Using global statistical tests in long‐term Parkinson's disease clinical trials
Identifieur interne : 002047 ( Main/Corpus ); précédent : 002046; suivant : 002048Using global statistical tests in long‐term Parkinson's disease clinical trials
Auteurs : Peng Huang ; Christopher G. Goetz ; Robert F. Woolson ; Barbara Tilley ; Douglas Kerr ; Yuko Palesch ; Jordan Elm ; Bernard Ravina ; Kenneth J. Bergmann ; Karl KieburtzSource :
- Movement Disorders [ 0885-3185 ] ; 2009-09-15.
English descriptors
- KwdEn :
Abstract
Parkinson's disease (PD) impairments are multidimensional, making it difficult to choose a single primary outcome when evaluating treatments to stop or lessen the long‐term decline in PD. We review commonly used multivariate statistical methods for assessing a treatment's global impact, and we highlight the novel Global Statistical Test (GST) methodology. We compare the GST to other multivariate approaches using data from two PD trials. In one trial where the treatment showed consistent improvement on all primary and secondary outcomes, the GST was more powerful than other methods in demonstrating significant improvement. In the trial where treatment induced both improvement and deterioration in key outcomes, the GST failed to demonstrate statistical evidence even though other techniques showed significant improvement. Based on the statistical properties of the GST and its relevance to overall treatment benefit, the GST appears particularly well suited for a disease like PD where disability and impairment reflect dysfunction of diverse brain systems and where both disease and treatment side effects impact quality of life. In future long term trials, use of GST for primary statistical analysis would allow the assessment of clinically relevant outcomes rather than the artificial selection of a single primary outcome. © 2009 Movement Disorder Society
Url:
DOI: 10.1002/mds.22645
Links to Exploration step
ISTEX:18E069528157DF39F4838E56F149062782877FCCLe document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">Using global statistical tests in long‐term Parkinson's disease clinical trials</title><author><name sortKey="Huang, Peng" sort="Huang, Peng" uniqKey="Huang P" first="Peng" last="Huang">Peng Huang</name><affiliation><mods:affiliation>Division of Oncology Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA</mods:affiliation></affiliation></author><author><name sortKey="Goetz, Christopher G" sort="Goetz, Christopher G" uniqKey="Goetz C" first="Christopher G." last="Goetz">Christopher G. Goetz</name><affiliation><mods:affiliation>Department of Medicine, Rush University Medical Center, Chicago, Illinois, USA</mods:affiliation></affiliation></author><author><name sortKey="Woolson, Robert F" sort="Woolson, Robert F" uniqKey="Woolson R" first="Robert F." last="Woolson">Robert F. Woolson</name><affiliation><mods:affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</mods:affiliation></affiliation></author><author><name sortKey="Tilley, Barbara" sort="Tilley, Barbara" uniqKey="Tilley B" first="Barbara" last="Tilley">Barbara Tilley</name><affiliation><mods:affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</mods:affiliation></affiliation></author><author><name sortKey="Kerr, Douglas" sort="Kerr, Douglas" uniqKey="Kerr D" first="Douglas" last="Kerr">Douglas Kerr</name><affiliation><mods:affiliation>Division of Oncology Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA</mods:affiliation></affiliation></author><author><name sortKey="Palesch, Yuko" sort="Palesch, Yuko" uniqKey="Palesch Y" first="Yuko" last="Palesch">Yuko Palesch</name><affiliation><mods:affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</mods:affiliation></affiliation></author><author><name sortKey="Elm, Jordan" sort="Elm, Jordan" uniqKey="Elm J" first="Jordan" last="Elm">Jordan Elm</name><affiliation><mods:affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</mods:affiliation></affiliation></author><author><name sortKey="Ravina, Bernard" sort="Ravina, Bernard" uniqKey="Ravina B" first="Bernard" last="Ravina">Bernard Ravina</name><affiliation><mods:affiliation>Department of Neurology, University of Rochester, Rochester, New York, USA</mods:affiliation></affiliation></author><author><name sortKey="Bergmann, Kenneth J" sort="Bergmann, Kenneth J" uniqKey="Bergmann K" first="Kenneth J." last="Bergmann">Kenneth J. Bergmann</name><affiliation><mods:affiliation>U.S. Food and Drug Administration, Silver Spring, Maryland, USA</mods:affiliation></affiliation></author><author><name