J03 The potential of a composite cognitive score for tracking progression in Huntington's disease
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Auteurs : C. Frost [Royaume-Uni] ; R. Jones [Royaume-Uni] ; I. Labuschange [Australie] ; M. Say [Royaume-Uni] ; D. Justo [France] ; A. Coleman [Canada] ; E. Dumas [Pays-Bas] ; E. 'T Hart [Royaume-Uni] ; G. Owen [Royaume-Uni] ; A. Durr [France] ; B. Leavitt [Canada] ; R. Roos [Pays-Bas] ; A. O'Regan [Australie] ; Sj Tabrizi [Royaume-Uni] ; Jc Stout [Australie]Source :
- Journal of Neurology, Neurosurgery & Psychiatry [ 0022-3050 ] ; 2012-09.
English descriptors
- KwdEn :
- 1movement disorders unit, 2biomedical research institute sant, 3european disease network, 3ucl institute, Accurate differentiation, Annualised rates, Aphp hopital, Bootstrap methodology, British columbia, Clinical characteristicsecognitive phenotype, Clinical characteristicsecognitive phenotype consequences, Clinical trial, Clinical trial design, Clinical trials, Cognitive, Cognitive alterations, Cognitive assessment, Cognitive decline, Cognitive impairment, Cognitive tasks, Cognitive test, Cognitive test scores, Cognitive variables, Composite score, Composite scores, Conclusions findings, Different patterns, Early stage, Effect sizes, Effects regression, European disease network, Future design, Germany background, Healthy controls, Information criterion, Iowa city, Leiden university, Likelihood ratio test, Linear regression models, Little uniformity, Logistic regression, London school, Long time, Longitudinal, Longitudinal analysis, Longitudinal change, Longitudinal changes, Longitudinal studies, Longitudinal trend, Medical genetics, Methods findings, Modelling techniques, Monash university, Morning afternoon, Motor diagnosis, Natural decline, Necessary step, Neurol neurosurg psychiatry september, Neuropsychological testing, Objective biomarkers, Optimal combination, Other measures, Other neurodegenerative disorders, Participant selection, Practice effects, Predicthd study, Prehd, Prehd population, Prehd stage, Prognostic values, Recent neuroimaging studies, Registry investigators, Results findings, Same sample, Sample sizes, Santa creu, Sensitive assessments, Several ways, Statistical models, Study entrance, Testing models, Time epochs, Triad symptoms characterising disease, Tropical medicine, Uniform criteria, Universitat munster, University college london, University hospital munster, Urgent need, Various outcomes, Westfalische wilhelms.
- Teeft :
- 1movement disorders unit, 2biomedical research institute sant, 3european disease network, 3ucl institute, Accurate differentiation, Annualised rates, Aphp hopital, Bootstrap methodology, British columbia, Clinical characteristicsecognitive phenotype, Clinical characteristicsecognitive phenotype consequences, Clinical trial, Clinical trial design, Clinical trials, Cognitive, Cognitive alterations, Cognitive assessment, Cognitive decline, Cognitive impairment, Cognitive tasks, Cognitive test, Cognitive test scores, Cognitive variables, Composite score, Composite scores, Conclusions findings, Different patterns, Early stage, Effect sizes, Effects regression, European disease network, Future design, Germany background, Healthy controls, Information criterion, Iowa city, Leiden university, Likelihood ratio test, Linear regression models, Little uniformity, Logistic regression, London school, Long time, Longitudinal, Longitudinal analysis, Longitudinal change, Longitudinal changes, Longitudinal studies, Longitudinal trend, Medical genetics, Methods findings, Modelling techniques, Monash university, Morning afternoon, Motor diagnosis, Natural decline, Necessary step, Neurol neurosurg psychiatry september, Neuropsychological testing, Objective biomarkers, Optimal combination, Other measures, Other neurodegenerative disorders, Participant selection, Practice effects, Predicthd study, Prehd, Prehd population, Prehd stage, Prognostic values, Recent neuroimaging studies, Registry investigators, Results findings, Same sample, Sample sizes, Santa creu, Sensitive assessments, Several ways, Statistical models, Study entrance, Testing models, Time epochs, Triad symptoms characterising disease, Tropical medicine, Uniform criteria, Universitat munster, University college london, University hospital munster, Urgent need, Various outcomes, Westfalische wilhelms.
