I
have blogged dozens of times on clinical trials run by TrialNet, but
I've never discussed TrialNet as an organization, so this blog contains some
information on TrialNet, starting with their web site:
A Little History
The
pre-history of TrialNet traces back to a large study called Diabetes
Prevention Trial of Type 1 (DPT-1) which started 1994, which was testing
oral insulin as a prevention of T1D. TrialNet was formally founded in
2001, and (for me) is best known for their huge study now called "Pathway to Prevention" (previously called "Natural History Study").
This study is central to the mission of preventing T1D, by both (a)
studying what is the normal progression of T1D and (b) creating a large
pool of people in the process of developing T1D, which makes
prevention focused clinical trials much easier to run.
Kevan C. Herold of Yale University became chair of TrialNet on June 1st, 2021. Prior to that, from 2015 to 2021, Carla J. Greenbaum of the Benaroya Research Institute was the chair, and before that, Jay Skyler. Carla Greenbaum continues to direct the TrialNet Clinical Hub.
In writing this, I searched for a concise history of TrialNet,
but was not able to find anything. So if you have an interest in the history of science,
this might make a great paper, or even a thesis. Also, I was not able to find any public organizational or governance materials, so can't include any information on how TrialNet decisions are made.
Goals and Methods
TrialNet's goal is to prevent, delay and slow the progression of the T1D. I would describe their basic method as a research funnel:
- They start out screening relatives of people with T1D, looking for those who have autoimmune antibodies.
- They then follow those people to see if the number of autoimmune antibodies increases, if they start having higher than normal blood glucose after eating carbohydrates, and if they are diagnosed with T1D.
- For those who develop T1D, they follow them to see how the disease evolves over time.
Throughout this whole process, they are recruiting people for more specific studies to test preventions or cures appropriate to their stage in the disease.
Without TrialNet, if a researcher wanted to recruit 50 people at-risk
for type-1 diabetes from the general population, they would need to test
thousands of people to find the 50 they were looking for. That process
alone would likely take years and cost hundreds of thousands, if not
millions, of dollars. Even if they could focus on the relatives of
people with T1D, they would still need to test 100s of people, and it
would still cost a lot and take a long time. But TrialNet has already found many people who can participate in those studies.
Research Achievements
I consider the following items to be TrialNet's three biggest achievements in chronological order:
First: showing the normal progression of T1D. In particular documenting the length of the honeymoon period, and what should be expected during that time. To understand why this is important, consider the saga of BCG. In the 1990s there was a small clinical trial which gave BCG to six people with newly diagnosed type-1 diabetes (no control group). One of them went a few weeks without injecting insulin. At the time (before the TrialNet results), this triggered a lot of optimism, including at least three follow-on studies. The follow-on studies all had control groups and all failed, because (in fact) that result is pretty normal for the honeymoon period without any treatment at all. With the TrialNet information, researchers do not waste their time following up these "normal, but we didn't know it was normal" results. Also, there is now much more and much better information on what should be expected during the honeymoon period, which is a very stressful time for everyone involved.
Second, showing that a person who tests positive for two autoantibodies would later develop T1D in nearly all cases. This process might take up to 10 years, but it would eventually happen. Without TrialNet we would not know how number of autoantibodies related to chance of being diagnosed with T1D, or how long it would take on average. The whole idea of using number of autoantibodies to predict chances of being diagnosed with T1D is based on TrialNet data.
I know that many people are unhappy with this knowledge, especially when their kids test positive for those first two autoantibodies. However, this knowledge has opened up a wide range of research to try and prevent this diagnoses which would never have been possible without it.
Third, Teplizumab, which I've blogged on before:
TrialNet did the earliest research into Teplizumab, and they continued researching Teplizumab even when clinical trials run by commercial companies were unsuccessful. This dogged determination led directly to Teplizumab's current status. In November 2020, Teplizumab was submitted for marketing approval by the FDA for preventing or delaying the onset of T1D when given to people at-risk of the disease. (Obviously, I'll blog if it is approved.) If approved it will be a huge breakthrough: the first treatment to delay the onset of T1D. More than that, the first treatment to change the immune reaction which causes T1D. First treatments are rarely perfect, but even if not perfect, they often point the way to better treatments, and TrialNet was key to Teplizumab's research success.
Current Research
List of TrialNet's honeymoon research:
In addition to TOPPLE T1D, which is for adults within 4 years of clinical diagnosis, TrialNet is
also running trials on Abatacept and Hydroxychloroquine (HCQ) for at-risk individuals. In the past, TrialNet and has run multiple trials in honeymooners, most recently on ATG/GCSF, and also run two and oral insulin trials in people at risk of T1D.
By far the largest research project is TrialNet’s Pathway to Prevention which is focused on Risk Screening and Monitoring. These are cooperative large scale monitoring trials, involving tens of thousands of people. Relatives of people with T1D are tested for autoantibodies, and then monitored or enrolled in prevention trials if autoantibodies are found. If they develop T1D, its progression is followed through the LIFT study. TrialNet's prevention studies are open to anyone who has autoantibodies, no matter if they have relatives with T1D or not.
In the past, I know that some people did not want to participate in risk screening style research, because they "didn't want to know if there was nothing they could do". However, that thinking is now out of date. Because of several clinical studies underway to prevent or delay T1D, there now is something you can do, if you know ahead of time. Furthermore, if Teplizumab is approved, then there will be a treatment available to delay the onset of T1D.
Also, these risk screening projects have been critical to learning how T1D naturally progresses, and also to finding people to participate in the more specific prevention and delay studies mentioned above. So participants are helping to move forward important parts of T1D research, no matter how much they personally benefit during the study.
A final word about terminology: TrialNet uses a four stage timeline of T1D progression described here:
The basic summary is that stages 1 and 2 are people who have two or more autoantibodies [
definition],
but no symptoms that a patient would notice. Stage 3 is honeymoon, and
stage 4 is established type-1 diabetes. However, this is not the
terminology used (or understood) by most people effected by T1D, which is why I use more informal terminology: "at-risk" meaning people with 2
or more antibodies, but no symptoms (stage 1 and 2 in TrialNet
terminology), and then "honeymoon" for stage 3 and "established" for stage
4.
More Reading
Joshua Levy
http://cureresearch4type1diabetes.blogspot.com
publicjoshualevy at gmail dot com
All
the views expressed here are those of Joshua Levy, and nothing here is
official JDRF or JDCA news, views, policies or opinions. My daughter has
type-1 diabetes and participates in clinical trials, which might be
discussed here. My blog contains a more complete non-conflict of
interest statement. Thanks to everyone who helps with the blog.