sortKey="Kieburtz, Karl" sort="Kieburtz, Karl" uniqKey="Kieburtz K" first="Karl" last="Kieburtz">Karl Kieburtz</name><affiliation><mods:affiliation>Department of Neurology, University of Rochester, Rochester, New York, USA</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:18E069528157DF39F4838E56F149062782877FCC</idno><date when="2009" year="2009">2009</date><idno type="doi">10.1002/mds.22645</idno><idno type="url">https://api.istex.fr/document/18E069528157DF39F4838E56F149062782877FCC/fulltext/pdf</idno><idno type="wicri:Area/Main/Corpus">002047</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">Using global statistical tests in long‐term Parkinson's disease clinical trials</title><author><name sortKey="Huang, Peng" sort="Huang, Peng" uniqKey="Huang P" first="Peng" last="Huang">Peng Huang</name><affiliation><mods:affiliation>Division of Oncology Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA</mods:affiliation></affiliation></author><author><name sortKey="Goetz, Christopher G" sort="Goetz, Christopher G" uniqKey="Goetz C" first="Christopher G." last="Goetz">Christopher G. Goetz</name><affiliation><mods:affiliation>Department of Medicine, Rush University Medical Center, Chicago, Illinois, USA</mods:affiliation></affiliation></author><author><name sortKey="Woolson, Robert F" sort="Woolson, Robert F" uniqKey="Woolson R" first="Robert F." last="Woolson">Robert F. Woolson</name><affiliation><mods:affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</mods:affiliation></affiliation></author><author><name sortKey="Tilley, Barbara" sort="Tilley, Barbara" uniqKey="Tilley B" first="Barbara" last="Tilley">Barbara Tilley</name><affiliation><mods:affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</mods:affiliation></affiliation></author><author><name sortKey="Kerr, Douglas" sort="Kerr, Douglas" uniqKey="Kerr D" first="Douglas" last="Kerr">Douglas Kerr</name><affiliation><mods:affiliation>Division of Oncology Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA</mods:affiliation></affiliation></author><author><name sortKey="Palesch, Yuko" sort="Palesch, Yuko" uniqKey="Palesch Y" first="Yuko" last="Palesch">Yuko Palesch</name><affiliation><mods:affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</mods:affiliation></affiliation></author><author><name sortKey="Elm, Jordan" sort="Elm, Jordan" uniqKey="Elm J" first="Jordan" last="Elm">Jordan Elm</name><affiliation><mods:affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</mods:affiliation></affiliation></author><author><name sortKey="Ravina, Bernard" sort="Ravina, Bernard" uniqKey="Ravina B" first="Bernard" last="Ravina">Bernard Ravina</name><affiliation><mods:affiliation>Department of Neurology, University of Rochester, Rochester, New York, USA</mods:affiliation></affiliation></author><author><name sortKey="Bergmann, Kenneth J" sort="Bergmann, Kenneth J" uniqKey="Bergmann K" first="Kenneth J." last="Bergmann">Kenneth J. Bergmann</name><affiliation><mods:affiliation>U.S. Food and Drug Administration, Silver Spring, Maryland, USA</mods:affiliation></affiliation></author><author><name sortKey="Kieburtz, Karl" sort="Kieburtz, Karl" uniqKey="Kieburtz K" first="Karl" last="Kieburtz">Karl Kieburtz</name><affiliation><mods:affiliation>Department of Neurology, University of Rochester, Rochester, New York, USA</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Movement Disorders</title><title level="j" type="abbrev">Mov. Disord.</title><idno type="ISSN">0885-3185</idno><idno type="eISSN">1531-8257</idno><imprint><publisher>Wiley Subscription Services, Inc., A Wiley Company</publisher><pubPlace>Hoboken</pubPlace><date type="published" when="2009-09-15">2009-09-15</date><biblScope unit="volume">24</biblScope><biblScope unit="issue">12</biblScope><biblScope unit="page" from="1732">1732</biblScope><biblScope unit="page" to="1739">1739</biblScope></imprint><idno type="ISSN">0885-3185</idno></series><idno type="istex">18E069528157DF39F4838E56F149062782877FCC</idno><idno type="DOI">10.1002/mds.22645</idno><idno type="ArticleID">MDS22645</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0885-3185</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>global treatment effect</term><term>multiple outcomes</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Parkinson's disease (PD) impairments are multidimensional, making it difficult to choose a single primary outcome when evaluating treatments to stop or lessen the long‐term decline in PD. We review commonly used multivariate statistical methods