RESEARCH ARTICLE
Mild cognitive impairment in Parkinson’s disease and its progression onto dementia: a 16-year outcome evaluation of the Denbighshire cohort Peter Hobson and Jolyon Meara Academic Unit, Glan Clwyd Hospital, Betsi Cadwaladr University Health Board, BodelwyddanLL18 5UJ, UK Correspondence to: Dr P. Hobson, Academic Unit, Glan Clwyd Hospital, Betsi Cadwaladr University Health Board, Sarn Lane, Bodelwyddan, LL18 5UJ, UK. E-mail: [email protected]
Mild cognitive impairment in Parkinson’s disease (PD-MCI) has been suggested to be a predictor for the development of PD dementia (PDD). This study explored the incidence and possible neuropsychological domain differences between PD patients with PD-MCI and without cognitive impairment (normal cognitive function with PD), on the basis of the Movement Disorders Task Force Guidelines for PD-MCI. Methods: At baseline (T1), 4 years (T2) and 6 years (T3), 166 patients with PD were administered global neuropsychological assessments. At 16 years, case note and neuropsychological assessment review was employed to calculate the number of patients who had progressed to PDD. Results: At baseline, 68 patients were classified as normal cognitive function with PD, 18 with PD-MCI and 80 with PDD. At T2, 12 of the PD-MCI cohort at T1 had progressed to PDD, and there were 15 incident cases of PD-MCI. At T3, nine PD-MCI cases at T2 had progressed to PDD. There were 10 incident cases of PD-MCI at T3. The incidence of progression from PD-MCI to PDD was 98.0 per 1000 person-years, with an annual conversion rate to PDD of 11%. Neuropsychological predictors for conversion from PD-MCI to PDD were semantic language, praxis (figure drawing/copying) and visuospatial deficits. At 16 years, 91% of the PD-MCI cohort had progressed to PDD. Conclusions: Mild cognitive impairment in Parkinson’s disease is an important predictor for the progression to PDD. This investigation also confirmed that if PD patients live long enough, they will develop cognitive impairment or dementia. Early detection of cognitive impairment in these individuals is possible with existing standardised global cognitive assessments, which include semantic language assessment. Copyright # 2015 John Wiley & Sons, Ltd. Objective:
Key words: Parkinson’s disease; mild cognitive impairment; Parkinson’s disease dementia; neuropsychological predictors History: Received 30 July 2014; Accepted 24 December 2014; Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/gps.4261
Introduction Patients with Parkinson’s disease (PD) are at greater risk of developing dementia, with a prevalence of around 40%, and an incidence estimated to be fivefold to sixfold that of the general population (Hobson and Meara, 2004; Aarsland et al., 2001). In general populations, mild cognitive impairment (MCI) has been proposed as a transitional stage of cognitive decline that does not meet explicit criteria for dementia (Petersen Copyright # 2015 John Wiley & Sons, Ltd.
et al., 1999; 2004; Winblad et al., 2004; Morris and Cummings, 2005; Petersen and Knopman, 2006). Longitudinal follow-up of MCI cohorts report conversion rates to dementia of around 12% per year (Luck et al., 2010; Brodart et al., 2013). In the PD literature, MCI has been suggested as a prodromal stage of PD dementia (PDD) (Caviness et al., 2007; Aarsland et al., 2009; Yarnall et al., 2013). As a construct in PD, MCI and its association with progression onto PD dementia has been reported in previous Int J Geriatr Psychiatry 2015
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investigations (Jacobs et al., 1995; Mahieux et al., 1998; Janvin et al., 2005; Hobson and Meara, 2004). However, until recently, there has been a lack of consensus or an agreed set of shared diagnostic guidelines for PD-MCI. The Movement Disorder Society (MDS) Task Force addressed this issue by drawing up diagnostic criteria for PD-MCI (Litvan et al., 2012). In view of this, there have been few prevalence and incidence studies to which these criteria have been applied (Broeders et al., 2013; Pedersen et al., 2013). In our earlier risk and incidence of investigation, we reported cases of MCI (Hobson and Meara. 2004). However, because at the time there was not an internationally agreed set of guidelines for PD-MCI, its interpretation as a risk factor for the progression to dementia was not fully explored. In the present study, we reanalysed our existing Denbighshire PD cohort data retrospectively and prospectively to explore the prevalence and incidence and possible neuropsychological domain differences between patients with and without MCI (and their subtypes), on the basis of the MDS Task Force Guidelines over a 16-year period.
Neuropsychological assessment
Methods
Mild cognitive impairment in Parkinson’s disease diagnosis
This study was approved by the North Wales (Central) Research and Ethics Committee. All subjects provided written and informed consent. The assembly of the PD cohort has been described elsewhere (Hobson and Meara, 2004). At baseline, 166 PD patients who fulfilled the PD Queen square criteria for probable PD were assessed with the Cambridge Cognitive Examination (CAMCOG) neuropsychological assessment (Gibb and Lees, 1988; Roth et al., 1986). Demographic details that include age, sex, physical function, marital status, social class, total years in education, place of residence and past medical history were recorded. In addition, functional activities of daily living, health-related quality of life and disease progression were measured with the EuroQoL five dimensions questionnaire, PD Activities of Living Scale, Hoehn and Yahr Scale and Unified PD Rating Scale motor section (Williams, 1990; Hobson et al., 2001; Hoehn and Yahr 1967; Fahn et al., 1987). Mood was measured with the 15-item Geriatric Depression Scale (Sheikh and Yesavage, 1986). Patients were assessed at baseline (T1), 4 years (T2) and 6 years (T3). Follow-up outcomes at 16 years were based upon a combination of case note review and neuropsychological assessment where available. Copyright # 2015 John Wiley & Sons, Ltd.
All patients were assessed with the CAMCOG cognitive screen, which comprises eight domains of cognitive function, orientation, language, memory, attention, praxis, calculation, abstract thinking and perception. The domains of the CAMCOG also comprise the following subscales: (1) (2) (3) (4) (5) (6) (7)
Orientation: time and place Language: comprehension and expression Memory: remote and recent Attention and calculation Praxis: copying, drawing and command actions Abstraction Perception: tactile and visual.
In addition, because the mini-mental state examination forms part of the CAMCOG, its score could be calculated independently (Folstein et al., 1975). Executive function was assessed with the clock drawing test and the summation of the abstract and fluency sections (maximum score of 14 points) of the CAMCOG (Sunderland et al., 1989).
The application of the MDS diagnostic criteria (Litvan et al., 2012) for PD-MCI requires patients to have the following: (1) Clinically established diagnosis of PD (2) Gradual cognitive decline reported by patients, informants or clinicians involved in their care (3) Cognitive impairment evident upon neuropsychological testing (4) Cognitive impairment that does not significantly impinge on the patient’s functional independence. We employed cut-off values falling 1.5 standard deviations (SDs) or more below normative population means in at least two total scores from different cognitive domains, to establish a diagnosis of PD-MCI. Because we employed a single global neuropsychological test in the present study, level 1 guidelines were used. However, we were able to classify patients into either single-domain MCI, on the basis of abnormalities in two sections within a single cognitive domain (analysis of the subscales of the CAMCOG), or for multiple-domain MCI abnormalities, where two or more cognitive domain deficits were present. Int J Geriatr Psychiatry 2015
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Parkinson’s disease dementia diagnosis The application of PDD criteria at level 1 was employed (Dubois et al., 2007). This included case note review, informant interviews and review of neuropsychological assessment, taking account of age and educational level. We also controlled for the confounding effects of major depression, delirium and other neuropsychiatric disorders that may give a false positive diagnosis for dementia. R. J. M. and P. H. independently applied the PDD and MDS PD-MCI criteria on the basis of the review of each patient’s clinical and neuropsychological outcomes. Standard cut-points were applied for all assessments.
Statistical analysis The incidence rate for cases of dementia (assumed to be the midpoint of the interval between assessments) was calculated by division of new cases by the total number of person-years at risk. The relative risks and 95% confidence intervals (CIs) were calculated by the ratio of patients considered as cases and noncases. The demographic characteristics of the cohort and CAMCOG neuropsychological assessments were summarised with descriptive statistics. All of the data presented here as means ± SDs. Bivariate analysis was used to test for the strength of linear association between variables along with the Wilcoxon–Mann–Whitney and multiple linear
regression when appropriate. In non-normal distributions the Kruskal–Wallis H median test was employed to assess group differences. Significant associations with PD-MCI status and those who converted to PDD were entered into a logistic regression model, employing a backward stepwise method of entry. SPSS version 18 was employed for the analysis in the study, and p < 0.05 was considered to be statistically significant.
