RESEARCH ARTICLE

CLINICAL PRACTICE

Development of Clinical Dementia Rating Scale Cut-off Scores for Patients With Parkinson’s Disease Kathryn A. Wyman-Chick, M.A.,1,* BJ Scott, PsyD1

Abstract: Background: The aim of this study was to explore validity of the Clinical Dementia Rating Scale (CDR) in measuring cognitive impairment among individuals with Parkinson’s disease (PD). The scale was created for use in patients with Alzheimer’s disease, and, to date, there have been no published studies examining whether this tool is appropriate for patients with PD. Methods: The data were obtained from the National Alzheimer’s Coordinating Center database and included 490 subjects diagnosed with PD, further categorized as having PD dementia (n = 151), mild cognitive impairment (n = 186), or normal cognition (n = 153) by a treating physician. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated for the CDR Scale Global Score as well as the Sum of Boxes Score using existing cut-off scores. Finally, new cut-off scores were calculated using sensitivity and specificity values derived using receiver operating characteristic curves. Results: Sensitivity and specificity of the published Global Score cut-off scores for patients with dementia were 0.34 and 0.10, respectively. The newly calculated cut-off scores for patients with dementia yielded a sensitivity of 0.79 and a specificity of 0.96. The area under the curve was 0.92 (95% confidence interval = 0.90–0.95). Conclusion: The CDR is a useful tool in identifying dementia in patients with PD when the cut-off scores are adjusted.

The aim of this study was to calculate the sensitivity and specificity of the Clinical Dementia Rating Scale (CDR) in measuring dementia and mild cognitive impairment among individuals diagnosed with Parkinson’s disease (PD). The CDR uses a semistructured interview to rate six domains associated with dementia: memory; orientation; judgment and problem solving; community affairs; home and hobbies; and personal care. To date, there have been no published studies specifically examin-

ing whether the published CDR cut-off scores are appropriate for patients with PD.

Neuropsychological Profile in PD and PD Dementia Nondemented patients with PD often experience neuropsychological deficits related to the disease process, including executive

1

School of Professional Psychology, Pacific University, Hillsboro, Oregon, USA

* Correspondence to: Ms. Kathryn A. Wyman-Chick, Pacific University School of Professional Psychology, 190 Southeast 8th Avenue, Hillsboro, OR 97123, USA; E-mail: [email protected]

Keywords: Parkinson’s disease, dementia, mild cognitive impairment, cognitive screening. Relevant disclosures and conflicts of interest are listed at the end of this article. Data used in the preparation of this article were obtained from the National Alzheimer’s Coordinating Center (NACC) database. The NACC database is funded by National Institute on Aging/National Institutes of Health Grant U01 AG016976. NACC data are contributed by the NIA-funded Alzheimer’s Disease Centers: P30 AG019610 (principal investigator [PI] Eric Reiman, MD), P30 AG013846 (PI Neil Kowall, MD), P50 AG008702 (PI Scott Small, MD), P50 AG025688 (PI Allan Levey, MD, PhD), P30 AG010133 (PI Andrew Saykin, PsyD), P50 AG005146 (PI Marilyn Albert, PhD), P50 AG005134 (PI Bradley Hyman, MD, PhD), P50 AG016574 (PI Ronald Petersen, MD, PhD), P50 AG005138 (PI Mary Sano, PhD), P30 AG008051 (PI Steven Ferris, PhD), P30 AG013854 (PI M. Marsel Mesulam, MD), P30 AG008017 (PI Jeffrey Kaye, MD), P30 AG010161 (PI David Bennett, MD), P30 AG010129 (PICharles DeCarli, MD), P50 AG016573 (PI Frank LaFerla, PhD), P50 AG016570 (PI David Teplow, PhD), P50 AG005131 (PI Douglas Galasko, MD), P50 AG023501 (PI Bruce Miller, MD), P30 AG035982 (PI Russell Swerdlow, MD), P30 AG028383 (PI Linda Van Eldik, PhD), P30 AG010124 (PI John Trojanowski, MD, PhD), P50 AG005133 (PI Oscar Lopez, MD), P50 AG005142 (PI Helena Chui, MD), P30 AG012300 (PI Roger Rosenberg, MD), P50 AG005136 (PI Thomas Montine, MD, PhD), P50 AG033514 (PI Sanjay Asthana, MD, FRCP), and P50 AG005681 (PI John Morris, MD). The investigators within the NACC did not participate in the design, analysis, or writing of the manuscript. Received 18 October 2014; revised 31 January 2015; accepted 3 February 2015. Published online 20 April 2015 in Wiley InterScience (www.interscience.wiley.com). DOI:10.1002/mdc3.12163