for assessing a treatment's global impact, and we highlight the novel Global Statistical Test (GST) methodology. We compare the GST to other multivariate approaches using data from two PD trials. In one trial where the treatment showed consistent improvement on all primary and secondary outcomes, the GST was more powerful than other methods in demonstrating significant improvement. In the trial where treatment induced both improvement and deterioration in key outcomes, the GST failed to demonstrate statistical evidence even though other techniques showed significant improvement. Based on the statistical properties of the GST and its relevance to overall treatment benefit, the GST appears particularly well suited for a disease like PD where disability and impairment reflect dysfunction of diverse brain systems and where both disease and treatment side effects impact quality of life. In future long term trials, use of GST for primary statistical analysis would allow the assessment of clinically relevant outcomes rather than the artificial selection of a single primary outcome. © 2009 Movement Disorder Society</div></front></TEI><istex><corpusName>wiley</corpusName><author><json:item><name>Peng Huang PhD</name><affiliations><json:string>Division of Oncology Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA</json:string></affiliations></json:item><json:item><name>Christopher G. Goetz MD</name><affiliations><json:string>Department of Medicine, Rush University Medical Center, Chicago, Illinois, USA</json:string></affiliations></json:item><json:item><name>Robert F. Woolson PhD</name><affiliations><json:string>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</json:string></affiliations></json:item><json:item><name>Barbara Tilley PhD</name><affiliations><json:string>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</json:string></affiliations></json:item><json:item><name>Douglas Kerr MD</name><affiliations><json:string>Division of Oncology Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA</json:string></affiliations></json:item><json:item><name>Yuko Palesch PhD</name><affiliations><json:string>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</json:string></affiliations></json:item><json:item><name>Jordan Elm MA</name><affiliations><json:string>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</json:string></affiliations></json:item><json:item><name>Bernard Ravina MD, CCRC</name><affiliations><json:string>Department of Neurology, University of Rochester, Rochester, New York, USA</json:string></affiliations></json:item><json:item><name>Kenneth J. Bergmann MD</name><affiliations><json:string>U.S. Food and Drug Administration, Silver Spring, Maryland, USA</json:string></affiliations></json:item><json:item><name>Karl Kieburtz MD</name><affiliations><json:string>Department of Neurology, University of Rochester, Rochester, New York, USA</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>multiple outcomes</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>global treatment effect</value></json:item></subject><articleId><json:string>MDS22645</json:string></articleId><language><json:string>eng</json:string></language><abstract>Parkinson's disease (PD) impairments are multidimensional, making it difficult to choose a single primary outcome when evaluating treatments to stop or lessen the long‐term decline in PD. We review commonly used multivariate statistical methods for assessing a treatment's global impact, and we highlight the novel Global Statistical Test (GST) methodology. We compare the GST to other multivariate approaches using data from two PD trials. In one trial where the treatment showed consistent improvement on all primary and secondary outcomes, the GST was more powerful than other methods in demonstrating significant improvement. In the trial where treatment induced both improvement and deterioration in key outcomes, the GST failed to demonstrate statistical evidence even though other techniques showed significant improvement. Based on the statistical properties of the GST and its relevance to overall treatment benefit, the GST appears particularly well suited for a disease like PD where disability and impairment reflect dysfunction of diverse brain systems and where both disease and treatment side effects impact quality of life. In future long term trials, use of GST for primary statistical analysis would allow the assessment of clinically relevant outcomes rather than the artificial selection of a single primary outcome. © 