Abstract
Background/Aims We investigated the ability of composite scores developed using statistical models to differentiate progressive cognitive deterioration in Huntington's disease (HD) from natural decline in healthy controls. Methods Using data from TRACK-HD the optimal combination of 24-month changes in quantitative cognitive measures to differentiate early stage HD individuals from controls was determined using logistic regression. Composite scores were calculated from the parameters of the model. Linear regression models were used to calculate effect sizes (ES) quantifying the difference in longitudinal change in the composite over 24 months between premanifest and early stage HD groups and controls respectively. This ES was compared with those for individual cognitive outcomes and other measures used in HD research. 0.632 bootstrap methodology was used to allow for biases which result from developing and testing models in the same sample. Results The composite score gave an ES for the difference in rate of 24-month change between early HD and controls of 1.14 (95% CI 0.90 to 1.39): larger than that for any of the individual cognitive outcomes and those for the UHDRS TFC and TMS. Additionally the composite gave a statistically significant difference in the rate of change in premanifest HD compared to controls over 24-months (ES: 0.24; 95% CI 0.04 to 0.44), despite none of the individual cognitive outcomes having statistically significant ES over this period. Conclusions Composite scores developed using appropriate statistical modelling techniques have the potential to materially reduce required sample sizes for randomised controlled trials.
Url:
DOI: 10.1136/jnnp-2012-303524.113
Affiliations:
- Australie, Canada, France, Pays-Bas, Royaume-Uni
- Angleterre, Grand Londres, Hollande-Méridionale, Île-de-France
- Leyde, Londres, Paris
- University College de Londres
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O'Regan</name><affiliation wicri:level="1"><country xml:lang="fr">Australie</country><wicri:regionArea>School of Psychology and Psychiatry, Monash University, Victoria</wicri:regionArea><wicri:noRegion>Victoria</wicri:noRegion></affiliation></author><author><name sortKey="Tabrizi, Sj" sort="Tabrizi, Sj" uniqKey="Tabrizi S" first="Sj" last="Tabrizi">Sj Tabrizi</name><affiliation wicri:level="4"><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>UCL Institute of Neurology, University College London, London</wicri:regionArea><placeName><settlement type="city">Londres</settlement><region type="country">Angleterre</region><region type="région" nuts="1">Grand Londres</region><settlement type="city">Londres</settlement></placeName><orgName type="university">University College de Londres</orgName></affiliation></author><author><name sortKey="Stout, Jc" sort="Stout, Jc" uniqKey="Stout J" first="Jc" last="Stout">Jc Stout</name><affiliation wicri:level="1"><country xml:lang="fr">Australie</country><wicri:regionArea>School of Psychology and Psychiatry, Monash University, Victoria</wicri:regionArea><wicri:noRegion>Victoria</wicri:noRegion></affiliation></author></analytic><monogr></monogr><series><title level="j">Journal of Neurology, Neurosurgery & Psychiatry</title><title level="j" type="abbrev">J Neurol Neurosurg Psychiatry</title><idno type="ISSN">0022-3050</idno><idno type="eISSN">1468-330X</idno><imprint><publisher>BMJ Publishing Group Ltd</publisher><date type="published" when="2012-09">2012-09</date><biblScope unit="volume">83</biblScope><biblScope unit="issue">Suppl 1</biblScope><biblScope unit="page" from="A36">A36</biblScope></imprint><idno type="ISSN">0022-3050</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0022-3050</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>1movement disorders unit</term><term>2biomedical research institute sant</term><term>3european disease network</term><term>3ucl institute</term><term>Accurate differentiation</term><term>Annualised rates</term><term>Aphp hopital</term><term>Bootstrap methodology</term><term>British columbia</term><term>Clinical characteristicsecognitive phenotype</term><term>Clinical characteristicsecognitive phenotype consequences</term><term>Clinical trial</term><term>Clinical trial design</term><term>Clinical trials</term><term>Cognitive</term><term>Cognitive alterations</term><term>Cognitive assessment</term><term>Cognitive decline</term><term>Cognitive impairment</term><term>Cognitive tasks</term><term>Cognitive test</term><term>Cognitive test scores</term><term>Cognitive