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dysfunction and visual-spatial problems. Psychological and behavioral features associated with PD can include apathy, depression, visual hallucinations, delusions, and excessive daytime sleepiness.1 Thus, diagnosis of PD dementia (PDD) can be complicated owing to these and other issues related to medication, depression, fatigue related to sleep disturbance, and functional impairment resulting from motor symptoms.2 Although patients with PD may experience cognitive deficits, the neuropsychological characteristics of PDD by nature are more severe and often include impairment in multiple domains, including processing speed, working memory, and attention in addition to executive dysfunction and visual-spatial deficits.3,4 In 2007, the International Parkinson and Movement Disorder Society (MDS) Task Force published guidelines for diagnosing PDD, which requires diagnosis of PD based on Queen Square Brain Bank criteria, slowly progressive decline from premorbid levels, impairment in more than one cognitive domain, at least one behavioral feature, and significant functional impairment independent of motor symptoms.5

Mild Cognitive Impairment in PD According to the International Working Group on Mild Cognitive Impairment, mild cognitive impairment (MCI) is a condition that is neither normal nor demented, but there is evidence of functional decline; however, activities of daily living (ADLs) are relatively intact.6 In PD, MCI may present with executive dysfunction7 and visual-spatial deficits.8 MCI exists as a prodromal stage for PDD. Authors of a recent study9 examined MCI in patients with PD using the Mattis Dementia Rating Scale (MDRS). PD-MCI participants had nonmemory deficits in domains such as construction, attention, and conceptualization, compared to patients with Alzheimer’s Disease (AD). A recent study10 examined 1,346 nondemented PD patients who underwent a clinical interview and neuropsychological assessment measuring verbal memory, visuospatial ability, and attention/executive functioning. Inclusion criteria for the study required participants to have been diagnosed with PD for less than 2 years. The results indicated that 25.8% met criteria for PD-MCI, highlighting the importance of identifying cognitive impairment in the early stages of PD.

Parkinson’s Clinical Dementia Rating Scale for individuals with PD and PDD to have features of AD14 or for the two conditions to coexist.15

CDR Scale The CDR was developed as a tool to differentiate between stages of dementia. Individuals with PD were explicitly excluded from the original studies leading to development of the CDR.16 However, the CDR may be an ideal staging tool for PDD, given that the score reflects the impact of cognitive impairment on daily activities and excludes physical disability as a result of the disease process. The updated CDR uses a semistructured interview to rate performances across six domains associated with dementia: memory; orientation; judgment and problem solving; community affairs; home and hobbies; and personal care.17 The domains are scored independently of one another, although memory is considered to be the primary category. The category with the highest ranking (i.e., greatest level of impairment) is used to determine the CDR global score (CDR-GS), which ranges between 0 and 3, where 0 = absence of symptoms, 0.5 = questionable, 1 = mild, 2 = moderate, and 3 = severe dementia.16,17 The sum of boxes score (CDR-SB) is an additional score, which includes scores from all six domains and ranges between 0 and 18.17,18 In this score, all of the domains have equal weight. O’Bryant et al.18 used the CDR-SB to compare groups with MCI, probable AD, possible AD, Lewy body dementia (LBD), vascular dementia, primary progressive aphasia, frontotemporal dementia, and “dementia other,” which included alcohol-related dementia, dementia of undetermined etiology, PSP, prion disease, and Huntington’s disease. For AD, the CDR-SB recommended cut-off scores were as follows: 0.5 to 4 = questionable; 4.5 to 9 = mild and 9.5 to 15.5 = moderate; and 16 to 18 = severe. The researchers argued that the CDR-SB is more sensitive than the CDR-GS in tracking disease progression. They also posited that the expanded range of scores for the CDR-SB is more beneficial for research and clinical applications than the CDR-GS scores.18 A limitation of this study was the exclusion of patients with PDD; therefore, it is not known whether published CDR-SB ranges apply to this group.