2009 Movement Disorder Society</abstract><qualityIndicators><score>7.412</score><pdfVersion>1.3</pdfVersion><pdfPageSize>612 x 810 pts</pdfPageSize><refBibsNative>true</refBibsNative><keywordCount>2</keywordCount><abstractCharCount>1369</abstractCharCount><pdfWordCount>5215</pdfWordCount><pdfCharCount>34756</pdfCharCount><pdfPageCount>8</pdfPageCount><abstractWordCount>201</abstractWordCount></qualityIndicators><title>Using global statistical tests in long‐term Parkinson's disease clinical trials</title><genre><json:string>review-article</json:string></genre><host><volume>24</volume><publisherId><json:string>MDS</json:string></publisherId><pages><total>8</total><last>1739</last><first>1732</first></pages><issn><json:string>0885-3185</json:string></issn><issue>12</issue><subject><json:item><value>Viewpoint</value></json:item></subject><genre><json:string>Journal</json:string></genre><language><json:string>unknown</json:string></language><eissn><json:string>1531-8257</json:string></eissn><title>Movement Disorders</title><doi><json:string>10.1002/(ISSN)1531-8257</json:string></doi></host><publicationDate>2009</publicationDate><copyrightDate>2009</copyrightDate><doi><json:string>10.1002/mds.22645</json:string></doi><id>18E069528157DF39F4838E56F149062782877FCC</id><fulltext><json:item><original>true</original><mimetype>application/pdf</mimetype><extension>pdf</extension><uri>https://api.istex.fr/document/18E069528157DF39F4838E56F149062782877FCC/fulltext/pdf</uri></json:item><json:item><original>false</original><mimetype>application/zip</mimetype><extension>zip</extension><uri>https://api.istex.fr/document/18E069528157DF39F4838E56F149062782877FCC/fulltext/zip</uri></json:item><istex:fulltextTEI uri="https://api.istex.fr/document/18E069528157DF39F4838E56F149062782877FCC/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a" type="main" xml:lang="en">Using global statistical tests in long‐term Parkinson's disease clinical trials</title></titleStmt><publicationStmt><authority>ISTEX</authority><publisher>Wiley Subscription Services, Inc., A Wiley Company</publisher><pubPlace>Hoboken</pubPlace><availability><p>WILEY</p></availability><date>2009</date></publicationStmt><notesStmt><note type="content">*Potential conflict of interest: Nothing to report.</note><note>MCRF</note><note>FHA05CRF</note><note>NIH/NINDS - No. U01NS043127; No. U01NS043128;</note></notesStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a" type="main" xml:lang="en">Using global statistical tests in long‐term Parkinson's disease clinical trials</title><author><persName><forename type="first">Peng</forename><surname>Huang</surname></persName><roleName type="degree">PhD</roleName><note type="correspondence"><p>Correspondence: SKCCC Biostatistics Division, School of Medicine, Johns Hopkins University, 550 N. Broadway, STE 1103, Baltimore, Maryland 21209</p></note><affiliation>Division of Oncology Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA</affiliation></author><author><persName><forename type="first">Christopher G.</forename><surname>Goetz</surname></persName><roleName type="degree">MD</roleName><affiliation>Department of Medicine, Rush University Medical Center, Chicago, Illinois, USA</affiliation></author><author><persName><forename type="first">Robert F.</forename><surname>Woolson</surname></persName><roleName type="degree">PhD</roleName><affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</affiliation></author><author><persName><forename type="first">Barbara</forename><surname>Tilley</surname></persName><roleName type="degree">PhD</roleName><affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</affiliation></author><author><persName><forename type="first">Douglas</forename><surname>Kerr</surname></persName><roleName type="degree">MD</roleName><affiliation>Division of Oncology Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA</affiliation></author><author><persName><forename type="first">Yuko</forename><surname>Palesch</surname></persName><roleName type="degree">PhD</roleName><affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</affiliation></author><author><persName><forename type="first">Jordan</forename><surname>Elm</surname></persName><roleName type="degree">MA</roleName><affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</affiliation></author><author><persName><forename type="first">Bernard</forename><surname>Ravina</surname></persName><roleName type="degree">MD, CCRC</roleName><affiliation>Department of Neurology, University of Rochester, Rochester, New York, USA</affiliation></author><author><persName><forename type="first">Kenneth J.