variables</term><term>Composite score</term><term>Composite scores</term><term>Conclusions findings</term><term>Different patterns</term><term>Early stage</term><term>Effect sizes</term><term>Effects regression</term><term>European disease network</term><term>Future design</term><term>Germany background</term><term>Healthy controls</term><term>Information criterion</term><term>Iowa city</term><term>Leiden university</term><term>Likelihood ratio test</term><term>Linear regression models</term><term>Little uniformity</term><term>Logistic regression</term><term>London school</term><term>Long time</term><term>Longitudinal</term><term>Longitudinal analysis</term><term>Longitudinal change</term><term>Longitudinal changes</term><term>Longitudinal studies</term><term>Longitudinal trend</term><term>Medical genetics</term><term>Methods findings</term><term>Modelling techniques</term><term>Monash university</term><term>Morning afternoon</term><term>Motor diagnosis</term><term>Natural decline</term><term>Necessary step</term><term>Neurol neurosurg psychiatry september</term><term>Neuropsychological testing</term><term>Objective biomarkers</term><term>Optimal combination</term><term>Other measures</term><term>Other neurodegenerative disorders</term><term>Participant selection</term><term>Practice effects</term><term>Predicthd study</term><term>Prehd</term><term>Prehd population</term><term>Prehd stage</term><term>Prognostic values</term><term>Recent neuroimaging studies</term><term>Registry investigators</term><term>Results findings</term><term>Same sample</term><term>Sample sizes</term><term>Santa creu</term><term>Sensitive assessments</term><term>Several ways</term><term>Statistical models</term><term>Study entrance</term><term>Testing models</term><term>Time epochs</term><term>Triad symptoms characterising disease</term><term>Tropical medicine</term><term>Uniform criteria</term><term>Universitat munster</term><term>University college london</term><term>University hospital munster</term><term>Urgent need</term><term>Various outcomes</term><term>Westfalische wilhelms</term></keywords><keywords scheme="Teeft" xml:lang="en"><term>1movement disorders unit</term><term>2biomedical research institute sant</term><term>3european disease network</term><term>3ucl institute</term><term>Accurate differentiation</term><term>Annualised rates</term><term>Aphp hopital</term><term>Bootstrap methodology</term><term>British columbia</term><term>Clinical characteristicsecognitive phenotype</term><term>Clinical characteristicsecognitive phenotype consequences</term><term>Clinical trial</term><term>Clinical trial design</term><term>Clinical trials</term><term>Cognitive</term><term>Cognitive alterations</term><term>Cognitive assessment</term><term>Cognitive decline</term><term>Cognitive impairment</term><term>Cognitive tasks</term><term>Cognitive test</term><term>Cognitive test scores</term><term>Cognitive variables</term><term>Composite score</term><term>Composite scores</term><term>Conclusions findings</term><term>Different patterns</term><term>Early stage</term><term>Effect sizes</term><term>Effects regression</term><term>European disease network</term><term>Future design</term><term>Germany background</term><term>Healthy controls</term><term>Information criterion</term><term>Iowa city</term><term>Leiden university</term><term>Likelihood ratio test</term><term>Linear regression models</term><term>Little uniformity</term><term>Logistic regression</term><term>London school</term><term>Long time</term><term>Longitudinal</term><term>Longitudinal analysis</term><term>Longitudinal change</term><term>Longitudinal changes</term><term>Longitudinal studies</term><term>Longitudinal trend</term><term>Medical genetics</term><term>Methods findings</term><term>Modelling techniques</term><term>Monash university</term><term>Morning afternoon</term><term>Motor diagnosis</term><term>Natural decline</term><term>Necessary step</term><term>Neurol neurosurg psychiatry september</term><term>Neuropsychological testing</term><term>Objective biomarkers</term><term>Optimal combination</term><term>Other measures</term><term>Other neurodegenerative disorders</term><term>Participant selection</term><term>Practice effects</term><term>Predicthd study</term><term>Prehd</term><term>Prehd population</term><term>Prehd stage</term><term>Prognostic values</term><term>Recent neuroimaging studies</term><term>Registry investigators</term><term>Results findings</term><term>Same sample</term><term>Sample sizes</term><term>Santa