CDC Multi-site Study: Heterogeneity in ME/CFS Illness Measures Not Explained by Clinical Practice, 2024, Unger et al

[Three Chord Monty]

Heterogeneity in Measures of Illness among Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Is Not Explained by Clinical Practice: A Study in Seven U.S. Specialty Clinics

Elizabeth R. Unger on behalf of the MCAM Study Group
Jin-Mann S. Lin 1, Yang Chen 1, Monica E. Cornelius 1, Britany Helton 1, Anindita N. Issa 1, Jeanne Bertolli 1,Nancy G. Klimas 2,3, Elizabeth G. Balbin 2, Lucinda Bateman 4, Charles W. Lapp 5, Wendy Springs 5, Richard N. Podell 6,Trisha Fitzpatrick 6, Daniel L. Peterson 7, C. Gunnar Gottschalk 7, Benjamin H. Natelson 8, Michelle Blate 8, Andreas M. Kogelnik 9, Catrina C. Phan 9, and on behalf of the MCAM Study Group

1 Division of High-Consequence Pathogens and Pathology, Centers for Disease Control and Prevention (CDC), Atlanta, GA 30329-4027, USA
2 Institute for Neuro Immune Medicine, Nova Southeastern University, Fort Lauderdale, FL 33314, USA
3 VA Medical Center, Geriatric Research and Education Clinical Center, Miami, FL 33125, USA
4 Bateman Horne Center, Salt Lake City, UT 84102, USA
5 Hunter-Hopkins Center, Charlotte, NC 28226, USA
6 Richard N. Podell Medical, Summit, NJ 07901, USA
7 Sierra Internal Medicine, Incline Village, NV 89451, USA
8 Department of Neurology, Mount Sinai Beth Israel, New York, NY 10029, USA
9 Open Medicine Clinic, Mountain View, CA 94040, USA

https://www.mdpi.com/2077-0383/13/5/1369

 

[Three Chord Monty]

Abstract

Background: One of the goals of the Multi-site Clinical Assessment of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (MCAM) study was to evaluate whether clinicians experienced in diagnosing and caring for patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) recognized the same clinical entity. Methods: We enrolled participants from seven specialty clinics in the United States. We used baseline data (n = 465) on standardized questions measuring general clinical characteristics, functional impairment, post-exertional malaise, fatigue, sleep, neurocognitive/autonomic symptoms, pain, and other symptoms to evaluate whether patient characteristics differed by clinic. Results: We found few statistically significant and no clinically significant differences between clinics in their patients’ standardized measures of ME/CFS symptoms and function. Strikingly, patients in each clinic sample and overall showed a wide distribution in all scores and measures. Conclusions: Illness heterogeneity may be an inherent feature of ME/CFS. Presenting research data in scatter plots or histograms will help clarify the challenge. Relying on case–control study designs without subgrouping or stratification of ME/CFS illness characteristics may limit the reproducibility of research findings and could obscure underlying mechanisms.

This is in the Journal of Clinical Medicine's current special issue on ME/CFS. Not sure if it's officially a CDC publication but given their involvement I'll say I'm not sure I've ever seen something like this in an MDPI journal, even taking into consideration some are better than others & we've seen a good number of ME/CFS-related papers in MDPI journals recently.

 

[Three Chord Monty]

4. Discussion
We initiated this study to characterize patients with ME/CFS based on the clinical opinion of clinicians with recognized expertise in diagnosing and caring for these patients. The goal of this analysis was to determine if differences in clinical practice resulted in different subgroups of patients. We used standardized instruments to measure the major domains of illness experienced by patients with ME/CFS and evaluated these characteristics for patients seen at each clinic and overall. The specialty clinics differed in size (solo practice, small group, academic, hospital-based), location (metropolitan, urban, and rural), and practice characteristics (time spent with patients, charges for initial visit, follow-up visits). The board certifications of the physicians included internal medicine, environmental medicine, infectious diseases, immunology, hematology, neurology, and pediatrics. Certifications could influence referral patterns and approaches to laboratory testing, diagnosis, and management. There were statistical differences between sites in the general characteristics of their patients.

In the face of these practice differences, it is striking that we found few statistically significant and no clinically meaningful differences between clinics in their patients’ standardized measures of ME/CFS symptoms and function (Table 4, Table 5, Table 6, Table 7, Table 8, Table 9 and Table 10). This suggests that expert clinicians are recognizing the same clinical entity, albeit one that is far from homogeneous.

