(Are different ME/CFS doctors seeing different types of ME/CFS patients. Would closely examining those patients reveal the elusive subsets researcher have been talking about for decades? At the FDA Workshop on April 26, Dr Elizabeth Unger, head of the CDC’s Chronic Fatigue Syndrome programme revealed the initial results of their multi-clinic study assessing ME/CFS patients. Please welcome Simon McGrath to Health Rising as he digs deeper into the first fruits of this fascinating study)
Things are changing at the CDC. Previously known for it’s insularity, the CDC set up a collaboration with the top ME/CFS clinics in the States to look at patients in detail (and even collaborated with the clinics on designing the study protocol ). The goals were to see if and how patients differed between clinics, to gather hard data to help address the issue of case definition, and to find the best ways of measuring this illness.
ME/CFS Physicians Take the Lead in Deciding Who Has ME/CFS
The study set out to capitalize on the expertise of leading clinicians working with ME/CFS patients, including Dan Peterson in Incline Village, Nancy Klimas in Florida and Ben Natelson in New York City (see map). Having chosen clinics run by these top physicians, the CDC left it to them to include the patients that they considered to have “CFS, ME/CFS or anything that fits under this umbrella diagnosis”.
This inclusive approach should help show up any differences between the types of patients that different clinicians consider to have “ME/CFS”. Also, collecting data like this gives a broader population, and any ‘true’ group of patients (eg ICC) should emerge as clusters in deeper analysis.
A Mountain of Data
The study collected a vast amount of data: physical examination results, clinical history, lab test results, immunisation history, demographics. Then patients had a LOT of self-report questionnaires to complete, including mental health, CDC Symptom inventory, DePaul Questionnaire, SF36 health survey and the Mulit-Fatigue Inventory. Also, sleep and pain measures, and a battery of the NIH’s PROMIS questionnaires. Phew! No wonder Beth Unger was keen to thank all the patients patients taking part. Many questionnaires were made available online so that patients could complete them in their own time.
The first results…
The first results are now in, based on an interim analysis of 393 patients (which will ultimately be 450). Starting with the basics:
- Average age: 48.6
- Female: 71%
- BMI: 27.2 (about average for the US)
This is broadly in line with other studies, though the 71% female is a little low, with one clinic having barely over 60%. (77% of patients were women in a recent UK study with a large clinical sample).
It’s also worth noting that this sample isn’t fully representative of all patients: it’s 95% white and 78% college-educated, probably reflecting the fact that 98% were medically-insured. Whether or not this sample is typical of ME/CFS generally, despite this demographic bias, is unclear. Also, like just about every other ME/CFS research study ever done, this one excludes severely affected patients as they are too ill to make it to the clinics.
Burden of Chronic Fatigue Syndrome Laid Bare
The numbers coming out of this large study illustrate the high burden ME/CFS imposes:
- Average time to diagnosis: 4.5 years
- Typical length of illness: 15 years
- Average age at diagnosis: 38 years
- Not working: 75%
- Pain in the last week: 80%
- SF-36 Physical Function mean score: 37 (100 is full-health, 90 is typical for working-age population)
- MFI General Fatigue mean score: 18 ex 20
Take a look at this in the graphic below:
Thirty-seven percent of patients scored the maximum possible 20 points for MFI General Fatigue subscale, showing a serious ‘ceiling’ problem where the scale cannot tell the difference between very bad fatigue and even worse fatigue. The same situation applies to the Chalder Fatigue Scale, widely used in the UK. Clearly a more sensitive measure of fatigue is needed.
Fifteen years is a long, long time to be ill, and while those who have recovered obviously aren’t included in this study, those still ill probably have many more years to serve. It’s shocking that it takes an average of nearly five years to get diagnosed – by comparison, the average time for diagnosing Rheumatoid Arthritis is nine months.
All the different sleep questionnaires found severe impairment of sleep, which was also the most disabling symptom reported.
Elizabeth Unger zipped through a lot of results in half an hour, with 27 graphs just for symptom scores. Here are some of the other highlights:
- Unsurprisingly, the top symptoms were poor sleep, post-exertional fatigue and muscle aches and pains.