Results At baseline (T1), 68/166 patients had a classification of normal cognitive function with PD (PD-NCI), 18 (21%) patients fulfilled criteria for PD-MCI and the remaining 80 patients fulfilled criteria for PDD (Table 1 and Figure 1). Comparisons between the PD-NCI and PD-MCI cohorts did not reveal any significant differences in their baseline demographic or clinical indices (p < 0.05). Comparing the PDD with the PD-NCI group revealed that the PDD patients were older, more likely to reside in institutional care, reported more hallucinations, had worse motor function, were on a lower antiparkinsonian drug treatment regime and had poorer self reported ADL and healthrelated quality of life (p < 0.05, Table 1). At baseline compared with the PD-NCI patients, those with PDD and PD-MCI had poorer neuropsychological assessment performance in the cognitive domains of orientation, language, praxis, memory, abstraction,
Table 1 Baseline (T1) demographic and clinical details (n = 166)
Age Gender (female, %) Age of onset Disease duration UPDRS H&Y PADL GDS Institutional care Hallucinations Dyskinesia EQ-5D EQ-5D VAS (%)
PD-NCI n = 68
PD-MCI n = 18
71.3 (8.6) 40 64.9 (11.0) 6.5 (5.2) 21.0 (10.3) 2.7 (0.64) 2.6 (0.98) 4.8 (2.7) 4/68 8/68 9/68 0.55 (0.33)a 63 (14.2)a
74.8 (7.9) 33 68.5 (10.5) 6.7 (4.7) 23.9 (10.2) 2.9 (0.64) 2.8 (0.73) 4.3 (2.6) 1/18 4/18 4/18 0.44 (0.31)b 55 (14.3)b
PDD n = 80 77.6 (7.2)2 52 68.3 (10.8) 9.0 (8.1) 33.4 (10.6)1 3.2 (0.73)2 3.5 (1.0)1 6.1 (3.0)1 32/801 30/802 16/80 0.55 (0.33)c 46 (15.6)c
PD-NCI, normal cognitive function with Parkinson’s disease; PD-MCI, mild cognitive impairment in Parkinson’s disease; PDD, Parkinson’s disease dementia; UPDRS, Unified Parkinson’s Disease Rating Scale; H&Y, Hoehn and Yahr; PADL, Parkinson’s Disease Activities of Living Scale; GDS, Geriatric Depression Scale; EQ-5D, EuroQoL five dimensions questionnaire; VAS, visual analogue scale. 1 p < 0.05 PD-MCI patients compared with PDD patients. 2 p < 0.05 PD-NCI patients compared with PDD patients. a n = 58; bn = 16; cn = 48.
Copyright # 2015 John Wiley & Sons, Ltd.
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Figure 1 Flowchart summarising the outcome and follow-up assessments of the total cohort. PD, Parkinson’s disease; PD-NCI, normal cognitive function with PD; PD-MCI, mild cognitive function with PD; PDD, PD dementia.
perception and executive function (p < 0.05, Table 2). However, no differences were observed between the PD-NCI and PD-MCI cohorts in their age, sex, motor function, mood, duration or onset of symptoms (p > 0.05). Review at approximately 4 years (T2; mean 4.36, SD 0.26) revealed that 53 patients had died (22 PD-NCI, 4 PD-MCI and 27 PDD). Five were lost to follow-up, three had their diagnosis reclassified as not probable PD and one withdrew consent, leaving a cohort of 104 (37 PD-NCI, 14 PD-MCI and 53 PDD) available for reassessment at T2 (Figure 1). From T1 to T2, six incident cases of PDD were observed in the PD-NCI group, and 15 cases of PD-MCI. Reassessment of the T1 PD-MCI cohort (n = 18) at T2 revealed that 12 had progressed to PDD, 2 remained as MCI cases and the remaining 4 patients died between assessments. Copyright # 2015 John Wiley & Sons, Ltd.
The neuropsychological assessment performance of the PD-MCI patients who progressed to PDD declined significantly in the cognitive domains of orientation, language, memory and perception (p < 0.05) compared with the PD-NCI cohort. No patient with a PD-MCI diagnosis had reverted to PD-NCI at T2. Six years postbaseline (T3; mean 6.25, SD 0.46), 57/157 (36%) of the cohort were available for reassessment (Figure 1). Between T2 and T3, 47 patients died (2 PD-NCI, 3 PD-MCI and 42 PDD). Within the PD-NCI cohort, 10 incident cases of PD-MCI were observed at T3 and 2 had further progressed to PDD. Review of the T2 incident PD-MCI cohort (n = 15) found that nine had progressed to a PDD and four remained as PD-MCI cases, with the remaining case reverting to a PD-NCI. From baseline to T3, 21/33 (63.6%) of the Int J Geriatr Psychiatry 2015
Mild cognitive impairment in Parkinson’s disease Table 2 Baseline (T1) mean (standard deviation) neuropsychological assessments for the total cohort (n = 166)
Orientation Attention Language Comprehension Expression Total score Memory Remote Recent Learning Total score Praxis Calculation Abstraction Perception CAMCOG total MMSE total Executive function Clock drawing test
PD-NCI
PD-MCI
PDD
9.7 (0.6) 5.9 (1.5)
9.3 (0.9)* 5.4 (1.6)1
7.8 (2.3)2 3.4 (2.4)2
8.5 (0.6) 18.3 (1.5) 26.8 (1.8)
8.0 (1.0)1 16.5 (2.8)1 24.5 (3.1)1
7.2 (1.4)2 14.1 (2.7)2 21.2 (3.6)2
5.4 (0.9) 3.7 (0.3) 15.0 (1.9) 25.4 (2.4) 10.2 (1.5) 1.9 (0.3) 5.6 (1.7) 10.0 (1.3) 92.1 (5.4) 27.2 (1.9) 9.7 (2.4) 7.3 (0.7)
5.1 (0.9)* 3.4 (0.6)1 12.6 (2.1)1 24.5 (3.1)1 7.8 (2.8)1 1.5 (0.6)1 4.9 (1.7)* 7.2 (2.6)1 82.1 (4.0)1 25.7 (2.3)1 7.8 (2.3)1 6.7 (2.0)*
3.9 (1.8)2 12.6 (2.1)2 9.8 (3.3)2 16.3 (4.5)2 6.5 (2.6)2 1.2 (0.8)* 2.4 (1.9)2 6.7 (1.9)* 65.7 (13.5)2 19.7 (4.9)2 5.3 (2.7)2 4.7 (2.7)2
PD-NCI, normal cognitive function with Parkinson’s disease; PDMCI, mild cognitive impairment in Parkinson’s disease; PDD, Parkinson’s disease dementia; CAMCOG, Cambridge Cognitive Examination; PMMSE, mini-mental state examination. 1 p < 0.05 PD-NCI patients compared with PD-MCI patients. 2 p < 0.05 PD-MCI patients and PDD patients. 3 p < 0.001 PD-NCI patients and PDD patients. *Non significant (p < 0.05).
incident PD-MCI cohort progressed to PDD. The average for progression from PD-MCI to PDD per year was 10.6%. The overall incidence rate for progression to dementia per 1000 person-years of observation amongst in the PD-MCI and PD-NCI cohorts was 113.31 (95% CI, 77.9–159.12). In the PD-MCI cohort, it was 98.1 (95% CI, 64.1–143.6), and in the PD-NCI cohort, it was 31.5 (95% CI, 12.7–64.9) per 1000 person-years of observation. The overall relative risk for conversion to PDD in the PD-MCI group from T1–T3 was 4.2 (95% CI, 2.1–17.3), compared with 1.76 (95% CI, 1.1–2.9), in the PD-NCI cohort. Bivariate analysis of the PD-MCI cohort’s demographic and clinical indices revealed significant associations with increasing age (0.37, p < 0.001), worsening motor function (0.47, p < 0.001), hallucinations (0.28, p < 0.001) and residing in institutional care (0.38, p < 0.001). The median change in the decline of CAMCOG scores for the PD-MCI cohort from T1 to T3 was 2 points per year (range +0.33 to 8.3 points). The PD-MCI cohort had a significantly greater decline in CAMCOG scores from T1 to T2 (H(1) = 8.52, p < 0.01) and T2 to T3 (H(1) = 6.04, p < 0.01) than the PD-NCI cohort. Cognitive decline in the PD-MCI cohort (bivariate analysis) was associated lower scores in the CAMCOG domains of Copyright # 2015 John Wiley & Sons, Ltd.
