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Disease progression modeling of the North Star Ambulatory Assessment for Duchenne Muscular Dystrophy
Duchenne muscular dystrophy (DMD) is a rare genetic disorder caused by decreased or absent dystrophin gene leading to progressive muscle degeneration and weakness in young boys. Disease progression models for the North Star Ambulatory Assessment (NSAA), a functional measurement widely used to assess...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10014057/ https://www.ncbi.nlm.nih.gov/pubmed/36718719 http://dx.doi.org/10.1002/psp4.12921 |
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author | Hibma, Jennifer E. Jayachandran, Priya Neelakantan, Srividya Harnisch, Lutz O. |
author_facet | Hibma, Jennifer E. Jayachandran, Priya Neelakantan, Srividya Harnisch, Lutz O. |
author_sort | Hibma, Jennifer E. |
collection | PubMed |
description | Duchenne muscular dystrophy (DMD) is a rare genetic disorder caused by decreased or absent dystrophin gene leading to progressive muscle degeneration and weakness in young boys. Disease progression models for the North Star Ambulatory Assessment (NSAA), a functional measurement widely used to assess outcomes in clinical trials, were developed using a longitudinal population modeling approach. The relationship between NSAA total score over time, loss of ambulation, and potential covariates that may influence disease progression were evaluated. Data included individual participant observations from an internal placebo‐controlled phase II clinical trial and from the external natural history database for male patients with DMD obtained through the Cooperative International Neuromuscular Research Group (CINRG). A modified indirect response model for NSAA joined to a loss of ambulation (LOA) time‐to‐event model described the data well. Age was used as the independent variable because ambulatory function is known to vary with age. The NSAA and LOA models were linked using the dissipation rate constant parameter from the NSAA model by including the parameter as a covariate on the hazard equation for LOA. No covariates were identified. The model was then used as a simulation tool to explore various clinical trial design scenarios. This model contributes to the quantitative understanding of disease progression in DMD and may guide model‐informed drug development decisions for ongoing and future DMD clinical trials. |
format | Online Article Text |
id | pubmed-10014057 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100140572023-03-15 Disease progression modeling of the North Star Ambulatory Assessment for Duchenne Muscular Dystrophy Hibma, Jennifer E. Jayachandran, Priya Neelakantan, Srividya Harnisch, Lutz O. CPT Pharmacometrics Syst Pharmacol Research Duchenne muscular dystrophy (DMD) is a rare genetic disorder caused by decreased or absent dystrophin gene leading to progressive muscle degeneration and weakness in young boys. Disease progression models for the North Star Ambulatory Assessment (NSAA), a functional measurement widely used to assess outcomes in clinical trials, were developed using a longitudinal population modeling approach. The relationship between NSAA total score over time, loss of ambulation, and potential covariates that may influence disease progression were evaluated. Data included individual participant observations from an internal placebo‐controlled phase II clinical trial and from the external natural history database for male patients with DMD obtained through the Cooperative International Neuromuscular Research Group (CINRG). A modified indirect response model for NSAA joined to a loss of ambulation (LOA) time‐to‐event model described the data well. Age was used as the independent variable because ambulatory function is known to vary with age. The NSAA and LOA models were linked using the dissipation rate constant parameter from the NSAA model by including the parameter as a covariate on the hazard equation for LOA. No covariates were identified. The model was then used as a simulation tool to explore various clinical trial design scenarios. This model contributes to the quantitative understanding of disease progression in DMD and may guide model‐informed drug development decisions for ongoing and future DMD clinical trials. John Wiley and Sons Inc. 2023-02-14 /pmc/articles/PMC10014057/ /pubmed/36718719 http://dx.doi.org/10.1002/psp4.12921 Text en © 2023 Pfizer Inc. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Hibma, Jennifer E. Jayachandran, Priya Neelakantan, Srividya Harnisch, Lutz O. Disease progression modeling of the North Star Ambulatory Assessment for Duchenne Muscular Dystrophy |
title | Disease progression modeling of the North Star Ambulatory Assessment for Duchenne Muscular Dystrophy |
title_full | Disease progression modeling of the North Star Ambulatory Assessment for Duchenne Muscular Dystrophy |
title_fullStr | Disease progression modeling of the North Star Ambulatory Assessment for Duchenne Muscular Dystrophy |
title_full_unstemmed | Disease progression modeling of the North Star Ambulatory Assessment for Duchenne Muscular Dystrophy |
title_short | Disease progression modeling of the North Star Ambulatory Assessment for Duchenne Muscular Dystrophy |
title_sort | disease progression modeling of the north star ambulatory assessment for duchenne muscular dystrophy |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10014057/ https://www.ncbi.nlm.nih.gov/pubmed/36718719 http://dx.doi.org/10.1002/psp4.12921 |
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