Article

The TrialNet Natural History Study of the Development of Type 1 Diabetes: objectives, design, and initial results.

Division of Endocrinology and Metabolism, University of Western Ontario, London, ON, Canada.
Pediatric Diabetes (Impact Factor: 2.13). 10/2008; 10(2):97-104. DOI: 10.1111/j.1399-5448.2008.00464.x
Source: PubMed

ABSTRACT TrialNet's goal to test preventions for type 1 diabetes has created an opportunity to gain new insights into the natural history of pre-type 1 diabetes. The TrialNet Natural History Study (NHS) will assess the predictive value of existing and novel risk markers for type 1 diabetes and will find subjects for prevention trials.
The NHS is a three-phase, prospective cohort study. In phase 1 (screening), pancreatic autoantibodies (glutamic acid decarboxylase, insulin, ICA-512, and islet cell antibodies) are measured. Phase 2 (baseline risk assessment) includes oral glucose tolerance tests (OGTTs) in antibody-positive subjects and estimation of 5-yr diabetes risks according to the OGTT and number of confirmed positive antibody tests. Phase 3 (follow-up risk assessments) requires OGTTs every 6 months. In phases 2 and 3, samples are collected for future tests of T-lymphocyte function, autoantibody isotypes, RNA gene expression, and proteomics. The primary outcome is diabetes onset.
Of 12 636 relatives screened between March 2004 and December 2006, 605 (4.8%) were positive for at least one biochemical antibody. Of these, 322 were confirmed antibody positive and completed phase 2, of whom 296 subjects were given preliminary 5-yr diabetes risks of <25% (n = 132), > or =25% (n = 36), and > or =50% (n = 128) where the latter two categories represent different subjects based on number of confirmed positive antibodies (2, > or =25%; 3 or more, > or =50%) and/or an abnormal OGTT (> or =50%).
The NHS is identifying potential prevention trial subjects and is assembling a large cohort that will provide new natural history information about pre-type 1 diabetes. Follow-up to diabetes will help establish the biological significance and clinical value of novel type 1 diabetes risk markers.

Download full-text

Full-text

Available from: Clinton Thompson, Jul 22, 2015
0 Followers
 · 
254 Views
  • Source
  • [Show abstract] [Hide abstract]
    ABSTRACT: Aims/hypothesis This paper presents a rationale for the selection of intermediate endpoints to be used in the design of type 1 diabetes prevention clinical trials. Methods Relatives of individuals diagnosed with type 1 diabetes were enrolled on the TrialNet Natural History Study and screened for diabetes-related autoantibodies. Those with two or more such autoantibodies were analysed with respect to increased HbA1c, decreased C-peptide following an OGTT, or abnormal OGTT values as intermediate markers of disease progression. Results Over 2 years, a 10% increase in HbA1c, and a 20% or 30% decrease in C-peptide from baseline, or progression to abnormal OGTT, occurred with a frequency between 20% and 41%. The 3- to 5-year risk of type 1 diabetes following each intermediate endpoint was high, namely 47% to 84%. The lower the incidence of the endpoint being reached, the higher the risk of diabetes. A diabetes prevention trial using these intermediate endpoints would require a 30% to 50% smaller sample size than one using type 1 diabetes as the endpoint. Conclusions/interpretation The use of an intermediate endpoint in diabetes prevention is based on the generally held view of disease progression from initial occurrence of autoantibodies through successive immunological and metabolic changes to manifest type 1 diabetes. Thus, these markers are suitable for randomised phase 2 trials, which can more rapidly screen promising new therapies, allowing them to be subsequently confirmed in definitive phase 3 trials.
    Diabetologia 06/2013; 56(9). DOI:10.1007/s00125-013-2960-7 · 6.88 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: A study of the solar cell model concerning the effect of shunt resistance (R<sub>sh</sub>) and the reverse saturation current (I<sub>O </sub>) on the performance of solar cells is presented. It is found that an upper bound for the fill factor determines the maximum attainable efficiency. Also, there is a shunt value after which the model behaves independently of the value of the shunt resistance. The effect of the product of R<sub>sh</sub> and I<sub>O</sub> on the maximum efficiency was further studied. This resulted in detecting a region of improved performance for both R<sub>sh</sub> and I<sub>O</sub>
    Radio Science Conference, 1996. NRSC '96., Thirteenth National; 04/1996
Show more