orientation 0.23( p < 0.04), language 0.30 (p < 0.01), praxis 0.40 (p < 0.001), memory 0.37 (p < 0.001) and perception 0.33 (p < 0.002). These variables were entered into a multivariate analysis model controlling for age, which revealed that cognitive decline in the PD-MCI group was predicted by poorer semantic (expressive) language function, praxis (copying and drawing), memory (recent) and perception (Table 3). This multivariate model was repeated for PD-MCI patients progressing to PDD. Semantic language function, praxis (visuospatial construction) and memory impairment (explicit) were found to be predictive of developing PDD in this cohort (p < 0.01), explaining 77% of the variance. Subtype cognitive profile classification of the total PD-MCI cohort (n = 43) found that 36 (84%) had multidomain cognitive abnormalities and the remainder had single-domain abnormalities. The most frequent impairment in patients with single-domain deficits was in either memory or executive function. The most frequently reported multidomain deficits were a combination of two or more impairments in the domains of memory, language, attention, executive function or perception. Bivariate analysis of these variables found significant associations in the cognitive domain of language function (semantic 0.49, p < 0.002, and comprehension 0.32, p < 0.037). Comparing both cohorts revealed that the multidomain PD-MCI group had significantly more impairments in their language function (U = 34.5, z = 3.1, p < 0.002, r = 0.49). These variables that entered in a multivariate model revealed that the strongest cognitive predictor within the multidomain PD-MCI cohort was impaired semantic language function (ß = 0.392, 95% CI, 0.017–0.122, p < 0.01), explaining around 15% of the variance (r2 = 1.52). The clinical records (157/166) of the total cohort were reviewed at 16 years. In total, 152/157 was deceased at review (Figure 1). Two of the survivors fulfilled criteria for PD-MCI, and the remaining three fulfilled criteria for PDD. Overall, a total of 124/157 (79%) patients in the total cohort had developed deTable 3 Multivariate regression model for neuropsychological predictors for mild cognitive impairment as the dependent variable, 1 F = 19.66, p < 0.0001, R = 0.473 Variable Constant Language expression Memory recent Praxis Perception
ß coefficient 1.76 0.36 0.33 0.28 0.24
p-value 0.0001 0.0001 0.0001 0.003 0.01
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mentia. The PD-MCI cohort survival at the 16-year review revealed that all were deceased. Upon review of the PD-MCI cohort’s clinical records, 39/43 (91%) had progressed to PDD, with four at their time of death remaining as PD-MCI cases. Discussion This investigation employed the MDS diagnostic guidelines for PD-MCI, to establish the prevalence, incidence and risk factors for the development of PDMCI and its progression to PDD in our community cohort. The prevalence of PD-MCI at baseline was around 21%, by four years it was 33% and by six years it was 38%. The incidence of PD-MCI patients converting to PDD was around 98.0 per 1000 person-years greater than 6 years, compared with 31.5 in the PD-NCI cohort. The risk of progression to PDD in the PD-MCI cohort was over four times that of the PD-NCI cohort. Amongst the incident cases of PD-MCI observed over this period, approximately 64% progressed on to PDD. This equates in our cohort to an annual conversion rate (ACR) from PD-MCI to PDD of around 11%. An earlier community-based PD population study at 4 years reported that 62% of their PD-MCI cohort progressed to PDD, equating to an ACR of around 15% (Janvin et al., 2006). A PD-MCI population followed for approximately 2 years revealed an overall rate of progression from MCI to PDD of 29%, with an ACR of around 14% (Lee et al., 2014). Longitudinal population studies employing the MDS Task Force guidelines for PD-MCI report prevalence rates between 20% and 50%(Broeders et al., 2013; Pedersen et al., 2013). Broeders and colleagues 5-year investigation reported that greater than 50% of their cohort had developed PD-MCI. They however did not report the person-year incident rates. The ParkWest study (Pedersen et al., 2013) reported incidence rates of progression from PD-MCI to PDD of 99 per 1000 person-years, which is comparable with the incidence rate we reported of 98 per 1000 person-years. The proportion of patients developing PD-MCI was not reported at their 3-year follow-up. In the present study by 6 years, 50% of our cohort had developed PD-MCI. However, we must be cautious with the interpretation of the results because of methodological differences between this and previous studies including the differing periods of observation. We examined the records of patients with established PD, which is in contrast to the outcomes reported in prevalence studies of Copyright # 2015 John Wiley & Sons, Ltd.
newly diagnosed patients. The range and type of neuropsychological assessments employed in previous investigations could have been more sensitive in detecting more subtle cognitive deficits. The global cognitive assessment we employed may have been less sensitive in the detection of subtle cognitive deficits, than those employed in previous studies. Despite these differences, the ACR we report in present study of around 11% is similar to these studies and is comparable with larger general population investigations. In general population studies, MCI cases are often reported as remaining stable, or reverting to normal cognition. Reversion rates of around 30–40% from MCI to normal cognitive function suggest MCI is not a stable diagnosis (Mitchell and Shiri-Feshki, 2009). PD investigations report variable reversion rates. The ParkWest study reported around 25% of PD-MCI cases reverting to normal cognition over a 3-year period. Broeders et al. (2013) reported less than a 10% reversal of PD-MCI to normal cognition at 5 years. In the present study, only one patient reversed to normal cognition and by 12 years (patient’s death); they had progressed to PDD. The disparities between studies are likely to be a reflection of methodological differences. What is unknown is if MCI patients who revert to a NCI diagnosis that are followed long enough will eventually progress back to MCI, or onto dementia. Our follow-up period allowed us to observe the evolution of cognitive impairment over its full spectrum. By 16 years, greater than 90% had progressed to PDD, and we believe if previous studies had followed their patients for a similar period, they may observe similar conversion rates. The present study and the Sydney Multicenter Study (Hely et al., 2008) confirm that nearly all PD patients if they live long enough will develop significant cognitive impairment or dementia. The neuropsychological predictors for the progression from PD-MCI to PDD that we found were poorer semantic fluency, praxis (drawing/copying figures), memory (explicit) and perception (visuospatial). Earlier clinical studies have reported similar predictors for conversion from normal cognition to dementia in PD cohorts (Jacobs et al., 1995; Mahieux et al., 1998). More recently, Janvin et al. (2006) reported impairments in memory, executive function and visuospatial function in PD-MCI patients. The CamPalGN cohort study reported impairments in semantic fluency and copying drawings (intersecting pentagons) as independent predictors for the progression to PDD (Williams-Gray et al., 2007; 2009). Aarsland et al. (2010) multicenter study reported Int J Geriatr Psychiatry 2015
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deficits in memory, visuospatial, attention and executive function. Broeders et al. (2013) reported that PD-MCI converters to PDD had greater verbal memory and attention deficits. Structural changes in the brains of PD-MCI patients have been explored (Lee et al., 2014; Mak et al., 2014). These investigations have reported atrophy in the grey matter structures of the brain in PD-MCI patients with poorer neuropsychological test performance in executive, attention, memory, language function and visual recognition. These studies taken together would suggest that predictors for conversion to PDD may involve one or more abnormalities in the structures of the frontal, temporal or parietal lobes, and further longitudinal investigations are needed to establish their true relationship. In the current study, the most frequently reported multiple-domain cognitive impairments were found in the domains of memory, executive, language and visuospatial function. Dalrymple-Alford et al. (2011) reported 47% of their MCI sample had multidomain amnesic or nonamnesic impairments. Another clinical study reported that the majority of its patients also had multidomain PD-MCI, whereas the pooled investigation by Aarsland et al. (2010) reported just greater than 6% of patients with multiple-domain PD-MCI and around 20% with single-domain MCI. The dissimilarities reported by the investigation of Aarsland et al. (2010) may be due to differing application of MCI criteria and the cross sectional pooled analysis employed to determine PD-MCI classification. However, the variability between studies may reflect that the pattern of cognitive function is heterogeneous in PD-MCI. Previous studies have not, to our knowledge, explored if there are neuropsychological predictors within these subtypes. Our analysis revealed impaired semantic language function (naming) as the strongest predictor for the development of multidomain MCI. We believe that this is an important finding because early deficits in language function in PD in this and previous studies suggest that they are likely to be prognostic predictors for the development of significant cognitive impairment in PD. We would propose that initial global cognitive screening with additional validated assessments of semantic fluency and figure construction will prove to be valuable aids in the early detection of neuropsychological deficits in patients at high risk of developing dementia. This study advances our understanding of the progression of PD-MCI to PDD. The clinical importance of this is the possible earlier detection of this at risk group of patients, where it will allow new and more appropriate interventions to be piloted, or introduced. Copyright # 2015 John Wiley & Sons, Ltd.