- The comprehensive SF-36 health survey found that pretty well everthing was worse compared to healthy norms, especially Physical Function (no surprise there) and Vitality (or there). But what really stood out were the high mental health scores (see the graph; the data is from a single clinic, but clinics did not differ significantly). This suggests that ME/CFS patients are showing considerable mental resilience in the face of the serious problems they encounter in almost every other area.
- 67% of patients reported sudden onset (individual clinics ranged from 52%-76%).
- Patients said they did mild exercise an average of 3.4 times a week, again varying by clinic, though it’s not clear how ‘mild’ exercise was defined. 80% had pain in the previous week, with 64% taking medication.
Another intriguing finding is what Elizabeth Unger described as ‘U-shape curves’ for cognitive functions; there appear to be two distinct groups, a larger one with severe cognitive problems and a smaller one with only mild cognitive impairment. It would be interesting to see how these groups map onto different case definitions, eg ICC versus Fukuda.
Illness burden: CFS vs the rest
The final results slide Unger showed compared CFS with other conditions including Multiple Sclerosis, Muscular Dystrophy and Chronic Pelvic Pain. This was done using the NIH’s PROMIS survey that collects standardised data to help contrast different conditions. Pain in ME/CFS was on a par with Chronic Pelvic Pain, but in almost every other case CFS patients had much worse pain, fatigue and sleep scores than comparison illnesses. And of course, Nancy Klimas is on record as saying CFS is worse to have than being HIV positive – and she should know, since she treats both types of patient.
Goals of the study revisited
Do the Clinics have different types of patients?
One goal was to establish: do different Clinics see different types of patients? The answer is Yes and No. Many findings were statistically different between clinics (eg. the average length of fatigue) but generally the differences were not huge – and may not be biologically significant. While there were some differences between clinics, the differences between patients in any clinic was much greater. This is more confirmation of the heterogeneity of ME/CFS patients, and all the clinics seem to be seeing a similarly diverse range of patients – though this is only an interim analysis.
No sign yet of subgroups
So far, said Elizabeth Unger, the existing measures haven’t shown up any robust subgroups (another study goal), but a detailed cluster analysis will probe this in more detail. However, finding subgroups may not be easy, even where there is very good data, as the experience of Parkinson’s Disease shows.
Finding the best ways to measure ME/CFS
The third study goal is to establish the best measures of ME/CFS. The good thing about using so many different measures in one study is that it allows comparison of one measure against another (eg MFI defined fatigue vs PROMIS defined fatigue). Generally, different measures agreed well, which is encouraging. More analysis will be done on this, but the real test may come in the next stage of the study which involves tracking patients over time.
Which measures will best capture changes in ME/CFS is a key question in any clinical trial, but, remarkably, there has been almost no work on this in ME/CFS, or in any other disease. Using an objective measure like Treadmill time – as in the Ampligen study – is a good, perhaps better, alternative to a questionnaire, but where questionnaires are used they need to be shown to reliably measure change.
Elizabeth Unger said how valuable she found the networking: “We appreciate our expert clinicians, and one of the things we found most rewarding was our on-site visits with each other, and the clinicians also appreciate the opportunity for networking”. I think this study is probably the largest US clinical collaboration to date, and there seems to be an apetite from all the players to continue with this kind of work.
Bigger Study Underway
What’s great about this study is that it’s established a solid base camp, but much more is planned. A huge amount of data has been captured, showing the scale of problems in ME/CFS and the wide variation between patients. To establish the best measures, and to identify robust subgroups, or even validate a case definition, more data is needed and the CDC have plans to do just that.
First there will be follow-up of patients to see how things change over time. Second, for a subset there will be more and different data gathered: blood to look for biological markers, plus cognitive tests and exercise tests that might yield information that better reveals the true nature of ME/CFS.
To further understand the abnormalities of ME/CFS, the CDC plan control groups, both of healthy volunteers and ‘ill controls’, groups of patients with other illnesses that will help researchers pinpoint what is unique to ME/CFS. These early, interim results presented at the FDA are just an aperitif for a study that will be delivering a great deal more in the future.
- Graphics, (apart from ‘burden of’) were adapted from Elizabeth Unger’s presentation.
Simon McGrath has been ill with ME/CFS for way too long. He thinks research is finally kicking off after years spent wandering in the desert. He occasionally tweets about ME/CFS research: Follow @sjmnotes. Find more of his blogs on Phoenix Rising.
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