Aim of Current Study Comparison With AD Many studies examining cognitive impairment in PD use measurement tools developed for AD that do not sufficiently capture important domains (e.g., executive dysfunction) that may be prominent in non-AD forms of dementia.11 In this respect, the neuropsychological profiles of individuals with PDD are distinctly different from those with AD.12 For example, patients with AD experience more difficulty with memory and language,13 whereas individuals with PDD have greater impairment in executive functioning and attention.3,14 Unlike many patients with AD, patients with PDD typically have insight into the nature of their cognitive problems.4 However, it is possible

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The aim of this study is to examine the sensitivity and specificity of the CDR in detecting cognitive impairment among individuals diagnosed with PD. As noted above, patients with PDD exhibit more problems with executive functions, visual-spatial functions, and attention, whereas patients with AD experience more difficulty with language and memory.3 The CDR was developed to detect AD; many of the core symptoms of PDD and AD are different; therefore, there may be differences in the optimal cut-off scores between the two conditions. Previous investigators have used CDR cut-off scores developed for AD to classify stages of dementia in patients with PDD7,19,20; however, to date, there are no published studies specifically examin-

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K.A. Wyman-Chick and B.J. Scott

ing whether the published CDR cut-off scores are appropriate for patients with PD. The CDR scoring is weighted more heavily for memory and does not include a rating for visual-spatial ability or executive functions, which may limit the usefulness of this screening tool for patients with PD. The MDS Task Force emphasized that a diagnosis of dementia requires evidence of an impact on daily living activities that cannot be attributed to motor symptoms.5,21 The instructions for the CDR read, “Mark in only 1 box for each category, rating impairment as decline from the person’s usual level due to cognitive loss alone, not impairment due to other factors such as physical handicap or depression”17 (p. 2413). Therefore, the usefulness of the CDR in the screening and staging of PDD may be enhanced by the measurement of ADLs independent of noncognitive disease processes that affect abilities as well as executive functions (in the form of judgment and decision making). In this study, the CDR performance of three groups of patients with PD was compared: normal cognition, MCI, and dementia. The main hypotheses of the study are listed below. Because CDR-GS cut-off scores published for AD are heavily weighted for memory and do not include visuospatial functioning, it is hypothesized that the published cut-off scores would not adequately differentiate between normal cognition, PD-MCI, and PDD. The CDR-SB score will be more useful than CDR-GS for patients with PD, given that the CDR-SB includes scores from all of the six domains and memory is not scored as the primary domain.

Patients and Methods Participants The Pacific University Institutional Review Board (Hillsboro, OR) approved the present study. Participant data were obtained from the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set, which includes data from 34 National Institute on Aging (NIA)-funded Alzheimer’s Disease Centers (ADCs).22–24 Informed consent was obtained from participants or their proxies at the individual centers where the patients were examined. All participants in the data set had been examined using standardized protocols and diagnosed by experienced physicians using uniform guidelines.22,23 The NACC proce-

dures require several quality checks of the data before they are entered into the database.23