Acknowledgements We would like to thank all of the patients and their families who supported us with this study. This study was funded by Betsi Cadwaladr University Health Board. Author contributions P. H. and R. J. M. were involved in all aspects of the research project’s conception, organisation and execution. Statistical analysis was designed and executed by P. H. Review and critique was completed by R. J. M. Manuscript preparation, writing of drafts and review and critique were completed by both authors Conflict of interest None declared.
Key points
• • • •
We report a 16-year longitudinal follow-up of a community cohort of people with Parkinson’s disease. We assessed the cognitive function of the cohort at four periods. Progression from normal, cognitive function, to mild cognitive impairment to progression to dementia was reported. Neuropsychological predictors for the progression from mild cognitive impairment to dementia were reported.
References Aarsland D, Andersen K, Larsen JP, et al. 2001. Risk of dementia in Parkinson’s disease. a community-based, prospective study. Neurology 56: 730–736. Aarsland D, BrØnnick K, Larsen JP, et al. 2009. Cognitive impairment in incident untreated Parkinson’s disease: the Norwegian ParkWest study. Neurology 72:1121–6. Aarsland D, Bronnick K, Williams-Gray CH, et al., 2010. Mild cognitive impairment in Parkinson’s disease: a multicenter pooled analysis. Neurology. 2010;75:1062–1069 Brodart H, Heffernan M, Kochan NA, et al. 2013 Mild cognitive impairment in a community sample: the Sydney Memory and Ageing Study. Alzheimer’s and Dementia 9: 310–317. Broeders M, de Bie RMA, Velseboer DC, et al. 2013. Evolution of mild cognitive impairment in Parkinson’s disease. Neurology 81: 346–352. Caviness JN, Driver-Dunckley, Connor DJ, et al. 2007. Defining mild cognitive impairment in Parkinson’s disease. Mov Disord 22:1272–7. Dalrymple-Alford JC, Livingston L, MacAskill MR, et al. 2011. Characterizing mild cognitive impairment in Parkinson’s disease. Mov Disord 26: 629–635. Dubois B, Burn D, Goetz C, et al. 2007. Diagnostic procedures for Parkinson’s disease dementia: recommendations from the Movement Disorder Society Task Force. Mov Disord 22: 2314–2324.
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P. Hobson and J. Meara Fahn S, Elton RL, Committee MotUD. 1987. Unified Parkinson’s Disease Rating Scale. In Recent Developments in Parkinson’s Disease: Fahn S, Marsden CD, Calne DB, et al. (eds). Macmillan Health Care Information: Florham Park; 153–163. Folstein MF, Folstein SE, McHugh PR. 1975. ‘Mini-Mental State’. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12: 89–198. Gibb WRG, Lees AJ. 1988. The relevance of the Lewy body to the pathogenesis of idiopathic Parkinson’s disease. J of Neurol Neurosurg & Psych 51: 745–752. Hely MA, Reid WGJ, Adena MA, et al. 2008. The Sydney Multicenter Study of Parkinson’s disease: the inevitability of dementia at 20 years. Mov Disord 26: 837–844. Hobson JP, Edwards N, Meara RJ. 2001. The Parkinson’s Disease Activities of Daily Living Scale: a new simple and brief subjective measure of disability in Parkinson’s disease. Clin Rehab 15: 241–246. Hobson JP, Meara RJ. 2004. The risk and incidence of dementia in a cohort of older subjects with Parkinson’s disease in the UK. Mov Disord 19: 1043–1049. Hoehn M, Yahr MD. 1967. Parkinsonism: onset, progression, and mortality. Neurology 17:427–442. Jacobs DM, Marder K, Cote LJ, et al. 1995. Neuropsychological characteristics of preclinical dementia in Parkinson’s disease. Neurology 45:1691–1696. Janvin CC, Aarsland D, Larsen JP. 2005. Cognitive predictors of dementia in Parkinson’s disease: a community-based, 4-year longitudinal study. J of Geriat Psychiat and Neurol 18:149–154. Janvin CC, Larsen JP, Aarsland D, Hugdah l. 2006. Subtypes of mild cognitive impairment in Parkinson’s disease: progression to dementia. Mov Disord 21:1343–1349. Lee JE, Cho KH, Song SK, et al. 2014. Exploratory analysis of neuropsychological and neuroanatomical correlates of progressive mild cognitive impairment in Parkinson’s disease. J Neurol Neurosurg Psychiatry 85:7–16. Litvan I, Goldman JG, Tröster AI, et al. 2012. Diagnostic criteria for mild cognitive impairment in Parkinson’s disease: Movement Disorder Society Task Force guidelines. Mov Disord 27: 349–356. Luck T, Riedel-Heller SG, Luppa M, et al. 2010. Risk factors for incident mild cognitive impairment—results from the German Study on Ageing, Cognition and Dementia in primary care patients (AgeCoDe). Acta Psychiatr Scand 121:260–272. Mahieux F, Fenelon Tang MX, et al. 1998. Memory and executive function impairment predict dementia in Parkinson’s disease. J Neurol Neurosurg Psychiatry 64:178–183.
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Mak E, Zhou J, Tan LSC, et al. 2014. Cognitive deficits in mild Parkinson’s disease are associated with distinct areas of grey matter atrophy. J Neurol Neurosurg Psychiatry 85:576–580. Mitchell AJ, Shiri-Feshki M. 2009. Rate of progression of mild cognitive impairment to dementia—meta-analysis of 41 robust inception cohort studies. Acta Psychiatr Scand 119:252–265. Morris JC, Cummings JC. 2005. Mild cognitive impairment (MCI) represents early-stage Alzheimer’s disease. J Alzheimer’s disease 7:235–239. Pedersen FK, Larsen JP, Tysnes OB, et al. 2013. Prognosis of mild cognitive impairment in early Parkinson disease. JAMA Neurol 70:580–586. Petersen RC, Smith GE, Waring SC, et al. 1999. Mild cognitive impairment: clinical characterization and outcome. Arch Neurol 56:303–308. Petersen RC. 2004. Mild cognitive impairment as a diagnostic entity. J Intern Med 256:183–94. Petersen RC, Knopman DS. 2006. MCI is a clinically useful concept. Int Psychogeriatr 18: 394–402. Roth M, Tym E, Mountjoy CQ, et al. 1986. CAMDEX: a standardised instrument for the diagnosis of mental disorder in the elderly with special reference to elderly detection of dementia. Br J Psychiatry 149, 698–709. Sheikh JI, Yesavage JA. 1986. Geriatric Depression Scale (GDS): recent evidence and development of a shorter version In Clinical Gerontology: A Guide to Assessment and Intervention, The Hawthorn Press, New York; 165–173. Sunderland T, Hill JL, Mellow AM, et al. 1989. Clock drawing in Alzheimer’s disease: a novel measure of dementia severity. J Am Geriatr Soc 13: 495–502. Williams A. 1990. EuroQol—a new facility for the measurement of health-related quality of life. Health Policy 16:199–208. Williams-Gray CH, Foltynie T, Brayne CE et al. 2007. Evolution of cognitive dysfunction in an incident Parkinson’s disease cohort. Brain 130: 1787–1798. Williams-Gray CH, Evans JR, Goris An, et al. 2009. The distinct cognitive syndromes of Parkinson’s disease: 5 year follow-up of the CamPaIGN cohort. Brain 132: 2958–2969. Winblad BB,Palmer K, Kivipelto M, et al. 2004. Mild cognitive impairment—beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. J Intern Med 256:240–246. Yarnall AJ, Rochester L, Burn DJ. 2013. Mild cognitive impairment in Parkinson’s disease. Age & Ageing 42: 1–10.
