Predicting Ambulatory Capacity in Parkinson's Disease to Analyze Progression, Biomarkers, and Trial Design
In Parkinson's disease (PD), gait and balance is impaired, relatively resistant to available treatment and associated with falls and disability. Predictive models of ambulatory progression could enhance understanding of gait/balance disturbances and aid in trial design. To predict trajectories...
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Veröffentlicht in: | Movement disorders 2023-10, Vol.38 (10), p.1774-1785 |
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creator | Venuto, Charles S Smith, Greta Herbst, Konnor Zielinski, Robert Yung, Norman C W Grosset, Donald G Dorsey, E Ray Kieburtz, Karl |
description | In Parkinson's disease (PD), gait and balance is impaired, relatively resistant to available treatment and associated with falls and disability. Predictive models of ambulatory progression could enhance understanding of gait/balance disturbances and aid in trial design.
To predict trajectories of ambulatory abilities from baseline clinical data in early PD, relate trajectories to clinical milestones, compare biomarkers, and evaluate trajectories for enrichment of clinical trials.
Data from two multicenter, longitudinal, observational studies were used for model training (Tracking Parkinson's, n = 1598) and external testing (Parkinson's Progression Markers Initiative, n = 407). Models were trained and validated to predict individuals as having a "Progressive" or "Stable" trajectory based on changes of ambulatory capacity scores from the Movement Disorders Society Unified Parkinson's Disease Rating Scale parts II and III. Survival analyses compared time-to-clinical milestones and trial outcomes between predicted trajectories.
On external evaluation, a support vector machine model predicted Progressive trajectories using baseline clinical data with an accuracy, weighted-F1 (proportionally weighted harmonic mean of precision and sensitivity), and sensitivity/specificity of 0.735, 0.799, and 0.688/0.739, respectively. Over 4 years, the predicted Progressive trajectory was more likely to experience impaired balance, loss of independence, impaired function and cognition. Baseline dopamine transporter imaging and select biomarkers of neurodegeneration were significantly different between predicted trajectory groups. For an 18-month, randomized (1:1) clinical trial, sample size savings up to 30% were possible when enrollment was enriched for the Progressive trajectory versus no enrichment.
It is possible to predict ambulatory abilities from clinical data that are associated with meaningful outcomes in people with early PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. |
doi_str_mv | 10.1002/mds.29519 |
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To predict trajectories of ambulatory abilities from baseline clinical data in early PD, relate trajectories to clinical milestones, compare biomarkers, and evaluate trajectories for enrichment of clinical trials.
Data from two multicenter, longitudinal, observational studies were used for model training (Tracking Parkinson's, n = 1598) and external testing (Parkinson's Progression Markers Initiative, n = 407). Models were trained and validated to predict individuals as having a "Progressive" or "Stable" trajectory based on changes of ambulatory capacity scores from the Movement Disorders Society Unified Parkinson's Disease Rating Scale parts II and III. Survival analyses compared time-to-clinical milestones and trial outcomes between predicted trajectories.
On external evaluation, a support vector machine model predicted Progressive trajectories using baseline clinical data with an accuracy, weighted-F1 (proportionally weighted harmonic mean of precision and sensitivity), and sensitivity/specificity of 0.735, 0.799, and 0.688/0.739, respectively. Over 4 years, the predicted Progressive trajectory was more likely to experience impaired balance, loss of independence, impaired function and cognition. Baseline dopamine transporter imaging and select biomarkers of neurodegeneration were significantly different between predicted trajectory groups. For an 18-month, randomized (1:1) clinical trial, sample size savings up to 30% were possible when enrollment was enriched for the Progressive trajectory versus no enrichment.