Procedure The CDR was administered and scored by trained staff within their respective ADCs. A more detailed description of standardized test administration and database quality checks can be found in a 2009 publication by Weintraub et al.24 Participants in the NACC database had been classified into three diagnostic categories based upon physician diagnosis: normal cognition, MCI, or dementia. Inclusion criteria for the present study were a diagnosis of PD and complete CDR scores. Individuals with PD comorbid with probable or possible AD were specifically excluded from the study in order to increase internal validity of the study. Data from patients with other dementia syndromes, such as frontotemporal degeneration, vascular dementia, or primary diagnosis of LBD, also were excluded from the present study. In addition, data from individuals with a history of stroke contributing to cognitive problems, traumatic brain injury, prion disease, brain neoplasm, MSA, brain surgery, or normal pressure hydrocephalus were excluded. A total of 490 participants met inclusion criteria and were analyzed for the current study (see Table 1 for demographic information). A one-way analysis of variance (ANOVA) was conducted to evaluate significant differences in age between the three groups. Levene’s test was significant; therefore, the groups were not homogeneous. The one-way ANOVA was significant using Welch’s test (Fasymp (2, 313.16) = 13.72; P < 0.001). Follow-up tests were conducted to evaluate pair-wise differences among the group means. Games-Howell’s post-hoc test results indicated that the dementia group had a significantly higher age than both the PD-MCI and normal cognition groups. There was no significant difference in age between the PD-MCI group and the normal cognition group. A one-way ANOVA was conducted to evaluate potential differences in education between the three participant groups. Results were not significant (F(2, 487) = 2.64; P = 0.072), indicating that there were no significant differences in education among the three groups.

Statistical Analysis CDR-GS and CDR-SB scores from the NACC database were analyzed for this study (see Table 2). Scores were obtained from

TABLE 1 Group characteristics (mean  SD)

Age Education Sex (M/F) Ethnicity, % Caucasian African American Asian American Multiethnic

PD Normal Cognition (N = 153)

PD-MCI (N = 186)

PDD (N = 151)

70.08  10.46 16.25  2.86 100/53

71.38  8.52 16.69  9.06 139/47

75.07  7.87 15.19  3.04 120/31

94.8 2.0 2.0 0.49

(n (n (n (n

= = = =

145) 3) 3) 2)

91.9 4.8 1.1 2.1

(n (n (n (n

= = = =

171) 9) 2) 4)

95.4 4.0 0 0.7

(n (n (n (n

= = = =

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144) 6) 0) 1)

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Parkinson’s Clinical Dementia Rating Scale

TABLE 2 CDR Scale scores by group

CDR memory CDR orientation CDR judgment CDR community affairs CDR home and hobbies CDR personal care CDR-GS CDR-SB

PD Normal Cognition

PD-MCI

PDD

M

SD

M

SD

M

SD

0.08 0.02 0.05 0.06 0.05 0.01 0.09 0.27

0.21 0.11 0.18 0.19 0.18 0.11 0.21 0.77

1.34 0.12 0.41 0.33 0.32 0.10 0.50 1.78

0.21 0.24 0.31 0.38 0.34 0.39 0.18 1.26

1.34 0.99 1.35 1.37 1.48 1.05 1.36 7.59

0.76 0.81 0.78 0.81 0.88 1.15 0.80 4.65

TABLE 3 A comparison of CDRating Scale cut-off scores for PD CDR-GS

PD normal cognition PD-MCI PDD

CDR-SB

Publisher’s AD Cut-off Scores

Recommended PD Cut-off Scores

Publisher’s AD Cut-off Scores

Recommended PD Cut-off Scores

0–0.5a 1 2–3

0 0.5 ≥1

0–4b 4.5–9 9.5–18

0–0.5 1–4 ≥4.5

0.5 = “questionable” impairment. 0–4 = “questionable” impairment.

a

b

participants’ most recent visit in order to capture as many individuals with PD-MCI and PDD as possible, while maintaining independent observations among data. Descriptive data, including means and standard deviations (SDs) on the CDR-GS and CDR-SB, were computed for participants with normal cognition, PD-MCI, and PDD, as well as for the sample as a whole. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated using the diagnosis of dementia as the characteristic and various cut-off scores on the CDR-GS and CDR-SB, following procedures outlined in Strauss et al.25 This procedure was replicated for individuals with normal cognition and for those with a diagnosis of PD-MCI. Receiver operating characteristic (ROC) curves were generated to depict the diagnostic accuracy of CDR-GS and CDRSB scores in classifying MCI and dementia in patients with PD. These procedures were used to test the null hypothesis that the published CDR cut-off scores developed for AD are the same for PDD. Finally, new cut-off scores were calculated using sensitivity and specificity values derived from the ROC curves.