</forename><surname>Bergmann</surname></persName><roleName type="degree">MD</roleName><affiliation>U.S. Food and Drug Administration, Silver Spring, Maryland, USA</affiliation></author><author><persName><forename type="first">Karl</forename><surname>Kieburtz</surname></persName><roleName type="degree">MD</roleName><affiliation>Department of Neurology, University of Rochester, Rochester, New York, USA</affiliation></author></analytic><monogr><title level="j">Movement Disorders</title><title level="j" type="abbrev">Mov. Disord.</title><idno type="pISSN">0885-3185</idno><idno type="eISSN">1531-8257</idno><idno type="DOI">10.1002/(ISSN)1531-8257</idno><imprint><publisher>Wiley Subscription Services, Inc., A Wiley Company</publisher><pubPlace>Hoboken</pubPlace><date type="published" when="2009-09-15"></date><biblScope unit="volume">24</biblScope><biblScope unit="issue">12</biblScope><biblScope unit="page" from="1732">1732</biblScope><biblScope unit="page" to="1739">1739</biblScope></imprint></monogr><idno type="istex">18E069528157DF39F4838E56F149062782877FCC</idno><idno type="DOI">10.1002/mds.22645</idno><idno type="ArticleID">MDS22645</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>2009</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>Parkinson's disease (PD) impairments are multidimensional, making it difficult to choose a single primary outcome when evaluating treatments to stop or lessen the long‐term decline in PD. We review commonly used multivariate statistical methods for assessing a treatment's global impact, and we highlight the novel Global Statistical Test (GST) methodology. We compare the GST to other multivariate approaches using data from two PD trials. In one trial where the treatment showed consistent improvement on all primary and secondary outcomes, the GST was more powerful than other methods in demonstrating significant improvement. In the trial where treatment induced both improvement and deterioration in key outcomes, the GST failed to demonstrate statistical evidence even though other techniques showed significant improvement. Based on the statistical properties of the GST and its relevance to overall treatment benefit, the GST appears particularly well suited for a disease like PD where disability and impairment reflect dysfunction of diverse brain systems and where both disease and treatment side effects impact quality of life. In future long term trials, use of GST for primary statistical analysis would allow the assessment of clinically relevant outcomes rather than the artificial selection of a single primary outcome. © 2009 Movement Disorder Society</p></abstract><textClass xml:lang="en"><keywords scheme="keyword"><list><head>Keywords</head><item><term>multiple outcomes</term></item><item><term>global treatment effect</term></item></list></keywords></textClass><textClass><keywords scheme="Journal Subject"><list><head>article category</head><item><term>Viewpoint</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="2008-12-09">Received</change><change when="2009-04-03">Registration</change><change when="2009-09-15">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><original>false</original><mimetype>text/plain</mimetype><extension>txt</extension><uri>https://api.istex.fr/document/18E069528157DF39F4838E56F149062782877FCC/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Wiley, elements deleted: body"><istex:xmlDeclaration>version="1.0" encoding="UTF-8" standalone="yes"</istex:xmlDeclaration><istex:document><component version="2.0" type="serialArticle" xml:lang="en"><header><publicationMeta level="product"><publisherInfo><publisherName>Wiley Subscription Services, Inc., A Wiley Company</publisherName><publisherLoc>Hoboken</publisherLoc></publisherInfo><doi registered="yes">10.1002/(ISSN)1531-8257</doi><issn type="print">0885-3185</issn><issn type="electronic">1531-8257</issn><idGroup><id type="product" value="MDS"></id></idGroup><titleGroup><title type="main" xml:lang="en" sort="MOVEMENT DISORDERS">Movement Disorders</title><title type="short">Mov. Disord.