This application requests support for the continuing operations of the TrialNet Coordinating Center (TNCC) at the University of South Florida. The University of South Florida has served as the Coordinating Center for TrialNet since October, 2008. The primary objective of TrialNet is to prevent or delay initial onset and/or progression of type 1 diabetes (T1DM) by preserving insulin-producing beta cells in individuals at elevated risk and those who have been newly diagnosed with T1DM. To achieve this goal, TrialNet designs and implements prevention and interventional clinical trials intended to test treatments that may preserve remaining insulin secretion. The TNCC provides epidemiological, biostatistical, operational and administrative expertise and advice to the clinical centers, reference laboratories and the NIDDK which include the following tasks: 1) study- wide communications, procurement and dissemination of study materials, and related activities 2) data management and records maintenance; 3)clinical site and central laboratories monitoring; 4)data analyses; 5)preparation of study reports and papers for publication; 6)implementation of procedures to evaluate management, methodology, and cost-effectiveness of procedures utilized by the TNCC; and 7)periodic meetings. This new application provides additional support to address the identification of populations at risk for T1D, in collaboration with the new TrialNet HUB, tha can lead to trials to prevent or delay progression of T1D risk, address the feasibility of interventions in the population of subjects diagnosed with T1D who are absent of symptoms (silent diabetes), assist in the design and implementation of marker studies in collaboration with the TrialNet Biomarkers Panel (BMP) to better inform TrialNet studies on pathogenesis of the disease, provide enhancements and upgrades for communication, data collection, editing, processing, analysis, and reporting for TrialNet studies and operations including data quality, protocol adherence and data confidentiality, and provide for implementation and upgrading of procedures for coordinating submission of samples and data from the participating Clinical and Affiliate Centers to the TrialNet Central Laboratories and NIDDK Repository.
The goal of Type 1 Diabetes TrialNet is the identification of individuals at- risk for development of type 1 diabetes (T1DM). Identification of individuals at elevated risk of developing the disease will provide more information about risk factors, leading to a better understanding of disease pathogenesis. This proposal addresses support of the new Biomarker and Mechanisms Panel and the design and implementation of mechanistic studies using TrialNet subjects to add to our understanding of pathogenesis. Enrolling at-risk individuals in intervention studies to test treatments intended to delay or prevent the onset of type 1 diabetes and enrolling newly diagnosed individuals in intervention studies to test treatments intended to preserve remaining insulin secretion may result in new strategies to prevent, delay or reverse T1DM. This project will enrich this process by supporting new approaches to recruitment and the developing partnership with the recently formed TrialNet HUB. The TrialNet Coordinating Center will contribute to the design of new protocols to replace existing studies or to target new populations (such as individuals diagnosed asymptomatically) with new and innovative end points. Funds are also requested for operations to maintain study protocols, provide project oversight, coordination, communication, statistical analyses and capability to collect longitudinal data and results of laboratory analyses of biological specimens from individuals at-risk for diabetes.
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|Sosenko, Jay M (2016) Staging the progression to type 1 diabetes with prediagnostic markers. Curr Opin Endocrinol Diabetes Obes 23:297-305|
|Bundy, Brian N; Krischer, Jeffrey P; Type 1 Diabetes TrialNet Study Group (2016) A model-based approach to sample size estimation in recent onset type 1 diabetes. Diabetes Metab Res Rev 32:827-834|
|Xu, Ping; Krischer, Jeffrey P; Type 1 Diabetes TrialNet Study Group (2016) Prognostic Classification Factors Associated With Development of Multiple Autoantibodies, Dysglycemia, and Type 1 Diabetes-A Recursive Partitioning Analysis. Diabetes Care 39:1036-44|
|Insel, Richard A; Dunne, Jessica L; Atkinson, Mark A et al. (2015) Staging presymptomatic type 1 diabetes: a scientific statement of JDRF, the Endocrine Society, and the American Diabetes Association. Diabetes Care 38:1964-74|
|Miao, Dongmei; Steck, Andrea K; Zhang, Li et al. (2015) Electrochemiluminescence assays for insulin and glutamic acid decarboxylase autoantibodies improve prediction of type 1 diabetes risk. Diabetes Technol Ther 17:119-27|
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