Open The Chronic Illness Survey Adventure (Symptom Cluster Characterization in Complex Chronic Disease)

Kalliope

Kalliope

Senior Member (Voting Rights)
Partners: Patient-Led Research Collaborative, #MEAction, Columbia University Mailman School of Public Health, The Jackson Laboratory, Massachussetts ME/CFS & FM, The University of Edinburgh (MRC)

ABOUT
The Chronic Illness Survey Adventure (Symptom Cluster Characterization in Complex Chronic Disease) is a survey-based study to probe more deeply into ME/CFS, long COVID, POTS, hEDS, and MCAS. Our survey began by examining the symptoms listed in sets of diagnostic criteria for each illness. Then, we incorporated validated surveys for complex symptoms such as pain or fatigue. But that was just the beginning.

Next, we recruited clinical partners to help recruit participants and validate their own patients’ diagnoses, and partners with lived experience of each of these diseases. Together, we gathered patient-reported symptoms not present in any set of criteria.

Now, we need your help to gather the richest dataset on complex chronic disease ever created. Let’s discover more about what we have in common and more about what makes us unique. Join us on this year-long adventure!

https://www.meaction.net/epi/
 
It'sME(Jaime) on Twitter:

Here is my huge announcement! My new study, Symptom Cluster Characterization in Complex Chronic Disease is now enrolling. This survey-based study will probe more deeply into #MEcfs, #longCOVID, #POTS, #hEDS & #MCAS symptoms. https://meaction.net/epi (1/5)

Symptoms from diagnostic criteria & validated questionnaires on complex symptom sets like sensory sensitivity are just the beginning. The survey also has a wealth of patient-reported data from interviews and conversations that, up to now, only existed in the #NEISvoid. (2/5)

Our partners are@MassMECFS,@patientled,@mrc_hgu, and@jacksonlab-- my co-investigator, Dr. Mady Hornig at Columbia University’s Mailman School of Public Health (@mhornig). We’re honored to be in such good company! (3/5)

Clinical partners Drs. Bateman@BatemanHorne, Levine, Bonilla@StanfordMed, Chen, & Chu helped guide symptom characterization. Their validation of patient diagnoses will ensure that our data is derived from a core of confirmed cases.(4/5)

Now, we need your help to gather the richest dataset on complex chronic disease ever created. Let’s discover more about what we have in common & more about what makes us unique. Join us on this adventure! https://meaction.net/epi (5/5) #MEcfs #longCOVID #POTS #hEDS #MCAS #NEISvoid





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ME Action just announced this study. I'm interested In what others think.

I'm a bit concerned. Without a representative sample, a survey about symptom clusters and the relation with hEDS, MCAS, POTS etc. are likely to give misleading answers.

There also another issue which I will try to explain further. In my view the big question is not how do the diagnoses hEDS, MCAS, POTS etc relate to ME/CFS in terms of symptoms and characteristics. The big question is: are diagnoses such as hEDS, MCAS, POTS etc. justified and reliable? In contrast to ME/CFS, they refer to an abnormality (involving collagen, mast cells or tachycardia) without providing sound evidence that this is causally related to the severe symptoms of the syndrome.

Perhaps I could best explain this with an analogy. In Belgium, one of the most popular ME/CFS doctors is Kenny De Meirleir. For a couple of years, he has been diagnosing ME/CFS patients with chronic lyme disease based on dubious tests.

I'm part of a Belgian patient organisation. If we were to set up a survey of patients who went to see KDM and look for the relation in symptoms clusters between ME/CFS and KDM's lyme diagnoses, that would bring us no further. In fact, it would probably lead to misleading conclusions because the big question that needs to be answered is whether those chronic lyme diagnoses are reliable.

If I look at what the ME Action survey is hoping to study and then at the way it is set up, the two don't match. I can't see how one would get reliable epidemiological data by a survey in collaboration with a couple of ME/CFS specialists. Perhaps I'm missing something? What do others think?
 
