Robust Markers and Sample Sizes for Multicenter Trials of Huntington Disease.
Ann Neurol
; 87(5): 751-762, 2020 05.
Article
em En
| MEDLINE
| ID: mdl-32105364
ABSTRACT
OBJECTIVE:
The identification of sensitive biomarkers is essential to validate therapeutics for Huntington disease (HD). We directly compare structural imaging markers across the largest collective imaging HD dataset to identify a set of imaging markers robust to multicenter variation and to derive upper estimates on sample sizes for clinical trials in HD.METHODS:
We used 1 postprocessing pipeline to retrospectively analyze T1-weighted magnetic resonance imaging (MRI) scans from 624 participants at 3 time points, from the PREDICT-HD, TRACK-HD, and IMAGE-HD studies. We used mixed effects models to adjust regional brain volumes for covariates, calculate effect sizes, and simulate possible treatment effects in disease-affected anatomical regions. We used our model to estimate the statistical power of possible treatment effects for anatomical regions and clinical markers.RESULTS:
We identified a set of common anatomical regions that have similarly large standardized effect sizes (>0.5) between healthy control and premanifest HD (PreHD) groups. These included subcortical, white matter, and cortical regions and nonventricular cerebrospinal fluid (CSF). We also observed a consistent spatial distribution of effect size by region across the whole brain. We found that multicenter studies were necessary to capture treatment effect variance; for a 20% treatment effect, power of >80% was achieved for the caudate (n = 661), pallidum (n = 687), and nonventricular CSF (n = 939), and, crucially, these imaging markers provided greater power than standard clinical markers.INTERPRETATION:
Our findings provide the first cross-study validation of structural imaging markers in HD, supporting the use of these measurements as endpoints for both observational studies and clinical trials. ANN NEUROL 2020;87751-762.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Interpretação de Imagem Assistida por Computador
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Doença de Huntington
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Neuroimagem
Tipo de estudo:
Observational_studies
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Prognostic_studies
Limite:
Adult
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Ann Neurol
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Reino Unido