Saturday, December 29, 2012

Vitamin D for Prevention

This blog posting is discussing the recent news about using Vitamin D as a preventative for type-1 diabetes (not a cure).  You can read more about the study here (and many other places on the net):

News: http://drugstorenews.com/article/study-vitamin-d3-could-help-prevent-type-1-diabetes
Abstract: http://www.springerlink.com/content/j71m8203335h874v/
More personal and emotional news article: http://www.theatlantic.com/health/archive/2012/12/if-we-had-been-giving-our-daughter-vitamin-d-would-she-still-have-developed-diabetes/266010/

Quick Summary:  The researchers measured Vitamin D levels in the blood of people who were later diagnosed with type-1 diabetes, and compared that to levels in the blood of people who were not diagnosed.  The levels in the diagnosed group were significantly lower.  There was an obvious correlation.  Vitamin D was not an absolute preventative.  There was not a specific amount of Vitamin D where if you took more than that you would avoid type-1.  Rather there is a change in probabilities.  Higher levels of Vitamin D led, on average, to lower levels of type-1 diabetes.    Some people with high levels of Vitamin D still got type-1 diabetes, it was just less likely.  The reverse was also true: some people with low levels of Vitamin D avoided type-1 diabetes, but it was less likely.

A Little Background: It has been well known for decades that people who live near the equator have lower rates of type-1 diabetes than people who live nearer the poles.  However, it is not known why this is true.  Some people believe that a lack of sunlight or Vitamin D increases the rate of type-1 diabetes.  Other people think it might be wealth, genetics, diet, or any one of a huge number of differences.  (In the Americas, for example, Mexico is closer to the equator and has a lower rate, while USA is farther from the equator and has a higher rate.  But there are also large differences in wealth, genetics, diet, and so on.)

A Little More Background:  Research studies can broadly be put into two groups: population based studies and intervention studies.  Population based studies are studies that take two groups of people and compare them in some way.  Hopefully, the two groups should be as similar as possible, except for the one thing being studied.  Intervention studies take one group of people, and gives some of them a treatment (the intervention) and not the others, and then compares them.

It is important to remember that there is a clear difference in quality between the two types of studies: intervention studies are generally much higher quality and are much easier to interpret.  Population based studies are often apples to oranges comparisons where the differences seen have nothing to do with the change being studied.  The Mexico to USA comparison is an example.  Is Mexico's lower type-1 rate due to genetics?  sunlight?  wealth?  cleanliness?  With a population based study, it is usually impossible to know.

This study was a population study, and so it is not as strong evidence as an intervention study.

Understanding This Research

For the recent Vitamin D study, the researchers followed people in the military.  When they entered the military some of their blood was frozen.  So later (on average 1 year later), if they were diagnosed with type-1 diabetes, the blood was tested for Vitamin D levels.  Soldiers who were similar, but who did not come down with type-1 diabetes served as a control group.  It's a very resourceful experimental design, because normally it would be very hard to test Vitamin D levels months or years before diagnoses, so finding the store of available frozen blood was brilliant insight.

This research was unique in several ways.  For one thing, it is the first study I have seen that looked at relatively old people.  Previous studies that I have seen have dealt with infants.

This study has avoided many of the common pitfalls of population based research.  In particular, population based studies often compare people from different countries or different regions, who often have many differences.  In this study both the control group and the diabetes group were taken from the same pool of people (American service members), which is a huge advantage over many population based studies.

Should People Without Type-1 Diabetes Take Vitamin D?

Remember this study says nothing about the effects of Vitamin D on people who already have type-1 diabetes, so it provides no support for the idea that people who already have type-1 should take Vitamin D.  However, the open question is this: should people who don't yet have type-1 diabetes, especially brothers and sisters of people with type-1, take extra Vitamin D?

That depends entirely on your personal beliefs about how much evidence is required, before you will pay money for a treatment.  Right now there are two population based studies that suggest that Vitamin D has a protective effect (one is here: http://www.ncbi.nlm.nih.gov/pubmed/11705562).  Only you can decide if that is enough support for you to change your behavior and spend your money.  There have also been studies on Vitamin D that have shown no difference, and I'm sorry I don't have time for a full review of all the studies.  But the link below will take you to the 13 studies listed in clinical trials for "type-1 diabetes" which study vitamin d, if you want to review them all:
link to www.clinicaltrials.gov for type-1 and Vitamin D

For comparison, the FDA generally requires 4 intervention studies (and there are other quality requirements on these studies, as well) to approve a new drug.  Population studies don't count.  Of course, Vitamin D isn't a new drug.  Nevertheless, if it were, the FDA would say there is not yet enough data to approve it's use.

If you are considering extra Vitamin D, I strongly recommend you discuss it with your doctor first.  There are blood tests for Vitamin D that your doctor can order.  These are the exact words of Dr. Garland, who worked on this study:
“While there are a few conditions that influence vitamin D metabolism, for most people, 4,000 IU per day of vitamin D3 will be needed to achieve the effective levels,” Garland suggested. He advised interested patients to ask their healthcare provider to measure their serum calcidiol before increasing vitamin D3 intake. “This beneficial effect is present at these intakes only for vitamin D3,” Garland said. “Reliance should not be placed on different forms of vitamin D and mega doses should be avoided ..."
This research was funded by the US government via a grant to the Diabetes Research Institute (DRI).  It was published in Diabetologia, a first rate European diabetes medical journal.

I have blogged twice before about Vitamin D, here:
http://cureresearch4type1diabetes.blogspot.com/2012/01/possible-cures-for-type-1-in-news.html
http://cureresearch4type1diabetes.blogspot.com/2010/08/cinnamon-and-vitamin-d.html

Other researchers are studying Vitamin D, and in particular Dr. Taback is organizing a large, intervention study.  If you are the patient type, you might want to wait until it is complete.  That is the first intervention study that I know of, and intervention studies are a much stronger form of evidence than population studies.  Unfortunately, Dr. Taback's work will take years to complete.

Personal note: I rarely blog on population based studies, like this one.  In general, I'm very nervous about their level of quality.  (I've seen some particularly bad studies in the area of nutrition, Vitamins, and related fields.)  I think one of the main problems with science reporting is that it is far too optimistic in reporting the results of population based research, much of which turns out to be wrong.  I'm also sensitive to the fact that they do not help get a drug approved.  A treatment supported by 10 or even more population based studies will not get approved by the FDA, unless intervention trials are done.  However, I am blogging about this study, because I think these researchers did a particularly good job of designing their study.  But it is still just one population based study.  Even for intervention studies, I don't consider one study alone to be definitive, and even less so for a population based study.  This is a step down a path, not the end of a journey.

Excess Vitamin D can accumulate in the body, and you can overdose (especially smaller children, if given adult doses).   Do not think "It's a Vitamin, so it's always safe" or "It's a Vitamin so everyone can take it" or "if taking X amount is good, then taking 10 times that much must be better!".  None of these things are true, and all of them can be dangerous.


For examples of study where giving vitamin D to people who already had type-1 did nothing:

No protective effect of calcitriol on beta-cell function in recent-onset type 1 diabetes: the IMDIAB XIII trial.
http://www.ncbi.nlm.nih.gov/pubmed/20805274?dopt=Abstract
No effect of the 1alpha,25-dihydroxyvitamin D3 on beta-cell residual function and insulin requirement in adults with new-onset type 1 diabetes.
http://www.ncbi.nlm.nih.gov/pubmed/20357369?dopt=Abstract


Joshua Levy
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF or JDCA news, views, policies or opinions. My blog contains a more complete non-conflict of interest statement. 
Clinical Trials Blog: http://cureresearch4type1diabetes.blogspot.com
Cured in Mice Blog: http://t1dcuredinmice.blogspot.com/

Thursday, November 15, 2012

Possible Cures for Type-1 in the News (Nov-2012)


Summary of Three Months of New Trials

This is a quick summary of all of the new clinical trials into type-1 that started between July 1st and October 1st, 2012.  These are trials which were entered for the first time during these three months.  I got this list from the FDA's clinical trial database, which is on line here:
www.clinicaltrials.com

37 New clinical trials in total
-- ----------------------------
14 Delivery / New Insulins / New Test Kits
06 Long Term Side Effects
03 Artificial Pancreas
03 CGM
01 AAT
01 Psychological
08 Other (1 of these was a Vitamin-D trial)

My only comment is that only one of these (the AAT one) might lead to a cure.  That's not a lot.

What's Up with AAT (alpha-1 antitrypsin)?

The new AAT study reminded me that there are now a total of five AAT studies ongoing, and that's enough to have a summary of AAT research, so here it is.

