The spectrum of cognitive disorders in Parkinson's disease: A data‐driven approach
Identifieur interne : 001C25 ( Istex/Corpus ); précédent : 001C24; suivant : 001C26The spectrum of cognitive disorders in Parkinson's disease: A data‐driven approach
Auteurs : Kathy Dujardin ; Albert F. G. Leentjens ; Carole Langlois ; Anja J. H. Moonen ; Annelien A. Duits ; Anne-Sophie Carette ; Alain DuhamelSource :
- Movement Disorders [ 0885-3185 ] ; 2013-02.
Abstract
The objective of this study was to identify different cognitive phenotypes in Parkinson's disease (PD) using a data‐driven approach. A model‐based cluster analysis was conducted on the neuropsychological test results of 558 PD patients from 2 European movement disorder centers (Lille, n = 403; Maastricht, n = 155). The number of clusters was determined according to their clinical relevance as well as on the basis of 3 statistical criteria: the cubic cluster criterion, the pseudo F statistic, and the total squared correlation ratio (R2). A factorial discriminant analysis was performed to assess the quality of the cluster's separation. Descriptive variables were used to further characterize the clusters. A 5‐cluster model was considered the clinically most relevant. The 5 clusters comprised: (1) cognitively intact patients (19.39%); (2) patients without cognitive deficits but with slight mental slowing (41.29%); (3) patients with slightly impaired overall cognitive efficiency and deficits in all cognitive domains except recognition memory (12.93%); (4) patients with severe mental slowing, impaired overall cognitive efficiency, and severe cognitive impairment in all domains, including memory (23.88%); and (5) patients with very severe impairment in all cognitive domains (2.51%). Cognitively intact patients were significantly younger and had received more years of formal education. Patients in the last 3 clusters had more severe motor symptoms, longer disease duration, and more axial signs. In the last cluster, most patients were demented. Our results confirm the heterogeneity of cognitive presentations in PD, ranging from cognitively intact patients with rather high levels of performance in each cognitive domain to very severely impaired patients. © 2013 Movement Disorder Society
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DOI: 10.1002/mds.25311
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<front><div type="abstract">The objective of this study was to identify different cognitive phenotypes in Parkinson's disease (PD) using a data‐driven approach. A model‐based cluster analysis was conducted on the neuropsychological test results of 558 PD patients from 2 European movement disorder centers (Lille, n = 403; Maastricht, n = 155). The number of clusters was determined according to their clinical relevance as well as on the basis of 3 statistical criteria: the cubic cluster criterion, the pseudo F statistic, and the total squared correlation ratio (R2). A factorial discriminant analysis was performed to assess the quality of the cluster's separation. Descriptive variables were used to further characterize the clusters. A 5‐cluster model was considered the clinically most relevant. The 5 clusters comprised: (1) cognitively intact patients (19.39%); (2) patients without cognitive deficits but with slight mental slowing (41.29%); (3) patients with slightly impaired overall cognitive efficiency and deficits in all cognitive domains except recognition memory (12.93%); (4) patients with severe mental slowing, impaired overall cognitive efficiency, and severe cognitive impairment in all domains, including memory (23.88%); and (5) patients with very severe impairment in all cognitive domains (2.51%). Cognitively intact patients were significantly younger and had received more years of formal education. Patients in the last 3 clusters had more severe motor symptoms, longer disease duration, and more axial signs. In the last cluster, most patients were demented. Our results confirm the heterogeneity of cognitive presentations in PD, ranging from cognitively intact patients with rather high levels of performance in each cognitive domain to very severely impaired patients. © 2013 Movement Disorder Society</div>
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<abstract>The objective of this study was to identify different cognitive phenotypes in Parkinson's disease (PD) using a data‐driven approach. A model‐based cluster analysis was conducted on the neuropsychological test results of 558 PD patients from 2 European movement disorder centers (Lille, n = 403; Maastricht, n = 155). The number of clusters was determined according to their clinical relevance as well as on the basis of 3 statistical criteria: the cubic cluster criterion, the pseudo F statistic, and the total squared correlation ratio (R2). A factorial discriminant analysis was performed to assess the quality of the cluster's separation. Descriptive variables were used to further characterize the clusters. A 5‐cluster model was considered the clinically most relevant. The 5 clusters comprised: (1) cognitively intact patients (19.39%); (2) patients without cognitive deficits but with slight mental slowing (41.29%); (3) patients with slightly impaired overall cognitive efficiency