and 1 received an antipsychotic (risperidone). All participants or their caregivers provided written informed consent after a thorough explanation of the procedures which were approved by the local Institutional Review Board (IRB). 2.2. Procedure As part of a larger battery participants received the RBANS (Randolph, 1998) and either the Beck Depression Inventory (BDI-II; Beck, Steer, & Brown, 1996) or the Geriatric Depression Scale (GDS; Yesavage et al., 1983). The decision to administer the BDI or the GDS was made on the examiner s judgment of the patient s ability to comprehend test instructions. Most of the patients with PD received the BDI, while all but one patient with AD received the GDS. (Three patients with AD and two with PD did not receive either the BDI or the GDS because of time limitations.) When compared directly, the BDI and GDS appear equally satisfactory for detecting depression in the elderly (Holroyd & Clayton, 2000; Olin, Schneider, Eaton, Zemansky, & Pollock, 1992). Accordingly, data for depression are reported as the percentage of patients who scored at or above the cutoff for each test (10 for the BDI, 11 for the GDS). 2.3. Data analysis Scores for the six indexes (Immediate Memory, Visuospatial/Construction, Language, Attention, Delayed Memory, Total) were computed as described in the RBANS test manual (Randolph, 1998). The Cortical Subcortical Deviation Score (the Randolph ) was computed as described by Randolph et al. (1998). The value of the Randolph Index is computed from the RBANS Index Scores as: [(Visuospatial/Construction + Attention)/2] [(Language + Delayed Memory)/2].

W.W. Beatty et al. / Archives of Clinical Neuropsychology 18 (2003) 509 520 513 To test the hypotheses about differential patterns of performance by the PDD and AD patients outlined in Section 1, we obtained norms for the individual subtests from the test publisher. Like the norms for the RBANS Indexes, norms for the individual subtests are blocked by decade for individuals from 20 to 89 years of age. The sample of 540 normal volunteers is reasonably representative of the demographic characteristics of the US population. Using the normative data for each patient s age group, performances of the patients on the individual subtests were first converted to Z scores. Then the Z scores were subtracted pairwise one from the other to test each a priori hypothesis (e.g., Z recognition Z recall). The predicted patterns of differences between Z scores were analyzed in two ways: (a) was the average difference between Z scores for each patient group significantly different from 0; and (b) were there significant differences among the AD, PDD and PDND groups? Although the RBANS Indexes and the norms for the individual tests correct for age, they do not correct for education. As a precaution, we performed ANOVAs and ANCOVAs controlling for the significant differences among groups for age and the non-significant differences among groups, these analyses yielded identical results. To simplify exposition only the ANOVA results are reported below. 3. Results Table 1 summarizes the demographic, clinical and NP data for the three groups. Initial analyses revealed significant differences among groups on all variables [F s(2, 70) > 4.85, Ps <.05] except Education [F = 1.61] and Depression (χ 2 = 0.72). Subsequent analyses showed that the patients with AD were significantly older than the PD patients with dementia (t(48) = 3.65, P<.01), but the groups did not differ in education, MMSE, the Total Index, or the Immediate Memory Index (all ts < 1). Patients in the AD group evidenced more severe impairment on the Language (t(48) = 2.04, P<.05) and Delayed Memory Indexes (t(48) = 4.17, P<.001) while patients in the PDD group showed a greater deficit on the Attention Index (t(48) = 2.44, P<.05). The