This proposal is for a renewal of the TrialNet Clinical Center at Yale University. The Center was established in 2006. In the previous funding period, 8 new affiliates were added and 2 sites that were not productive discontinued their affiliation. The new affiliates were positioned in and near major metropolitan sites (Chicago, Milwaukee, Providence, New York) and two additional sites are currently being enrolled. The Center has been involved in the TN-01 screening study as well as intervention studies by TrialNet and other collaborating consortia. The Center director has been the PI of the "Comparative study...." and the TN-10 Anti-CD3 mAb prevention trial, as well as the ITN027AI (AbATE) and ITN819AI (Treg) trials in the ITN. The Center also was one of the sties able to perform the DirectNet/TrialNet Metabolic Control study. In addition to the direct clinical trial activities, th Center investigators have supported the TrialNet mission in mechanistic studies and leadership roles. Two significant challenges for TrialNet prevention studies are identified and will be addressed with ongoing and new studies. One of these is to identify which and when at-risk subjects are progressing to diabetes. The other is to determine which subjects are most likely to respond to therapies. Studies that address these questions would help to design more efficient trials that require fewer subjects, are shorter in duration, and have a lower risk:benefi ratios than trials that involve unselected individuals. In addition, these and other proposed studies may help in the selection of combinations of agents to be tested in prevention trials. The TrialNet investigators will continue studies of samples from and subjects in TrialNet studies to help with the development of these biomarkers. In the next funding period, we propose to enhance recruitment into TrialNet studies using novel methods that take advantage of the electronic medical record (Epic) that is used by most of our affiliates and advertisement with electronic media. With these tools, we will be able to identify patients whose family may be interested in TrialNet prevention studies but whom may not be familiar with TrialNet because they do not attend an endocrinologist who is involved in the consortium. Our approach will involve direct patient communications using Best Practices, My Chart, and registries that are created by Epic. In addition, we plan to also provide direct communication to subjects through an expanded use of media such as Yahoo and others that have already shown potential to increase trial related interest. The past funding period has shown substantial growth in the activities at the Yale site. Our plan to expand this work in the next funding period by using innovative technologies, continuing our enlistment of affiliates in areas of dense populations in the Northeast that are underserved, while maintaining our studies to improve the quality and efficiency of TrialNet trials.
This proposal is for a renewal of the TrialNet Center at Yale University. The Center serves the Northeast US and also has affiliates in cities in the Midwest. The Center investigators have been and are involved in screening and intervention studies of TrialNet and collaborating consortia.
|Fouts, Alexandra; Pyle, Laura; Yu, Liping et al. (2016) Do Electrochemiluminescence Assays Improve Prediction of Time to Type 1 Diabetes in Autoantibody-Positive TrialNet Subjects? Diabetes Care 39:1738-44|
|Triolo, Taylor M; Maahs, David M; Pyle, Laura et al. (2016) Effects of Frequency of Sensor-Augmented Pump Use on HbA1c and C-Peptide Levels in the First Year of Type 1 Diabetes. Diabetes Care 39:e61-2|
|Narsale, Aditi; Moya, Rosita; Robertson, Hannah Kathryn et al. (2016) Data on correlations between T cell subset frequencies and length of partial remission in type 1 diabetes. Data Brief 8:1348-51|
|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|
|Pugliese, Alberto; Boulware, David; Yu, Liping et al. (2016) HLA-DRB1*15:01-DQA1*01:02-DQB1*06:02 Haplotype Protects Autoantibody-Positive Relatives From Type 1 Diabetes Throughout the Stages of Disease Progression. Diabetes 65:1109-19|
|Hao, Wei; Gitelman, Steven; DiMeglio, Linda A et al. (2016) Fall in C-Peptide During First 4 Years From Diagnosis of Type 1 Diabetes: Variable Relation to Age, HbA1c, and Insulin Dose. Diabetes Care 39:1664-70|
|Bingley, Polly J; Boulware, David C; Krischer, Jeffrey P et al. (2016) The implications of autoantibodies to a single islet antigen in relatives with normal glucose tolerance: development of other autoantibodies and progression to type 1 diabetes. Diabetologia 59:542-9|
|DiMeglio, Linda A; Cheng, Peiyao; Beck, Roy W et al. (2016) Changes in beta cell function during the proximate post-diagnosis period in persons with type 1 diabetes. Pediatr Diabetes 17:237-43|
|Moya, Rosita; Robertson, Hannah Kathryn; Payne, Dawson et al. (2016) A pilot study showing associations between frequency of CD4(+) memory cell subsets at diagnosis and duration of partial remission in type 1 diabetes. Clin Immunol 166-167:72-80|
|Durning, Sean P; Preston-Hurlburt, Paula; Clark, Paul R et al. (2016) The Receptor for Advanced Glycation Endproducts Drives T Cell Survival and Inflammation in Type 1 Diabetes Mellitus. J Immunol 197:3076-3085|
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