and deficits in all cognitive domains except recognition memory (12.93%); (4) patients with severe mental slowing, impaired overall cognitive efficiency, and severe cognitive impairment in all domains, including memory (23.88%); and (5) patients with very severe impairment in all cognitive domains (2.51%). Cognitively intact patients were significantly younger and had received more years of formal education. Patients in the last 3 clusters had more severe motor symptoms, longer disease duration, and more axial signs. In the last cluster, most patients were demented. Our results confirm the heterogeneity of cognitive presentations in PD, ranging from cognitively intact patients with rather high levels of performance in each cognitive domain to very severely impaired patients. © 2013 Movement Disorder Society</abstract>
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<title>The spectrum of cognitive disorders in Parkinson's disease: A data‐driven approach</title>
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<affiliation>Neurology and Movement Disorders Department, Lille University Medical Center, Lille, France</affiliation>
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<author xml:id="author-2"><persName><forename type="first">Albert F.G.</forename>
<surname>Leentjens</surname>
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<author xml:id="author-4"><persName><forename type="first">Anja J.H.</forename>
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<author xml:id="author-5"><persName><forename type="first">Annelien A.</forename>
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<author xml:id="author-6"><persName><forename type="first">Anne‐Sophie</forename>
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<abstract><p>The objective of this study was to identify different cognitive phenotypes in Parkinson's disease (PD) using a data‐driven approach. A model‐based cluster analysis was conducted on the neuropsychological test results of 558 PD patients from 2 European movement disorder centers (Lille, n = 403; Maastricht, n = 155). The number of clusters was determined according to their clinical relevance as well as on the basis of 3 statistical criteria: the cubic cluster criterion, the pseudo F statistic, and the total squared correlation ratio (R2). A factorial discriminant analysis was performed to assess the quality of the cluster's separation. Descriptive variables were used to further characterize the clusters. A 5‐cluster model was considered the clinically most relevant. The 5 clusters comprised: (1) cognitively intact patients (19.39%); (2) patients without cognitive deficits but with slight mental slowing (41.29%); (3) patients with slightly impaired overall cognitive efficiency and deficits in all cognitive domains except recognition memory (12.93%); (4) patients with severe mental slowing, impaired overall cognitive efficiency, and severe cognitive impairment in all domains, including memory (23.88%); and (5) patients with very severe impairment in all cognitive domains (2.51%). Cognitively intact patients were significantly younger and had received more years of formal education. Patients in the last 3 clusters had more severe motor symptoms, longer disease duration, and more axial signs. In the last cluster, most patients were demented. Our results confirm the heterogeneity of cognitive presentations in PD, ranging from cognitively intact patients with rather high levels of performance in each cognitive domain to very severely impaired patients. © 2013 Movement Disorder Society</p>
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<correspondenceTo>Correspondence to: Dr. Kathy Dujardin, Neurologie et Pathologie du Mouvement, Neurologie A, Hôpital Salengro, Centre Hospitalier Universitaire, F‐59037 Lille cedex, France; <email>kathy.dujardin@univ-lille2.fr</email>
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<contentMeta><titleGroup><title type="main">The spectrum of cognitive disorders in <fc>P</fc>
arkinson's disease: A data‐driven approach</title>
<title type="short">Cognitive Phenotypes in <fc>PD</fc>
</title>
<title type="shortAuthors">Dujardin et al</title>
</titleGroup>
<creators><creator affiliationRef="#mds25311-aff-0001 #mds25311-aff-0002" corresponding="yes" creatorRole="author" xml:id="mds25311-cr-0001"><personName><givenNames>Kathy</givenNames>
<familyName>Dujardin</familyName>
<degrees>PhD</degrees>
</personName>
</creator>
<creator affiliationRef="#mds25311-aff-0003" creatorRole="author" xml:id="mds25311-cr-0002"><personName><givenNames>Albert F.G.</givenNames>
<familyName>Leentjens</familyName>
<degrees>MD, PhD</degrees>
</personName>
</creator>
<creator affiliationRef="#mds25311-aff-0004" creatorRole="author" xml:id="mds25311-cr-0003"><personName><givenNames>Carole</givenNames>
<familyName>Langlois</familyName>
<degrees>MSc</degrees>
</personName>
</creator>
<creator affiliationRef="#mds25311-aff-0003" creatorRole="author" xml:id="mds25311-cr-0004"><personName><givenNames>Anja J.H.</givenNames>
<familyName>Moonen</familyName>
<degrees>MSc</degrees>
</personName>
</creator>
<creator affiliationRef="#mds25311-aff-0003" creatorRole="author" xml:id="mds25311-cr-0005"><personName><givenNames>Annelien A.</givenNames>