I've blogged on AAT before, here:
http://cureresearch4type1diabetes.blogspot.com/search/label/AAT
and some background on AAT is here:
http://cureresearch4type1diabetes.blogspot.com/p/drugs-and-treatments-in-clinical-trials.html


Study Number  Phase Size Sponsor   Duration  Completion Date
NCT01304537     I    24  Kamada    1 year    November 2012
NCT01319331     I    15  Omni Bio  
2 years   September 2013
NCT01183468    II    16  NIAID     2 years   November 2014
NCT01183455    II    66  NIAID     2 years   November 2014
NCT01661192    II    24  Kamada    3 years   December 2016

Initially, that looks pretty good.  Unfortunately, one of these trials (the second one, by Omni Bio) released some early data, and this data was only slightly positive.  The treatment showed no benefit to people with established type-1, and relatively small improvements to people who took it soon after diagnosis.  No specific numbers were published, which I consider to be a bad sign.  The first complete study (Kamada's) should be done very soon, and that should give us a much better "feel" for the level of success.  By 2015 we should have results on four studies, which should be definitive.
Another Trial for Zhao's Cell Educator (if they raise money)

I've previously blogged on Zhao's work here:
http://cureresearch4type1diabetes.blogspot.com/search/label/Zhao


It looks like researchers in New Zealand are raising money specifically to replicate Dr. Zhao's work.

Here is their description of what they want to do:

In the first trial we would infuse activated stem cells back into the patient and measure their ability to switch the behaviour of aggressive T lymphocytes to ‘peaceful’ T regulator cells. Trials like this are occurring internationally but without the activation step, and results are not yet clear. The second trial will be similar to the Chicago study [Zhao's trial, which was actually done in China]. The stem cells from each person will be used in the laboratory to ‘condition’ their white blood cells in the laboratory, before re-infusing the white blood cells.
I don't usually put information about donating money in my blog posts, but I've gotten several requests for information on how to help fund Zhao.  I don't know how an individual can do that effectively, but the researchers in New Zealand have these instructions:
If you would like to make a donation towards this cause, then the Spinal Cord Society NZ website www.scsnz.org.nz provides a means for you to do that. An email plus a donation will ensure that your contribution goes only towards the joint SCSNZ-Diabetes research work.
Please remember: I know nothing about these guys or this organization.  I am not endorsing them!

News: http://www.scsnz.org.nz/assets/Uploads/diabetes-winter-2012-focus-2.pdf
News: http://www.stuff.co.nz/national/health/7914909/Stem-cell-study-holds-diabetes-cure-promise

I want to especially thank Brian Braxton for the information and sources he provided, and everyone else (there were several) who pointed this news out to me.

Joshua Levy
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF or JDCA news, views, policies or opinions. My blog contains a more complete non-conflict of interest statement.
Clinical Trials Blog: http://cureresearch4type1diabetes.blogspot.com
Cured in Mice Blog: http://t1dcuredinmice.blogspot.com/

Thursday, November 1, 2012

Type-1 Impact on the Brain

This posting is not about cure research, but is a summary of a talk about type-1's effect on the brain.

CarbDM  recently hosted a talk by Dr. Tandy Aye, who studies the impact of type-1 diabetes on developing brains.  That sounded to me like a very interesting talk, so I attended.  Below are my notes.  Please remember that these are my thoughts on the topic (not Dr. Aye's!) and that I only wrote a little during the talk, so most of this is from memory.

Historical Background

Diabetes effects on many parts of the body has been well known for decades, however study of type-1 diabetes's effects on the brain started in 1985.  Various IQ type tests have been used, and also various brain imaging technologies.  When a new brain imaging technique is developed, it is first applied to adults, and then to children, and then the next advance comes along, and the cycle repeats.

Doing brain imaging on child is more difficult than for adults, because most of these technologies require the patient to lie vary still, in a small, enclosed space, sometimes while the machine makes strange noises or vibrates.  Children are not good at this.  However, a major breakthrough was to have a monitor play movies that the kids could watch, and that would freeze if the kid moved.  This quickly teaches the kid not to move!

Brain Studies

Various brain studies have been published since 1985, mostly on adults, but a few on children.  A good summary (actually a meta-analysis) of the adult studies was published by Gaudieri in 2008.

Aye's pilot study included just under 30 children with type-1 diabetics, ran for a few years (3?), and is complete and published.   Dr. Aye had originally submitted a study proposal for a large multi-site study that would have told us a lot about how type-1 effects brain development.  That study was rejected because the reviewers thought that children would never sit still in an MRI machine long enough to get a clear image.  One of the main goals of this pilot study was to prove to the reviewers that children could do that (if properly motivated and supported).  This part of the trial was a complete success as the much larger study has now been approved.

A second, much larger study (about 200 children) that Dr. Aye is also participating in, has started, but is still underway.  Dr. Aye could only share some of the data from the patients when they started the study, but nothing about what happened during the study.

Results

There are three conclusions which I took away from the talk.  These conclusions come from Dr. Aye's completed small trial, from the initial measurements from the much larger trial, and (to a lessor degree) from the summary of all previous research, and especially the 2008 meta-analysis.

First, Type-1 diabetes does appear to effect the brain, although as a small effect.   For example, adults with type-1 have decreased grey matter density, on average, as compared to non-type-1s.  White matter (a different part of the brain) is expected to grow during childhood, but (on average) grows less or not at all in type-1 diabetics.  There were some differences in neurons, as well.  None of these changes pushed type-1 diabetics outside the normal range of human growth.  They were just statistical differences in overall populations.

Second, this effect (overall) is not good.  Gaudieri's meta analyses showed an over all decrease in IQ by about 5 points.  That's an average over all the people involved in all the different studies that were included in the meta analysis.  Verbal IQ scores seemed to be effected the most.  Some other IQ tests were not effected at all.  Another study showed that type-1s with A1c above 8.8 had a about 9% lower numbers than those with A1c below 7.4.  (My notes are unclear if this one one specific test, or all tests, or what.)

Note: I do not want to get into an argument about the accuracy or "truthfulness" of IQ tests.  If you don't believe in the accuracy or truthfulness of standard IQ tests, then you probably should not be reading this post at all.  Dr. Aye stressed that all of her tests were aimed at general IQ, not specific scholastic achievement.  Obviously, the arguments about the usefulness of these tests (compared to other tests, or no tests) are endless.

Third, type-1's effect on the brain is correlated with high BG levels, not with low BG levels.  (But see the "correlation vs. causation" discussion below.)  This focus on high BGs is a major change of view from the previous conventional wisdom.  I can remember very clearly being told (when my daughter was diagnosed, before 2008) that low BGs might effect brain development, and especially that there was nervousness that seizures specifically were bad for the developing brain.  But the data generally does not support this nervousness   Instead, it suggests that high BG numbers are correlated with whatever is hurting the brain.  (Much like high BG numbers are associated with other bad, long term side effects of type-1.)

The analysis of low BG looked at two different measures: first, the number of seizures that child had, and second, the overall-lifetime A1c.  The first is tied to "short deep" low BG numbers, and the second to "long average" low BG numbers.  But neither was associated with lower IQs.  (Side note: about 1/3 of the kids in the pilot study had at least one seizure.   I had no idea they were that common.)

The analysis of high BG numbers looked at he overall-lifetime A1c, and that showed a very clear correlation to lower Verbal IQ (not to other IQ measurements).  The graph showed generally higher verbal IQs at A1c of 6, and linearly dropping as the A1c rose to 9.

There was some discussion about "correlation vs. causation" for this data, as there should be.

One of the parents in the audience pointed out that the flow of causality might flow from IQ to low A1c, and not the other way around.  I thought this was an excellent point.  He pointed out that kids with higher IQ might remember more of their boluses.  They might be better at dosing, or they might just be more careful and thoughtful about managing their type-1 diabetes.  Therefore, high IQ might be a cause of lower A1c, and not the other way around (higher A1c causing lower IQ).  The big study is likely to provide strong data in this area, since it will measure IQ at the start and at the end of a multi-year test period.

Of course, we know that one of the long term bad side effects of type-1 diabetes is peripheral nerve damage ("Diabetic Peripheral Neuropathy") , and this is correlated with high A1c numbers.  So it is very reasonable to think that high A1c numbers might cause nerve damage in the brain as well.

So at the end of the day, we need to wait for the larger clinical trial to get data to answer the causality question.  And even then: one study is unlikely to answer all the questions, but it would be a nice start.

(An unrelated note, but I found interesting: is that people who were depressed tended to have noticeably higher A1c numbers.  I think this data came mostly from adults, but it makes sense to me, and was an important reminder that -- especially with type-1 diabetes -- a positive outlook really does help.  Also, while numbers are very important to managing type-1 diabetes, they are not the be-all and end-all of management feelings do matter.)

Thanks very much to CarbDM for organizing this event!