difference between groups on the Visuospatial/Construction Index was the predicted direction, but fell short of Table 1 Patient characteristics including RBANS Index scores: mean (S.D.) PDND PDD AD Age 65.5 (9.9) 70.2 (7.0) 77.1 (5.5) Education 13.4 (2.6) 11.9 (2.7) 12.5 (3.2) MMSE 28.7 (1.1) 23.1 (2.5) 22.3 (4.7) % Depressed 41 52 45 Immediate Memory 81.6 (17.5) 66.7 (12.0) 65.5 (15.7) Visuospatial/Construction 92.5 (16.9) 70.9 (18.3) 82.1 (25.3) Language 91.6 (8.1) 86.4 (10.3) 79.3 (13.7) Attention 91.0 (15.9) 69.3 (13.6) 81.2 (19.7) Delayed Memory 83.4 (16.4) 71.1 (16.3) 53.2 (14.1) Total 84.4 (13.6) 65.9 (11.0) 65.0 (16.3)

514 W.W. Beatty et al. / Archives of Clinical Neuropsychology 18 (2003) 509 520 Table 2 Classification algorithms for cortical/subcortical disease: mean (S.D.), percentage of patients correctly classified as cortical (AD) or subcortical (PDD, PDND) Randolph a PDND 4.3 (11.9), 39% PDD 8.7 (10.7), 78% AD 15.4 (17.5), 87% Scores 0 or below predict a subcortical pattern; scores above 0 predict a cortical pattern. a Randolph = [(Visuospatial/Construction + Attention)/2] [(Language + Delayed Memory)/2]. significance (t = 1.77), mainly because of highly variable performance by patients in the AD group. With three exceptions, patients in the PDND group differed from patients in the other two groups (ts > 2.13, Ps <.05). There was no significant difference between the PDND and PDD groups on the Language Index; likewise the PDND and AD groups did not differ significantly on the Visuospatial/Construction and Attention Indexes. On each of the six RBANS Indexes performance by the PDND group differed significantly from the expected value for normals (i.e., 100, ts(22) >2.12, Ps <.05). Table 2 reports data concerning the performance of the Randolph for classifying patients as subcortical or cortical. In the present study, the Randolph Index correctly classified 20 of 23 patients with AD (χ 2 (1) = 6.28, P<.05) and 21 of 27 patients in the PDD group (χ2 (1) = 4.17, P<.05). However, only 9 of 23 patients in the PDND were identified as subcortical and for this group, the average value of the Randolph Index was in the cortical range. Additional statistical analyses showed that the mean values of the Randolph Index differed from 0 for the AD (t(22) = 4.23, P<.001) and the PDD (t(26) = 4.22, P<.001) groups but not for the PDND group (t(22) = 1.72, ns). Because the norms for the RBANS Indexes adjust for age, no influence of the 7-year age difference between the PDD and AD groups was expected. Consistent with this prediction, correlations between the Randolph and age were small in magnitude and non-significant for the PDD (r =.116) and AD (r =.064) groups. A discriminant function analysis showed that the Randolph correctly classified 80% of the patients in PDD and AD groups. Neither age nor education significantly improved the accuracy of classification. Table 3 summarizes the results of tests of several predictions about the characteristics of deficits in memory, language, attention and visuospatial function in PD and AD. Consider first the comparisons related to motor skill and processing speed. For each of the comparisons, the tasks requiring greater motor skill (i.e., complex Figure Copy), greater processing speed (Semantic Fluency) or both (Coding) were performed more poorly, but the pattern of results was similar for all three groups. For the PDND and AD groups, the magnitude of the mean difference between Z scores differed significantly from 0 for all three comparisons: PDND (ts(22) >3.58, Ps <.001); AD (ts(22) >2.59, Ps <.01). For the PDD groups, differences between Naming and Semantic Fluency (ts(26) = 4.55, P<.001), and Digit Span and Coding (ts(26) = 6.49, P<.001) were significant, but the difference between Line Orientation and Figure Copy was not (t = 1.62).