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Mild cognitive impairment in Parkinson’s disease and its progression onto dementia: a 16-year outcome evaluation of the Denbighshire cohort Peter Hobson and Jolyon Meara Academic Unit, Glan Clwyd Hospital, Betsi Cadwaladr University Health Board, BodelwyddanLL18 5UJ, UK Correspondence to: Dr P. Hobson, Academic Unit, Glan Clwyd Hospital, Betsi Cadwaladr University Health Board, Sarn Lane, Bodelwyddan, LL18 5UJ, UK. E-mail: [email protected]
Mild cognitive impairment in Parkinson’s disease (PD-MCI) has been suggested to be a predictor for the development of PD dementia (PDD). This study explored the incidence and possible neuropsychological domain differences between PD patients with PD-MCI and without cognitive impairment (normal cognitive function with PD), on the basis of the Movement Disorders Task Force Guidelines for PD-MCI. Methods: At baseline (T1), 4 years (T2) and 6 years (T3), 166 patients with PD were administered global neuropsychological assessments. At 16 years, case note and neuropsychological assessment review was employed to calculate the number of patients who had progressed to PDD. Results: At baseline, 68 patients were classified as normal cognitive function with PD, 18 with PD-MCI and 80 with PDD. At T2, 12 of the PD-MCI cohort at T1 had progressed to PDD, and there were 15 incident cases of PD-MCI. At T3, nine PD-MCI cases at T2 had progressed to PDD. There were 10 incident cases of PD-MCI at T3. The incidence of progression from PD-MCI to PDD was 98.0 per 1000 person-years, with an annual conversion rate to PDD of 11%. Neuropsychological predictors for conversion from PD-MCI to PDD were semantic language, praxis (figure drawing/copying) and visuospatial deficits. At 16 years, 91% of the PD-MCI cohort had progressed to PDD. Conclusions: Mild cognitive impairment in Parkinson’s disease is an important predictor for the progression to PDD. This investigation also confirmed that if PD patients live long enough, they will develop cognitive impairment or dementia. Early detection of cognitive impairment in these individuals is possible with existing standardised global cognitive assessments, which include semantic language assessment. Copyright # 2015 John Wiley & Sons, Ltd. Objective:
Key words: Parkinson’s disease; mild cognitive impairment; Parkinson’s disease dementia; neuropsychological predictors History: Received 30 July 2014; Accepted 24 December 2014; Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/gps.4261
Introduction Patients with Parkinson’s disease (PD) are at greater risk of developing dementia, with a prevalence of around 40%, and an incidence estimated to be fivefold to sixfold that of the general population (Hobson and Meara, 2004; Aarsland et al., 2001). In general populations, mild cognitive impairment (MCI) has been proposed as a transitional stage of cognitive decline that does not meet explicit criteria for dementia (Petersen Copyright # 2015 John Wiley & Sons, Ltd.
et al., 1999; 2004; Winblad et al., 2004; Morris and Cummings, 2005; Petersen and Knopman, 2006). Longitudinal follow-up of MCI cohorts report conversion rates to dementia of around 12% per year (Luck et al., 2010; Brodart et al., 2013). In the PD literature, MCI has been suggested as a prodromal stage of PD dementia (PDD) (Caviness et al., 2007; Aarsland et al., 2009; Yarnall et al., 2013). As a construct in PD, MCI and its association with progression onto PD dementia has been reported in previous Int J Geriatr Psychiatry 2015
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investigations (Jacobs et al., 1995; Mahieux et al., 1998; Janvin et al., 2005; Hobson and Meara, 2004). However, until recently, there has been a lack of consensus or an agreed set of shared diagnostic guidelines for PD-MCI. The Movement Disorder Society (MDS) Task Force addressed this issue by drawing up diagnostic criteria for PD-MCI (Litvan et al., 2012). In view of this, there have been few prevalence and incidence studies to which these criteria have been applied (Broeders et al., 2013; Pedersen et al., 2013). In our earlier risk and incidence of investigation, we reported cases of MCI (Hobson and Meara. 2004). However, because at the time there was not an internationally agreed set of guidelines for PD-MCI, its interpretation as a risk factor for the progression to dementia was not fully explored. In the present study, we reanalysed our existing Denbighshire PD cohort data retrospectively and prospectively to explore the prevalence and incidence and possible neuropsychological domain differences between patients with and without MCI (and their subtypes), on the basis of the MDS Task Force Guidelines over a 16-year period.
Neuropsychological assessment
Methods
Mild cognitive impairment in Parkinson’s disease diagnosis
This study was approved by the North Wales (Central) Research and Ethics Committee. All subjects provided written and informed consent. The assembly of the PD cohort has been described elsewhere (Hobson and Meara, 2004). At baseline, 166 PD patients who fulfilled the PD Queen square criteria for probable PD were assessed with the Cambridge Cognitive Examination (CAMCOG) neuropsychological assessment (Gibb and Lees, 1988; Roth et al., 1986). Demographic details that include age, sex, physical function, marital status, social class, total years in education, place of residence and past medical history were recorded. In addition, functional activities of daily living, health-related quality of life and disease progression were measured with the EuroQoL five dimensions questionnaire, PD Activities of Living Scale, Hoehn and Yahr Scale and Unified PD Rating Scale motor section (Williams, 1990; Hobson et al., 2001; Hoehn and Yahr 1967; Fahn et al., 1987). Mood was measured with the 15-item Geriatric Depression Scale (Sheikh and Yesavage, 1986). Patients were assessed at baseline (T1), 4 years (T2) and 6 years (T3). Follow-up outcomes at 16 years were based upon a combination of case note review and neuropsychological assessment where available. Copyright # 2015 John Wiley & Sons, Ltd.
All patients were assessed with the CAMCOG cognitive screen, which comprises eight domains of cognitive function, orientation, language, memory, attention, praxis, calculation, abstract thinking and perception. The domains of the CAMCOG also comprise the following subscales: (1) (2) (3) (4) (5) (6) (7)
Orientation: time and place Language: comprehension and expression Memory: remote and recent Attention and calculation Praxis: copying, drawing and command actions Abstraction Perception: tactile and visual.
In addition, because the mini-mental state examination forms part of the CAMCOG, its score could be calculated independently (Folstein et al., 1975). Executive function was assessed with the clock drawing test and the summation of the abstract and fluency sections (maximum score of 14 points) of the CAMCOG (Sunderland et al., 1989).
The application of the MDS diagnostic criteria (Litvan et al., 2012) for PD-MCI requires patients to have the following: (1) Clinically established diagnosis of PD (2) Gradual cognitive decline reported by patients, informants or clinicians involved in their care (3) Cognitive impairment evident upon neuropsychological testing (4) Cognitive impairment that does not significantly impinge on the patient’s functional independence. We employed cut-off values falling 1.5 standard deviations (SDs) or more below normative population means in at least two total scores from different cognitive domains, to establish a diagnosis of PD-MCI. Because we employed a single global neuropsychological test in the present study, level 1 guidelines were used. However, we were able to classify patients into either single-domain MCI, on the basis of abnormalities in two sections within a single cognitive domain (analysis of the subscales of the CAMCOG), or for multiple-domain MCI abnormalities, where two or more cognitive domain deficits were present. Int J Geriatr Psychiatry 2015
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Parkinson’s disease dementia diagnosis The application of PDD criteria at level 1 was employed (Dubois et al., 2007). This included case note review, informant interviews and review of neuropsychological assessment, taking account of age and educational level. We also controlled for the confounding effects of major depression, delirium and other neuropsychiatric disorders that may give a false positive diagnosis for dementia. R. J. M. and P. H. independently applied the PDD and MDS PD-MCI criteria on the basis of the review of each patient’s clinical and neuropsychological outcomes. Standard cut-points were applied for all assessments.
Statistical analysis The incidence rate for cases of dementia (assumed to be the midpoint of the interval between assessments) was calculated by division of new cases by the total number of person-years at risk. The relative risks and 95% confidence intervals (CIs) were calculated by the ratio of patients considered as cases and noncases. The demographic characteristics of the cohort and CAMCOG neuropsychological assessments were summarised with descriptive statistics. All of the data presented here as means ± SDs. Bivariate analysis was used to test for the strength of linear association between variables along with the Wilcoxon–Mann–Whitney and multiple linear
regression when appropriate. In non-normal distributions the Kruskal–Wallis H median test was employed to assess group differences. Significant associations with PD-MCI status and those who converted to PDD were entered into a logistic regression model, employing a backward stepwise method of entry. SPSS version 18 was employed for the analysis in the study, and p < 0.05 was considered to be statistically significant.
