NIH intramural research program update

[searcher]

The NIH study will likely cost more per patient though-- subjects will be in-house for a week and will have CSF taken and extensively tested, along with fMRI and TMS, none of which can be done on the severely ill.
(Not to imply in any way that I don't want more subjects in the study.)

 

[viggster]

From the OMF Severely ill Big Data project
Gaining the extensive data set will require $25,000 per patient for logistics and supplies.

Assuming similar costs $1m more will get us up to 80 patients and then if we ditch one of the control groups we're at 100

Just a note of caution that NIH will never assign a dollar amount to an inpatient study in Bethesda. It's basically impossible to calculate - all of the studies piggyback on shared resources, and procedures like MRIs, etc., are not billed or priced out like in a regular hospital. (It's all "free" thanks to taxpayers.) Staff at the NIH Clinical Center typically split their time between many studies, so it's nearly impossible to quantify how expensive this or any study will be. As far as I know (going back almost 20 years), NIH has never assigned or announced a dollar figure for any of its internal clinical studies.

 

[BurnA]

Just a note of caution that NIH will never assign a dollar amount to an inpatient study in Bethesda. It's basically impossible to calculate - all of the studies piggyback on shared resources, and procedures like MRIs, etc., are not billed or priced out like in a regular hospital. (It's all "free" thanks to taxpayers.) Staff at the NIH Clinical Center typically split their time between many studies, so it's nearly impossible to quantify how expensive this or any study will be. As far as I know (going back almost 20 years), NIH has never assigned or announced a dollar figure for any of its internal clinical studies.

Yeah i wondered that. I assumed they must have some cost controls in place, so even if they don't announce a budget, staff costs and tests all need to be paid from some internal budget. Just like any organisation running a project where the staff allocate their hours to the project budget.

 

[viggster]

Yeah i wondered that. I assumed they must have some cost controls in place, so even if they don't announce a budget, staff costs and tests all need to be paid from some internal budget. Just like any organisation running a project where the staff allocate their hours to the project budget.

Staff hours are accounted for but lab tests, MRIs, procedures, etc., are not assigned any dollar value for individual studies. It's not like NINDS has to pay NIH headquarters when it orders tests for inpatients. It's like healthcare utopia - no billing department and no one has to wrestle with insurance companies!

 

[BurnA]

Staff hours are accounted for but lab tests, MRIs, procedures, etc., are not assigned any dollar value for individual studies. It's not like NINDS has to pay NIH headquarters when it orders tests for inpatients. It's like healthcare utopia - no billing department and no one has to wrestle with insurance companies!

If this is the case, it wouldn't be that much more costly to include more patients then ?

 

[viggster]

If this is the case, it wouldn't be that much more costly to include more patients then ?

Well resources are being used - rooms in the clinical center, staff time, etc. And those resources are finite and somehow get split up between the thousands of ongoing studies. What I'm saying is that NIH does not assign a dollar value to those resources in any way that can be broken out study-by-study.

 

[searcher]

I wanted to mention that the US Action Working Group (in which Phoenix Rising is a member) has been collecting questions to send to NIH at http://www.meaction.net/2016/02/12/usawg-submits-questions-to-the-nih/. It would be great to get more questions in a central location. There are already a few about the comparison groups but I don't think there are any yet about any of the investigators.

An initial set of questions was sent in soon after the protocol was posted and is at http://www.meaction.net/wp-content/uploads/2015/05/QuestionstoNIHreclinicalstudyFeb102016.pdf. Some of them have subsequently been answered but many have not. The questions were sent in last Wednesday and I don't think there has been an official response yet from NIH.

 

[Simon]

Probably a bit late, but here are some cleaned up slides that are a bit easier to read for the Nath presentation.

Read the transcript from #MEAction. Watch the video, starts at 42'38"

 

[olliec]

I don't think I saw anyone post the video yet

I added that to the MEpedia page http://me-pedia.org/wiki/NIH_Post-Infectious_ME/CFS_Study

 

[BurnA]

Clinicians refer patients to trials for reasons that have pretty little to do with them being representative cases. Usually it is because they are very unrepresentative and the clinician cannot think what to do with them.

This is concerning but is it less likely to happen in this case because clinicians generally don't know what to do with ME patients anyway.
Also, as this is not a treatment trial maybe there is less chance of this because it's not like a doctor is thinking that standard treatment hasn't worked but maybe this new trial treatment will work.
Or maybe this is all just wishful thinking on my part.

 

[Simon]

Strangely, the NIH is actually funding a population based cohort (I think 200) [for the UK biobank] already and this does not seem to appear in the study.

As the NIH want to do a whole load of in-house testing inc MRI, TMS and physiological tests (using a metabolic chamber), I assume it wouldn't be practical to use patients/samples from the UK.