W.W. Beatty et al. / Archives of Clinical Neuropsychology 18 (2003) 509 520 515 The impression that each of the three groups showed relative worsening on tasks within a domain that placed relatively greater emphasis of speed and motor skill was confirmed by the absence of differences among groups for comparisons between tasks in the language, attention, and visuospatial domains. A simple tally of the number of patients in each group who performed relatively better on all three tasks that demanded less skill or processing speed indicated that the observed frequencies differed from chance for all three patient groups (χ(1) 2 s > 9.01, Ps <.001), but differences among groups were not significant. As described earlier, the memory difficulties of patients with PD are supposed to be ameliorated by procedural manipulations that improve the organization of the to-be-remembered material (i.e., in a story) or require only recognition instead of unaided recall. The memory deficits of patients with AD are not supposed to benefit from these procedural variations. Table 3 summarizes the results of tests of these predictions. Consider first the acquisition of new information (i.e., Story Memory List Learning). On this measure, the difference scores were in the predicted direction for both PD groups, but the magnitude of the difference scores was not significantly different from 0 (ts < 1.78). Furthermore, differences between the PD groups and the AD group were not significant (ts < 1.34). The mean difference score for the AD group closely approximated the predicted value of 0, indicating equivalent impairment in learning word lists or stories. Contrary to prediction, the difference scores comparing Story Recall to List Recall were negative for all three groups, indicating relatively greater impairment in recalling stories than lists. For the AD group, the difference score was significantly less than 0 (t(22) = 4.63, P<.001) but the PD groups did not differ significantly from 0 (ts < 1.24). Exactly the same pattern was found for the comparison of List Recognition and List Recall. Again, difference scores for the PD groups were negative but not significantly different from 0 (ts < 1), while the difference score for the AD group was negative and significantly less than 0(t(22) = 3.52, P<.001). Finally, direct comparison of the difference scores for the PDD Table 3 Comparisons between RBANS subtests: mean (S.D.) difference between Z scores, percentage of patients showing predicted difference PDND PDD AD Memory Story Memory List Learning 0.38 (1.34), 65% 0.39 (1.12), 70% 0.01 (1.00), 39% Story Recall List Recall 0.23 (1.39), 30% 0.32 (1.24), 44% 1.25 (1.30), 22% List Recognition List Recall 0.03 (1.23), 43% 0.06 (2.05), 48% 1.69 (2.30), 30% Motor skills, processing speed Line Orientation and Figure Copy 0.75 (2.41), 57% 1.02 (3.30), 67% 0.83 (1.53), 76% Naming and Semantic Fluency 1.38 (0.90), 96% 1.32 (1.52), 85% 0.93 (1.51), 70% Digit Span and Coding 1.80 (1.40), 100% 2.27 (1.80), 93% 1.65 (1.88), 78% All three predictions about motor skills and processing speed 57% 59% 35% A positive value means that the average value of the mean difference between Z scores was in the predicted direction.

516 W.W. Beatty et al. / Archives of Clinical Neuropsychology 18 (2003) 509 520 and AD groups revealed significant differences for Story Recall vs. List Recall (t(48) = 2.58, P<.05) and List Recognition vs. List Recall (t(48) = 2.63, P<.05). One problem with the method used to analyze the memory data is that it is vulnerable to floor effects. One cannot recall fewer than 0 items, but on recognition a comparably severe memory deficit yields a score of about 10. To evaluate this problem we tallied the number of patients who recalled 0 items on the List Recall and Story Recall tests. Of 23 patients in the AD group, 21 scored 0 on List Recall and 13 scored 0 on Story Recall. Of 27 patients in the PDD group, 15 recalled 0 on List Recall and 2 recalled 0 on Story Recall. Only one patient in the PDND group recalled 0 words from the list and all patients in this group recalled at least 1 bit from the story. To correct for the possible bias caused by floor effects on List Recall, we re-analyzed the data from the PDD group, including only those patients (N = 12) who recalled at least one word from the list. For the Story Recall List Recall comparison, the mean difference in Z scores was 0.95 ± 1.23, (t(11) = 2.62, P<.05). For the List Recognition List Recall comparison, the mean difference in Z scores was 0.04 ± 1.36 (t <1). Because only two patients in the AD group recalled at least one word from the lists, it was not possible to conduct a meaningful analysis for these patients. Since only one patient in the PDND group failed to recall at least one word, it is obvious that the results would not be much affected by re-analyzing those data. Finally, on Story Memory and List Learning, all patients scored at least 1 on both tasks. 