Joshua Levy
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF, JDCA, or CarbDM news, views, policies or opinions. My blog contains a more complete non-conflict of interest statement. 
Clinical Trials Blog: http://cureresearch4type1diabetes.blogspot.com
Cured in Mice Blog: http://t1dcuredinmice.blogspot.com/

Sunday, October 28, 2012

Zhao Starts Phase-II Clinical Trial of "Stem Cell Educator"


Zhao Upgrades His Clinical Trial to Phase-II

I've previously blogged on Zhao's work here:
http://cureresearch4type1diabetes.blogspot.com/search/label/Zhao

He published his phase-I results in January 2012, and in July, he changed the basic nature of his clinical trial record from phase-I/II to phase-II.  Change a trial from I/II to II is uncommon, but it does happen. (The more common thing is to create a new clinical trial for the phase-II study.)  But the whole point of a I/II trial is that it can turn into a II if things go well.  In January, Dr. Zhao published data on 12 treated patients and 3 placebo patients, but the clinical trial record was for 100 people, so the remaining 80+ people (I assume) will be his phase-II trial.

Notice that it took him only 6 months to "turn around" from publishing his phase-I study to starting the phase-II study.  That's quicker than most research I follow.

The trial record was also updated in Augest and October, so if you group together all the changes made, here is a summary of the changes:
  • Phase goes from 1 to 2.
  • A second trial site has been added.  In addition to China, patients in Spain can enroll at Hospital Universitario Central de Asturias.
  • Purpose goes from "Safety/Efficacy" to "Efficacy" Study.
  • The study was expected to complete in 2012 now is expected to complete in September 2014.
  • Sponsor goes from University of Illinois to Tianhe Stem Cell Biotechnologies (Zhao's company).
  • Trial design went from single blind to open label, and 
  • There is no mention of a placebo or control group.
Also, Tianhe (Zhao's company) has also started a separate clinical trial aimed at using this same technology to cure/treat Alopecia Areata, which is another autoimmune disease involving T-cells. The trial is being run in China.

Finally, another researcher (Dr. Mark Atkinson) has been funded by JDRF for a year to test Dr. Zhao's Cell Educator "ex vivo" (not in living organisms, but in tissue samples or similar). The goal is to independently verify parts of Dr. Zhao's results.  You can read details here:
JDRF "lay abstract": http://onlineapps.jdfcure.org/AbstractReport.cfm?grant_id=38534&abs_type=LAY

Discussion

From my point of view, there is both good and bad news here.  Going from single blind to open label is a step backwards, in my mind.  Not having a placebo group is also going the wrong direction.   On the other hand, another site, more people, and an end point in the near future are all good things.

Corporate web site: http://www.tianhecell.com/
Clinical Trial Record: http://www.clinicaltrials.gov/ct2/show/NCT01350219

Joshua Levy
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF or JDCA news, views, policies or opinions. My blog contains a more complete non-conflict of interest statement.
Clinical Trials Blog: http://cureresearch4type1diabetes.blogspot.com
Cured in Mice Blog: http://t1dcuredinmice.blogspot.com/

Tuesday, September 25, 2012

Possible Cures for Type-1 in the News (late Sept-2012)


Prochymal Failed Phase-II Trials

I missed this, when it was published back in May, but luckily Kelly Close (of Close Concerns, who publishes DiaTribe) reported on it:
At 1 year, intravenous infusions of Prochymal were reportedly well tolerated, with no differences in adverse event rates between the Prochymal and placebo groups. 
With regard to efficacy, no significant differences in stimulated C-peptide levels were observed between the two arms (the primary efficacy endpoint), although a trend towards fewer hypoglycemic events in the Prochymal arm was observed. 
A full analysis will be performed following an additional year of follow-up (for a total of 24 months)
My translation is this:
  • The trial failed its primary endpoint.
  • The researchers are trying to be optimistic about a small, vague result in one of the secondary endpoints.
  • The study will get more data after another year, and they are hoping for better news.
Obviously, I'm hoping for better news next year, too.  But I'm not expecting it.

Scientific Press Coverage: http://onlinelibrary.wiley.com/doi/10.1111/j.1753-0407.2012.00197.x/full

DiaTribe is a free on line newsletter (http://www.diatribe.us/), which is is a great source of info on diabetes research, technology, etc.

NI-0401 by NovImmune Failed a Long Time Ago

Years ago a company called NovImmune started a phase-II trial for their drug NI-0401 aimed at type-1 diabetes.    After that, no news.  This drug was targeted at CD3, and all the other CD3 drugs failed, so I always assumed this one had, as well.  But there never was any news, and I never saw an official announcement.  However, NovImmune updated their entire web site, and NI-0401 is still there, but diabetes is not listed as a target at all.  Also, I found a European clinical trial registry, which showed that the long ago study had been canceled just months after it started.

So NI-0401 is dead, as far as I'm concerned, until I hear otherwise.

European clinical trials registry:
http://apps.who.int/trialsearch/trial.aspx?trialid=EUCTR2009-012988-34-AT
https://www.clinicaltrialsregister.eu/ctr-search/trial/2009-012988-34/AT

Corporate web site:
http://www.novimmune.com/products/ni-0401.html

DiaPep277 by Andromida is Fully Enrolled

This is the only treatment that I'm following that is currently in phase-III trials.  The results from previous work suggest it might be a "longer, strong honeymoon" type treatment, rather than a cure. they have already finished one phase-III trial, and this is their second.  The FDA requires two, so when this one completes, if it is successful, they will be ready to move into "marketing approval" phase, which takes a year or two.

Why is this important? For two reasons.  First, because it is now possible to predict when they will finish collecting data.  (Since this study gathers data for 2 years, it will finish about Sept 2014.) Second, because much of the uncertainty that surrounds clinical trials, is involved with recruiting participants.  It is often unclear how hard it will be to recruit people, and long it will take.   But that this point, all that cunertainty is behind the researchers.  From now on, it is just gather data, then analyze data, and then publish data.  Researchers have a lot more control over those later stages, then over recruiting people in the first place.

News: http://www.marketwatch.com/story/andromeda-biotech-successfully-completes-patient-recruitment-in-phase-iii-confirmatory-trial-for-its-lead-drug-diapep277-for-type-1-diabetes-2012-09-12

How Doctors Weigh Clinical Trial Funding

This was a very interesting study of doctors.  Basically, the researchers gave doctors summaries of research results.  These summaries breifly described a study's results, methodology, and source of funding.    The doctor was then asked questions to determine how much they trusted the results, and how willing they were to proscribe the medicine being tested, based on the trial.  (The research described was fictional, so the doctors did not have any prior knowledge of the drugs in question.)

Here is a summary of the results:
The study found that physicians weighted their assessment of the rigor of a trial based on pharma funding, and that they were half as willing to prescribe those disclosing industry sponsorship as they were those disclosing NIH funding, regardless of methodological rigor.
Discussion

I think these results are good in two separate (but related) ways.  First, they suggest to me that doctors properly "discount" clinical trials funded by industry.  Second, it suggests to me that when a doctor recommends a treatment, they are already taking into account who funded the studies suggesting its use.  The recent problems with pharma PR guys "ghost writing" research articles, and withholding placebos from some researchers has made some people nervous about the accuracy of studies they do fund.  I think it is proper that doctors are also nervous, and I feel good that the average doctor in the study took into account the funding source of clinical trials they read about.

Interestingly, the researchers who ran this particular trial are a little unhappy about their own results.  They seem to think that when comparing two studies, if the methodologies are equally rigorous, that the results should be weighted the same, no matter who did the funding.  They are specifically worried about doctors undervaluing what the researchers consider large scale, well designed, industry funded studies.   I disagree.  I think the prescribing doctors are doing the right thing by undervaluing (or "discounting") equally rigorous studies that are funded by industry.  I view the attitude of these researchers as being very "old school" (and in this case, out of date).  Sure, in the 1950s the idea was that rigorous trial methodology and peer review together were all that was needed to ensure accurate results.  The idea was that the scientific method was so good that who funded the trial was not critical to the quality of the results.  But 60 years later, I don't think that's the consensus opinion.   Now we know that quality starts with good methodology and peer review, but those alone are not enough.

News coverage: http://www.mmm-online.com/docs-downgrade-results-of-pharma-funded-clinical-trials/article/259981/

Symlin as a Treatment

Not for a cure, but of interest, are the results of two studies testing symlin in type-1 diabetics.  Only one was placebo controled, and it found:
analysis of 248 patients from a 29-week, placebo-controlled study, measurements in the normal range based on ADA criteria increased from 37.3 percent to 43.9 percent for SYMLIN-treated patients (n=115), compared to an increase from 38.2 percent to 40.9 percent in those receiving placebo (n=133). The percent of measurements in the normal range based on AACE criteria increased from 22.6 percent to 27.8 percent for SYMLIN-treated patients compared to an increase from 24.1 to 25.0 in those receiving placebo. The percentage of readings in the hypoglycemic range remained relatively stable.
Discussion

I'm not sure I'd take a second injection with meals (or a first injection for pump users) for that level of improvement, but it's still interesting.  I also think that A1c improvements would be a better measure of goodness than % inside of guidelines.   But you gotta start somewhere.

Maybe we'll end up with a tri-treatment artificial pancreas.  It will dose insulin for highs, glucagon for lows, and symlin with meal boluses.