</title></titleGroup></publicationMeta><publicationMeta level="part" position="120"><doi origin="wiley" registered="yes">10.1002/mds.v24:12</doi><numberingGroup><numbering type="journalVolume" number="24">24</numbering><numbering type="journalIssue">12</numbering></numberingGroup><coverDate startDate="2009-09-15">15 September 2009</coverDate></publicationMeta><publicationMeta level="unit" type="reviewArticle" position="3" status="forIssue"><doi origin="wiley" registered="yes">10.1002/mds.22645</doi><idGroup><id type="unit" value="MDS22645"></id></idGroup><countGroup><count type="pageTotal" number="8"></count></countGroup><titleGroup><title type="articleCategory">Viewpoint</title><title type="tocHeading1">Viewpoints</title></titleGroup><copyright ownership="thirdParty">Copyright © 2009 Movement Disorder Society</copyright><eventGroup><event type="manuscriptReceived" date="2008-12-09"></event><event type="manuscriptRevised" date="2009-03-23"></event><event type="manuscriptAccepted" date="2009-04-03"></event><event type="publishedOnlineEarlyUnpaginated" date="2009-06-09"></event><event type="firstOnline" date="2009-06-09"></event><event type="publishedOnlineFinalForm" date="2009-09-11"></event><event type="xmlConverted" agent="Converter:JWSART34_TO_WML3G version:2.3.15 mode:FullText source:FullText result:FullText" date="2010-07-15"></event><event type="xmlConverted" agent="Converter:WILEY_ML3G_TO_WILEY_ML3GV2 version:3.8.8" date="2014-02-02"></event><event type="xmlConverted" agent="Converter:WML3G_To_WML3G version:4.1.7 mode:FullText,remove_FC" date="2014-10-31"></event></eventGroup><numberingGroup><numbering type="pageFirst">1732</numbering><numbering type="pageLast">1739</numbering></numberingGroup><correspondenceTo>SKCCC Biostatistics Division, School of Medicine, Johns Hopkins University, 550 N. Broadway, STE 1103, Baltimore, Maryland 21209</correspondenceTo><linkGroup><link type="toTypesetVersion" href="file:MDS.MDS22645.pdf"></link></linkGroup></publicationMeta><contentMeta><countGroup><count type="figureTotal" number="0"></count><count type="tableTotal" number="3"></count><count type="referenceTotal" number="39"></count><count type="wordTotal" number="7178"></count></countGroup><titleGroup><title type="main" xml:lang="en">Using global statistical tests in long‐term Parkinson's disease clinical trials<link href="#fn1"></link></title><title type="short" xml:lang="en">Global Statistical Test for PD Trials</title></titleGroup><creators><creator xml:id="au1" creatorRole="author" affiliationRef="#af1" corresponding="yes"><personName><givenNames>Peng</givenNames><familyName>Huang</familyName><degrees>PhD</degrees></personName><contactDetails><email>phuang12@jhmi.edu</email></contactDetails></creator><creator xml:id="au2" creatorRole="author" affiliationRef="#af2"><personName><givenNames>Christopher G.</givenNames><familyName>Goetz</familyName><degrees>MD</degrees></personName></creator><creator xml:id="au3" creatorRole="author" affiliationRef="#af3"><personName><givenNames>Robert F.</givenNames><familyName>Woolson</familyName><degrees>PhD</degrees></personName></creator><creator xml:id="au4" creatorRole="author" affiliationRef="#af3"><personName><givenNames>Barbara</givenNames><familyName>Tilley</familyName><degrees>PhD</degrees></personName></creator><creator xml:id="au5" creatorRole="author" affiliationRef="#af1"><personName><givenNames>Douglas</givenNames><familyName>Kerr</familyName><degrees>MD</degrees></personName></creator><creator xml:id="au6" creatorRole="author" affiliationRef="#af3"><personName><givenNames>Yuko</givenNames><familyName>Palesch</familyName><degrees>PhD</degrees></personName></creator><creator xml:id="au7" creatorRole="author" affiliationRef="#af3"><personName><givenNames>Jordan</givenNames><familyName>Elm</familyName><degrees>MA</degrees></personName></creator><creator xml:id="au8" creatorRole="author" affiliationRef="#af4"><personName><givenNames>Bernard</givenNames><familyName>Ravina</familyName><degrees>MD, CCRC</degrees></personName></creator><creator xml:id="au9" creatorRole="author" affiliationRef="#af5"><personName><givenNames>Kenneth J.</givenNames><familyName>Bergmann</familyName><degrees>MD</degrees></personName></creator><creator xml:id="au10" creatorRole="author" affiliationRef="#af4"><personName><givenNames>Karl</givenNames><familyName>Kieburtz</familyName><degrees>MD</degrees></personName></creator></creators><affiliationGroup><affiliation xml:id="af1" countryCode="US" type="organization"><unparsedAffiliation>Division of Oncology Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA</unparsedAffiliation></affiliation><affiliation xml:id="af2" countryCode="US" type="organization"><unparsedAffiliation>Department of Medicine, Rush University Medical Center, Chicago, Illinois, USA</unparsedAffiliation></affiliation><affiliation