4. Discussion The present study confirms the usefulness of the algorithm proposed by Randolph et al. (1998) for classifying individual patients with AD or HD based on patterns of NP performance and extends their finding with patients with HD to PD, another disease that can produce subcortical dementia (Cummings & Benson, 1984). An earlier study (McCrea, Fink, & Randolph, 1999) reported a classification accuracy of 79% for patients with subcortical ischemic dementia. Taken together, these findings attest to the usefulness of the RBANS and its indexes for the NP assessment of dementia. The Randolph Index did not accurately classify patients in the PDND group. This is exactly what would be expected because (presumably) healthy controls would be randomly and symmetrically distributed about a mean of 0 on the Randolph algorithm. However, the average performance of patients in the PDND group was not normal on any of the RBANS Indexes and there was no sharp distinction in the test performances of patients in the PDND and PDD groups. This suggests that clinicians should obtain clear and independent evidence for dementia before applying the classification algorithms. By using the excellent RBANS norms we were able to test some cherished concepts about NP differences between cortical and subcortical dementia. The technique employed, converting raw scores to Z scores, permits direct comparisons of performances on tests with different numbers of items or ranges of scores. The prediction that dementia patients with PD would perform relatively more poorly on tests that emphasize motor skill and speed of processing was confirmed but the patients in the

W.W. Beatty et al. / Archives of Clinical Neuropsychology 18 (2003) 509 520 517 AD and PDND groups exhibited exactly the same pattern. These findings suggest that loss of the ability to process information rapidly is a general characteristic of neurodegenerative disease and may be evident early in the disease course in the absence of dementia. The analyses of the various memory measures used in the present study yielded conclusions that are at variance with widely held beliefs about differences in the memory disturbances in subcortical and cortical dementias. Cummings (1990) has stated the conventional position, namely that in subcortical dementia encoding and storage mechanisms are relatively intact while in cortical dementias such as AD, these functions are severely compromised presumably because of early pathology in the hippocampus and adjacent medial temporal lobe systems. Speaking specifically of PD, Taylor, Saint-Cyr, and Lang (1986) argued that their non-demented patients principal difficulties were in initiating and maintaining effective retrieval strategies. From these theoretical perspectives, patients with PD (whether demented or not) should have been less impaired at recalling stories than lists and less impaired at recognizing than recalling words from lists. Instead, both PDD and PDND groups showed non-significant benefits in acquiring stories relative to lists and non-significant deficits in recalling stories and recognizing lists relative to recalling lists. It could be argued that the method of data analysis used in the present study was insensitive because of inadequate sample size or some other reason. This explanation can be rejected because in four of the six comparisons involving memory for the PD groups, the mean difference in Z scores was in the opposite direction from that predicted by the prevalent theories of memory in subcortical disease. Furthermore, the method cannot have been insensitive in the statistical sense because it revealed significant differences between Story Recall and List Recall and between List Recognition and List Recall for the AD group. To be sure, these differences were also unexpected, because equivalent impairment for stories and lists and for recognition and recall was predicted for the patients with AD. Among the 23 patients with AD, 21 recalled 0 words from the list, 13 recalled 0 items from the story, but all patients scored at least 9 on recognition. Hence, it is possible that differential floor effects across the three memory tests account the unexpected relative impairment of these patients in recalling stories and recognizing lists (compared to recalling lists). A similar account may explain the significant differences between the PDD and AD groups on these memory measures. Because more patients in the PDD group attained 0 on List Recall than on Story Recall and List Recognition, differential floor effects might explain the failure to observe the predicted facilitation for stories and recognition. However, re-analyses excluding patients who attained 0 