Sample size

The problem is, as Scarecrow, says, that it is very easy to miss something important with a 40 patient cohort - just for statistical reasons, considering that it is very likely that the important thing may only apply to 30% or so of your cases (maybe even only 10%) with a heterogeneous pathophysiology...

I would use a 40 patient cohort for a look see study costing $100,000 targeting one particular biomarker - where you have no Bonferoni problems, which makes it easier to avoid type 2 errors [false negatives]. For a high cost study looking at lots of variables I find it hard to see how you are going to get reliable stats out of 40. And the key thing is that you may well miss the crucial markers, so going on to study what showed up on bigger populations takes you further and further down a blind alley.

I agree this looks on the small size. I always bangs on about the dangers multiple comparisons and given they plan looking at over 2,000 proteins they would expect 100 false positives by chance alone using p<0.05 (100 biomarkers!). So they would in theory need to use a much lower p value, eg p<0.005, risking missing real positives.

But I wonder if there is a different way? Nath implies they have a different approach in mind:

Initially we will be storing them and what we’ll be doing is looking at cell-free fluid in the CSF and the serum for not just a small number of cytokines– actually 1500 lysates-analytes, ok? So… but we want to be very, very comprehensive, and I’ve developed a proteomics assay in my own lab which will look at about at least 2500 proteins.

So when we look at those, that composite, I think it will be very clear to us what cell types may be dysfunctional in these patients and how we can subgroup those individuals. And that will then allow us to go back and now say, ‘Well this looks like an NK cell function, let’s look at it. Or this looks like a B cell function,’ because there’s just innumerable amounts of very time-consuming, tedious assays for each cell type that you could potentially do, or interactions between cell types. So, instead of doing that at the get-go on everything you could possibly think (of), I think that’s a good screening tool, and then we can focus on the real aspects that we think are really dysfunctional.”

So basically they will look at the patterns in the overall data to identify which cell functions are off, then focus on the most promising area with fewer tests. I don't know how you would handle this statistically, but the basic idea makes sense to me. Does this make a difference from your perspective?

Even so, with heterogeneity, there's a real danger of having at least several different types of patients and I don't know if this kind of rich data is capable of detecting such subtypes. The point is they wouldnt' be looking for individual marker differences, but clustering of different markers. I don't know enough abou the stats as to how many markers/how many patients are needed to get robust results.

Post-infcetious fatigue "Versus" mecfs

I suppose the key question is, does PIF = ME. My gut says no..

I think it depends - certainly I've come across plenty of people with long-term mecfs that began as glandular fever. What seem to happen in various study is that as time goes by, fewer and fewer PIF cases recover:

The case rate for provisional post-infective fatigue syndrome was:

• 35% (87/250) at six weeks
• 27% (67/250) at three months
• 12% (29/250) at six months,
  
• and 9% (22/250) at 12 months.
• (from memory, it was about 6% at 24 months, different paper though)

So while just-6-months-fatigue cases may well be iffy, I doubt they will have many at all of those, and certainly once you get to 2 years you are probably looking at mecfs. Interestingly, Mady Hornig and Ian Lipkin had huge problems finding enough patients using <3 years ill for their study, which might explain why the NIH have set the threshold at 5 years. My guess is there will be very few cases in practice of under two years, but you would want that info and a sub analysis of the shortest-term cases.

 

[Sasha]

I think it depends - certainly I've come across plenty of people with long-term mecfs that began as glandular fever. What seem to happen in various study is that as time goes by, fewer and fewer PIF cases recover:

I don't know that PIF = ME; I think it might be that PIF can become ME in a subset of cases. If so, looking at PIF people is going to be misleading (especially if a small proportion of the PIF subset get ME).

 

[Simon]

I don't know that PIF = ME; I think it might be that PIF can become ME in a subset of cases. If so, looking at PIF people is going to be misleading (especially if a small proportion of the PIF subset get ME).

I'd love to see the test that distinguishes 'long-term PIF who meet CCC' from ME; as I pointed out above, the evidence from Dubbo (and other studies) is that there is an asymptote to a low rate of long-term PIF. (And I'm not aware of any evidence that says recovery rates from non-infectious-onset ME is any different from what's seen for long-term PIF cases who meet CCC and Fukuda ie you would expect some people to recover in any case.)

As I said above, if you are looking 2+ years on (and the Hornig/Lipkin experience is that they struggle to get very short term cases) I don't see any reason to assume these cases are something different from mecfs - if they meet CCC and Fukuda criteria as all study participants will.

I genuinely don't understand your rationale, given the above. To me it's like saying there should be a CCC exclusion clause: "meets all the criteria, but PIF onset". What am I missing?