If it's prevalence they are trying to determine, then I agree with you @Michiel Tack that this doesn't look like the right way to get a true epidemiological picture.

I get the impression that it's more about trying to describe in more detail the groups of symptoms experienced by people given these various diagnoses. If each condition with a name is diagnosed by a set of symptoms, then I'm guessing the aim is to find out whether, for example, people diagnosed with ME/CFS have overlapping symptoms with people diagnosed with, say, MCAS, even if they aren't listed on clinical diagnostic criteria. So, for example, are headaches or sensory sensitivities experienced in both groups.

I'm not clear what the purpose is.
 
@Michiel Tack I suspect you're misunderstanding the goal of the study. I think it's meant to document what symptoms patients are experiencing and highlight symptoms that may be receiving little attention, as well as showing overlap between POTS, MCAS, ME/CFS, long covid.

If there is a lot of overlap and few differences then it would suggest that maybe these are the same illness. If there are clear differences then maybe these are different illnesses. In any case it wouldn't tell us that MCAS is really due to mast cells.
 
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Trish said:
If each condition with a name is diagnosed by a set of symptoms, then I'm guessing the aim is to find out whether, for example, people diagnosed with ME/CFS have overlapping symptoms with people diagnosed with, say, MCAS,
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Yes, but if they are recruiting through ME/CFS patient organisations and clinicians then any data obtained in this way is likely to be misleading.

And even if a representative sample is obtained, I'm afraid symptom overlap is unlikely to give useful clues about POTS, MCAS, hEDS etc. It all depends on whether the explanations these syndromes refer to (abnormalities in collagen/hypermobility, mast cells or postural tachycardia) have anything to do with the symptoms that are being measured. Otherwise, It could be as irrelevant as measuring symptom clustering in the chronic Lyme patients KDM diagnoses.

Hope I'm not being too harsh. Just have a hard time seeing how measuring symptom clustering in this way is going to provide reliable data.
 
Michiel Tack said:
Just have a hard time seeing how measuring symptom clustering in this way is going to provide reliable data.
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I don’t know the thinking behind this specific survey, but my understanding is that surveys are useful to get general ideas and possibilities, which are then along with other evidence sources used to inform further structured research that gives hopefully more reliable answers.
 
I think we can assume that people are going to be biased towards reporting the symptoms consistent with the diagnostic labels they were given.

However they also get the chance to report symptoms that are rarely mentioned in connection to the respective diagnostic labels and here we could be seeing interesting new information, e.g. eye symptoms in ME/CFS.

The overlap is also potentially interesting. What if see increased MCAS-like symptoms in the +POTS -MCAS group but not the +ME -MCAS group? It suggests that whatever it is that is being diagnosed as MCAS may have overlap with POTS. This is independent of any explanations of how these illnesses work.
 
I would like to ask why they are choosing these specific conditions. Why not include MS, or migraine, for example? I agree it's hard to understand what the aim is and whether it will be achieved with self selected samples.
 
Kalliope said:
It'sME(Jaime) on Twitter:

Here is my huge announcement! My new study, Symptom Cluster Characterization in Complex Chronic Disease is now enrolling. This survey-based study will probe more deeply into #MEcfs, #longCOVID, #POTS, #hEDS & #MCAS symptoms. https://meaction.net/epi (1/5)

Symptoms from diagnostic criteria & validated questionnaires on complex symptom sets like sensory sensitivity are just the beginning. The survey also has a wealth of patient-reported data from interviews and conversations that, up to now, only existed in the #NEISvoid. (2/5)

Our partners are@MassMECFS,@patientled,@mrc_hgu, and@jacksonlab-- my co-investigator, Dr. Mady Hornig at Columbia University’s Mailman School of Public Health (@mhornig). We’re honored to be in such good company! (3/5)

Clinical partners Drs. Bateman@BatemanHorne, Levine, Bonilla@StanfordMed, Chen, & Chu helped guide symptom characterization. Their validation of patient diagnoses will ensure that our data is derived from a core of confirmed cases.(4/5)

Now, we need your help to gather the richest dataset on complex chronic disease ever created. Let’s discover more about what we have in common & more about what makes us unique. Join us on this adventure! https://meaction.net/epi (5/5) #MEcfs #longCOVID #POTS #hEDS #MCAS #NEISvoid
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Does anyone know what the hashtag #NEISvoid stands for? It seems to be an umbrella term for the conditions the survey is directed towards.