scores on List Recall revealed a non-significant negative difference for the List Recognition List Recall comparison and a significant relative disadvantage in recalling stories compared to word lists. Thus, eliminating possible differential floor effects did not affect the List Recognition List Recall comparison and converted a non-significant difference between Story Recall List Recall into significant difference, albeit in the opposite direction from prediction. The Z score method used in the present study is also sensitive to the size of the standard deviations for the normative measures. Smaller standard deviations could potentially inflate the size of difference scores, magnifying certain effects and diminishing others. To evaluate this problem we calculated the ratio of standard deviations for the various memory measures using normative data for ages 50 89 (obtained from the RBANS test publisher). The ratios are

518 W.W. Beatty et al. / Archives of Clinical Neuropsychology 18 (2003) 509 520 Story Memory:List Learning = 0.78; List Recognition:List Recall = 0.52; Story Recall:List Recall = 1.00. Because the average Z scores for all groups were negative on all measures, potential biases against the research hypotheses may exist for the Story Memory List Learning comparison, and, somewhat more strongly, for the List Recognition List Recall comparison. However, no such bias exists for the Story Recall List Recall comparison because the ratio of standard deviations from the normative data set equals 1.0. Like any method for comparing performances across tasks, the one used in the present study has its limitations, two of which are discussed above. Based on these considerations, one might dismiss the results of the Story Memory List Learning and List Recognition List Recall comparisons because of differences in the size of the standard deviations across memory measures. This artifact plus differential floor effects perhaps account for the puzzling findings for the memory comparisons involving the AD group. However, the finding that patients in the PDD group who scored at least 1 on delayed recall of the word list showed significantly poorer performance on Story Recall than on word List Recall cannot be explained by differential floor or variability effects. Several studies of anterograde learning and memory are consistent with our earlier report (Beatty et al., 1989) that in non-demented patients with PD verbal recall but not verbal recognition is impaired (Breen, 1993; Flowers, Pearce, & Pearce, 1984; Taylor et al., 1986; Weingartner, Burns, Diebel, & LeWitt, 1984). In each of these studies the recognition memory performance by the patients was poorer than that of controls, but the differences were not significant, possibly because of ceiling effects, small sample size or other factors that limited statistical power. Previous studies of patients with PD and dementia have documented significant deficits relative to healthy controls on both free recall and recognition (Beatty et al., 1989; Helkala, Laukimaa, Soininen, & Riekkinen, 1988, 1989). Because the chance rate for success on recognition is 50% compared to nearly 0 for recall, the apparent relative improvement for List Recognition vs. List Recall may be illusory. However, the relatively greater improvement on List Recognition vs. List Recall for PD compared to AD groups of roughly comparable dementia severity (Helkala et al., 1988, 1989) as well as the different patterns of errors produced by PD and AD groups cannot be easily dismissed. On anterograde verbal memory tasks, patients with PD do not spontaneously adopt strategies that can foster encoding such as semantic clustering, but they can make use of such strategies given explicit instructions with a resultant improvement in recall (Buytenhuis et al., 1994; Van Spaendonck, Berger, Horstink, Borm, & Cools, 1996). Randolph, Braun, Goldberg, and Chase (1993) reported that a similar manipulation (cueing by semantic category) improved the performance of patients with HD or PD on Semantic Fluency tasks (the Supermarket test and the Animals test). By contrast, patients with AD showed no significant improvement with category or subcategory cueing. Ostensibly, these findings imply that retrieval failure is a more important cause of memory dysfunction in HD and PD than in AD. However, marked differences in the severity of dementia as judged by average DRS scores for the groups (PD = 138.0, HD = 130.0, AD = 114.8) make it impossible to determine whether dementia severity or dementia type was the more influential variable. More recently, Portin, Laatu, Revonsuo, and Rinne (2000) reported that mildly impaired patients with PD (mean MMSE = 25.0) showed deficits on semantic memory tasks that were not alleviated by cueing.

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