Karaa, A;
Rahman, S;
Lombes, A;
Yu-Wai-Man, P;
Sheikh, MK;
Alai-Hansen, S;
Cohen, BH;
... Goldstein, A; + view all
(2017)
Common data elements for clinical research in mitochondrial disease: a National Institute for Neurological Disorders and Stroke project.
Journal of Inherited Metabolic Disease
, 40
(3)
pp. 403-414.
10.1007/s10545-017-0035-5.
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Abstract
OBJECTIVES: The common data elements (CDE) project was developed by the National Institute of Neurological Disorders and Stroke (NINDS) to provide clinical researchers with tools to improve data quality and allow for harmonization of data collected in different research studies. CDEs have been created for several neurological diseases; the aim of this project was to develop CDEs specifically curated for mitochondrial disease (Mito) to enhance clinical research. METHODS: Nine working groups (WGs), composed of international mitochondrial disease experts, provided recommendations for Mito clinical research. They initially reviewed existing NINDS CDEs and instruments, and developed new data elements or instruments when needed. Recommendations were organized, internally reviewed by the Mito WGs, and posted online for external public comment for a period of eight weeks. The final version was again reviewed by all WGs and the NINDS CDE team prior to posting for public use. RESULTS: The NINDS Mito CDEs and supporting documents are publicly available on the NINDS CDE website (https://commondataelements.ninds.nih.gov/), organized into domain categories such as Participant/Subject Characteristics, Assessments, and Examinations. CONCLUSION: We developed a comprehensive set of CDE recommendations, data definitions, case report forms (CRFs), and guidelines for use in Mito clinical research. The widespread use of CDEs is intended to enhance Mito clinical research endeavors, including natural history studies, clinical trial design, and data sharing. Ongoing international collaboration will facilitate regular review, updates and online publication of Mito CDEs, and support improved consistency of data collection and reporting.
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