This proposal from the Johns Hopkins University Center for Clinical Trials (CCT) is for a Data Coordinating Center (DCC) to support the Non-Alcoholic Steato-Hepatitis (NASH) clinical research network. The network will focus on the etiology, natural history, and therapy of NASH. The goal of this consortium is to perform clinical, epidemiological, and therapeutic research in NASH in the United States. The DCC will work with the NIDDK and the Steering Committee (SC) to provide an infrastructure that can rapidly and efficiently design and conduct clinical trials for effective interventions to prevent disease progression. The DCC in collaboration with the SC will work to design, evaluate, and select studies for implementation by assembling and distributing materials needed to decide among design options. At the direction of the SC, the DCC will cull information from the literature or other sources and make sample size calculations needed to make informed selections of standardized outcome measures for each study. For the trials selected by the network, the DCC will play a leadership role in organizing their implementation, conduct, and quality control. The DCC will assume responsibility for all data analytic tasks needed for interim safety and efficacy monitoring and for presentations and publications from the trials. To support these activities, the DCC has assembled an interdisciplinary staff with trial-related expertise and experience in statistical design and analysis, clinical epidemiology, and obesity-related disease. Building from systems developed for ongoing studies coordinated by the CCT, the DCC will provide a comprehensive information management system to support network activities including the development and distribution of design documents (protocols, manuals, forms, policy memoranda, etc), a study website for up-to-date access to study-related materials, a distributed database management system for trial data capture and processing, a reporting system for monitoring recruitment performance and quality control, and analysis systems for interim and final data analysis. The DCC has biostatistical expertise to support the analytic needs of the network including design-specific determinations of sample size and power and the use of standard or non-standard methods for the analysis of data. The DCC will provide other support including the establishment of centralized laboratories, reading centers, or specimen banking resources (possibly through subcontracts, as needed).

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01DK061730-03
Application #
6743238
Study Section
Special Emphasis Panel (ZDK1-GRB-7 (J1))
Program Officer
Robuck, Patricia R
Project Start
2002-05-01
Project End
2009-02-28
Budget Start
2004-03-01
Budget End
2005-02-28
Support Year
3
Fiscal Year
2004
Total Cost
$1,489,129
Indirect Cost
Name
Johns Hopkins University
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21218
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Arsik, Idil; Frediani, Jennifer K; Frezza, Damon et al. (2018) Alanine Aminotransferase as a Monitoring Biomarker in Children with Nonalcoholic Fatty Liver Disease: A Secondary Analysis Using TONIC Trial Data. Children (Basel) 5:
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Brunt, Elizabeth M; Kleiner, David E; Wilson, Laura A et al. (2018) Improvements in Histologic Features and Diagnosis associated with Improvement in Fibrosis in NASH: Results from the NASH Clinical Research Network Treatment Trials. Hepatology :
Harlow, Kathryn E; Africa, Jonathan A; Wells, Alan et al. (2018) Clinically Actionable Hypercholesterolemia and Hypertriglyceridemia in Children with Nonalcoholic Fatty Liver Disease. J Pediatr 198:76-83.e2
Middleton, Michael S; Van Natta, Mark L; Heba, Elhamy R et al. (2018) Diagnostic accuracy of magnetic resonance imaging hepatic proton density fat fraction in pediatric nonalcoholic fatty liver disease. Hepatology 67:858-872
Haufe, William M; Wolfson, Tanya; Hooker, Catherine A et al. (2017) Accuracy of PDFF estimation by magnitude-based and complex-based MRI in children with MR spectroscopy as a reference. J Magn Reson Imaging 46:1641-1647

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