xml:id="af3" countryCode="US" type="organization"><unparsedAffiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</unparsedAffiliation></affiliation><affiliation xml:id="af4" countryCode="US" type="organization"><unparsedAffiliation>Department of Neurology, University of Rochester, Rochester, New York, USA</unparsedAffiliation></affiliation><affiliation xml:id="af5" countryCode="US" type="organization"><unparsedAffiliation>U.S. Food and Drug Administration, Silver Spring, Maryland, USA</unparsedAffiliation></affiliation></affiliationGroup><keywordGroup xml:lang="en" type="author"><keyword xml:id="kwd1">multiple outcomes</keyword><keyword xml:id="kwd2">global treatment effect</keyword></keywordGroup><fundingInfo><fundingAgency>MCRF</fundingAgency></fundingInfo><fundingInfo><fundingAgency>FHA05CRF</fundingAgency></fundingInfo><fundingInfo><fundingAgency>NIH/NINDS</fundingAgency><fundingNumber>U01NS043127</fundingNumber><fundingNumber>U01NS043128</fundingNumber></fundingInfo><abstractGroup><abstract type="main" xml:lang="en"><title type="main">Abstract</title><p>Parkinson's disease (PD) impairments are multidimensional, making it difficult to choose a single primary outcome when evaluating treatments to stop or lessen the long‐term decline in PD. We review commonly used multivariate statistical methods for assessing a treatment's global impact, and we highlight the novel Global Statistical Test (GST) methodology. We compare the GST to other multivariate approaches using data from two PD trials. In one trial where the treatment showed consistent improvement on all primary and secondary outcomes, the GST was more powerful than other methods in demonstrating significant improvement. In the trial where treatment induced both improvement and deterioration in key outcomes, the GST failed to demonstrate statistical evidence even though other techniques showed significant improvement. Based on the statistical properties of the GST and its relevance to overall treatment benefit, the GST appears particularly well suited for a disease like PD where disability and impairment reflect dysfunction of diverse brain systems and where both disease and treatment side effects impact quality of life. In future long term trials, use of GST for primary statistical analysis would allow the assessment of clinically relevant outcomes rather than the artificial selection of a single primary outcome. © 2009 Movement Disorder Society</p></abstract></abstractGroup></contentMeta><noteGroup><note xml:id="fn1"><p>Potential conflict of interest: Nothing to report.</p></note></noteGroup></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Using global statistical tests in long‐term Parkinson's disease clinical trials</title></titleInfo><titleInfo type="abbreviated" lang="en"><title>Global Statistical Test for PD Trials</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Using global statistical tests in long‐term Parkinson's disease clinical trials</title></titleInfo><name type="personal"><namePart type="given">Peng</namePart><namePart type="family">Huang</namePart><namePart type="termsOfAddress">PhD</namePart><affiliation>Division of Oncology Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA</affiliation><description>Correspondence: SKCCC Biostatistics Division, School of Medicine, Johns Hopkins University, 550 N. Broadway, STE 1103, Baltimore, Maryland 21209</description><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Christopher G.</namePart><namePart type="family">Goetz</namePart><namePart type="termsOfAddress">MD</namePart><affiliation>Department of Medicine, Rush University Medical Center, Chicago, Illinois, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Robert F.</namePart><namePart type="family">Woolson</namePart><namePart type="termsOfAddress">PhD</namePart><affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Barbara</namePart><namePart type="family">Tilley</namePart><namePart type="termsOfAddress">PhD</namePart><affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Douglas</namePart><namePart type="family">Kerr</namePart><namePart type="termsOfAddress">MD</namePart><affiliation>Division of Oncology Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Yuko</namePart><namePart type="family">Palesch</namePart><namePart type="termsOfAddress">PhD</namePart><affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Jordan</namePart><namePart type="family">Elm</namePart><namePart type="termsOfAddress">MA</namePart><affiliation>Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Bernard</namePart><namePart type="family">Ravina</namePart><namePart type="termsOfAddress">MD, CCRC</namePart><affiliation>Department of Neurology, University of Rochester, Rochester, New York, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Kenneth J.