 

[Sasha]

I'd love to see the test that distinguishes 'long-term PIF who meet CCC' from ME; as I pointed out above, the evidence from Dubbo (and other studies) is that there is an asymptote to a low rate of long-term PIF. (And I'm not aware of any evidence that says recovery rates from non-infectious-onset ME is any different from what's seen for long-term PIF cases who meet CCC and Fukuda ie you would expect some people to recover in any case.)

As I said above, if you are looking 2+ years on (and the Hornig/Lipkin experience is that they struggle to get very short term cases) I don't see any reason to assume these cases are something different from mecfs - if they meet CCC and Fukuda criteria as all study participants will.

I genuinely don't understand your rationale, given the above. To me it's like saying there should be a CCC exclusion clause: "meets all the criteria, but PIF onset". What am I missing?

I was talking about short-term PIF. I agree with you about long-term PIF (I'm a long-term PIF case and fulfil CCC ME criteria).

Sorry if I posted something confusing - not firing on all brain cylinders today.

 

[Simon]

not firing on all brain cylinders today.

That's two of us, at least.

 

[Scarecrow]

I think it depends - certainly I've come across plenty of people with long-term mecfs that began as glandular fever. What seem to happen in various study is that as time goes by, fewer and fewer PIF cases recover:

Weirdly, the quotation above this text in your post correctly links back to my post but shows Sasha's name!

I'd love to see the test that distinguishes 'long-term PIF who meet CCC' from ME; as I pointed out above, the evidence from Dubbo (and other studies) is that there is an asymptote to a low rate of long-term PIF.-

What if PIF is genuinely self-limiting and the reason why there is an asymptote is because the ME/CFS cases make it look like an asymptote? If we can't distinguish apparent non-infectious onset cases from those with an apparent infectious onset, why should we be able to distinguish PIF from ME/CFS? (By distinguish, I'm referring to sets of symptoms, not to potential biomarkers.)

(And I'm not aware of any evidence that says recovery rates from non-infectious-onset ME is any different from what's seen for long-term PIF cases who meet CCC and Fukuda ie you would expect some people to recover in any case.)

If there is no such thing as genuinely long term PIF, only ME/CFS with an infectious onset, would we expect to see different recovery rates?

 

[searcher]

I think it is very rare for the US specialist clinics to see patients in the first year and likely two, which could explains why Lipkin/Hornig had trouble finding patients in the first two years. Many of them have long waiting lists so even if you have figured out what's going on in six months and you are prepared to pay out of pocket (most of the specialists don't take insurance) you may not be seeing a doctor for another year. And they probably wouldn't refer patients who they had only seen once because I think all of these clinic do extensive testing to rule out other diseases which typically requires multiple visits. So I would be really surprised if the NIH had many subjects who were between 6-12 months from onset unless they specifically request those referrals from the clinics.

 

[Sasha]

Weirdly, the quotation above this text in your post correctly links back to my post but shows Sasha's name!

I was wondering how I'd got into this! But, oddly, I didn't realise I hadn't said anything!

 

[Jonathan Edwards]

So when we look at those, that composite, I think it will be very clear to us what cell types may be dysfunctional in these patients and how we can subgroup those individuals. And that will then allow us to go back and now say, ‘Well this looks like an NK cell function, let’s look at it. Or this looks like a B cell function,’ because there’s just innumerable amounts of very time-consuming, tedious assays for each cell type that you could potentially do, or interactions between cell types. So, instead of doing that at the get-go on everything you could possibly think (of), I think that’s a good screening tool, and then we can focus on the real aspects that we think are really dysfunctional.”

So basically they will look at the patterns in the overall data to identify which cell functions are off, then focus on the most promising area with fewer tests. I don't know how you would handle this statistically, but the basic idea makes sense to me. Does this make a difference from your perspective?

I have a suspicion that people like Mady Hornig, Oysten Fluge, Amolok Bansal, Juliá Blanco, Carmen Scheibenbogen, James Baraniuk, and Jo Cambridge might think 'hmm, strange that we did all the tests we could possibly think of and struggled to find anything, and when we did find something, it did not look like any standard pattern anyone got before'. This was more or less the conclusion from the IiME workshop last year - people are finding things but not in line with giveaway cell signatures - if anything back to front of that. I don't want to dampen any spirits but a few other people have tried slaying this particular Minotaur in ten easy steps.

 

[BurnA]

If they've done all the tests they could think of and have drawn a blank, where do they go or what do they do next ?

Is it reasonable enough for the NIH to start from scratch so to speak, and maybe pick up on something that hasn't been done before?
Or are you saying more or less all the NIH testing has been done before ? ( excluding pre and post exercise I presume )