The Prevalence of Pediatric Myalgic Encephalomyelitis/Chronic Fatigue Syndrome in a Community-Based Sample (2020) Jason et al.

One likely option is that it's easier to identify children with ME, as their parents will likely still be healthy and able to answer the phone and go through the process. Since most ME patients have little to no support, a substantial % live alone and simply never answer the phone directly, will simply never bother going through the process unlike the healthy parent of a sick child.

The country that found the highest prevalence, Canada, did so by literally asking the entire population. It's part of regular census work that is done by StatsCan and the method used was to mail census forms to every single household in the country.

This patient population is very hard to reach, especially by health care services that have simply left us to rot and die erased from society. An Ontario health ministry panel reported approximately 1M Canadians suffering from either of fibromyalgia, ME or MCAS. I think that those 3 diagnoses are likely confused for one another liberally and probably paint a more accurate picture as a whole, since they are so commonly misdiagnosed.

I think there should be strong consideration to the possibility that the real numbers are actually on the higher side of estimates. I remember the numbers used for a while by the CDC of CFIDS at the time, spoke of about 5M US citizens, which is roughly equivalent to the ~500K Canadians.

I would suggest this is Occam's razor's most likely explanation. There have never been significant efforts to identify those patients and health care services routinely mishandle recording those cases, if they even count them at all. There have been so many efforts to bury and dismiss this disease, not surprising that its true extent would be buried as well. Bit like how some socially regressive countries insist there are no gays among their population. They don't look, don't want to know, don't report and there are no numbers that can contradict their claims since no one is counting and you can't make them.

Not surprising that something many insist does not exist would be underreported. Pretty much the most predictable outcome imaginable, actually.

 

Reeves et al (2007), a CDC study, found a prevalence of 2.54%. However, it used the so-called empiric criteria for CFS (Reeves et al 2005), which are really rubbish.

 

Complete rubbish. I wouldn’t trust those results for a minute.

 

Physicians do not even know how to diagnose it. And then they may simply confound fibromyalgia with ME because FM is a little better known. But FM does not get a lot more respect over here. The main researcher from FM in Canada actually preaches that patients should receive less care, not more.

We do not know what happens in children hospitals, how and whether ME is diagnosed properly and what recommendations they are making to their patients and parents on management of the disease.

 

@Simon M don't forget this analysis from last year: https://www.frontiersin.org/articles/10.3389/fped.2018.00435/full

 

On CDC's 2003 epi study - If I remember correctly, there are serious questions with the accuracy of the diagnostic methods used in this study - for instance, only 21% of the patients were still classified as having CFS at the two and three year follow-ups and only 7.5 percent of the patients maintained a CFS classification two years in a row. 60% of the study subjects were working and only 17% were unemployed due to the disease. Finally, when CDC rediagnosed these patients a few years later using the same methods as the original study methods, only 13% still had a CFS diagnosis. All remarkable given the low rates of recovery and employment.

CDC concluded that the methods used in the 2003 study had “showed scant stability over time.” This led to the development of the Fukuda-based Empirical criteria and methods. But that selection approach was also flawed - focused on "chronic unwellness" and resulted in a 10 fold increase in prevalence. The IOM discredited that study because it included an overrepresentation of PTSD and depression.

 

On the point about the prevalence rate possibly being inflated due to bias in who took part:
Only 2 of the participants who were diagnosed with ME/CFS had an existing diagnosis of ME/CFS.
So, by itself, it doesn't suggest lots of people with an existing diagnosis of ME/CFS decided to take part and go on to inflate the prevalence figures (if people with an existing diagnosis of ME/CFS took part, but went on to be considered non-cases, that will actually lower the prevalence rate, not increase it).
Put another way, exclude those 2 people and the prevalence rate doesn't go down much.

Bias towards people who have fatigue could still be a significant factor.

 

I think that PVFS has been made the same as ME since CFS was used for both. That is nasty but doesn't last lifelong the way ME does and is a different disease even if it can lead to true ME. EBV was also known to take months if not years to resolve but again it can lead to me but the prolonged syndrome is not ME and affected children can get back to normal after a while.

 

I think that there are misconceptions regarding the use of the term PVFS. In the late 1980's it was certainly used by Behan and others to describe a chronic condition. The difficulties surrounding the term ME had become clear. When I was given a diagnosis of chronic PVFS I was told that it was the same as ME, but they no longer used that term. The term was in use to describe the long term condition before CFS muddied the waters further.