Results CDR-GS ROC Curve ROC curve analyses were conducted for the CDR-GS for each group. According to the ROC curve for CDR-GS, a cut-off score of 0 yielded the best sensitivity and specificity (0.84 and 0.98, respectively) for the normal cognition group. The area under the curve (AUC) was 0.07 (95% confidence interval [CI] = 0.05–0.10). A CDR-GS score of 0.05 yielded the best sensitivity and specificity for the PD-MCI group (0.88 and

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0.82, respectively). The AUC was 0.51 (95% CI = 0.56–0.56). Finally, for individuals with PDD, a CDR-GS of >1 yielded the best sensitivity and specificity (0.79 and 0.96, respectively). The AUC was 0.92 (95% CI = 0.90–0.95).

CDR-SB ROC Curve ROC curve analyses were conducted for the CDR-SB for each group. In individuals with normal cognition, a CDR-SB score between 0 and 0.5 yielded the best sensitivity and specificity (0.91 and 0.87, respectively). The AUC was 0.05 (95% CI = 0.03–0.07). For the CDR-SB, a score between 1 and 4 provided the best sensitivity and specificity (0.71 and 0.82, respectively) in individuals with PD-MCI. The AUC was 0.48 (95% CI = 0.43–0.54). Finally, for individuals with PDD, the ideal CDR-SB cut-off score was ≥4.5, which yielded the best sensitivity and specificity (0.74 and 0.98, respectively). The AUC was 0.97 (95% CI = 0.96–0.98).

Overall Sensitivity and Specificity for the CDR Table 3 displays a comparison between CDR cut-off scores developed by test developers and the recommended CDR cutoff scores for individuals with PD found in this study. Table 4 provides sensitivity and specificity values for the recommended cut-off scores found in this study. The recommended values for CDR-GS normal cognition found in this study had slightly lower sensitivity than for previously published scores; however, specificity was increased. For the CDR-SB, sensitivity for the normal and PD-MCI groups were slightly lower than for previously published scores; however, this was considered an

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TABLE 4 Sensitivity and specificity values for the CDRating Scale for patients with PD CDR-GS

PD normal cognition PD-MCI PDD

CDR-SB

Publisher’s AD Cut-off Scores Sensitivity/Specificity

Recommended PD Cut-off Scores Sensitivity/Specificity

Publisher’s AD Cut-off Scores Sensitivity/Specificity

Recommended PD Cut-off Scores Sensitivity/Specificity

0.99/0.39 0.07/0.79 0.34/1.0

0.84/0.98 0.88/0.82 0.79/0.96

0.99/0.87 0.77/0.80 0.34/1.0

0.91/0.87 0.71/0.82 0.74/0.98

acceptable trade-off for increasing sensitivity and specificity for the dementia group.

physician and received a cognitive evaluation to diagnose their cognitive status (i.e., normal cognition, MCI, or dementia).

Discussion

Limitations

The first hypothesis in this study was upheld. The CDR-GS published cut-off scores did not accurately categorize individuals with MCI or dementia; however, individuals with normal cognition were accurately categorized using cut-off scores published by test developers. The second hypothesis was partially upheld. The expanded CDR-SB scores were more useful than CDRGS scores for patients with PD; however, this was only true for the PD-MCI group. The CDR-SB did not have greater sensitivity/specificity for the group with dementia. However, if the cut-off scores are adjusted, the CDR-GS and CDR-SB appear to be useful screening tools for normal cognition, MCI, and dementia in individuals with PD. Overall, the results indicate that the CDR is a useful tool for identifying MCI and dementia in patients with PD when the cut-off scores are adjusted. In this respect, it is important to highlight that the CDR is a brief screening tool and it is not adequate for assessing all cognitive and functional domains, and a comprehensive neuropsychological evaluation may be necessary for differential diagnosis. The present findings on the CDR compare favorably to another study,15 which examined sensitivity and specificity values of the MDRS-2 for dementia (sensitivity = 1.0; sensitivity = 1.0) and for MCI (sensitivity = 0.86; sensitivity = 0.54). It should be noted that the CDR does not measure cognitive impairment in the same way as the MDRS-2. The MDRS-2 objectively measures cognitive functioning through testing, and the CDR uses a diagnostic interview to rate functional impairment. Future studies may examine the concurrent validity of the MDRS-2 and CDR to measure cognitive changes in PD. Age is a significant risk factor for dementia in PD.26 In this study, e patients with PDD were significantly older than patients with PD-MCI and those with normal cognition. There was no significant difference in age between the PD-MCI group and the normal cognition group.