</namePart><namePart type="family">Bergmann</namePart><namePart type="termsOfAddress">MD</namePart><affiliation>U.S. Food and Drug Administration, Silver Spring, Maryland, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Karl</namePart><namePart type="family">Kieburtz</namePart><namePart type="termsOfAddress">MD</namePart><affiliation>Department of Neurology, University of Rochester, Rochester, New York, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="review-article" displayLabel="reviewArticle"></genre><originInfo><publisher>Wiley Subscription Services, Inc., A Wiley Company</publisher><place><placeTerm type="text">Hoboken</placeTerm></place><dateIssued encoding="w3cdtf">2009-09-15</dateIssued><dateCaptured encoding="w3cdtf">2008-12-09</dateCaptured><dateValid encoding="w3cdtf">2009-04-03</dateValid><copyrightDate encoding="w3cdtf">2009</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType><extent unit="tables">3</extent><extent unit="references">39</extent><extent unit="words">7178</extent></physicalDescription><abstract lang="en">Parkinson's disease (PD) impairments are multidimensional, making it difficult to choose a single primary outcome when evaluating treatments to stop or lessen the long‐term decline in PD. We review commonly used multivariate statistical methods for assessing a treatment's global impact, and we highlight the novel Global Statistical Test (GST) methodology. We compare the GST to other multivariate approaches using data from two PD trials. In one trial where the treatment showed consistent improvement on all primary and secondary outcomes, the GST was more powerful than other methods in demonstrating significant improvement. In the trial where treatment induced both improvement and deterioration in key outcomes, the GST failed to demonstrate statistical evidence even though other techniques showed significant improvement. Based on the statistical properties of the GST and its relevance to overall treatment benefit, the GST appears particularly well suited for a disease like PD where disability and impairment reflect dysfunction of diverse brain systems and where both disease and treatment side effects impact quality of life. In future long term trials, use of GST for primary statistical analysis would allow the assessment of clinically relevant outcomes rather than the artificial selection of a single primary outcome. © 2009 Movement Disorder Society</abstract><note type="content">*Potential conflict of interest: Nothing to report.</note><note type="funding">MCRF</note><note type="funding">FHA05CRF</note><note type="funding">NIH/NINDS - No. U01NS043127; No. U01NS043128; </note><subject lang="en"><genre>Keywords</genre><topic>multiple outcomes</topic><topic>global treatment effect</topic></subject><relatedItem type="host"><titleInfo><title>Movement Disorders</title></titleInfo><titleInfo type="abbreviated"><title>Mov. Disord.</title></titleInfo><genre type="Journal">journal</genre><subject><genre>article category</genre><topic>Viewpoint</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>2009</date><detail type="volume"><caption>vol.</caption><number>24</number></detail><detail type="issue"><caption>no.</caption><number>12</number></detail><extent unit="pages"><start>1732</start><end>1739</end><total>8</total></extent></part></relatedItem><identifier type="istex">18E069528157DF39F4838E56F149062782877FCC</identifier><identifier type="DOI">10.1002/mds.22645</identifier><identifier type="ArticleID">MDS22645</identifier><accessCondition type="use and reproduction" contentType="copyright">Copyright © 2009 Movement Disorder Society</accessCondition><recordInfo><recordContentSource>WILEY</recordContentSource><recordOrigin>Wiley Subscription Services, Inc., A Wiley Company</recordOrigin></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Sante/explor/ParkinsonV1/Data/Main/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 002047 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Corpus/biblio.hfd -nk 002047 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Sante
|area= ParkinsonV1
|flux= Main
|étape= Corpus
|type= RBID
|clé= ISTEX:18E069528157DF39F4838E56F149062782877FCC
|texte= Using global statistical tests in long‐term Parkinson's disease clinical trials
}}
| This area was generated with Dilib version V0.6.23. |  |