Journal article
Short-interval observational data to inform clinical trial design in Huntington's disease
Journal of neurology, neurosurgery and psychiatry, Vol.86(12), pp.1291-1298
12/2015
DOI: 10.1136/jnnp-2014-309768
PMID: 25669748
Abstract
ObjectivesTo evaluate candidate outcomes for disease-modifying trials in Huntington's disease (HD) over 6-month, 9-month and 15-month intervals, across multiple domains. To present guidelines on rapid efficacy readouts for disease-modifying trials.Methods40 controls and 61 patients with HD, recruited from four EU sites, underwent 3 T MRI and standard clinical and cognitive assessments at baseline, 6 and 15 months. Neuroimaging analysis included global and regional change in macrostructure (atrophy and cortical thinning), and microstructure (diffusion metrics). The main outcome was longitudinal effect size (ES) for each outcome. Such ESs can be used to calculate sample-size requirements for clinical trials for hypothesised treatment efficacies.ResultsLongitudinal changes in macrostructural neuroimaging measures such as caudate atrophy and ventricular expansion were significantly larger in HD than controls, giving rise to consistently large ES over the 6-month, 9-month and 15-month intervals. Analogous ESs for cortical metrics were smaller with wide CIs. Microstructural (diffusion) neuroimaging metrics ESs were also typically smaller over the shorter intervals, although caudate diffusivity metrics performed strongly over 9 and 15 months. Clinical and cognitive outcomes exhibited small longitudinal ESs, particularly over 6-month and 9-month intervals, with wide CIs, indicating a lack of precision.ConclusionsTo exploit the potential power of specific neuroimaging measures such as caudate atrophy in disease-modifying trials, we propose their use as (1) initial short-term readouts in early phase/proof-of-concept studies over 6 or 9 months, and (2) secondary end points in efficacy studies over longer periods such as 15 months.
Details
- Title: Subtitle
- Short-interval observational data to inform clinical trial design in Huntington's disease
- Creators
- Nicola Z Hobbs - Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UKRuth E Farmer - Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UKElin M Rees - Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UKJames H Cole - Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UKSalman Haider - Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UKIan B Malone - Dementia Research Centre, UCL Institute of Neurology, University College London, London, UKReiner Sprengelmeyer - Department of Neurology, Ulm University, Ulm, GermanyHans Johnson - Department of Psychiatry, University of Iowa, Iowa City, Iowa, USAHans-Peter Mueller - Department of Neurology, Ulm University, Ulm, GermanySigurd D Sussmuth - Department of Neurology, Ulm University, Ulm, GermanyRaymund A C Roos - Department of Neurology, Leiden University Medical Centre, Leiden, The NetherlandsAlexandra Durr - APHP–Department of Genetics and INSERM UMR S, ICM (Brain and Spine Institute), Salpêtrière University Hospital, Paris, FranceChris Frost - Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UKRachael I Scahill - Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UKBernhard Landwehrmeyer - Department of Neurology, Ulm University, Ulm, GermanySarah J Tabrizi - Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, UK
- Resource Type
- Journal article
- Publication Details
- Journal of neurology, neurosurgery and psychiatry, Vol.86(12), pp.1291-1298
- DOI
- 10.1136/jnnp-2014-309768
- PMID
- 25669748
- NLM abbreviation
- J Neurol Neurosurg Psychiatry
- ISSN
- 0022-3050
- eISSN
- 1468-330X
- Language
- English
- Date published
- 12/2015
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Psychiatry; The Iowa Institute for Biomedical Imaging; The Iowa Initiative for Artificial Intelligence; Iowa Informatics Initiative
- Record Identifier
- 9984221729702771
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