Results At baseline (T1), 68/166 patients had a classification of normal cognitive function with PD (PD-NCI), 18 (21%) patients fulfilled criteria for PD-MCI and the remaining 80 patients fulfilled criteria for PDD (Table 1 and Figure 1). Comparisons between the PD-NCI and PD-MCI cohorts did not reveal any significant differences in their baseline demographic or clinical indices (p < 0.05). Comparing the PDD with the PD-NCI group revealed that the PDD patients were older, more likely to reside in institutional care, reported more hallucinations, had worse motor function, were on a lower antiparkinsonian drug treatment regime and had poorer self reported ADL and healthrelated quality of life (p < 0.05, Table 1). At baseline compared with the PD-NCI patients, those with PDD and PD-MCI had poorer neuropsychological assessment performance in the cognitive domains of orientation, language, praxis, memory, abstraction,
Table 1 Baseline (T1) demographic and clinical details (n = 166)
Age Gender (female, %) Age of onset Disease duration UPDRS H&Y PADL GDS Institutional care Hallucinations Dyskinesia EQ-5D EQ-5D VAS (%)
PD-NCI n = 68
PD-MCI n = 18
71.3 (8.6) 40 64.9 (11.0) 6.5 (5.2) 21.0 (10.3) 2.7 (0.64) 2.6 (0.98) 4.8 (2.7) 4/68 8/68 9/68 0.55 (0.33)a 63 (14.2)a
74.8 (7.9) 33 68.5 (10.5) 6.7 (4.7) 23.9 (10.2) 2.9 (0.64) 2.8 (0.73) 4.3 (2.6) 1/18 4/18 4/18 0.44 (0.31)b 55 (14.3)b
PDD n = 80 77.6 (7.2)2 52 68.3 (10.8) 9.0 (8.1) 33.4 (10.6)1 3.2 (0.73)2 3.5 (1.0)1 6.1 (3.0)1 32/801 30/802 16/80 0.55 (0.33)c 46 (15.6)c
PD-NCI, normal cognitive function with Parkinson’s disease; PD-MCI, mild cognitive impairment in Parkinson’s disease; PDD, Parkinson’s disease dementia; UPDRS, Unified Parkinson’s Disease Rating Scale; H&Y, Hoehn and Yahr; PADL, Parkinson’s Disease Activities of Living Scale; GDS, Geriatric Depression Scale; EQ-5D, EuroQoL five dimensions questionnaire; VAS, visual analogue scale. 1 p < 0.05 PD-MCI patients compared with PDD patients. 2 p < 0.05 PD-NCI patients compared with PDD patients. a n = 58; bn = 16; cn = 48.
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Figure 1 Flowchart summarising the outcome and follow-up assessments of the total cohort. PD, Parkinson’s disease; PD-NCI, normal cognitive function with PD; PD-MCI, mild cognitive function with PD; PDD, PD dementia.
perception and executive function (p < 0.05, Table 2). However, no differences were observed between the PD-NCI and PD-MCI cohorts in their age, sex, motor function, mood, duration or onset of symptoms (p > 0.05). Review at approximately 4 years (T2; mean 4.36, SD 0.26) revealed that 53 patients had died (22 PD-NCI, 4 PD-MCI and 27 PDD). Five were lost to follow-up, three had their diagnosis reclassified as not probable PD and one withdrew consent, leaving a cohort of 104 (37 PD-NCI, 14 PD-MCI and 53 PDD) available for reassessment at T2 (Figure 1). From T1 to T2, six incident cases of PDD were observed in the PD-NCI group, and 15 cases of PD-MCI. Reassessment of the T1 PD-MCI cohort (n = 18) at T2 revealed that 12 had progressed to PDD, 2 remained as MCI cases and the remaining 4 patients died between assessments. Copyright # 2015 John Wiley & Sons, Ltd.
The neuropsychological assessment performance of the PD-MCI patients who progressed to PDD declined significantly in the cognitive domains of orientation, language, memory and perception (p < 0.05) compared with the PD-NCI cohort. No patient with a PD-MCI diagnosis had reverted to PD-NCI at T2. Six years postbaseline (T3; mean 6.25, SD 0.46), 57/157 (36%) of the cohort were available for reassessment (Figure 1). Between T2 and T3, 47 patients died (2 PD-NCI, 3 PD-MCI and 42 PDD). Within the PD-NCI cohort, 10 incident cases of PD-MCI were observed at T3 and 2 had further progressed to PDD. Review of the T2 incident PD-MCI cohort (n = 15) found that nine had progressed to a PDD and four remained as PD-MCI cases, with the remaining case reverting to a PD-NCI. From baseline to T3, 21/33 (63.6%) of the Int J Geriatr Psychiatry 2015
Mild cognitive impairment in Parkinson’s disease Table 2 Baseline (T1) mean (standard deviation) neuropsychological assessments for the total cohort (n = 166)
Orientation Attention Language Comprehension Expression Total score Memory Remote Recent Learning Total score Praxis Calculation Abstraction Perception CAMCOG total MMSE total Executive function Clock drawing test
PD-NCI
PD-MCI
PDD
9.7 (0.6) 5.9 (1.5)
9.3 (0.9)* 5.4 (1.6)1
7.8 (2.3)2 3.4 (2.4)2
8.5 (0.6) 18.3 (1.5) 26.8 (1.8)
8.0 (1.0)1 16.5 (2.8)1 24.5 (3.1)1
7.2 (1.4)2 14.1 (2.7)2 21.2 (3.6)2
5.4 (0.9) 3.7 (0.3) 15.0 (1.9) 25.4 (2.4) 10.2 (1.5) 1.9 (0.3) 5.6 (1.7) 10.0 (1.3) 92.1 (5.4) 27.2 (1.9) 9.7 (2.4) 7.3 (0.7)
5.1 (0.9)* 3.4 (0.6)1 12.6 (2.1)1 24.5 (3.1)1 7.8 (2.8)1 1.5 (0.6)1 4.9 (1.7)* 7.2 (2.6)1 82.1 (4.0)1 25.7 (2.3)1 7.8 (2.3)1 6.7 (2.0)*
3.9 (1.8)2 12.6 (2.1)2 9.8 (3.3)2 16.3 (4.5)2 6.5 (2.6)2 1.2 (0.8)* 2.4 (1.9)2 6.7 (1.9)* 65.7 (13.5)2 19.7 (4.9)2 5.3 (2.7)2 4.7 (2.7)2
PD-NCI, normal cognitive function with Parkinson’s disease; PDMCI, mild cognitive impairment in Parkinson’s disease; PDD, Parkinson’s disease dementia; CAMCOG, Cambridge Cognitive Examination; PMMSE, mini-mental state examination. 1 p < 0.05 PD-NCI patients compared with PD-MCI patients. 2 p < 0.05 PD-MCI patients and PDD patients. 3 p < 0.001 PD-NCI patients and PDD patients. *Non significant (p < 0.05).
incident PD-MCI cohort progressed to PDD. The average for progression from PD-MCI to PDD per year was 10.6%. The overall incidence rate for progression to dementia per 1000 person-years of observation amongst in the PD-MCI and PD-NCI cohorts was 113.31 (95% CI, 77.9–159.12). In the PD-MCI cohort, it was 98.1 (95% CI, 64.1–143.6), and in the PD-NCI cohort, it was 31.5 (95% CI, 12.7–64.9) per 1000 person-years of observation. The overall relative risk for conversion to PDD in the PD-MCI group from T1–T3 was 4.2 (95% CI, 2.1–17.3), compared with 1.76 (95% CI, 1.1–2.9), in the PD-NCI cohort. Bivariate analysis of the PD-MCI cohort’s demographic and clinical indices revealed significant associations with increasing age (0.37, p < 0.001), worsening motor function (0.47, p < 0.001), hallucinations (0.28, p < 0.001) and residing in institutional care (0.38, p < 0.001). The median change in the decline of CAMCOG scores for the PD-MCI cohort from T1 to T3 was 2 points per year (range +0.33 to 8.3 points). The PD-MCI cohort had a significantly greater decline in CAMCOG scores from T1 to T2 (H(1) = 8.52, p < 0.01) and T2 to T3 (H(1) = 6.04, p < 0.01) than the PD-NCI cohort. Cognitive decline in the PD-MCI cohort (bivariate analysis) was associated lower scores in the CAMCOG domains of Copyright # 2015 John Wiley & Sons, Ltd.