<familyName>Duits</familyName>
<degrees>PhD</degrees>
</personName>
</creator>
<creator affiliationRef="#mds25311-aff-0002" creatorRole="author" xml:id="mds25311-cr-0006"><personName><givenNames>Anne‐Sophie</givenNames>
<familyName>Carette</familyName>
<degrees>MSc</degrees>
</personName>
</creator>
<creator affiliationRef="#mds25311-aff-0004" creatorRole="author" xml:id="mds25311-cr-0007"><personName><givenNames>Alain</givenNames>
<familyName>Duhamel</familyName>
<degrees>PhD</degrees>
</personName>
</creator>
</creators>
<affiliationGroup><affiliation countryCode="FR" type="organization" xml:id="mds25311-aff-0001"><orgDiv>Laboratoire de Neurosciences Fonctionnelles et Pathologies</orgDiv>
<orgName>University of Lille 2</orgName>
<address><postCode>EA4559</postCode>
<city>Lille</city>
<country>France</country>
</address>
</affiliation>
<affiliation countryCode="FR" type="organization" xml:id="mds25311-aff-0002"><orgDiv>Neurology and Movement Disorders Department</orgDiv>
<orgName>Lille University Medical Center</orgName>
<address><city>Lille</city>
<country>France</country>
</address>
</affiliation>
<affiliation countryCode="NL" type="organization" xml:id="mds25311-aff-0003"><orgDiv>Department of Psychiatry</orgDiv>
<orgName>Maastricht University Medical Center</orgName>
<address><city>Maastricht</city>
<country>the Netherlands</country>
</address>
</affiliation>
<affiliation countryCode="FR" type="organization" xml:id="mds25311-aff-0004"><orgDiv>Department of Biostatistics</orgDiv>
<orgName>Lille University Medical Center</orgName>
<address><city>Lille</city>
<country>France</country>
</address>
</affiliation>
</affiliationGroup>
<keywordGroup type="author"><keyword xml:id="mds25311-kwd-0001">cognition</keyword>
<keyword xml:id="mds25311-kwd-0002">behavior</keyword>
<keyword xml:id="mds25311-kwd-0003">dementia</keyword>
<keyword xml:id="mds25311-kwd-0004">cluster analysis</keyword>
</keywordGroup>
<supportingInformation><p>Additional Supporting Information may be found in the online version of this article.</p>
<supportingInfoItem><mediaResource alt="application/doc" href="urn-x:wiley:08853185:media:mds25311:mds25311-sup-0001-suppinfo"></mediaResource>
<caption>Supporting Information</caption>
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<abstractGroup><abstract type="main"><title type="main">ABSTRACT</title>
<p>The objective of this study was to identify different cognitive phenotypes in <fc>Parkinson</fc>
's disease (<fc>PD</fc>
) using a data‐driven approach. A model‐based cluster analysis was conducted on the neuropsychological test results of 558 <fc>PD</fc>
patients from 2 European movement disorder centers (<fc>Lille</fc>
, n = 403; Maastricht, n = 155). The number of clusters was determined according to their clinical relevance as well as on the basis of 3 statistical criteria: the cubic cluster criterion, the pseudo <i>F</i>
statistic, and the total squared correlation ratio (<i>R</i>
<sup>2</sup>
). A factorial discriminant analysis was performed to assess the quality of the cluster's separation. Descriptive variables were used to further characterize the clusters. A 5‐cluster model was considered the clinically most relevant. The 5 clusters comprised: (1) cognitively intact patients (19.39%); (2) patients without cognitive deficits but with slight mental slowing (41.29%); (3) patients with slightly impaired overall cognitive efficiency and deficits in all cognitive domains except recognition memory (12.93%); (4) patients with severe mental slowing, impaired overall cognitive efficiency, and severe cognitive impairment in all domains, including memory (23.88%); and (5) patients with very severe impairment in all cognitive domains (2.51%). Cognitively intact patients were significantly younger and had received more years of formal education. Patients in the last 3 clusters had more severe motor symptoms, longer disease duration, and more axial signs. In the last cluster, most patients were demented. Our results confirm the heterogeneity of cognitive presentations in <fc>PD</fc>
, ranging from cognitively intact patients with rather high levels of performance in each cognitive domain to very severely impaired patients. © 2013 <i>Movement</i>
Disorder Society</p>
</abstract>
</abstractGroup>
</contentMeta>
<noteGroup><note xml:id="mds25311-note-0001"><p><b>Funding agencies:</b>
This study was funded by the Michael J. Fox Foundation for Parkinson's Research.</p>
</note>
<note xml:id="mds25311-note-0002a"><p><b>Relevant conflicts of interest/financial disclosures</b>
: Nothing to report.</p>
</note>
</noteGroup>
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<mods version="3.6"><titleInfo lang="en"><title>The spectrum of cognitive disorders in Parkinson's disease: A data‐driven approach</title>
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<titleInfo type="abbreviated" lang="en"><title>Cognitive Phenotypes in PD</title>
</titleInfo>
<titleInfo type="alternative" contentType="CDATA" lang="en"><title>The spectrum of cognitive disorders in Parkinson's disease: A data‐driven approach</title>
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<name type="personal"><namePart type="given">Kathy</namePart>
<namePart type="family">Dujardin</namePart>
