| Literature DB >> 30690581 |
Mark G Luciano1, Ulrich Batzdorf2, Roger W Kula3, Brandon G Rocque4, Cormac O Maher5, John Heiss6, Bryn A Martin7, Paolo A Bolognese3, Allison Ashley-Koch8, David Limbrick9, Dorothy J Poppe10, Kaitlyn M Esposito10, Joanne Odenkirchen11, Joy R Esterlitz12, Sherita Ala'i12, Kristen Joseph12, Robin S Feldman12, Robert Riddle11.
Abstract
The management of Chiari I malformation (CMI) is controversial because treatment methods vary and treatment decisions rest on incomplete understanding of its complex symptom patterns, etiologies, and natural history. Validity of studies that attempt to compare treatment of CMI has been limited because of variable terminology and methods used to describe study subjects. The goal of this project was to standardize terminology and methods by developing a comprehensive set of Common Data Elements (CDEs), data definitions, case report forms (CRFs), and outcome measure recommendations for use in CMI clinical research, as part of the CDE project at the National Institute of Neurological Disorders and Stroke (NINDS) of the US National Institutes of Health. A working group, comprising over 30 experts, developed and identified CDEs, template CRFs, data dictionaries, and guidelines to aid investigators starting and conducting CMI clinical research studies. The recommendations were compiled, internally reviewed, and posted online for external public comment. In October 2016, version 1.0 of the CMI CDE recommendations became available on the NINDS CDE website. The recommendations span these domains: Core Demographics/Epidemiology; Presentation/Symptoms; Co-Morbidities/Genetics; Imaging; Treatment; and Outcome. Widespread use of CDEs could facilitate CMI clinical research trial design, data sharing, retrospective analyses, and consistent data sharing between CMI investigators around the world. Updating of CDEs will be necessary to keep them relevant and applicable to evolving research goals for understanding CMI and its treatment.Entities:
Keywords: Chiari Malformation; Common Data Elements
Mesh:
Year: 2019 PMID: 30690581 PMCID: PMC7054710 DOI: 10.1093/neuros/nyy475
Source DB: PubMed Journal: Neurosurgery ISSN: 0148-396X Impact factor: 4.654