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Robust Markers and Sample Sizes for Multicenter Trials of Huntington Disease
Author(s) -
Wijeratne Peter A.,
Johnson Eileanoir B.,
Eshaghi Arman,
Aksman Leon,
Gregory Sarah,
Johnson Hans J.,
Poudel Govinda R.,
Mohan Amrita,
Sampaio Cristina,
GeorgiouKaristianis Nellie,
Paulsen Jane S.,
Tabrizi Sarah J.,
Scahill Rachael I.,
Alexander Daniel C.
Publication year - 2020
Publication title -
annals of neurology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.764
H-Index - 296
eISSN - 1531-8249
pISSN - 0364-5134
DOI - 10.1002/ana.25709
Subject(s) - sample size determination , magnetic resonance imaging , white matter , neuroimaging , clinical trial , statistical power , medicine , huntington's disease , nuclear medicine , pathology , disease , radiology , statistics , mathematics , psychiatry
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;87:751–762