<namePart type="termsOfAddress">PhD</namePart>
<affiliation>Laboratoire de Neurosciences Fonctionnelles et Pathologies, University of Lille 2, EA4559, Lille, France</affiliation>
<affiliation>Neurology and Movement Disorders Department, Lille University Medical Center, Lille, France</affiliation>
<affiliation>E-mail: kathy.dujardin@univ-lille2.fr</affiliation>
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<name type="personal"><namePart type="given">Albert F.G.</namePart>
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<affiliation>Department of Psychiatry, Maastricht University Medical Center, Maastricht, the Netherlands</affiliation>
<role><roleTerm type="text">author</roleTerm>
</role>
</name>
<name type="personal"><namePart type="given">Carole</namePart>
<namePart type="family">Langlois</namePart>
<namePart type="termsOfAddress">MSc</namePart>
<affiliation>Department of Biostatistics, Lille University Medical Center, Lille, France</affiliation>
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<name type="personal"><namePart type="given">Anja J.H.</namePart>
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<affiliation>Department of Psychiatry, Maastricht University Medical Center, Maastricht, the Netherlands</affiliation>
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<name type="personal"><namePart type="given">Annelien A.</namePart>
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<name type="personal"><namePart type="given">Anne‐Sophie</namePart>
<namePart type="family">Carette</namePart>
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<affiliation>Neurology and Movement Disorders Department, Lille University Medical Center, Lille, France</affiliation>
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<name type="personal"><namePart type="given">Alain</namePart>
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<originInfo><publisher>Blackwell Publishing Ltd</publisher>
<dateIssued encoding="w3cdtf">2013-02</dateIssued>
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<abstract>The objective of this study was to identify different cognitive phenotypes in Parkinson's disease (PD) using a data‐driven approach. A model‐based cluster analysis was conducted on the neuropsychological test results of 558 PD patients from 2 European movement disorder centers (Lille, n = 403; Maastricht, n = 155). The number of clusters was determined according to their clinical relevance as well as on the basis of 3 statistical criteria: the cubic cluster criterion, the pseudo F statistic, and the total squared correlation ratio (R2). A factorial discriminant analysis was performed to assess the quality of the cluster's separation. Descriptive variables were used to further characterize the clusters. A 5‐cluster model was considered the clinically most relevant. The 5 clusters comprised: (1) cognitively intact patients (19.39%); (2) patients without cognitive deficits but with slight mental slowing (41.29%); (3) patients with slightly impaired overall cognitive efficiency and deficits in all cognitive domains except recognition memory (12.93%); (4) patients with severe mental slowing, impaired overall cognitive efficiency, and severe cognitive impairment in all domains, including memory (23.88%); and (5) patients with very severe impairment in all cognitive domains (2.51%). Cognitively intact patients were significantly younger and had received more years of formal education. Patients in the last 3 clusters had more severe motor symptoms, longer disease duration, and more axial signs. In the last cluster, most patients were demented. Our results confirm the heterogeneity of cognitive presentations in PD, ranging from cognitively intact patients with rather high levels of performance in each cognitive domain to very severely impaired patients. © 2013 Movement Disorder Society</abstract>
<subject><genre>keywords</genre>
<topic>cognition</topic>
<topic>behavior</topic>
<topic>dementia</topic>
<topic>cluster analysis</topic>
</subject>
<relatedItem type="host"><titleInfo><title>Movement Disorders</title>
</titleInfo>
<titleInfo type="abbreviated"><title>Mov Disord.</title>
</titleInfo>
<genre type="journal">journal</genre>
<note type="content"> Additional Supporting Information may be found in the online version of this article.Supporting Info Item: Supporting Information - </note>
<subject><genre>article-category</genre>
<topic>Research Article</topic>
</subject>
<identifier type="ISSN">0885-3185</identifier>
<identifier type="eISSN">1531-8257</identifier>
<identifier type="DOI">10.1002/(ISSN)1531-8257</identifier>
<identifier type="PublisherID">MDS</identifier>
<part><date>2013</date>
<detail type="volume"><caption>vol.</caption>
<number>28</number>
</detail>
<detail type="issue"><caption>no.</caption>
<number>2</number>
</detail>
<extent unit="pages"><start>183</start>
<end>189</end>
<total>7</total>
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<identifier type="DOI">10.1002/mds.25311</identifier>
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<accessCondition type="use and reproduction" contentType="copyright">Copyright © 2013 Movement Disorder SocietyCopyright © 2013 Movement Disorder Society</accessCondition>
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