Also, has anyone had a go yet at the survey? How was it?
 
I have just signed up. You have to give a user name and an email address and they will send an email to a link to the survey in a week's time, then again once a month for 6 months. There is also an FAQ section which gives more information about what they are doing and why. I still don't really feel any the wiser, but time will tell.
 
This is from the FAQ:

Why do patient-reported symptoms matter? Why does patient-centered research matter?
Patient and public involvement is a very important part of research projects that aim to engage with and inquire deeply into the patient experience. In order to better understand the disease presentation and course, it is important to directly engage with patients. Over the course of our investigations, we encountered several symptoms common in ME/CFS and other chronic complex diseases that were not part of any existing set of diagnostic criteria.

Patient-centered data in rare and rarely diagnosed diseases is different from that gathered by researchers or clinicians only. A recent paper co-authored by our partners in the Human Phenotype Ontology (HPO) Project demonstrates that patient-reported versus clinician-reported symptoms differ significantly in long COVID, for example — and that patient-reported data is richer, more detailed, and more complete. This supports a wealth of evidence for the value of patient participation in research at every stage.
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strategist said:
What if see increased MCAS-like symptoms in the +POTS -MCAS group but not the +ME -MCAS group? It suggests that whatever it is that is being diagnosed as MCAS may have overlap with POTS.
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To be frank it's these type of conclusions that I'm concerned about.

I think these difference will likely be affected by random statistical noise, unrepresentative recruiting into the study, and biases of the clinicians who give these diagnoses because they think these are valid and useful. For all, we know these diagnoses might not be valid and useful. In my view, it doesn't make much sense to focus on symptom clustering and differences in symptom reporting in these syndromes until we know more about their validity.
 
Michiel Tack said:
To be frank it's these type of conclusions that I'm concerned about.

I think these difference will likely be affected by random statistical noise, unrepresentative recruiting into the study, and biases of the clinicians who give these diagnoses because they think these are valid and useful. For all, we know these diagnoses might not be valid and useful. In my view, it doesn't make much sense to focus on symptom clustering and differences in symptom reporting in these syndromes until we know more about their validity.
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The odds that the actual clinical diagnoses are reliable are essentially nil, not as concepts but in the hands of indifferent physicians who treat them as garbage disposal with zero care for accuracy. The overarching theme is basically chronic illness that is systematically misdiagnosed so in that sense it is a specific category with a significant overlap, just one that medicine has no ability to deal with and even less interest in.

This is basically doing the first step that medicine never did: mapping the terrain. A terrain made of symptoms, which of the oddest reasons possible medicine has no interest in because symptoms are only a means to determine what disease is present. There's definitely value in that. It's as if there is a time limit during which to do the first steps and if the time passes and the work isn't done it becomes taboo to go back to the beginning and people just work around the fact that no one bothered doing that.

Frankly this is the kind of research that is needed but medicine doesn't have the ability to do correctly. For that alone it's worth doing because no one else will. And if it turns out not be particularly useful, it would still be more useful than most of the research out there, the output is just that bad.
 
strategist said:
I think we can assume that people are going to be biased towards reporting the symptoms consistent with the diagnostic labels they were given
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I was wondering what biases this study design is subjected to. Selection bias comes to mind, patients identifying themselves in one category, or the physicians they sought to confirming their diagnosis. I also agree with @Michiel Tack ‘s remarks.
 
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