This study’s strength lies in the clinical expertise and combined data from seven ME/CFS specialty clinics. However, this strength is also a limitation as those seen in other clinics, by primary care physicians, or not having access to any care are not represented. This could bias the study sample and may limit the generalizability of the findings. Patients with illness severity that prevents travel to clinics were not included, and this should be kept in mind when interpreting the results. The study population is largely white, highly educated, and insured. Increasing patient diversity would be unlikely to decrease the heterogeneity of illness characteristics; thus, the major observation that ME/CFS is a heterogenous illness and that the heterogeneity is not explained by different clinical practices remains. Study designs that incorporate illness heterogeneity to shed light on underlying pathogenesis are needed.

 

[ME/CFS Skeptic]

So the main conclusion is that the ME/CFS patient population is heterogenous but that without many differences between the cohorts at different clinics. Or as they write: "This suggests that expert clinicians are recognizing the same clinical entity, albeit one that is far from homogeneous."

Strange that only 57% of these patients met the IOM-criteria, compared to 83% for the Fukuda criteria.

 

[Keela Too]

It seems to me that it doesn’t necessarily tell us much about the patients, but that rather the clinicians admitting patients are admitting similar patients to all the clinics. Thus they must all be using similar criteria.

Whether those criteria actually correctly identify ME, is probably less certain than the fact they are all roughly agreeing on who to admit.

It might also be that clinicians admit on slightly looser criteria, in order to ensure they don’t lose patients to overly strict criteria? (Eg PEM may be difficult to ascertain in some-one newly ill, especially if the patient hasn’t yet recognised the pattern.)

Interesting all the same.

 

[wigglethemouse]

This must be old data and I suspect the paper is a retrospective review of the older data.

We have published the overall socio-demographic characteristics of the initial study sample (n = 471) from baseline enrollment between January 2012 and May 2013 [7]. Six of those enrolled were later confirmed to be age-ineligible and removed from further analysis; thus, the current analysis includes data from 465 ME/CFS patients. Patient characteristics are examined by site (A through G) as well as overall.

The 471 cases came from their 2017 paper. The 2017 paper lists the study length.
Thread : https://www.s4me.info/threads/multi...spective-retrospective-2017-unger-et-al.9056/

MCAM was initiated in 2012 and is anticipated to continue in multiple stages through 2017

So SEVEN years to analyze this and produce a paper. Absolutely no urgency in the Federal Government organizations.

 

[wigglethemouse]

Here is the CDC webpage for the study.
https://www.cdc.gov/me-cfs/programs/multi-site-clinical-assessment.html

Info on the 7 sites.

There are seven participating clinical sites:

1. Pain and Fatigue Study Center, NY
2. Center for Neuro-Immune Disorders, FL
3. Open Medicine Institute (OMI) consortium:
* Open Medicine Clinic, CA
* Sierra Internal Medicine Associates, NV
* Fatigue Consultation Clinic, UT
* Hunter-Hopkins Center, NC
* Richard Podell Clinic, NJ

 

[Medfeb]

This must be old data and I suspect the paper is a retrospective review of the older data.

So SEVEN years to analyze this and produce a paper. Absolutely no urgency in the Federal Government organizations.

This is just an additional paper from CDC's multi-site "MCAM" study, initiated in 2011. It's typical of CDC to dribble out papers from their studies - at least the ME studies - over many years. Maddening especially given the incredibly narrow scope of its goals.

Strange that only 57% of these patients met the IOM-criteria, compared to 83% for the Fukuda criteria.

I'm surprised that so few met IOM. In their 2017 paper on this study, they reported the following percentages of PEM, unrefreshing sleep, fatigue, and cognitive.

 

[Mij]

Merged - this is about an article discussing the paper that is the subject of this thread

A new CDC-funded paper includes criteria that may be leading to inaccurate prevalence rates

The stock photo . . .

https://www.medpagetoday.com/opinion/second-opinions/109274?trw=no

 

[Hutan]

The article is by Leonard Jason
I thought this was a very good exposition of the arguments against using ME/CFS (CFS) criteria that don't include PEM.

However, I have my doubts about the conclusion, made in the very last sentence:

Ideally, researchers should determine a unified, and more appropriate, criteria so that we can study this illness accurately and to the greatest benefit of those suffering.

I think, until we have a diagnostic biomarker, an effort to create a 'unified and more appropriate criteria' is not going to get us very far and could just distract research effort and funds that are better applied elsewhere. I'd be happy with researchers just using a criteria that includes PEM, and clearly stating the criteria, the exclusions and the selection process in their reports.

 

[Sean]

I don't see criteria being able to be improved much until we have a better characterisation of the phenomenon.