Although every attempt was made to exclude cases with mixed etiology, a limitation of this study is the lack of neuropathological confirmation, given that patients with PD may have additional histopathological markers of changes consistent with comorbid neurodegenerative conditions, such as AD.13,27 Therefore, generalization of these findings to individuals with mixed-etiology dementias should be made with caution. A major limitation of this study is that it is unknown whether all participants had a caregiver to interview for the CDR or whether the patient’s diagnosis was blind to the individual administering the CDR. Whereas it is a strength that the participants were confirmed to have PD by a physician, a major limitation is that it is unknown how many participants were diagnosed using recommended diagnostic procedures from the MDS Task Force. Participants in the NACC database have agreed to participate in longitudinal research studies at academic medical centers and may under-represent the full range of individuals in the community who meet criteria for dementia.28 Weintraub et al.24 noted that one limitation of the NACC data set is that the participants tend to be highly educated; therefore, the data may not apply to the general population. In the present study, the mean level of education was equivalent to a bachelor’s degree, and it is unknown to what extent education may protect patients with PD from the early effects of cognitive decline.29 In the present study, 93.9% of the participants were Caucasian; therefore, the results may not accurately apply to individuals from different ethnic backgrounds; this is a major limitation of the study. Several barriers exist in the recruitment of culturally diverse older adults for participation in research, including the sampling approach, lack of culturally relevant incentives for participation, history of discrimination in health care settings, mistrust of involvement in research owing to historical events (e.g., Tuskegee syphilis experiments), and lack of community involvement by institutions conducting research.30 The data utilized in this study were archival, and therefore it was impossible to address such recruiting issues in this study. However, it would be important for future researchers utilizing community samples of patients with PD to develop culturally relevant methods of recruiting participants from diverse backgrounds in order to reflect the general population of patients with PD.

Strengths One major strength of the present study is the large sample size that is similar, in many ways, to the general population of individuals with PD. Another strength is the quality of NACC data. All participants in this study were diagnosed with PD by a

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Summary

8. Goldman JG, Litvan I. Mild cognitive impairment in Parkinson’s disease. Minerva Med 2011;102:441–459.

The present study supports the use of the CDR in patients with PD when the cut-off scores are adjusted. This provides researchers and clinicians a tool for measuring the various stages of cognitive impairment in individuals with PD. Future research should focus on replicating this study in community samples.

9. Matteau E, Dupre N, Langlois M, Provencher P, Simard M. Clinical validity of the Mattis Dementia Rating Scale 2 in Parkinson disease with MCI and dementia. J Geriatr Psychiatry Neurol 2012;25:100–106.

Author Roles (1) Research Project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript Preparation: A. Writing of the First Draft, B. Review and Critique. K.A.W.-C.: 1A, 1B, 1C, 2A, 2B, 3A B.J.S.: 1B, 1C, 3B

Acknowledgments Data used in the preparation of this article were obtained from the NACC database. The NACC database is supported by NIA Grant AG16976. The investigators within the NACC did not participate in the design, analysis, or writing of the manuscript. The authors of this article report no financial or other conflict of interest relevant to the subject of this article.

