Five multivariate Duchenne muscular dystrophy progression models bridging six-minute walk distance and MRI relaxometry of leg muscles
© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature..
The study aimed to provide quantitative information on the utilization of MRI transverse relaxation time constant (MRI-T2) of leg muscles in DMD clinical trials by developing multivariate disease progression models of Duchenne muscular dystrophy (DMD) using 6-min walk distance (6MWD) and MRI-T2. Clinical data were collected from the prospective and longitudinal ImagingNMD study. Disease progression models were developed by a nonlinear mixed-effect modeling approach. Univariate models of 6MWD and MRI-T2 of five muscles were developed separately. Age at assessment was the time metric. Multivariate models were developed by estimating the correlation of 6MWD and MRI-T2 model variables. Full model estimation approach for covariate analysis and five-fold cross validation were conducted. Simulations were performed to compare the models and predict the covariate effects on the trajectories of 6MWD and MRI-T2. Sigmoid Imax and Emax models best captured the profiles of 6MWD and MRI-T2 over age. Steroid use, baseline 6MWD, and baseline MRI-T2 were significant covariates. The median age at which 6MWD is half of its maximum decrease in the five models was similar, while the median age at which MRI-T2 is half of its maximum increase varied depending on the type of muscle. The models connecting 6MWD and MRI-T2 successfully quantified how individual characteristics alter disease trajectories. The models demonstrate a plausible correlation between 6MWD and MRI-T2, supporting the use of MRI-T2. The developed models will guide drug developers in using the MRI-T2 to most efficient use in DMD clinical trials.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2024 |
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| Enthalten in: |
Journal of pharmacokinetics and pharmacodynamics - (2024) vom: 12. Apr. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Yoon, Deok Yong [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Revised 12.04.2024 published: Print-Electronic Citation Status Publisher |
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| doi: |
10.1007/s10928-024-09910-1 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM370989872 |
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| 520 | |a The study aimed to provide quantitative information on the utilization of MRI transverse relaxation time constant (MRI-T2) of leg muscles in DMD clinical trials by developing multivariate disease progression models of Duchenne muscular dystrophy (DMD) using 6-min walk distance (6MWD) and MRI-T2. Clinical data were collected from the prospective and longitudinal ImagingNMD study. Disease progression models were developed by a nonlinear mixed-effect modeling approach. Univariate models of 6MWD and MRI-T2 of five muscles were developed separately. Age at assessment was the time metric. Multivariate models were developed by estimating the correlation of 6MWD and MRI-T2 model variables. Full model estimation approach for covariate analysis and five-fold cross validation were conducted. Simulations were performed to compare the models and predict the covariate effects on the trajectories of 6MWD and MRI-T2. Sigmoid Imax and Emax models best captured the profiles of 6MWD and MRI-T2 over age. Steroid use, baseline 6MWD, and baseline MRI-T2 were significant covariates. The median age at which 6MWD is half of its maximum decrease in the five models was similar, while the median age at which MRI-T2 is half of its maximum increase varied depending on the type of muscle. The models connecting 6MWD and MRI-T2 successfully quantified how individual characteristics alter disease trajectories. The models demonstrate a plausible correlation between 6MWD and MRI-T2, supporting the use of MRI-T2. The developed models will guide drug developers in using the MRI-T2 to most efficient use in DMD clinical trials | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Clinical trial simulation | |
| 650 | 4 | |a Disease progression | |
| 650 | 4 | |a Drug development tools | |
| 650 | 4 | |a Duchenne muscular dystrophy | |
| 650 | 4 | |a Magnetic resonance imaging | |
| 650 | 4 | |a Model-informed drug development | |
| 650 | 4 | |a Quantitative imaging biomarkers | |
| 650 | 4 | |a Rare diseases | |
| 650 | 4 | |a Six-minute walk distance | |
| 700 | 1 | |a Daniels, Michael J |e verfasserin |4 aut | |
| 700 | 1 | |a Willcocks, Rebecca J |e verfasserin |4 aut | |
| 700 | 1 | |a Triplett, William T |e verfasserin |4 aut | |
| 700 | 1 | |a Morales, Juan Francisco |e verfasserin |4 aut | |
| 700 | 1 | |a Walter, Glenn A |e verfasserin |4 aut | |
| 700 | 1 | |a Rooney, William D |e verfasserin |4 aut | |
| 700 | 1 | |a Vandenborne, Krista |e verfasserin |4 aut | |
| 700 | 1 | |a Kim, Sarah |e verfasserin |4 aut | |
| 700 | 0 | |a DMD MR Biomarker Steering Committee |e verfasserin |4 aut | |
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