Press Release: http://www.businesswire.com/news/home/20120609005027/en/SYMLIN%C2%AE-Helped-Patients-Type-2-Type-1

Joshua Levy
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF or JDCA news, views, policies or opinions. My blog contains a more complete non-conflict of interest statement.
Clinical Trials Blog: http://cureresearch4type1diabetes.blogspot.com
Cured in Mice Blog: http://t1dcuredinmice.blogspot.com/

Tuesday, September 11, 2012

JDRF Funding for a Cure 2012

In the US, we are starting the "Walking Season" when JDRF asks us to walk to raise money for cure. So I'd like to do my part, by reminding you all how important JDRF is to the human trials of potential cures for type-1 diabetes, which I track.

Let me give you the punch line up front: 63% of the treatments currently in human trials have been funded by JDRF. (And the number is  66% for the later phase trials) This is an strong impact; one that any non-profit should be proud of.

This summary does not include Artificial Pancreas research or stem cell trials, which I discuss separately.  The list is a list of treatments, not a list of trials.  For example, the "ATG and autotransplant" treatment is actually running three trials, but since they are testing the same treatment, it is only one item in the list.  DiaPep277 is running several trials, Rituximab has two, and so on.  Finally, those treatments marked "(Established)" have at least one trial which is open to people who have had type-1 diabetes for over a year.  So those are open to non-honeymoon diabetics.

Also remember that I give an organization credit for funding a treatment if they funded it any any point in development; I don't limit it to the current trial.  For example, JDRF is not funding the current trials for DiaPep277, but they did fund much of the early research into it, which allowed it to grow into human trials.

Cures in Phase-III Human Trials
Summary: there is only one treatment in phase-III right now, and it has been funded by JDRF.
  • Andromedia's DiaPep227 
This treatment has more than one study active right now.

Cures in Phase-II Human Trials
Summary: there are 14, and 9 of them have been funded by JDRF, either directly or indirectly through ITN. Here are the treatments that have been funded by JDRF:
  • Abatacept by Orban at Joslin Diabetes Center
  • Diabecell by Living Cell Technologies    (Established)
  • Exsulin (previously INGAP) by Exsulin    (Established)
  • Kineret / Anakinra by Mandrup-Poulsen at Steno Diabetes Center
  • Rituximab by Pescovitz at Indiana
  • Sitagliptin and Lansoprazole at Sanford Health
  • Thymoglobulin (also known as ATG) by Gitelman
  • Umbilical Cord Blood Infusion by Haller at University of Florida
  • Xoma 52 by Xoma Corp  (Established)
Not funded by JDRF:
  • ATG and autotransplant by Burt, and also Snarski, and also Li
  • Atorvastatin (Lipitor) by Willi at Children's Hospital of Philadelphia
  • Brod at University of Texas-Health Science Center
  • Canakinumab by TrialNet
  • NI-0401 by NovImmune

Cures in Phase-I Human Trials
Summary: there are 23, and 14 of the are funded by JDRF and 9 are not. Here is the list funded by JDRF:
  • Alefacept by TrialNet
  • AAT or Alpha-1 antitrypsin by OmniBio and also Kamada
  • ATG and GCSF by Haller at University of Florida    (Established)
  • BHT 3021 by Bayhill Theraputics   (Established)
  • CGSF by Haller at University of Florida
  • Trucco at Children’s Hospital of Pittsburgh    (Established)
  • IBC-VS01 by Orban at Joslin Diabetes Center
  • Leptin by Garg at University of Texas
  • Nasal insulin by Harrison at Melbourne Health
  • Polyclonal Tregs by Gitelman at University of California San Francisco
  • Pro insulin peptide by Dayan at Cardiff University
  • Proleukin and Rapamune by Greenbaum at Benaroya Research Institute    (Established)
  • Lisofylline by DiaKine
  • Stem Cell Educator by Zhao (Established).
Not funded by JDRF:
  • BCG by Faustman at MGH (Established)
  • CGSF and autotransplant by Esmatjes at Hospital Clinic of Barcelona  (Established)
  • Encapsulated Islets at University clinical Hospital Saint-Luc    (Established)
  • Etanercept (ENBREL) by Quattrin at University at Buffalo School of Medicine
  • GABA by Lunsford at the University of Alabama at Birmingham.
  • Monolayer Cellular Device (Established)
  • Rilonacept by White at University of Texas
  • The Sydney Project, Encapsulated Stem Cells (Established) 
  • Pioglitazone by Wilson at Stony Brook 
Summary of all Trials
38 in total
24 funded by JDRF
So  63 % of the human trials currently underway are funded (either directly or indirectly) by JDRF. Everyone who donates to JDRF should be proud of this huge impact; and everyone who works for JDRF or volunteers for it, should be doubly proud.

Just Looking at Trials on Established Type-1 Diabetics
13 in total (34% of all trials)
8 funded by JDRF
So 62% of the trials recruiting established type-1 diabetics, are funded by JDRF.

Compared to Last Year
In 2011 there were 37 treatments in clinical trials, in 2012 there are  38  (growth of 3%)
In 2011 there was 1 treatments in Phase-III trials, in 2012 there is still  1  (no change).
In 2011 there were 16 treatments in Phase-II trials, in 2012 there are 13  (drop of 23%).
In 2011 there were 20 treatments in Phase-I trials, in 2012 there are 23 (growth of 13%).

In previous years I have included some drugs that were basically being tested as treatments (adjuncts to insulin that would give people better control or help them use less insulin).  This year, I have removed those from the list.  I included them before because there was always a chance they would lead to a cure.  I'm now of the opinion that was wishful thinking, so I'm no longer including them here.

How I Count Trials for This Comparison
  • I give an organization credit for funding a cure if it funded that cure at any point in it's development cycle.
  • I mark the start of a research trial when the researchers start recruiting patients (and if there is any uncertainty, when the first patient is dosed).  Some researchers talk about starting a trial when they submit the paper work, which is usually months earlier.
  • For trials which use combinations of two or more different treatments, I give funding credit, if the organization in the past funded any component of a combination treatment, or if they are funding the current combined treatment. Also, I list experiments separately if they use at least one different drug.
  • The ITN (Immune Tolerance Network) has JDRF as a major funder, so I count ITN as indirect JDRF funding.
  • I have made no attempt to find out how much funding different organizations gave to different research. This would be next to impossible for long research programs, anyway.
  • Funding of research is not my primary interest, so I don't spend a lot of time tracking down details in this area. I might be wrong on details.
  • I use the term "US Gov" for all the different branches and organizations within the United States of America's federal govenment (so includes NIDDK, NIAID, NICHD, etc.)
  • I don't work for the US Gov, JDRF, or any of the other organizations discussed here. I'm an adviser to JDCA. I also own stock in several of the companies discussed here.
This is an update and extension to blog postings that I've made for the previous four years:
http://cureresearch4type1diabetes.blogspot.com/2011/10/jdrf-funding-research-for-cure-2011.html
http://cureresearch4type1diabetes.blogspot.com/2010/09/jdrf-funding-research-for-cure-2010.html
http://cureresearch4type1diabetes.blogspot.com/2009/09/jdrf-funding-research-for-cure.html
http://cureresearch4type1diabetes.blogspot.com/2008/10/jdrf-funding-of-cure-research-phases-ii.html

Please think of this posting as being my personal  "thank you" note to all the JDRF staff, volunteers, and everyone who donates money to research a cure for type-1 diabetes:
Thank You!

Finally, if you see any mistakes or oversights in this posting, please tell me!  There is a lot of information packed into this small posting, and I've made mistakes in the past.


Here is a chart of the number of total clinical trials, and broken down by phases, for each of the last few years:



Joshua Levy
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF or JDCA news, views, policies or opinions.  My blog contains a more complete non-conflict of interest statement. 
Blog: http://cureresearch4type1diabetes.blogspot.com
Cured in Mice Blog: http://t1dcuredinmice.blogspot.com/

Friday, September 7, 2012

Possible Cures for Type-1 in the News (early Sept-2012)

Phase-II Trial to Test Intranasal Insulin for Type-1 Prevention

Several different groups are experimenting with using insulin to prevent or cure type-1 diabetes.  This is similar to giving people with food allergies the food they are allergic to in tiny doses, gradually building up the dose over years until they are no longer allergic.  Because insulin is basically a protein, it gets digested, so you can't take pills of insulin.  Different groups are experimenting with different methods of getting insulin into a person, in the hopes that it will result in a cure.

This particular group is using a nasal spray.  They want to enroll 120 people, and started back in 2006, but I've not previously blogged on it.  They are now hoping to finish in late 2016.  Obviously, it's been going on for a long time.  Because it is being done in Australia (with it's lower population), I'm sure it is taking them longer than they would like to fully enroll it.