orientation 0.23( p < 0.04), language 0.30 (p < 0.01), praxis 0.40 (p < 0.001), memory 0.37 (p < 0.001) and perception 0.33 (p < 0.002). These variables were entered into a multivariate analysis model controlling for age, which revealed that cognitive decline in the PD-MCI group was predicted by poorer semantic (expressive) language function, praxis (copying and drawing), memory (recent) and perception (Table 3). This multivariate model was repeated for PD-MCI patients progressing to PDD. Semantic language function, praxis (visuospatial construction) and memory impairment (explicit) were found to be predictive of developing PDD in this cohort (p < 0.01), explaining 77% of the variance. Subtype cognitive profile classification of the total PD-MCI cohort (n = 43) found that 36 (84%) had multidomain cognitive abnormalities and the remainder had single-domain abnormalities. The most frequent impairment in patients with single-domain deficits was in either memory or executive function. The most frequently reported multidomain deficits were a combination of two or more impairments in the domains of memory, language, attention, executive function or perception. Bivariate analysis of these variables found significant associations in the cognitive domain of language function (semantic 0.49, p < 0.002, and comprehension 0.32, p < 0.037). Comparing both cohorts revealed that the multidomain PD-MCI group had significantly more impairments in their language function (U = 34.5, z = 3.1, p < 0.002, r = 0.49). These variables that entered in a multivariate model revealed that the strongest cognitive predictor within the multidomain PD-MCI cohort was impaired semantic language function (ß = 0.392, 95% CI, 0.017–0.122, p < 0.01), explaining around 15% of the variance (r2 = 1.52). The clinical records (157/166) of the total cohort were reviewed at 16 years. In total, 152/157 was deceased at review (Figure 1). Two of the survivors fulfilled criteria for PD-MCI, and the remaining three fulfilled criteria for PDD. Overall, a total of 124/157 (79%) patients in the total cohort had developed deTable 3 Multivariate regression model for neuropsychological predictors for mild cognitive impairment as the dependent variable, 1 F = 19.66, p < 0.0001, R = 0.473 Variable Constant Language expression Memory recent Praxis Perception
ß coefficient 1.76 0.36 0.33 0.28 0.24
p-value 0.0001 0.0001 0.0001 0.003 0.01
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mentia. The PD-MCI cohort survival at the 16-year review revealed that all were deceased. Upon review of the PD-MCI cohort’s clinical records, 39/43 (91%) had progressed to PDD, with four at their time of death remaining as PD-MCI cases. Discussion This investigation employed the MDS diagnostic guidelines for PD-MCI, to establish the prevalence, incidence and risk factors for the development of PDMCI and its progression to PDD in our community cohort. The prevalence of PD-MCI at baseline was around 21%, by four years it was 33% and by six years it was 38%. The incidence of PD-MCI patients converting to PDD was around 98.0 per 1000 person-years greater than 6 years, compared with 31.5 in the PD-NCI cohort. The risk of progression to PDD in the PD-MCI cohort was over four times that of the PD-NCI cohort. Amongst the incident cases of PD-MCI observed over this period, approximately 64% progressed on to PDD. This equates in our cohort to an annual conversion rate (ACR) from PD-MCI to PDD of around 11%. An earlier community-based PD population study at 4 years reported that 62% of their PD-MCI cohort progressed to PDD, equating to an ACR of around 15% (Janvin et al., 2006). A PD-MCI population followed for approximately 2 years revealed an overall rate of progression from MCI to PDD of 29%, with an ACR of around 14% (Lee et al., 2014). Longitudinal population studies employing the MDS Task Force guidelines for PD-MCI report prevalence rates between 20% and 50%(Broeders et al., 2013; Pedersen et al., 2013). Broeders and colleagues 5-year investigation reported that greater than 50% of their cohort had developed PD-MCI. They however did not report the person-year incident rates. The ParkWest study (Pedersen et al., 2013) reported incidence rates of progression from PD-MCI to PDD of 99 per 1000 person-years, which is comparable with the incidence rate we reported of 98 per 1000 person-years. The proportion of patients developing PD-MCI was not reported at their 3-year follow-up. In the present study by 6 years, 50% of our cohort had developed PD-MCI. However, we must be cautious with the interpretation of the results because of methodological differences between this and previous studies including the differing periods of observation. We examined the records of patients with established PD, which is in contrast to the outcomes reported in prevalence studies of Copyright # 2015 John Wiley & Sons, Ltd.
newly diagnosed patients. The range and type of neuropsychological assessments employed in previous investigations could have been more sensitive in detecting more subtle cognitive deficits. The global cognitive assessment we employed may have been less sensitive in the detection of subtle cognitive deficits, than those employed in previous studies. Despite these differences, the ACR we report in present study of around 11% is similar to these studies and is comparable with larger general population investigations. In general population studies, MCI cases are often reported as remaining stable, or reverting to normal cognition. Reversion rates of around 30–40% from MCI to normal cognitive function suggest MCI is not a stable diagnosis (Mitchell and Shiri-Feshki, 2009). PD investigations report variable reversion rates. The ParkWest study reported around 25% of PD-MCI cases reverting to normal cognition over a 3-year period. Broeders et al. (2013) reported less than a 10% reversal of PD-MCI to normal cognition at 5 years. In the present study, only one patient reversed to normal cognition and by 12 years (patient’s death); they had progressed to PDD. The disparities between studies are likely to be a reflection of methodological differences. What is unknown is if MCI patients who revert to a NCI diagnosis that are followed long enough will eventually progress back to MCI, or onto dementia. Our follow-up period allowed us to observe the evolution of cognitive impairment over its full spectrum. By 16 years, greater than 90% had progressed to PDD, and we believe if previous studies had followed their patients for a similar period, they may observe similar conversion rates. The present study and the Sydney Multicenter Study (Hely et al., 2008) confirm that nearly all PD patients if they live long enough will develop significant cognitive impairment or dementia. The neuropsychological predictors for the progression from PD-MCI to PDD that we found were poorer semantic fluency, praxis (drawing/copying figures), memory (explicit) and perception (visuospatial). Earlier clinical studies have reported similar predictors for conversion from normal cognition to dementia in PD cohorts (Jacobs et al., 1995; Mahieux et al., 1998). More recently, Janvin et al. (2006) reported impairments in memory, executive function and visuospatial function in PD-MCI patients. The CamPalGN cohort study reported impairments in semantic fluency and copying drawings (intersecting pentagons) as independent predictors for the progression to PDD (Williams-Gray et al., 2007; 2009). Aarsland et al. (2010) multicenter study reported Int J Geriatr Psychiatry 2015
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deficits in memory, visuospatial, attention and executive function. Broeders et al. (2013) reported that PD-MCI converters to PDD had greater verbal memory and attention deficits. Structural changes in the brains of PD-MCI patients have been explored (Lee et al., 2014; Mak et al., 2014). These investigations have reported atrophy in the grey matter structures of the brain in PD-MCI patients with poorer neuropsychological test performance in executive, attention, memory, language function and visual recognition. These studies taken together would suggest that predictors for conversion to PDD may involve one or more abnormalities in the structures of the frontal, temporal or parietal lobes, and further longitudinal investigations are needed to establish their true relationship. In the current study, the most frequently reported multiple-domain cognitive impairments were found in the domains of memory, executive, language and visuospatial function. Dalrymple-Alford et al. (2011) reported 47% of their MCI sample had multidomain amnesic or nonamnesic impairments. Another clinical study reported that the majority of its patients also had multidomain PD-MCI, whereas the pooled investigation by Aarsland et al. (2010) reported just greater than 6% of patients with multiple-domain PD-MCI and around 20% with single-domain MCI. The dissimilarities reported by the investigation of Aarsland et al. (2010) may be due to differing application of MCI criteria and the cross sectional pooled analysis employed to determine PD-MCI classification. However, the variability between studies may reflect that the pattern of cognitive function is heterogeneous in PD-MCI. Previous studies have not, to our knowledge, explored if there are neuropsychological predictors within these subtypes. Our analysis revealed impaired semantic language function (naming) as the strongest predictor for the development of multidomain MCI. We believe that this is an important finding because early deficits in language function in PD in this and previous studies suggest that they are likely to be prognostic predictors for the development of significant cognitive impairment in PD. We would propose that initial global cognitive screening with additional validated assessments of semantic fluency and figure construction will prove to be valuable aids in the early detection of neuropsychological deficits in patients at high risk of developing dementia. This study advances our understanding of the progression of PD-MCI to PDD. The clinical importance of this is the possible earlier detection of this at risk group of patients, where it will allow new and more appropriate interventions to be piloted, or introduced. Copyright # 2015 John Wiley & Sons, Ltd.