10. Aarsland D, Bronnick K, Williams-Gray C, et al. Mild cognitive impairment in Parkinson disease: a multicenter pooled analysis. Neurology 2010;75:1062–1069. 11. Harvey PD, Ferris SH, Cummings JL, et al. Evaluation of dementia rating scales in Parkinson’s disease dementia. Am J Alzheimers Dis Other Demen 2010;25:142–148. 12. Tr€ oster A. Neuropsychological characteristics of dementia with Lewy bodies and Parkinson’s disease with dementia: differentiation, early detection, and implications for “Mild Cognitive Impairment” and biomarkers. Neuropsychol Rev 2008;18:103–119. 13. Mahieux F, Fenelon G, Flahault A, Manifacier M, Michelet D, Boller F. Neuropsychological prediction of dementia in Parkinson’s disease. J Neurol Neurosurg Psychiatry 1998;64:178–183. 14. Anderson KE. Dementia in Parkinson’s disease. Curr Treat Options Neurol 2004;6:201–207. 15. Rajput AH, Rozdilsky B, Rajput A. Alzheimer’s disease and idiopathic Parkinson’s disease coexistence. J Geriatr Psychiatry Neurol 1993;6:170– 176. 16. Hughes CP, Berg L, Danziger WL, Cobin LA, Martin RL. A new scale for the staging of dementia. Br J Psychiatry 1982;140:566–572. 17. Morris JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 1993;43:2412–2414. 18. O’Bryant SE, Lacritz LH, Hall J, et al. Validation of the new interpretive guidelines for the Clinical Dementia Rating Scale sum of boxes score in the National Alzheimer’s Coordinating Center Database. Arch Neurol 2010;67:746–749. 19. Galvin JE. Cognitive change in Parkinson disease. Alzheimer Dis Assoc Disord 2006;20:302–310.

Disclosures Funding Sources and Conflicts of Interest: The authors report no sources of funding and no conflicts of interest. Financial Disclosures for previous 12 months: The authors declare that there are disclosures to report.

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20. Kovari E, Gold G, Herrmann FR. Lewy body densities in the entorhinal and anterior cingulate cortex predict cognitive deficits in Parkinson’s disease. Acta Neuropathol 2003;106:83–88. 21. Dubois B, Burn D, Goetz C, et al. Diagnostic procedures for Parkinson’s disease dementia: recommendations from the Movement Disorder Society Task Force. Mov Disord 2007;22:83–88. 22. Beekly DL, Ramos EM, Lee WW, et al. The National Alzheimer’s Coordinating Center (NACC) database. The uniform data set. Alzheimer Dis Assoc Disord 2007;21:249–258. 23. Beekly DL, Ramos EM, van Bell G, et al. The National Alzheimer’s Coordinating Center (NACC) database: an Alzheimer disease database. Alzheimer Dis Assoc Disord 2004;18:270–277.

2. Marti MJ, Tolosa E, de la Cerda A. Dementia in Parkinson’s disease. J Neurol 2007;254:41–48.

24. Weintraub S, Salmon D, Mercaldo N, et al. The Alzheimer’s Disease Centers’ uniform data set (UDS): the neuropsychologic test battery. Alzheimer Dis Assoc Disord 2009;23:91–101.

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4. Emre M. General features, mode of onset and course of dementia in Parkinson’s disease. In: Emre M, ed. Cognitive Impairment and Dementia in Parkinson’s Disease. New York, NY: Oxford University Press; 2005:15–25.

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27. Braak H, Rub U, Steur J, Del Tredici K, de Vos RA. Cognitive status correlates with neuropathologic stage in Parkinson disease. Neurology 2005;64:1404–1410. 28. Morris JC, Weitraub S, Chui HC, et al. The uniform data set (UDS): clinical and cognitive variables and descriptive data from Alzheimer disease centers. Alzheimer Dis Assoc Disord 2006;20:210–216. 29. Glatt SL, Hubble JP, Lyons K, et al. Risk factors for dementia in Parkinson’s disease: effect of education. Neuroepidemiology 1996;15:20–25. 30. Feldman S, Radermacher H, Browning C, Bird S, Thomas S. Challenges of recruitment and retention of older people from culturally diverse communities in research. Aging Soc 2008;28:473–493.

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DEVELOPMENT OF CLINICAL DEMENTIA RATING SCALE CUTOFF SCORES FOR PATIENTS WITH PARKINSON'S DISEASE.

The purpose of this study was to explore validity of the Clinical Dementia Rating Scale in measuring cognitive impairment among individuals with Parki...
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