The identification of Parkinson's disease subtypes using cluster analysis: a systematic review.
Identifieur interne : 002B85 ( Ncbi/Curation ); précédent : 002B84; suivant : 002B86The identification of Parkinson's disease subtypes using cluster analysis: a systematic review.
Auteurs : Stephanie M. Van Rooden [Pays-Bas] ; Willem J. Heiser ; Joost N. Kok ; Dagmar Verbaan ; Jacobus J. Van Hilten ; Johan MarinusSource :
- Movement disorders : official journal of the Movement Disorder Society [ 1531-8257 ] ; 2010.
English descriptors
- KwdEn :
- MESH :
- classification : Parkinson Disease.
- statistics & numerical data : PubMed.
- Algorithms, Cluster Analysis, Humans.
Abstract
The clinical variability between patients with Parkinson's disease (PD) may point at the existence of subtypes of the disease. Identification of subtypes is important, since a focus on homogeneous groups may enhance the chance of success of research on mechanisms of disease and may also lead to tailored treatment strategies. Cluster analysis (CA) is an objective method to classify patients into subtypes. We systematically reviewed the methodology and results of CA studies in PD to gain a better understanding of the robustness of identified subtypes. We found seven studies that fulfilled the inclusion criteria. Studies were limited by incomplete reporting and methodological limitations. Differences between studies rendered comparisons of the results difficult. However, it appeared that studies which applied a comparable design identified similar subtypes. The cluster profiles "old age-at-onset and rapid disease progression" and "young age-at-onset and slow disease progression" emerged from the majority of studies. Other cluster profiles were less consistent across studies. Future studies with a rigorous study design that is standardized with respect to the included variables, data processing, and CA technique may advance the knowledge on subtypes in PD.
DOI: 10.1002/mds.23116
PubMed: 20535823
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Heiser</name></author><author><name sortKey="Kok, Joost N" sort="Kok, Joost N" uniqKey="Kok J" first="Joost N" last="Kok">Joost N. Kok</name></author><author><name sortKey="Verbaan, Dagmar" sort="Verbaan, Dagmar" uniqKey="Verbaan D" first="Dagmar" last="Verbaan">Dagmar Verbaan</name></author><author><name sortKey="Van Hilten, Jacobus J" sort="Van Hilten, Jacobus J" uniqKey="Van Hilten J" first="Jacobus J" last="Van Hilten">Jacobus J. Van Hilten</name></author><author><name sortKey="Marinus, Johan" sort="Marinus, Johan" uniqKey="Marinus J" first="Johan" last="Marinus">Johan Marinus</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2010">2010</date><idno type="doi">10.1002/mds.23116</idno><idno type="RBID">pubmed:20535823</idno><idno type="pmid">20535823</idno><idno type="wicri:Area/PubMed/Corpus">001817</idno><idno type="wicri:Area/PubMed/Curation">001817</idno><idno type="wicri:Area/PubMed/Checkpoint">001565</idno><idno type="wicri:Area/Ncbi/Merge">002B85</idno><idno type="wicri:Area/Ncbi/Curation">002B85</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">The identification of Parkinson's disease subtypes using cluster analysis: a systematic review.</title><author><name sortKey="Van Rooden, Stephanie M" sort="Van Rooden, Stephanie M" uniqKey="Van Rooden S" first="Stephanie M" last="Van Rooden">Stephanie M. Van Rooden</name><affiliation wicri:level="3"><nlm:affiliation>Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands. s.m.van_rooden@lumc.nl</nlm:affiliation><country xml:lang="fr">Pays-Bas</country><wicri:regionArea>Department of Neurology, Leiden University Medical Center, Leiden</wicri:regionArea><placeName><settlement type="city">Leyde</settlement><region nuts="2" type="province">Hollande-Méridionale</region></placeName></affiliation></author><author><name sortKey="Heiser, Willem J" sort="Heiser, Willem J" uniqKey="Heiser W" first="Willem J" last="Heiser">Willem J. Heiser</name></author><author><name sortKey="Kok, Joost N" sort="Kok, Joost N" uniqKey="Kok J" first="Joost N" last="Kok">Joost N. Kok</name></author><author><name sortKey="Verbaan, Dagmar" sort="Verbaan, Dagmar" uniqKey="Verbaan D" first="Dagmar" last="Verbaan">Dagmar Verbaan</name></author><author><name sortKey="Van Hilten, Jacobus J" sort="Van Hilten, Jacobus J" uniqKey="Van Hilten J" first="Jacobus J" last="Van Hilten">Jacobus J. Van Hilten</name></author><author><name sortKey="Marinus, Johan" sort="Marinus, Johan" uniqKey="Marinus J" first="Johan" last="Marinus">Johan Marinus</name></author></analytic><series><title level="j">Movement disorders : official journal of the Movement Disorder Society</title><idno type="eISSN">1531-8257</idno><imprint><date when="2010" type="published">2010</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Cluster Analysis</term><term>Humans</term><term>Parkinson Disease (classification)</term><term>PubMed (statistics & numerical data)</term></keywords><keywords scheme="MESH" qualifier="classification" xml:lang="en"><term>Parkinson Disease</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>PubMed</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Cluster Analysis</term><term>Humans</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The clinical variability between patients with Parkinson's disease (PD) may point at the existence of subtypes of the disease. Identification of subtypes is important, since a focus on homogeneous groups may enhance the chance of success of research on mechanisms of disease and may also lead to tailored treatment strategies. Cluster analysis (CA) is an objective method to classify patients into subtypes. We systematically reviewed the methodology and results of CA studies in PD to gain a better understanding of the robustness of identified subtypes. We found seven studies that fulfilled the inclusion criteria. Studies were limited by incomplete reporting and methodological limitations. Differences between studies rendered comparisons of the results difficult. However, it appeared that studies which applied a comparable design identified similar subtypes. The cluster profiles "old age-at-onset and rapid disease progression" and "young age-at-onset and slow disease progression" emerged from the majority of studies. Other cluster profiles were less consistent across studies. Future studies with a rigorous study design that is standardized with respect to the included variables, data processing, and CA technique may advance the knowledge on subtypes in PD.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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