Nothing is straightforward with this condition. I am unclear as to how the term PVFS became restricted to the short term condition, if, indeed, such usage is universal.

 

I wonder if it's because 'chronic' usually means 6 months+ in medical terms, whereas 'post' just means 'after'. So there was need for a term to describe patients with symptoms of less than six months in duration, and PVFS already existed?

 

Thanks for all the helpful comments.

I will just recap some of the strengths of the study, which I think addresses some of the issues here, but not all of them:

1. The community screen followed by a medical workup is a well-established and widely used methodology for measuring prevalence.
2. The team used a fairly broad telephone screen; those that insist on a whole bunch of symptoms on the initial screen might accidentally screen out people that should be included.
3. Every youth was examined by Ben Katz, a highly experienced specialist in ME/CFS.
4. The study used a collection of criteria, requiring all 3 to be met (albeit the PEM result states quite add up).

So there is a lot to like here.

Really interesting point. Functional impairment was mandatory to get through the screen but I don't knw how bad that was. Ben Katz was the key physician and my guess is he does know what PEM is. My ME began as pvfs and I had PEM then - I wonder if ther are just a lot of cases of PVFS with PEM that do meet mecfs criteria but perhaps often resolve befor people make it to the research cohort we are familiar with.

They collected a ton of data in the study and Lenny says there will be more analysis and presumably more papers to follow. Hopefully, this will include duration.

I didn't realise (ormore likely did and have forgotten!) that so many of the CDC-diagnosed cases were not cases a few years later. You would certainly expect a moderate rate of recovery from a community study that will sweep up fairly new diagnoses which seem to have a much better outcome. And it may be that any good prevalence study will have more cases resolving the kind of cases that wind up in most research studies, almost all of which come from specialist clinics and tend to be made up of people who have been ill for quite a while.

Asking this question on a census form is a fabulous methodology because it is likely to lead to high response rate reduces the chance of bias. However, unless there was specialist medical evaluation of the potential cases identified, I think you would have to assume those numbers are a substantial over estimates (sorry, I am not familiar with the methodology of three Canadian prevalence study)

Writing this, I do wonder if an explanation for the high prevalence rate in the study is PVFS (PIFS) that do equate to ME/CFS, but cases that resolve within a couple of years. Perhaps adolescents are more prone to this because they pick up more infections (not least glandular fever/EBV). And perhaps we are not used to seeing a lot of these short-term cases, because unlike a community-based survey, research cohorts rely on people having found their way to specialist help and a diagnosis, often after several years of illness. TBH, the same probably goes for members of our community.

 

Leonard Jason did a long-term follow-up of the Chicago adult prevalence study. Diagnoses seem to be more stable than with the CDC study, though I don't remember anyone ever discussing a comparison:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171164/

 

Around 70% of adolescents who satisfied CFS criteria at 6 months after infectious mononucleosis (a.k.a. glandular fever or mono) didn't satisfy them at 2 years. I can't remember if we have similar figures for adults; I think somebody posted ones unofficial figures from the Dubbo study that very few were ill at 2 years.

Anyway, perhaps, a higher proportion of young people than adults get ill with CFS after infectious mononucleosis.

 

That's a good point and certainly a possibility that needs to be kept in mind as we go forward - highlights need for followup over a number of years.

But for the 2003 CDC study, even CDC said that the criteria and method used were not reliable. They said that when they applied both the 2003 criteria/method and the Empirical criteria/method at the same time to the same patients, only 25% of the patients diagnosed as CFS by the 2003 criteria also met the Empirical criteria. So its hard to know who CDC was actually counting.

It's worth noting that CDC is reportedly focusing its epidemiological efforts on the Behavioral Risk Factor Surveillance Survey (BRFSS) - as reported in the NIH August 2019 meeting at which CDC spoke (transcript)

Our other major epidemiologic study is being conducted in partnership with CDC's Behavioral Risk Factor Surveillance Survey known as the BRFSS. The 2019 BRFSS included an optional ME/CFS module to ask participants about whether they had ever been diagnosed with ME/CFS by a doctor or other healthcare professionals along with two other follow up questions. We don’t yet know how many states have include this module. However, we do have data from the 2014 and 2016 state added ME/CFS questions that were very similar. From the 2014-16 data, we learned that 1.6% of those surveyed had received a diagnosis of ME/CFS and 71% of those diagnosed still had ME/CFS. ​

But those estimates are based on patient self-report of a previous diagnosis of CFS by a doctor. The original BRFSS pilot (I think in adults) reported 1.6% lifetime and 1.2% current. Even with the pedi/adult difference, its difficult to jive the BRFSS prevalence estimates with Jason's report of 95% of patients not being previously diagnosed.