News: http://au.news.yahoo.com/today-tonight/health/article/-/14475192/diabetes-vaccine-trial
Web site: http://www.stopdiabetes.com.au/
Clinical Trial Record: http://www.clinicaltrials.gov/ct2/show/NCT00336674


IL-2 and Sirolimus Fail in Phase-I

This clinical trial failed in phase-I, in a pretty obvious way.  Here's the quote from the researchers:
Rapamycin/IL-2 therapy, as given in this phase 1 study, resulted in transient β-cell dysfunction despite an increase in Tregs.
So it hurt the patients (although only temporarily) and did not help them.   Plus they threw in this (which should really go in my "Cured in Mice" blog:
Such results highlight the difficulties in translating therapies to the clinic and emphasize the importance of broadly interrogating the immune system to evaluate the effects of therapy.
They sure do!

News: http://medicalxpress.com/news/2012-08-experimental-combo-treatment-worsens-diabetes.html
Abstract: http://diabetes.diabetesjournals.org/content/early/2012/06/15/db12-0049.abstract?sid=2b59c310-a735-4fc8-a3e1-f14f9678c935
Clinical Trial Record: http://www.clinicaltrials.gov/ct2/show/NCT00525889


Phase-I Clinical Trial of IL-2 is Complete

This is the other IL-2 clinical trial.  It involves 25 people who have had type-1 for less than 2 years.  It is complete, meaning they have gathered all the data needed, but have not yet published the results.  Since they were complete in April, if they have a positive result, I would expect publication by April 2013, and if they have a neutral, negative, or hard to interpret result, publication after that.

Clinical Trial Record: http://www.clinicaltrials.gov/ct2/show/NCT01353833


Joshua Levy
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF or JDCA news, views, policies or opinions. My blog contains a more complete non-conflict of interest statement.
Clinical Trials Blog: http://cureresearch4type1diabetes.blogspot.com
Cured in Mice Blog: http://t1dcuredinmice.blogspot.com/


Wednesday, August 29, 2012

Summary of Dr.Faustman's Phase-I Results


This is a short summary of Dr. Faustman's research.  If you want the long, detailed version, that was yesterday's blog, and you can see it here:
http://cureresearch4type1diabetes.blogspot.com/2012/08/details-of-dr-faustmans-phase-i-results.html

Dr. Faustman has published the peer reviewed results of her phase-I clinical trial.
The trial was complex, and the results are complex, and I know there is a lot of interest in this particular research, so this post contains a quick summary of the results. 

If you want more explanation of anything I say here, please take a look at that detailed posting first.  If it doesn't answer your questions, then comment or email me.  Thanks.

I've blogged extensively on Dr. Faustman's research in the past, which you can read here:

Background to Dr. Faustman's Research

The essence of Dr. Faustman's theory on how to cure type-1 diabetes is:
  • Part 1: BCG causes the body to generate TNF
  • Part 2: TNF causes fewer autoreactive T-cells
  • Part 3: Fewer autoreactive T-cells results in beta cell regrowth and more insulin generation
  • Part 4: More insulin generation is the path to curing type-1
BCG (Bacillus Calmette–Guérin) is a biologic which has been given to over a billion people (in low dose) as a tuberculosis vaccine, and is also approved (in much higher doses) as a bladder cancer treatment.  It is a generic drug with a very long record of safety.  This trial focuses on parts 1-3 of the theory.  Part 4 is not controversial at all, and part 1 is widely believed as well, so it is parts 2 and 3 that really need testing.

TNF ("Tumor necrosis factor" or TNF-alpha) is a naturally occurring protein that can cause cells to die.  It is involved in the natural regulation of immune cells.

"Autoreactive" refers to immune cells which mistakenly attack the body's own beta cells.  The destruction of these beta cells leads to type-1 diabetes.  This is sometimes referred to as an "autoimmune attack" because the body's own immune system attacks the body itself.

Summary of Results

In this day of 10 second sound bytes and 140 character messages, everyone wants a short summary.  But this is a complex trial, and just about any quick summary will be an over simplification.   This is the best that I can do:

This trial was supposed to provide support for three parts of Dr. Faustman's theory, but:
1. It provided no data to support part 1 of Dr. Faustman's theory.
2. It provided data that part 2 was not happening (ie. it contradicted part 2 of Dr. Faustman's theory).  In particular, no change in live autoreactive T cells were reported.
3. The study shows a very small improvement to C-peptide numbers (but that was dependent on using a particular control group).  This improvement to C-peptide production supports part 3 of Dr. Faustman's theory.

Result 2 above, suggests that Dr. Faustman's theory about how BCG could help cure type one diabetes, was wrong.  But result 3 holds out a sliver of hope, that maybe in some different way BCG will be part of a cure.  Therefore, all discussions about the success or failure of this experiment are going to quickly boil down to the importance (and even existence) of the very small increase in C-peptide production in item 3 above.  This very small increase in C-peptide production was "brittle", meaning it was only seen with a particular control group.


Other important points:
4. There were no safety issues, although this was expected considering BCG's long safety history, and the fact that it was chosen specifically because it was known to be safe.
5. The improvement to C-peptide numbers, is much smaller than that seen in established type-1 diabetics enrolled in Dr. Zhao's or LCT's previously published phase-I clinical trials.
6. In this very small study, A1c numbers got worse for people given BCG.  For me, this was a worrisome effect, although the paper does not treat it as such.
7. Part of the paper described one patient who came down with Epstein Bar Virus (EBV) during the trial.  I consider that a single patient case study, not a clinical trial, so I'm not going over it in detail. If you're interested in that one patient, you should read those parts of the paper.

The Future of This Research

In one sense, the future of this research is easy to predict.  Dr. Faustman has already gathered $8 million for the follow-on phase-II trial, so I have every expectation that a follow-on clinical trial will be done.

But scientifically, the future is much more murky.   Moving this research forward is not going to be easy.  Because the current results are 100s of times too small for a cure, I don't think it is reasonable to just give "linear" higher doses or more frequent doses.  Certainly, not a dose 100s of times higher.  Often, it is the theory about why the treatment works that gives you clues about how to change doses between phase-I and phase-II.  If there is an important threshold, for example.  But in this case the theory about why the treatment works has not been supported by phase-I, so there is no help there.

Of course, research is always about the future: what can this grow into?  But if you are betting on future improvements, then it makes sense to start with a stronger base, and Dr. Zhao had much better results 6 months ago, and LCT for longer than that.

My opinion: Everyone wants to know if this clinical trial succeeded or failed.  This trial did not succeed, but did it fail?  Maybe, I would phrase it a little differently.  One way to phrase it is this: This trial succeeded in telling us that the previous theory was wrong.  Another way to phrase it is this: This trial is more indicative of a basic research result, than a path-to-product research result.  There were anomalies that might turn out to be interesting: the dead autoreactive T cells and also the change in GAD/TnT8A antibodies and regulatory T cells, but these represent basic research and there is no obvious path from these results to a cure.

Joshua Levy
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF or JDCA news, views, policies or opinions. My blog contains a more complete non-conflict of interest statement.
Clinical Trials Blog: http://cureresearch4type1diabetes.blogspot.com
Cured in Mice Blog: http://t1dcuredinmice.blogspot.com/

Tuesday, August 28, 2012

Details of Dr. Faustman's Phase-I Results for BCG


Dr. Faustman has published the peer reviewed results of her phase-I clinical trial.
The trial was complex, and the results are complex, and I know there is a lot of interest in this particular research, so this is a very long post describing her results in detail, along with the issues they bring up.   I've blogged extensively on her research in the past, which you can read here:
http://cureresearch4type1diabetes.blogspot.com/search/label/Faustman

Musical accompaniment for this blog posting is from the best band ever to come out of Palo Alto High School (in California, USA).  The Donna's It's On The Rocks:
http://www.youtube.com/watch?v=1eFMW6vE9Sg

Because this is a long, complex posting, I've put in three different types of footnotes:
    [dNN] refer to extra discussion, extra details, etc.
    [rNN] are references to papers, web pages, etc.
    [rpNN] are references to specific parts of the Faustman paper.
All of these are at the end of the posting.

If you have already read my posting "Summary of Dr. Faustman's Phase-I Results for BCG", then you can skip the next two sections (Background and Summary), as they are identical, except for the footnotes.

Background to Dr. Faustman's Research

The essence of Dr. Faustman's theory on how to cure type-1 diabetes is [r2]:
  • Part 1: BCG causes the body to generate TNF
  • Part 2: TNF causes fewer autoreactive T-cells  [r3]
  • Part 3: Fewer autoreactive T-cells results in beta cell regrowth and more insulin generation
  • Part 4: More insulin generation is the path to curing type-1
BCG (Bacillus Calmette–Guérin) is a biologic which has been given to over a billion people (in low dose) as a tuberculosis vaccine, and is also approved (in much higher doses) as a bladder cancer treatment.  It is a generic drug with a very long record of safety.  More information [r4]. This trial focuses on parts 1-3 of the theory.  Part 4 is not controversial at all, and part 1 is widely believed as well, so it is parts 2 and 3 that really need testing.