It is possible to predict ambulatory abilities from clinical data that are associated with meaningful outcomes in people with early PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</description><identifier>ISSN: 0885-3185</identifier><identifier>ISSN: 1531-8257</identifier><identifier>EISSN: 1531-8257</identifier><identifier>DOI: 10.1002/mds.29519</identifier><identifier>PMID: 37363815</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Balance ; Biomarkers ; Clinical trials ; Cognition ; Disease Progression ; Dopamine transporter ; Gait ; Humans ; Mental Status and Dementia Tests ; Movement disorders ; Neurodegeneration ; Neurodegenerative diseases ; Parkinson Disease - complications ; Parkinson's disease ; Physical Therapy Modalities ; Prediction models</subject><ispartof>Movement disorders, 2023-10, Vol.38 (10), p.1774-1785</ispartof><rights>2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</rights><rights>2023. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c364t-d600520960c4a9121a1a6e925473266481c9541457e969519ebc13863d2a81f63</cites><orcidid>0000-0002-2394-9513</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37363815$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Venuto, Charles S</creatorcontrib><creatorcontrib>Smith, Greta</creatorcontrib><creatorcontrib>Herbst, Konnor</creatorcontrib><creatorcontrib>Zielinski, Robert</creatorcontrib><creatorcontrib>Yung, Norman C W</creatorcontrib><creatorcontrib>Grosset, Donald G</creatorcontrib><creatorcontrib>Dorsey, E Ray</creatorcontrib><creatorcontrib>Kieburtz, Karl</creatorcontrib><title>Predicting Ambulatory Capacity in Parkinson's Disease to Analyze Progression, Biomarkers, and Trial Design</title><title>Movement disorders</title><addtitle>Mov Disord</addtitle><description>In Parkinson's disease (PD), gait and balance is impaired, relatively resistant to available treatment and associated with falls and disability. Predictive models of ambulatory progression could enhance understanding of gait/balance disturbances and aid in trial design.
To predict trajectories of ambulatory abilities from baseline clinical data in early PD, relate trajectories to clinical milestones, compare biomarkers, and evaluate trajectories for enrichment of clinical trials.
Data from two multicenter, longitudinal, observational studies were used for model training (Tracking Parkinson's, n = 1598) and external testing (Parkinson's Progression Markers Initiative, n = 407). Models were trained and validated to predict individuals as having a "Progressive" or "Stable" trajectory based on changes of ambulatory capacity scores from the Movement Disorders Society Unified Parkinson's Disease Rating Scale parts II and III. Survival analyses compared time-to-clinical milestones and trial outcomes between predicted trajectories.
On external evaluation, a support vector machine model predicted Progressive trajectories using baseline clinical data with an accuracy, weighted-F1 (proportionally weighted harmonic mean of precision and sensitivity), and sensitivity/specificity of 0.735, 0.799, and 0.688/0.739, respectively. Over 4 years, the predicted Progressive trajectory was more likely to experience impaired balance, loss of independence, impaired function and cognition. Baseline dopamine transporter imaging and select biomarkers of neurodegeneration were significantly different between predicted trajectory groups. For an 18-month, randomized (1:1) clinical trial, sample size savings up to 30% were possible when enrollment was enriched for the Progressive trajectory versus no enrichment.
It is possible to predict ambulatory abilities from clinical data that are associated with meaningful outcomes in people with early PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</description><subject>Balance</subject><subject>Biomarkers</subject><subject>Clinical trials</subject><subject>Cognition</subject><subject>Disease Progression</subject><subject>Dopamine transporter</subject><subject>Gait</subject><subject>Humans</subject><subject>Mental Status and Dementia Tests</subject><subject>Movement disorders</subject><subject>Neurodegeneration</subject><subject>Neurodegenerative diseases</subject><subject>Parkinson Disease - complications</subject><subject>Parkinson's disease</subject><subject>Physical Therapy Modalities</subject><subject>Prediction models</subject><issn>0885-3185</issn><issn>1531-8257</issn><issn>1531-8257</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdkU1PGzEQhq2KqgTaQ_9AZYlDQWKpx157vScUQr8kpOZAz5bjdYLDrh08u5XCr2dTKIKe5jCPXr0zDyEfgZ0BY_xL1-AZryXUb8gEpIBCc1ntkQnTWhYCtNwnB4hrxgAkqHdkX1RCCQ1yQtbz7Jvg-hBXdNothtb2KW_pzG6sC_2WhkjnNt-GiCl-RnoZ0Fv0tE90Gm27vfd0ntMqe8SQ4im9CKkbcZ_xlNrY0OscbEsvPYZVfE_eLm2L_sPTPCS_v329nv0orn59_zmbXhVOqLIvGsWY5KxWzJW2Bg4WrPI1l2UluFKlBlfLEkpZ-VrtjvYLB0Ir0XCrYanEITl_zN0Mi843zsc-29ZschirbU2ywbzexHBjVumPAaZAVsDGhOOnhJzuBo-96QI637Y2-jSg4VowzrmU5Yge_Yeu05DH1-wozTlIrnbUySPlckLMfvncBpjZKTSjQvNX4ch-eln_mfznTDwAUqqV5A</recordid><startdate>20231001</startdate><enddate>20231001</enddate><creator>Venuto, Charles