Bottom line - we need proper epidemiological studies in adults and more than just for prevalence estimates

 

A lot if not most epidemiological research in the UK involved biopsychosocial researchers. The "wrong sort" of epidemiological research can cause problems.

 

Until I went to Australia two years ago, I had heard them being used interchangeably. In Australia, I found that there was a clear distinction--that someone with PVFS might get all better after two years and so it wasn't ME. There were cases of athletes in particular who really seemed to be "recovered" after a year, and here or there would attribute it to GET, and people would say they obviously had PVFS and not ME. I hadn't heard such a clear distinction before that. I'm not sure what is meant elsewhere.

 

I apolgise, I used the wrong term. When I was a microbiology student in the early 70s and in general, it was accepted that some infections left people feeling ill and fatigued for months, especially things like flu and that glandular fever could take a long time to get over. I am not sure if there was a specific term for it, but we loosely called it a post viral.

Before the CDC invented CFS there was no requirement for 6 months of fatigue because fatigue was not a primary symptom. We went along quite happily calling it ME. Then Mowbray (?) said there was no continuing viral involvement so said it should be called Post Viral Fatigue Syndrome. (This was strange because he did the VP1 test which found actual virus particles in people but still) In the strange way things happen in the ME world this was suddenly accepted and overnight ME became PVFS and they would not publish Ramsay's book unless he called it PVFS and not ME as he had to use the "correct" name for the disease.

There was no internet the way there is now so I never found out what the politics behind it all was. Then the CDC came up with CFS including that 6 months wait!

Just when we were reeling from all that the weasel cabal suddenly popped up from nowhere and said the disease was actually CFS, which they defined differently from the US CFS.

I think we were sunk because the UK doctors who treated patients and did research were talked over by medics who cared about politics more than the patients or the truth.

 

42 out of 10000. Isn’t the prevalence 0,0042 = 0,42% then?
Why does the study say 0,75% ? Could someone please explain.

 

From the page 8 of the paper, https://sci-hub.se/10.1007/s10566-019-09543-3

The prevalence of ME/CFS was calculated using the formula cited in Jason et al. (2012). This formula takes into account the actual number of participants who had ME/CFS as well as those who had a chance of diagnosis based on screening positive in Stage 1 but may not have participated in Stage 2, yielding a more encompassing prevalence estimate. The total number of respondents screened in Stage 1 is represented by N. The proportion of screened positives over the total number of screens in Stage 1 is represented by PI, and the proportion of screened negatives over the total number of screens in Stage 1 is represented by 1−PI. The proportion of screened positives who were evaluated in Stage 2 and diagnosed with ME/CFS is represented by L1 and the proportion of screened negatives who were evaluated in Stage 2 and diagnosed with ME/CFS is represented by L2.

This information was then used in the following formula to obtain the Prevalence P: P=L1 *PI+L2*(1−PI). Chi square analyses were used to examine group diferences between screen positive participants and screen positive non-participants frst to determine whether there were any signifcant diferences in gender, age, and race/ethnicity and whether equal prevalence could be assumed. Second, descriptive statistics, Chi square analyses, and t tests were used to examine diferences in prevalence rates among groups and symptom endorsement between those diagnosed with ME/CFS and screen negative control participants.

Results Table 1 presents frequency data for screen positive and screen negative participants as well as fnal diagnoses for ME/CFS. There were no signifcant diferences between the screen positive subjects and screen negative controls in terms of gender, race/ethnicity, and age, as expected, as test negative control participants were invited to participate based on a demographic-matching process. Prevalence rates, using the formula delineated above, classifed ME/CFS if youth met the Fukuda et al. (1994), IOM (2015), and Pediatric (Jason et al. 2006) case defnitions.

Table 1
Data on participant selection and completion of the study
Number of participants

[Numbers are for] Screened positive [and] Screened negative
Completed phase one screen 865 / 9254
Selected for phase two of evaluation 298 / 243
Completed phase two of evaluation (physician review) 165 / 42
Final diagnosis of ME/CFS 42 / 0

P = (42∕165) ∗ (298∕10, 119) + (0∕42) ∗ (1 − 298∕10, 119)
P = (0.2545 ∗ 0.0294) + 0
P = 0.0075 = 750∕100, 000

Thus, the prevalence for ME/CFS in this community-based pediatric population was found to be 0.75% (95% confdence interval, 0.54–0.96%), or 750 per 100,000.