TNF ("Tumor necrosis factor" or TNF-alpha) is a naturally occurring protein that can cause cells to die.  It is involved in the natural regulation of immune cells.

"Autoreactive" refers to immune cells which mistakenly attack the body's own beta cells.  The destruction of these beta cells leads to type-1 diabetes.  This is sometimes referred to as an "autoimmune attack" because the body's own immune system attacks the body itself.


Summary of Results

In this day of 10 second sound bytes and 140 character messages, everyone wants a short summary.  But this is a complex trial, and just about any quick summary will be an over simplification.   This is the best that I can do:

 
This trial was supposed to provide support for three parts of Dr. Faustman's theory, but:
1. It provided no data to support part 1 of Dr. Faustman's theory.
2. It provided data that part 2 was not happening (ie. it contradicted part 2 of Dr. Faustman's theory).  In particular, no change in live autoreactive T cells were reported.
3. The study shows a very small improvement to C-peptide numbers (but that was dependent on using a particular control group).  This improvement to C-peptide production supports part 3 of Dr. Faustman's theory.

Result 2 above, suggests that Dr. Faustman's theory about how BCG could help cure type one diabetes, was wrong.  But result 3 holds out a sliver of hope, that maybe in some different way BCG will be part of a cure.  Therefore, all discussions about the success or failure of this experiment are going to quickly boil down to the importance (and even existence) of the vary small increase in C-peptide production in item 3 above.  This very small increase in C-peptide production was "brittle", meaning it was only seen with a particular control group.

Other important points:
4. There were no safety issues, although this was expected considering BCG's long safety history, and the fact that it was chosen specifically because it was known safe.
For item 5 please refer to the SummaryOfFaustmanCPeptides.pdf file attached to this email.
5. The improvement to C-peptide numbers, is much smaller than that seen in established type-1 diabetics enrolled in Dr. Zhao's or LCT's previously published phase-I clinical trials.
6. In this very small study, A1c numbers got worse for people given BCG.  For me, this was a worrisome effect, although the paper does not treat it as such, and the study size may be too small to be significant.
7. Part of the paper described one patient who came down with Epstein Bar Virus (EBV) during the trial.  I consider that a single patient case study, not a clinical trial, so I'm not going over it in detail. If you're interested in that one patient, you should read those parts of the paper.


Results In Detail

For each result, I present the data and then discuss it.  I've put them in order of most important to least important [d1].  I also discuss data that was supposed to be collected, but was not reported.

C-Peptides

C-peptide measures are critical for two reasons.  From a scientific point of view, they are the gold standard that the body is producing it's own insulin.  (Measuring insulin will confuse injected insulin and produced insulin, but C-peptide is a side effect of the production process.  If you see that, you know the body is generating it's own insulin.)  Also read [d6].  From a regulatory point of view, the US FDA has issued guidance that C-peptide numbers will be used to approve any future cure or treatment for type-1 diabetes.  So these numbers will be central to the approval of any new treatment.

Of the three patients who got BCG, two of them had a short term, but statistically significant [d18], rise in insulin production (as measured by C-peptide) when compared to the reference subjects. The reference subjects averaged 1.65 pmol/L and the two BCG patients were 3.49 and 2.57, so averaged 3.03. So the net average benefit (for the two patients who responded) was about 1.38 pmol/L.

How do these numbers compare to a cure?

According to the Mayo clinic an average person (non-diabetic) generates a minimum of 365 pmol/L.
Dr. Zhao used a lower reference number of about 199 pmol/L.  [d2]

If we use the Mayo numbers, then these patients were about 1 / 264 th of the way to a cure.
If we use the Zhao numbers, then they are about 1 / 144 th of the way to a cure.



How do these number compare to other researchers?
Details on the source of this data and the calculations to compare them are in [d3].
I think it is reasonable to compare these results to other clinical trials in established type-1 diabetes, that use a safe treatment.   Comparing them to improvements seen in honeymoon type-1 diabetics would be unfair, as would comparing them to risky treatments [d4].  The closest comparison is Dr. Zhao's research [r5], and LCT is another good comparison.

For Dr. Faustman (see [d3] for difference between "all treated" and "responders only"):
Average improvement (all treated patients) was .37 pmol/L
Average improvement (responders only) was 1.38 pmol/L

For Dr. Zhao:
Average improvement (all treated patients) was 157 pmol/L

To put it bluntly, if you compare all treated by Dr. Zhao to all treated by Dr. Faustman, Dr. Zhao has about 425 times bigger effect than Dr. Faustman (157 vs .37).  If you compare all treated by Dr. Zhao to those treated by Dr. Faustman who responded well, then Zhao's effect is "only" about 114 times bigger (157 vs 1.38).  Also, Dr. Zhao's saw those results in a sample size four times larger than Dr. Faustman's, and the improvement in C-peptide numbers was seen for a longer time period in Dr. Zhao's trials as compared to Dr. Faustman's.  [d5]

Unfortunately LCT reports on insulin dose, rather than C-peptide [d6].  In their most recent clinical trials, they saw an average dose of 41 units drop to 36 and then 30 [r6].  Taken at face value and very roughly, this would imply a C-peptide number of about 91 pmol/L (using the Mayo reference), or  50 pmol/L (using the Zhao reference) [d7]. Both numbers vastly larger than Dr. Faustmans 1.38 or .37.

HbA1c (commonly called "A1c")

The results: The paper said "There were no significant changes in any of the clinical trial patients in ... HbA1c levels" [rp14].  The HbA1c data below was included in figures [rp15]:

The three BCG treated patients had these A1c changes:
5 weeks after first treatment the changes were +0.6, +0.1, and 0.  Average +0.2.
20 weeks after first treatment the changes were +0.7, +0.5, and +0.2.  Average +0.5.

The two untreated patients who did not get EBV had these A1c numbers:
5 weeks after first treatment the changes were 0 and -0.2.  Average -0.1.
20 weeks after first treatment the changes were  +0.4 and -0.5.  Average 0 (no change).

What this means: In the placebo patients, some went up, some down.  In the BCG group all went up.  After 5 weeks one BCG patient has a A1c change of 0.5 or greater, and after 20 weeks, 2 had.  Since I consider an A1c change of 0.5 or more to be important, that is a worrisome result [r8].  But with only three treated patients, these differences may not be statistically significant [d19].   Discussion of 5 vs. 20 week importance is here [d8].

Insulin-autoreactive T cells

When the trial was first designed this was the primary outcome [r7].  This outcome is critical to  part 2 of Dr. Faustman's theory of how to cure type-1 diabetes.  It is important that the number of autoreactive cells drop [r5].  Even if there are no clinical improvements, if there were a drop in Insulin autoreactive T cells, then there would be hope for the research theory.

The results:

1. The total number of Insulin-autoreactive T cells was much higher in the BCG treated patients. [rp2]
2. However, the extra Insulin-autoreactive T cells were generally dead. [rp3]
3. The paper did not report on any statistically significant change in the number of "live" Insulin autoreactive T cells in the patients treated with BCG as compared those who were not.
4. The paper did report a statistically significant increase in dead autoreactive T cells, but no drop in live ones.

What this means: So in terms of showing that BCG resulted is fewer living Insulin-autoreactive T cells, the trial was a failure.  This means it failed it's primary end point, as specified by Dr. Faustman when the trial started [r7][d9].  More importantly it means that her basic theory (that BCG would lead to TNF would lead to fewer "bad"/autoreactive T-cells) was wrong [d10].

If BCG works at all, someone will need to come up with a different underlying theory of mechanism that explains it.  This isn't an insurmountable problem however, plenty of treatments are used successful without being fully understood, especially early on.  However, it does make it hard to predict dosing, side effects, effective populations, etc.

Autoantibody Levels

The paper reported on autoantibodies, which are another form of autoimmune cells.  If BCG did not work by lowering autoimmune T cells, the hope here is that it worked by lowering autoimmune antibody cells.

The results:  For GAD "There was a statistically significant and sustained change in GAD autoantibody levels in two of the three BCG-treated subjects after injections, with one diabetic showing a decrease and the other an increase relative to self-baseline" [rp4].  Basically one BCG treated patient went up, another went down, and a third stayed the same.  For IA-A2 and ZnT8A "only ZnT8A had statistically significant decreases in one BCG treatment subject." [rp4].  So with six combinations (two autoantibodies and three people) they got one statistically significant decrease.

If you look at the graphs for 17 weeks, there doesn't seem to be a difference between the starting point and ending point. Nor is there any obvious up or down trends right after the BCG is given.

What this means: Overall, I would describe this as a whole lot of nothing.

Regulatory T Cells

Originally, this was not part of the trial [r7], but it was reported on.  These are immune cells which police other cells, so more of them are expected to help type-1 diabetes.  But these cells are not type-1 specific, they don't just regulate the bad T cells that cause type-1.  They regulate all T cells. Extra regulatory T cells can be expected to slow down the whole immune system, not just the bad autoimmune part [d11].