creu</term><term>Sensitive assessments</term><term>Several ways</term><term>Statistical models</term><term>Study entrance</term><term>Testing models</term><term>Time epochs</term><term>Triad symptoms characterising disease</term><term>Tropical medicine</term><term>Uniform criteria</term><term>Universitat munster</term><term>University college london</term><term>University hospital munster</term><term>Urgent need</term><term>Various outcomes</term><term>Westfalische wilhelms</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract">Background/Aims We investigated the ability of composite scores developed using statistical models to differentiate progressive cognitive deterioration in Huntington's disease (HD) from natural decline in healthy controls. Methods Using data from TRACK-HD the optimal combination of 24-month changes in quantitative cognitive measures to differentiate early stage HD individuals from controls was determined using logistic regression. Composite scores were calculated from the parameters of the model. Linear regression models were used to calculate effect sizes (ES) quantifying the difference in longitudinal change in the composite over 24 months between premanifest and early stage HD groups and controls respectively. This ES was compared with those for individual cognitive outcomes and other measures used in HD research. 0.632 bootstrap methodology was used to allow for biases which result from developing and testing models in the same sample. Results The composite score gave an ES for the difference in rate of 24-month change between early HD and controls of 1.14 (95% CI 0.90 to 1.39): larger than that for any of the individual cognitive outcomes and those for the UHDRS TFC and TMS. Additionally the composite gave a statistically significant difference in the rate of change in premanifest HD compared to controls over 24-months (ES: 0.24; 95% CI 0.04 to 0.44), despite none of the individual cognitive outcomes having statistically significant ES over this period. Conclusions Composite scores developed using appropriate statistical modelling techniques have the potential to materially reduce required sample sizes for randomised controlled trials.</div></front></TEI><affiliations><list><country><li>Australie</li><li>Canada</li><li>France</li><li>Pays-Bas</li><li>Royaume-Uni</li></country><region><li>Angleterre</li><li>Grand Londres</li><li>Hollande-Méridionale</li><li>Île-de-France</li></region><settlement><li>Leyde</li><li>Londres</li><li>Paris</li></settlement><orgName><li>University College de Londres</li></orgName></list><tree><country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Frost, C" sort="Frost, C" uniqKey="Frost C" first="C" last="Frost">C. Frost</name></region><name sortKey=" T Hart, E" sort=" T Hart, E" uniqKey=" T Hart E" first="E" last="'T Hart">E. 'T Hart</name><name sortKey="Jones, R" sort="Jones, R" uniqKey="Jones R" first="R" last="Jones">R. Jones</name><name sortKey="Owen, G" sort="Owen, G" uniqKey="Owen G" first="G" last="Owen">G. Owen</name><name sortKey="Say, M" sort="Say, M" uniqKey="Say M" first="M" last="Say">M. Say</name><name sortKey="Tabrizi, Sj" sort="Tabrizi, Sj" uniqKey="Tabrizi S" first="Sj" last="Tabrizi">Sj Tabrizi</name></country><country name="Australie"><noRegion><name sortKey="Labuschange, I" sort="Labuschange, I" uniqKey="Labuschange I" first="I" last="Labuschange">I. Labuschange</name></noRegion><name sortKey="O Regan, A" sort="O Regan, A" uniqKey="O Regan A" first="A" last="O'Regan">A. O'Regan</name><name sortKey="Stout, Jc" sort="Stout, Jc" uniqKey="Stout J" first="Jc" last="Stout">Jc Stout</name></country><country name="France"><region name="Île-de-France"><name sortKey="Justo, D" sort="Justo, D" uniqKey="Justo D" first="D" last="Justo">D. Justo</name></region><name sortKey="Durr, A" sort="Durr, A" uniqKey="Durr A" first="A" last="Durr">A. Durr</name></country><country name="Canada"><noRegion><name sortKey="Coleman, A" sort="Coleman, A" uniqKey="Coleman A" first="A" last="Coleman">A. Coleman</name></noRegion><name sortKey="Leavitt, B" sort="Leavitt, B" uniqKey="Leavitt B" first="B" last="Leavitt">B. Leavitt</name></country><country name="Pays-Bas"><region name="Hollande-Méridionale"><name sortKey="Dumas, E" sort="Dumas, E" uniqKey="Dumas E" first="E" last="Dumas">E. Dumas</name></region><name sortKey="Roos, R" sort="Roos, R" uniqKey="Roos R" first="R" last="Roos">R. Roos</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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