The overall goal of the NETT Network is to create a research network of clinicians in emergency medicine, neurology and neurosurgery to promote efficiency in the design, implementation and analysis of clinical trials of therapies for patients with acute neurological disorders. To achieve this endeavor, the NINDS has planned a research infrastructure with: (1) a clinical coordinating center (CCC) to provide overall leadership and coordination of activities of the NETT;(2) a statistical and data management center (SDMC);(3) clinical centers (in a hub and spoke model) to recruit and treat study subjects;and (4) the NINDS to provide scientific input and oversight through a Data and Safety Monitoring Board (DSMB) and an external advisory group. The SDMC's role is to establish a collaborative relationship with all parties involved in the Network and provide efficient data management and statistical contribution in the design and analysis of the two large Phase III clinical trials to be conducted by the Network during the grant period. With the support of the Data Coordination Unit (DCU) housed within the Department of Biostatistics, Bioinformatics and Epidemiology (DB2E) at the Medical University of South Carolina (MUSC), we are well-equipped to fill this role and partner with the clinical teams on these trials. Our experience in directing statistical and data coordinating center for large multicenter clinical studies of similar type has enabled us to develop web-based data and project management systems in which high data quality is ensured directly by site research staff;study activities are coordinated with high efficiency and study information is available to authorized personnel in real time. As the SDMC, our goal is to promote and facilitate the NETT Network research activities and contribute to collaborative research. As the SDMC for the NETT Network, we will accomplish the following aims: (1) to establish a collaborate relationship with the Network participants;(2) to actively contribute to the planning and conduct of two large clinical trials of neurological emergencies to be developed by the Network and approved by the Advisory Group;(3) to develop and implement the web-based databases using the WebDCU system for data entry and management and to facilitate the work of the CCC for the clinical trials;(4) to conduct interim and final statistical analyses of safety and efficacy data of the clinical trials;(5) to generate reports to the Steering Committee and the DSMB;and (6) in collaboration with the Steering Committee and the Network investigators, disseminate the study results in the form of abstract presentations, manuscript publications, and through the trial websites accessible to the public.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01NS059041-04
Application #
7690795
Study Section
Special Emphasis Panel (ZNS1-SRB-K (40))
Program Officer
Janis, Scott
Project Start
2006-09-30
Project End
2011-07-31
Budget Start
2009-08-01
Budget End
2010-07-31
Support Year
4
Fiscal Year
2009
Total Cost
$680,993
Indirect Cost
Name
Medical University of South Carolina
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
183710748
City
Charleston
State
SC
Country
United States
Zip Code
29425
Johnston, S Claiborne; Easton, J Donald; Farrant, Mary et al. (2018) Clopidogrel and Aspirin in Acute Ischemic Stroke and High-Risk TIA. N Engl J Med 379:215-225
Fan, Liqiong; Yeatts, Sharon D; Wolf, Bethany J et al. (2018) The impact of covariate misclassification using generalized linear regression under covariate-adaptive randomization. Stat Methods Med Res 27:20-34
Zhao, Wenle; Everett, Colin C; Weng, Yanqiu et al. (2017) Guessing strategies for treatment prediction under restricted randomization with unequal allocation. Contemp Clin Trials 59:118-120
Jiang, Yunyun; Zhao, Wenle; Durkalski-Mauldin, Valerie (2017) Impact of adaptation algorithm, timing, and stopping boundaries on the performance of Bayesian response adaptive randomization in confirmative trials with a binary endpoint. Contemp Clin Trials 62:114-120
Mawocha, Samkeliso C; Fetters, Michael D; Legocki, Laurie J et al. (2017) A conceptual model for the development process of confirmatory adaptive clinical trials within an emergency research network. Clin Trials 14:246-254
Zhao, Wenle; Pauls, Keith (2016) Architecture design of a generic centralized adjudication module integrated in a web-based clinical trial management system. Clin Trials 13:223-33
Meurer, William J; Legocki, Laurie; Mawocha, Samkeliso et al. (2016) Attitudes and opinions regarding confirmatory adaptive clinical trials: a mixed methods analysis from the Adaptive Designs Accelerating Promising Trials into Treatments (ADAPT-IT) project. Trials 17:373
Zhao, Wenle; Ramakrishnan, Viswanathan (2016) Generalization of Wei's urn design to unequal allocations in sequential clinical trials. Contemp Clin Trials Commun 2:75-79
Weng, Yanqiu; Palesch, Yuko Y; DeSantis, Stacia M et al. (2016) Assessing the impact of safety monitoring on the efficacy analysis in large Phase III group sequential trials with non-trivial safety event rate. J Biopharm Stat 26:672-85
Qureshi, Adnan I; Palesch, Yuko Y; Barsan, William G et al. (2016) Intensive Blood-Pressure Lowering in Patients with Acute Cerebral Hemorrhage. N Engl J Med 375:1033-43

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