 

[alex3619]

I think, until we have a diagnostic biomarker, an effort to create a 'unified and more appropriate criteria' is not going to get us very far and could just distract research effort and funds that are better applied elsewhere.

This. I consider a biomarker absolutely essential for steady research progress without relying on serendipity.

However there are three possibilities that present different issues. One, all or nearly all patients have the same disease, we just have not found the biomarker yet. It might be something yet to be even discovered as a biochemical or whatever it is. This is highly likely in my view.

Two, ME is many different diseases. In which case we are looking for many biomarkers, complicating the search. This might be right.

Three, the most disturbing, ME is not a disease in the classical sense. There IS NO biomarker. In this view ME would be a spectrum disorder or disease. If you have several hundred or thousands of the many thousands of things that can go wrong, you have ME. We might be looking for a phantom when we look for biomarkers. My conception of this view is linked to the emergency immune response idea, leading to major metabolomic changes like we find in ME, sepsis and severe burns. In this process many epigenetic and expression changes occur, and something can go wrong during this process. Then the immune challenge is cleared, such as an infection. Then we rewrite the entire response to reset to normal. Something can go wrong here too. So with thousands of things that can go wrong, in many different ways, there are potentially many thousands or even millions of types of ME. Its a spectrum, not a discrete disease entity. I hope this idea is wrong, but the unifying factor here would lead to a focus on rewriting the immune and metabolic response. Don't cure it, hit the reset switch instead.

 

[Tom Kindlon]

Merged - this is about an article discussing the paper that is the subject of this thread

A new CDC-funded paper includes criteria that may be leading to inaccurate prevalence rates

The stock photo . . .

https://www.medpagetoday.com/opinion/second-opinions/109274?trw=no

The #CFS empirical case criteria (Reeves et al., 2005) are a weird operationalisation of the Fukuda criteria. I campaigned against them previously, including setting up this petition against them which people can still sign https://www.ipetitions.com/petition/empirical_defn_and_CFS_research

https://twitter.com/user/status/1771191671214031357

 

[Dolphin]

Summary article:


Disease heterogeneity among people with ME/CFS
https://www.meresearch.org.uk/disease-heterogeneity-among-people-with-me-cfs/

https://twitter.com/user/status/1812774107932660134

 

[bobbler]

The article is by Leonard Jason
I thought this was a very good exposition of the arguments against using ME/CFS (CFS) criteria that don't include PEM.

However, I have my doubts about the conclusion, made in the very last sentence:

I think, until we have a diagnostic biomarker, an effort to create a 'unified and more appropriate criteria' is not going to get us very far and could just distract research effort and funds that are better applied elsewhere. I'd be happy with researchers just using a criteria that includes PEM, and clearly stating the criteria, the exclusions and the selection process in their reports.

And of course now I know the date it was planned and likely done it just makes me wonder whether what they are picking up is ‘within patient’ differences due to PEM and thresholds rather than being ‘across patient’ due to something different happening.

bith are sort of possible because I wonder about types just meeting others with ME and sleep reversal being one big example that tends to come with other differences that sound like a type. But that would be down to what that eventually turns out to be and what we technically count as a different’type’

a lot could be if you define ME/CFS as something to do with pEM / reaction and recovery cycles (or not completing said cycles) to exertion. And then you’ve differences due to timings different exertion in the preceding however many days then hours has on timing of different bodily reactions or changes.

then you’ve thresholds due to severity / individual weak pints (some might be particularly light, noise, speaking or physical movements affected vs other things).

so I maybe don’t have an issue with the flagging , more if the interpretation and suggestion. If it’s within person you’re never going to get that imaginary homogeneity. Unless you are controlling for threshold, PEM, exertion or at least taking info on these so you can see if the ‘high scores’ are the night owls for a 9am test or those who had to travel by train the day before so are beginning to be in PEM etc.

But then despite all this being predictable it isn’t consistent in exact times across all of us, and then I know my body can just make itself go off-kilter and ill for no reason sometimes for example. But at least if this stuff was better studied we’d know enough maybe to spot if someone was in PEM or over-threshold from other measures.

so it to me should have been about methodology focus rather than sample. Or at least as much. I’m pretty sure studies still don’t ask people how far they travelled and waited, what they’ve had on in their preceding days (if in PEM already), their normal timings for PEM or other fatiguability. Which are pretty fundamental to know what they were actually testing in each person. You could have 5in PEM and the rest not for example.

but who knows when it was 2011-17 there could be those without PEM. Which obviously would need to be essential guest.