A review of disease progression models of Parkinson's disease and applications in clinical trials
ABSTRACT Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In Parkinson's disease (PD), several models have described longitudinal changes in the Unified Parkinson's Disease Rating Scale (...
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| Published in | Movement disorders Vol. 31; no. 7; pp. 947 - 956 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Blackwell Publishing Ltd
01.07.2016
Wiley Subscription Services, Inc |
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| Online Access | Get full text |
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| Abstract | ABSTRACT
Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In Parkinson's disease (PD), several models have described longitudinal changes in the Unified Parkinson's Disease Rating Scale (UPDRS), one of the most utilized outcome measures for PD trials assessing disease progression. We conducted a literature review to examine the methods and applications of quantitative disease progression modeling for PD using a combination of key words including “Parkinson disease,” “progression,” and “model.” For this review, we focused on models of PD progression quantifying changes in the total UPDRS scores against time. Four different models reporting equations and parameters have been published using linear and nonlinear functions. The reasons for constructing disease progression models of PD thus far have been to quantify disease trajectories of PD patients in active and inactive treatment arms of clinical trials, to quantify and discern symptomatic and disease‐modifying treatment effects, and to demonstrate how model‐based methods may be used to design clinical trials. The historical lack of efficiency of PD clinical trials begs for model‐based simulations in planning for studies that result in more informative conclusions, particularly around disease modification. © 2016 International Parkinson and Movement Disorder Society |
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| AbstractList | Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In Parkinson's disease (PD), several models have described longitudinal changes in the Unified Parkinson's Disease Rating Scale (UPDRS), one of the most utilized outcome measures for PD trials assessing disease progression. We conducted a literature review to examine the methods and applications of quantitative disease progression modeling for PD using a combination of key words including "Parkinson disease," "progression," and "model." For this review, we focused on models of PD progression quantifying changes in the total UPDRS scores against time. Four different models reporting equations and parameters have been published using linear and nonlinear functions. The reasons for constructing disease progression models of PD thus far have been to quantify disease trajectories of PD patients in active and inactive treatment arms of clinical trials, to quantify and discern symptomatic and disease-modifying treatment effects, and to demonstrate how model-based methods may be used to design clinical trials. The historical lack of efficiency of PD clinical trials begs for model-based simulations in planning for studies that result in more informative conclusions, particularly around disease modification. © 2016 International Parkinson and Movement Disorder Society Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In Parkinson's disease (PD), several models have described longitudinal changes in the Unified Parkinson's Disease Rating Scale (UPDRS), one of the most utilized outcome measures for PD trials assessing disease progression. We conducted a literature review to examine the methods and applications of quantitative disease progression modeling for PD using a combination of key words including "Parkinson disease," "progression," and "model." For this review, we focused on models of PD progression quantifying changes in the total UPDRS scores against time. Four different models reporting equations and parameters have been published using linear and nonlinear functions. The reasons for constructing disease progression models of PD thus far have been to quantify disease trajectories of PD patients in active and inactive treatment arms of clinical trials, to quantify and discern symptomatic and disease-modifying treatment effects, and to demonstrate how model-based methods may be used to design clinical trials. The historical lack of efficiency of PD clinical trials begs for model-based simulations in planning for studies that result in more informative conclusions, particularly around disease modification. © 2016 International Parkinson and Movement Disorder Society. Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In Parkinson's disease (PD), several models have described longitudinal changes in the Unified Parkinson's Disease Rating Scale (UPDRS), one of the most utilized outcome measures for PD trials assessing disease progression. We conducted a literature review to examine the methods and applications of quantitative disease progression modeling for PD using a combination of key words including "Parkinson disease," "progression," and "model." For this review, we focused on models of PD progression quantifying changes in the total UPDRS scores against time. Four different models reporting equations and parameters have been published using linear and nonlinear functions. The reasons for constructing disease progression models of PD thus far have been to quantify disease trajectories of PD patients in active and inactive treatment arms of clinical trials, to quantify and discern symptomatic and disease-modifying treatment effects, and to demonstrate how model-based methods may be used to design clinical trials. The historical lack of efficiency of PD clinical trials begs for model-based simulations in planning for studies that result in more informative conclusions, particularly around disease modification. © 2016 International Parkinson and Movement Disorder Society.Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In Parkinson's disease (PD), several models have described longitudinal changes in the Unified Parkinson's Disease Rating Scale (UPDRS), one of the most utilized outcome measures for PD trials assessing disease progression. We conducted a literature review to examine the methods and applications of quantitative disease progression modeling for PD using a combination of key words including "Parkinson disease," "progression," and "model." For this review, we focused on models of PD progression quantifying changes in the total UPDRS scores against time. Four different models reporting equations and parameters have been published using linear and nonlinear functions. The reasons for constructing disease progression models of PD thus far have been to quantify disease trajectories of PD patients in active and inactive treatment arms of clinical trials, to quantify and discern symptomatic and disease-modifying treatment effects, and to demonstrate how model-based methods may be used to design clinical trials. The historical lack of efficiency of PD clinical trials begs for model-based simulations in planning for studies that result in more informative conclusions, particularly around disease modification. © 2016 International Parkinson and Movement Disorder Society. Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In Parkinson's disease (PD), several models have described longitudinal changes in the Unified Parkinson's Disease Rating Scale (UPDRS), one of the most utilized outcome measures for PD trials assessing disease progression. We conducted a literature review to examine the methods and applications of quantitative disease progression modeling for PD using a combination of key words including "Parkinson disease," "progression," and "model." For this review, we focused on models of PD progression quantifying changes in the total UPDRS scores against time. Four different models reporting equations and parameters have been published using linear and nonlinear functions. The reasons for constructing disease progression models of PD thus far have been to quantify disease trajectories of PD patients in active and inactive treatment arms of clinical trials, to quantify and discern symptomatic and disease-modifying treatment effects, and to demonstrate how model-based methods may be used to design clinical trials. The historical lack of efficiency of PD clinical trials begs for model-based simulations in planning for studies that result in more informative conclusions, particularly around disease modification. copyright 2016 International Parkinson and Movement Disorder Society Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In Parkinson's disease [PD], several models have described longitudinal changes in the Unified Parkinson's Disease Rating Scale [UPDRS], one of the most utilized outcome measures for PD trials assessing disease progression. We conducted a literature review to examine the methods and applications of quantitative disease progression modeling for PD using a combination of keywords including “Parkinson disease”, “progression”, and “model”. For this review, we focused on models of PD progression quantifying changes in the total UPDRS scores against time. Four different models reporting equations and parameters have been published using linear and nonlinear functions. The reasons for constructing disease progression models of PD thus far have been to quantify disease trajectories of PD patients in active and inactive treatment arms of clinical trials, to quantify and discern symptomatic and disease-modifying treatment effects, and to demonstrate how model-based methods may be used to design clinical trials. The historical lack of efficiency of PD clinical trials begs for model-based simulations in planning for studies that result in more informative conclusions, particularly around disease modification. ABSTRACT Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In Parkinson's disease (PD), several models have described longitudinal changes in the Unified Parkinson's Disease Rating Scale (UPDRS), one of the most utilized outcome measures for PD trials assessing disease progression. We conducted a literature review to examine the methods and applications of quantitative disease progression modeling for PD using a combination of key words including “Parkinson disease,” “progression,” and “model.” For this review, we focused on models of PD progression quantifying changes in the total UPDRS scores against time. Four different models reporting equations and parameters have been published using linear and nonlinear functions. The reasons for constructing disease progression models of PD thus far have been to quantify disease trajectories of PD patients in active and inactive treatment arms of clinical trials, to quantify and discern symptomatic and disease‐modifying treatment effects, and to demonstrate how model‐based methods may be used to design clinical trials. The historical lack of efficiency of PD clinical trials begs for model‐based simulations in planning for studies that result in more informative conclusions, particularly around disease modification. © 2016 International Parkinson and Movement Disorder Society |
| Author | Kieburtz, Karl Venuto, Charles S. Potter, Nicholas B. Ray Dorsey, E. |
| AuthorAffiliation | 1 Center for Human Experimental Therapeutics, University of Rochester, Rochester, NY, USA 2 Department of Neurology, University of Rochester, Rochester NY USA |
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| Keywords | UPDRS Parkinson's disease disease progression pharmacometrics disease model |
| Language | English |
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| Notes | istex:CD8AC1BE5CFB5E4129B9B3413C6AA55C757AA4ED National Institute of Neurological Disorders and Stroke - No. (1P20NS092529-01) ark:/67375/WNG-F04Q7ZTR-1 National Institute of Allergy and Infectious Diseases - No. (1K23AI108355-01A1) ArticleID:MDS26644 Charles S. Venuto and Nicholas B. Potter contributed equally to this article. This work was supported by grants from the Michael J. Fox Foundation for Parkinson's Research, National Institute of Neurological Disorders and Stroke (1P20NS092529‐01), and National Institute of Allergy and Infectious Diseases (1K23AI108355‐01A1). Relevant conflicts of interests/financial disclosures Funding agencies Charles S. Venuto, E. Ray Dorsey, and Karl Kieburtz receive research support from the Michael J. Fox Foundation for Parkinson's Research and the National Institute of Neurological Disorders and Stroke. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Review-3 content type line 23 |
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Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and... Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In... |
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| SubjectTerms | disease model Disease Progression Humans Models, Theoretical Movement disorders Parkinson Disease Parkinson's disease pharmacometrics UPDRS |
| Title | A review of disease progression models of Parkinson's disease and applications in clinical trials |
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