If there were no drop in Insulin autoreactive T cells and no drop in autantibodies, then perhaps there is an increase in regulator T cells?

The results: There were clearly more T-reg cells in the BCG treated patients than in paired healthy controls, or in the placebo group.

What this means: I'm not sure that it means anything [d12].  The whole point of vaccines is to stimulate an immune response.  (And viruses do this as well.)   It makes sense that the response would include regulator T cells and all other types of T cells, in equal proportion.   A therapeutic effect would only be expected if regulator T cells went up and other T cells stayed the same, or went down (or at least did not go up as much).  No data on T cells in general is included, so there is no way to know if reg T cells went up in sync with all T cells or not.

No TNF Results

The results: The original experimental design was going to measure TNF, TNF-receptors, [and] other cytokines [r7].  None of that data was reported in the paper, although the text did say that BCG was chosen specifically because it induced TNF generation [rp5].

What this means: By not reporting this data, the clinical trial could not show that part 1 of Dr. Faustman's theory on how to cure type-1 diabetes was correct.  Now, part 1 is less controversial than parts 2 and 3, but still: the original experimental design would have shown conclusively that part 1 was correct and did happen in people, and would have given valueable dosing information for future trials.  It's the scientific equivalent of "low hanging fruit" and it's puzzling that it was dropped.

Weaknesses in Data Analysis

In the discussion above, I have taken all the results reported in the paper as correct without question.  However, there are two important weaknesses in how the data analysis was done, which call into question these results.  These weaknesses especially effect the C-peptide numbers.

As background remember how you were taught to do scientific experiments back in school:  Take a group of similar people, divide them into two groups.  Give one group the drug you are studying and give the other a "placebo" (do nothing) treatment.  Compare results between the two groups.  This is the "gold standard" of experimental design.  However, this paper doesn't use this treated-vs-placebo design [rp6].

But there are other ways to do comparisons in clinical trials.  For example, you might compare data from before a person was treated to data from after they were treated.  This can be thought of as a sort of "silver standard": still very good.   In some cases this is the only comparison available [d13].  Or, you might compare data from your treated group, to data from a similar reference group.  This technique can be done well or poorly, depending on how the reference group is created [d14].   This paper uses both a before-vs-after design and high quality versions of compare-to-reference designs.

Obviously, researchers prefer to use the gold standard, but sometimes they can not, especially in phase-I trials [d13].  However, this trial is unique in my experience, because they did have a placebo group, and collected all the data needed for the "gold standard" comparison, but then chose not to do that, and to use a "silver standard" comparison instead.  And here's the punchline: if they had done the "gold standard" comparison of treated vs. placebo group the results would likely not have been statistically significant, and the entire trial would have been a failure.

To understand how this works, consider the placebo group first (the two who did not get EBV). [rp7].    Notice that the first patient's C-peptide numbers ranged from about 180 to about 280, and the second from about 20 to 140.  So that means these guys naturally varied by over 100 pmol/L.   Now take a look at the three patients who actually got BCG.  The three of them varied from about 2.2 to 4.4, from 1.8 to 6.2 and from 1.8 to about 6 [d16].  (All numbers very rough since I'm reading off of graphs.)

Here is the bottom line: people who were not given BCG naturally varied by 100 points during the trial.  People who were given BCG varied by less than 5 points.  The BCG changes were much less than the random fluxuations in the untreated people.  It's the very definition of "not statistically significant".  But remember, this is all based on the gold standard of comparing treated to placebo.  In fact, the results reported on in the paper are comparing the BCG treated patients to the "reference group" described in part C of the figure [d15].

The second weakness is an unusual technique of multiple control groups.  Obviously, most clinical trials report on several different results, and this trial is no exception, reporting on five different types of results.  The common thing to do is to use the same comparison group for all the results.  If you are comparing the treated group to a reference group (for example), you do that for C-peptide and A1c and insulin usage and whatever else you are testing for.  But this study uses a different comparison group for each different result [rp8].  Although the paper is very clear that this was done, there is no discussion of why it was done.  Here are the comparison groups, as I understand them:

The C-peptide results compared the treated group to the reference patients.
The Autoantibody results compared before and after data in the treated group.
The T-reg results compared the treated group and paired controls or to the placebo group.
The auto-reactive T cells  results compared treated group to healthy controls, to reference diabetics and to reference healthy controls.
The A1c comparison group was not specified.

Obviously, this brings up a whole host of questions, the most important is: why not use one control group for everything?  Are the results so fragile that they are dependent on careful selection of the control group?  See above for why that might be true for the C-peptide data, and it may well be true for the other data also.

Based on all of this, I think it is a mistake to say, as many have, that the study shows a very small improvement to C-peptide numbers.   I think it is more accurate to say that the study shows a very small improvement to C-peptide number, but this is dependent on the control group used.

The Future of This Research

In one sense, the future of this research is easy to predict.  Dr. Faustman has already gathered $8 million for the follow on phase-II trial, so I have every expectation that a follow on clinical trial will be done.

But scientifically, the future is much more murky.  In a nutshell, here are the current problems:
  1. Dr. Faustman's theory that BCG would lower the number of autoreactive T cells (or any other immune cells specific to type-1 diabetes) is not supported by this data.  No improvement is seen in living autoreactive T cells.
  2. There was no clinically significant good outcomes.  The C-peptide improvements, even if real, are too small to impact a person [d18]. 
  3. There was a worrisome outcome in A1c results.
Of course, research is always about the future: what can this grow into?  But if you are betting on future improvements, then it makes sense to start with a stronger base, and Dr. Zhao had much better results 6 months ago, and LCT for longer than that.

Moving this research forward is not going to be easy.  Because the current results are 100s of times too small for a cure, I don't think it is reasonable to just give "linear" higher doses or more frequent doses.  Certainly, not a dose 100s of times higher.  Often, it is the theory about why the treatment works that gives you clues about how to change doses between phase-I and phase-II.  If there is an important threshold, for example.  But in this case the theory about why the treatment works has not been supported by the phase-I, so there is no help there.

My opinion: Everyone wants to know if this clinical trial succeeded or failed.  This trial did not succeed, but did it fail?  Maybe, but I would phrase it a little differently.  One way to phrase it is this: This trial succeeded in telling us that the (BCG to TNF to less autoreactrive T cells to more beta cells to more insulin) theory was wrong.  Another way to phrase it is this: This trial is more indicative of a basic research result, than a path-to-product research result.  There were anomalies that might turn out to be interesting: the dead autoreactive T cells and also the change in GAD/TnT8A antibodies and regulatory T cells, but these represent basic research and there is no obvious path from these results to a cure.

Extra Discussion and References

Discussion

[d1] I view clinical results (ie. effects that directly help a person with type-1) as much more important that research results (ie. effects that might lead to further research, or are interesting and novel).  So C-peptide is the most important clinical result because it means less insulin is used, and is the official FDA marker for cures of type-1 diabetes.  A1c is second most important clinical result because it is highly cooralted with fewer long term complications of type-1.  For the research results, autoreactive T-cells are the most important because they are central to Dr. Faustman's theory (and I"m sure that's why this was the primary outcome listed).  The autoreactive antibody are next because they are specific to type-1 diabetes, while the reglatory  T cells are near the bottom because they are not type-1 specific, and TNF is  sort of an internal check of Dr. Faustman's theory, so I put it last.

[d2] According to the Mayo clinic [r9], their testing shows reference numbers (for fasting) of:
1.1-4.4 ng/mL which converts to: 365 - 1456 pmol/L.  Zhao's uses a lower reference number of about 0.6 ng/ml which is 199 pmol/L.  Zhao's research was done in China, and Zhao believes that the Chinese have, on average, lower fasting C-peptide numbers than the Americans who make up the baseline of the Mayo clinic's numbers.  Web poster "Celsus" used a range of 260 pmol/L - 1320 pmol/L here: http://islet.org/forum/messages/55197.htm

[d3] Details on C-peptide Calculations

Faustman's C-peptides (paper in pmol/L):
Two responding BCG treated patients: 3.49+2.57 = 6.06 / 2 = 3.03 [rp1]
All BCG treated paitents: 3.49+2.57+0 = 6.06 / 3 = 2.0.2
Baseline average: 1.65

Average improvement (responders only): 3.03 - 1.65 = 1.38 pmol/L
Average improvement (all treated patients): 2.02 - 1.65 = .37 pmol/L

Zhao's C-peptides (paper in ng/ml):
Average improvement for Group B: 0.5 ng/ml x 331 = 165.5 pmol/L
Average improvement for Group A: 0.45 ng/ml x 331 = 149 pmol/L
Average improvement (all treated patients): 165.5+149 / 2 = 157 pmol/L
These numbers are approximate, because I read them off of Zhao's graph at 24 weeks.[r9]

For Dr. Zhao:
Average improvement (all treated patients): 165.5+149 / 2 = 157 pmol/L

[d4] I'm specifically excluding Burt research (including both the Snarski and Li follow on work) because of the risk involved.