S</creator><creator>Smith, Greta</creator><creator>Herbst, Konnor</creator><creator>Zielinski, Robert</creator><creator>Yung, Norman C W</creator><creator>Grosset, Donald G</creator><creator>Dorsey, E Ray</creator><creator>Kieburtz, Karl</creator><general>Wiley Subscription Services, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-2394-9513</orcidid></search><sort><creationdate>20231001</creationdate><title>Predicting Ambulatory Capacity in Parkinson's Disease to Analyze Progression, Biomarkers, and Trial Design</title><author>Venuto, Charles S ; Smith, Greta ; Herbst, Konnor ; Zielinski, Robert ; Yung, Norman C W ; Grosset, Donald G ; Dorsey, E Ray ; Kieburtz, Karl</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c364t-d600520960c4a9121a1a6e925473266481c9541457e969519ebc13863d2a81f63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Balance</topic><topic>Biomarkers</topic><topic>Clinical trials</topic><topic>Cognition</topic><topic>Disease Progression</topic><topic>Dopamine transporter</topic><topic>Gait</topic><topic>Humans</topic><topic>Mental Status and Dementia Tests</topic><topic>Movement disorders</topic><topic>Neurodegeneration</topic><topic>Neurodegenerative diseases</topic><topic>Parkinson Disease - complications</topic><topic>Parkinson's disease</topic><topic>Physical Therapy Modalities</topic><topic>Prediction models</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Venuto, Charles S</creatorcontrib><creatorcontrib>Smith, Greta</creatorcontrib><creatorcontrib>Herbst, Konnor</creatorcontrib><creatorcontrib>Zielinski, Robert</creatorcontrib><creatorcontrib>Yung, Norman C W</creatorcontrib><creatorcontrib>Grosset, Donald G</creatorcontrib><creatorcontrib>Dorsey, E Ray</creatorcontrib><creatorcontrib>Kieburtz, Karl</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Movement disorders</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Venuto, Charles S</au><au>Smith, Greta</au><au>Herbst, Konnor</au><au>Zielinski, Robert</au><au>Yung, Norman C W</au><au>Grosset, Donald G</au><au>Dorsey, E Ray</au><au>Kieburtz, Karl</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting Ambulatory Capacity in Parkinson's Disease to Analyze Progression, Biomarkers, and Trial Design</atitle><jtitle>Movement disorders</jtitle><addtitle>Mov Disord</addtitle><date>2023-10-01</date><risdate>2023</risdate><volume>38</volume><issue>10</issue><spage>1774</spage><epage>1785</epage><pages>1774-1785</pages><issn>0885-3185</issn><issn>1531-8257</issn><eissn>1531-8257</eissn><abstract>In Parkinson's disease (PD), gait and balance is impaired, relatively resistant to available treatment and associated with falls and disability. Predictive models of ambulatory progression could enhance understanding of gait/balance disturbances and aid in trial design.
To predict trajectories of ambulatory abilities from baseline clinical data in early PD, relate trajectories to clinical milestones, compare biomarkers, and evaluate trajectories for enrichment of clinical trials.
Data from two multicenter, longitudinal, observational studies were used for model training (Tracking Parkinson's, n = 1598) and external testing (Parkinson's Progression Markers Initiative, n = 407). Models were trained and validated to predict individuals as having a "Progressive" or "Stable" trajectory based on changes of ambulatory capacity scores from the Movement Disorders Society Unified Parkinson's Disease Rating Scale parts II and III. Survival analyses compared time-to-clinical milestones and trial outcomes between predicted trajectories.
On external evaluation, a support vector machine model predicted Progressive trajectories using baseline clinical data with an accuracy, weighted-F1 (proportionally weighted harmonic mean of precision and sensitivity), and sensitivity/specificity of 0.735, 0.799, and 0.688/0.739, respectively. Over 4 years, the predicted Progressive trajectory was more likely to experience impaired balance, loss of independence, impaired function and cognition. Baseline dopamine transporter imaging and select biomarkers of neurodegeneration were significantly different between predicted trajectory groups. For an 18-month, randomized (1:1) clinical trial, sample size savings up to 30% were possible when enrollment was enriched for the Progressive trajectory versus no enrichment.
It is possible to predict ambulatory abilities from clinical data that are associated with meaningful outcomes in people with early PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>37363815</pmid><doi>10.1002/mds.29519</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-2394-9513</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Balance Biomarkers Clinical trials Cognition Disease Progression Dopamine transporter Gait Humans Mental Status and Dementia Tests Movement disorders Neurodegeneration Neurodegenerative diseases Parkinson Disease - complications Parkinson's disease Physical Therapy Modalities Prediction models |
title | Predicting Ambulatory Capacity in Parkinson's Disease to Analyze Progression, Biomarkers, and Trial Design |
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