Acknowledgements We would like to thank all of the patients and their families who supported us with this study. This study was funded by Betsi Cadwaladr University Health Board. Author contributions P. H. and R. J. M. were involved in all aspects of the research project’s conception, organisation and execution. Statistical analysis was designed and executed by P. H. Review and critique was completed by R. J. M. Manuscript preparation, writing of drafts and review and critique were completed by both authors Conflict of interest None declared.
Key points
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We report a 16-year longitudinal follow-up of a community cohort of people with Parkinson’s disease. We assessed the cognitive function of the cohort at four periods. Progression from normal, cognitive function, to mild cognitive impairment to progression to dementia was reported. Neuropsychological predictors for the progression from mild cognitive impairment to dementia were reported.
References Aarsland D, Andersen K, Larsen JP, et al. 2001. Risk of dementia in Parkinson’s disease. a community-based, prospective study. Neurology 56: 730–736. Aarsland D, BrØnnick K, Larsen JP, et al. 2009. Cognitive impairment in incident untreated Parkinson’s disease: the Norwegian ParkWest study. Neurology 72:1121–6. Aarsland D, Bronnick K, Williams-Gray CH, et al., 2010. Mild cognitive impairment in Parkinson’s disease: a multicenter pooled analysis. Neurology. 2010;75:1062–1069 Brodart H, Heffernan M, Kochan NA, et al. 2013 Mild cognitive impairment in a community sample: the Sydney Memory and Ageing Study. Alzheimer’s and Dementia 9: 310–317. Broeders M, de Bie RMA, Velseboer DC, et al. 2013. Evolution of mild cognitive impairment in Parkinson’s disease. Neurology 81: 346–352. Caviness JN, Driver-Dunckley, Connor DJ, et al. 2007. Defining mild cognitive impairment in Parkinson’s disease. Mov Disord 22:1272–7. Dalrymple-Alford JC, Livingston L, MacAskill MR, et al. 2011. Characterizing mild cognitive impairment in Parkinson’s disease. Mov Disord 26: 629–635. Dubois B, Burn D, Goetz C, et al. 2007. Diagnostic procedures for Parkinson’s disease dementia: recommendations from the Movement Disorder Society Task Force. Mov Disord 22: 2314–2324.
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P. Hobson and J. Meara Fahn S, Elton RL, Committee MotUD. 1987. Unified Parkinson’s Disease Rating Scale. In Recent Developments in Parkinson’s Disease: Fahn S, Marsden CD, Calne DB, et al. (eds). Macmillan Health Care Information: Florham Park; 153–163. Folstein MF, Folstein SE, McHugh PR. 1975. ‘Mini-Mental State’. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12: 89–198. Gibb WRG, Lees AJ. 1988. The relevance of the Lewy body to the pathogenesis of idiopathic Parkinson’s disease. J of Neurol Neurosurg & Psych 51: 745–752. Hely MA, Reid WGJ, Adena MA, et al. 2008. The Sydney Multicenter Study of Parkinson’s disease: the inevitability of dementia at 20 years. Mov Disord 26: 837–844. Hobson JP, Edwards N, Meara RJ. 2001. The Parkinson’s Disease Activities of Daily Living Scale: a new simple and brief subjective measure of disability in Parkinson’s disease. Clin Rehab 15: 241–246. Hobson JP, Meara RJ. 2004. The risk and incidence of dementia in a cohort of older subjects with Parkinson’s disease in the UK. Mov Disord 19: 1043–1049. Hoehn M, Yahr MD. 1967. Parkinsonism: onset, progression, and mortality. Neurology 17:427–442. Jacobs DM, Marder K, Cote LJ, et al. 1995. Neuropsychological characteristics of preclinical dementia in Parkinson’s disease. Neurology 45:1691–1696. Janvin CC, Aarsland D, Larsen JP. 2005. Cognitive predictors of dementia in Parkinson’s disease: a community-based, 4-year longitudinal study. J of Geriat Psychiat and Neurol 18:149–154. Janvin CC, Larsen JP, Aarsland D, Hugdah l. 2006. Subtypes of mild cognitive impairment in Parkinson’s disease: progression to dementia. Mov Disord 21:1343–1349. Lee JE, Cho KH, Song SK, et al. 2014. Exploratory analysis of neuropsychological and neuroanatomical correlates of progressive mild cognitive impairment in Parkinson’s disease. J Neurol Neurosurg Psychiatry 85:7–16. Litvan I, Goldman JG, Tröster AI, et al. 2012. Diagnostic criteria for mild cognitive impairment in Parkinson’s disease: Movement Disorder Society Task Force guidelines. Mov Disord 27: 349–356. Luck T, Riedel-Heller SG, Luppa M, et al. 2010. Risk factors for incident mild cognitive impairment—results from the German Study on Ageing, Cognition and Dementia in primary care patients (AgeCoDe). Acta Psychiatr Scand 121:260–272. Mahieux F, Fenelon Tang MX, et al. 1998. Memory and executive function impairment predict dementia in Parkinson’s disease. J Neurol Neurosurg Psychiatry 64:178–183.
Copyright # 2015 John Wiley & Sons, Ltd.
Mak E, Zhou J, Tan LSC, et al. 2014. Cognitive deficits in mild Parkinson’s disease are associated with distinct areas of grey matter atrophy. J Neurol Neurosurg Psychiatry 85:576–580. Mitchell AJ, Shiri-Feshki M. 2009. Rate of progression of mild cognitive impairment to dementia—meta-analysis of 41 robust inception cohort studies. Acta Psychiatr Scand 119:252–265. Morris JC, Cummings JC. 2005. Mild cognitive impairment (MCI) represents early-stage Alzheimer’s disease. J Alzheimer’s disease 7:235–239. Pedersen FK, Larsen JP, Tysnes OB, et al. 2013. Prognosis of mild cognitive impairment in early Parkinson disease. JAMA Neurol 70:580–586. Petersen RC, Smith GE, Waring SC, et al. 1999. Mild cognitive impairment: clinical characterization and outcome. Arch Neurol 56:303–308. Petersen RC. 2004. Mild cognitive impairment as a diagnostic entity. J Intern Med 256:183–94. Petersen RC, Knopman DS. 2006. MCI is a clinically useful concept. Int Psychogeriatr 18: 394–402. Roth M, Tym E, Mountjoy CQ, et al. 1986. CAMDEX: a standardised instrument for the diagnosis of mental disorder in the elderly with special reference to elderly detection of dementia. Br J Psychiatry 149, 698–709. Sheikh JI, Yesavage JA. 1986. Geriatric Depression Scale (GDS): recent evidence and development of a shorter version In Clinical Gerontology: A Guide to Assessment and Intervention, The Hawthorn Press, New York; 165–173. Sunderland T, Hill JL, Mellow AM, et al. 1989. Clock drawing in Alzheimer’s disease: a novel measure of dementia severity. J Am Geriatr Soc 13: 495–502. Williams A. 1990. EuroQol—a new facility for the measurement of health-related quality of life. Health Policy 16:199–208. Williams-Gray CH, Foltynie T, Brayne CE et al. 2007. Evolution of cognitive dysfunction in an incident Parkinson’s disease cohort. Brain 130: 1787–1798. Williams-Gray CH, Evans JR, Goris An, et al. 2009. The distinct cognitive syndromes of Parkinson’s disease: 5 year follow-up of the CamPaIGN cohort. Brain 132: 2958–2969. Winblad BB,Palmer K, Kivipelto M, et al. 2004. Mild cognitive impairment—beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. J Intern Med 256:240–246. Yarnall AJ, Rochester L, Burn DJ. 2013. Mild cognitive impairment in Parkinson’s disease. Age & Ageing 42: 1–10.
Int J Geriatr Psychiatry 2015