[d5] Remember that I have not done any analysis of measurement error here.


[d6]. I consider measuring injected insulin to be an inferior measurement as compared to measuring C-peptide.  If a person eats less carbs, or lets their A1c number rise, they will need less insulin, but that is not an improvement.  On the other hand, C-peptide measures how much insulin their body is naturally producing.

[d7]  I'm assuming that if a person's insulin needs go down by 10%, and the minium C-peptide a non-type-1 diabetic needs is about 200 pmol/L, then that is equivelent to generating 10 pmol/L.  It's a very rough estimate.

[d8] A1c numbers were recorded at "Baseline", "Week 5", and "Week 20".  Officially, A1c numbers are supposed to be an average of the last 13 weeks, although the most recent 2-4 weeks seem to have more impact than the 9 earlier weeks.  BCG was dosed at week 0 and 4, the best time to measure A1c is dependant on how long it takes for the BCG to become maximally effective and how long it would be effective for.  For example, if the BCG took 1 week to reach maximum effectiveness, and then was effective for 1 more week, then measuring A1c on week 7 would give the strongest results.  On the other hand, if BCG was effective for 4 weeks and took effect immediately, then the best A1c would be measured at 9 weeks.  Unfortunately, if you look at Figure 8 part A, there is no clear trend on either how long it takes to take effect or how long effectriveness lasts.

[d9] People using phrases like "success" and "failure" with respect to a clinical trial may have different ideas about what exactly they mean.  However, I use the following definition which is pretty standard: "A statistically significant positive result in the primary outcome."

[d10] As you might expect, Dr. Faustman does not share this view.  The paper is very specific: 
The rapid release of dead insulin-autoreactive T cells supports the hypothesis, first demonstrated in the NOD-mouse model of autoimmune diabetes, that BCG ameliorates the advanced autoimmune process underlying type 1 diabetes by stimulating TNF, which selectively kills only disease-causing cells and, further, permits pancreas regeneration as evidenced by the transient increase in C-peptide secretion we observed using an ultrasensitive C-peptide assay [rp16].
I can not agree that excess dead autoreactive T cells (with no drop in live ones) supports the hypothesis.  Not without a long stretch and a lot of wishful thinking.

[d11] Dr. Faustman has always made a big point of the fact that BCG was supposed to target the specific immune cells that were misbehaving, and not a whole class of immune cells.  For example:
unlike other immunosuppressive therapies for autoimmune diseases that harm both healthy and disease-causing T-cells, this treatment appears to provide a way to achieve “targeted  removal” of only autoimmune disease-causing cells.
which is from: http://www.faustmanlab.org/docs/newsletters/Faustman_updates_f09.pdf


[d12] For a recent spectacular example of why regulatory T cell drops may be nothing, consider this research:
http://medicalxpress.com/news/2012-08-experimental-combo-treatment-worsens-diabetes.html
These guys were testing something that prevented type-1 in NOD mice, but found that the same treatment in people made type-1 worse, but also increased regulatory T cells.

[d13]  For example, in a phase-I trial it might be too expensive or too much hassle to recruit twice as many people.  Or, the treatment may be hard to placebo (maybe it has a unique taste, or is some form of exercise/training where everyone involves knows if you did it or not).  Or the disease may be so rare that getting enough people for the treated group is hard enough, and getting more for a placebo group is not reasonable.  Obviously, none of these things applied to this trial.  In fact, they had a placebo group.  They just didn't use it for the important analysis.

[d14] For example, comparing people from two different countries often makes for awful science, because the groups are often not fundamentally similar.  In fact, they are often quite different.  On the other hand, a reference group specifically recruited from the same population as the treated group can be much better, and that's what was done for this trial.

[d15] This reference group was not mentioned in the original experimental design [r7], but was included in the published paper [r1] showing that it was added later.  There was a few sentences about AUC measurements of C-peptide levels being higher, but no mention of if it were statistically significant [rp17]. 

[d16]  As you read the graph in the paper, notice the different labeling on the Y access.  The BCG and EBV patients are labeled from 0-8, but the placebo patients are labeled from 0 to 400 or 600: that's a huge difference.  Imagine what these graphs would look like, if all the patients were graphed on the same Y access!

[d100] This is the data reported in Faustman's abstract.  She implies that the third patient did not see improvement in C-peptide, but does not provide exact data.

[d18] It is important to understand the difference between "statistically significant" and "clinically significant".  Statistically significant means the result is unlikely to be an accident or due to random fluctuations.  In a sense, it means there really is a difference between the treated and untreated patients.  Clinically significant is a difference that matters to the patient.  It is a difference that makes them healthier, or makes the management of their disease easier,  in a way they can experience.

[d19] Of course, the C-peptide numbers only came from three people as well, so (in theory) they should have the same problems with small sample size as the A1c numbers.  However, for the C-peptide number the researchers used a larger "reference group" for comparison, rather than the very small placebo group.  They didn't publish A1c numbers for the reference group, so I can not compare those patients to the BCG group.

References

[r1] This is the URL for Dr. Faustman's paper, which is available for free on the web.
(Thanks PLoS One!)
http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0041756

[r2] Dr. Faustman's Newsletter here:
http://www.faustmanlab.org/docs/newsletters/Faustman_updates_f06.pdf
Especially the article "Why use bacillus Calmette-Guérin (BCG)?" which says:
BCG causes the body to make a natural substance called TNF. TNF helps to regulate the immune system and can kill a portion of the “bad” T cells that cause diabetes.
Another newsletter, with the same info is here: http://www.faustmanlab.org/docs/newsletters/Faustman_updates_f09.pdf
Especially the article "BCG Therapy At Work" on page 5.

[r3] Secondary source is here:
http://en.wikipedia.org/wiki/Denise_Faustman
Primary source is here:
http://www.ncbi.nlm.nih.gov/pubmed/15968469
As far as I can tell this was first suggested by Alleva in 1993:
http://www.ncbi.nlm.nih.gov/pubmed/8244447

[r7] Original experimental design is summarized here:
http://clinicaltrials.gov/beta/show/NCT00607230

[r5] You can find extensive discussion of Dr. Zhao's work here:
http://cureresearch4type1diabetes.blogspot.com/search/label/Zhao

[r4] General information on BCG is here:
http://en.wikipedia.org/wiki/Bacillus_Calmette-Gu%C3%A9rin
http://www.nlm.nih.gov/medlineplus/druginfo/meds/a682809.html
http://blcwebcafe.org/bcg.asp

[r6]
http://www.lctglobal.com/html/blob.php/110606_LCT_IPITA_Presentations_FINAL.pdf?attach=0&documentCode=3505&elementId=20084

[r8] For example, from this document: http://www.nice.org.uk/nicemedia/live/12165/44318/44318.pdf
In general, 0.5% HbA1c is considered a clinically significant change (e.g. treatment guidelines from ADA/EASD and NICE)
Another example is this study:
http://www.ncbi.nlm.nih.gov/pubmed/17561790
reported that lowering A1c by 0.4 was a good result, so  raising it more than that would be a bad one.

[r9]  The 331 constant for the conversion and the 1.1-4.4 ng/mL baseline comes from the Mayo clinic's web page: http://www.mayomedicallaboratories.com/test-catalog/Clinical+and+Interpretive/8804

References from the Paper

[rp1] Information from the paper's abstract.

[rp11] Figure 6 A. on page 11.

[rp2] Figure 4 A on page 8.
http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041756.g004/largerimage

[rp3] Figure 4 B on page 8 and also Figure 5 on page 9 for one specific example.
http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041756.g004/largerimage
http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041756.g005/largerimage

[rp5] Third paragraph of the Introduction.  She uses this paper as a reference:
http://www.plospathogens.org/article/info%3Adoi%2F10.1371%2Fjournal.ppat.0020004
but I don't see any references to BCG in there.

[rp6] From the first paragraph of "Statistical Analysis" on page 9:
None of the analyses compared the BCG-treated to placebo-treated clinical trial subjects.
[rp7] Look in the lower left have side of this diagram:
http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041756?imageURI=info:doi/10.1371/journal.pone.0041756.g001

[rp8] Figure 8 on page 13 has the C-peptide data.

[rp6] This is the exact quote, from the section "Statistical Analysis" (1st paragraph):
"None of the analyses compared the BCG-treated to placebo-treated clinical trial subjects."

[rp35] All this data came from ...

[rp4]  The paragraph just after figure 4 on page 8.

[rp14] Page 10, the paragraph "Other Clinical and Safety Monitoring"

[rp15] Figure 2, page 7, last few rows.

[rp16] This is from the first paragraph under "Discussion" on page 10.  I've removed the footnotes.

[rp17] The last paragraph in the "Fasting Insulin Secretion Temporarily Increased..." section on page 10.

Joshua Levy
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF or JDCA news, views, policies or opinions. My blog contains a more complete non-conflict of interest statement.
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