Who Exactly Has ME/CFS and How Is CDC Counting Patients?
Reliance on the 30-year-old Fukada criteria is best, a CDC-funded study finds, when applied to the upper-class well-educated white women recruited for their study
On the heels of a tiny, unilluminating study of ME/CFS conducted by the National Institutes of Health (1), the Centers for Disease Control and Prevention (CDC) published a paper arguing that the 1994 CDC criteria for describing ME/CFS—called the Fukuda Criteria, after its CDC-based author—is much more accurate than the newer Institute of Medicine (IOM) criteria for diagnosing ME/CFS, which is coming up on being a decade old itself. And the 2003 “Canadian algorithm” landed at the bottom of the pile in this CDC-funded paper. (2)
More than 20 authors—including such well-known ME/CFS researchers as Nancy Klimas, Charles Lapp, and Dan Peterson—took part in the study led by CDC researcher Elizabeth R. Unger. Referred to as the MCAM study (“Multi-site Clinical Assessment of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome”), its goal was to determine if physicians treating patients with ME/CFS “recognized the same clinical entity.” (2)
According to the CDC’s paper: maybe they do, maybe they don’t.
Unger et al. essentially concluded that ME/CFS is a scatterbrain syndrome; doctors and patients just need to deal with its “heterogeneity.”
And while lamenting the lack of a specific test for ME/CFS, the CDC paper simultaneously described the syndrome as a grab bag of symptoms, rendering ME/CFS, in these investigators’ opinions, almost undiagnosably vague. (2)
That conclusion was based not only on the MCAM study but also on a 2019 paper by another well-known ME/CFS researcher, Anthony L. Komaroff. (3)
Unger et al. suggested that “Presenting research data in scatter plots or histograms will help clarify the challenge,” i.e., the challenge of defining ME/CFS as a discreet disease. However, “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.” (2)
They explained:
Patients with ME/CFS experience a wide range of symptoms, most
characteristically significantly decreased function associated with
severe fatigue, post-exertional malaise, unrefreshing sleep, cognitive
impairment, and orthostatic intolerance. However, chronic widespread
pain, allergies, sensitivity to light and sound, chemical and food sensitiv-
ities, headaches, and other symptoms are common. The pathogenesis of
this biologic illness remains a mystery despite decades of research. While
a wide variety of objective differences between patients with ME/CFS and
healthy controls have been reported, none are specific and sensitive enough
to be used in diagnosis. (2)
For the MCAM study, the CDC enrolled 465 patients from seven “specialty clinics” treating ME/CFS patients. Investigators compared the 1994 Fukada criteria (4), the 2003 Canadian consensus criteria (5), and the 2015 IOM clinical case definition (6).
“Females predominated at each site, with an overall female-to-male ratio of 2.9 (range of 1.6 to 5.6 across sites),” Unger and colleagues reported. “Patients were predominantly white, comprising 94.4% of the study sample (range of 84.4% to 100% across sites). More than half were married or in a committed relationship, but the proportion ranged from 40.8% to 73.3% across sites. Overall, about 75% were unemployed (range of 64.3% to 89.1% across sites).” (2)
They wrote that they “used the duration of fatigue as a surrogate for the duration of ME/CFS, as not all symptoms may appear at the same time.”
However, they found that sudden onset was much more common than gradual onset.
“Overall, the mean age at diagnosis was 38.3 years (SD = 12.6), whereas by site, the mean age at diagnosis ranged from 33.5 to 40.9 years,” they reported. “... Sudden illness onset was reported by 65.4% of patients overall, and this varied significantly by clinic, ranging from 49.3% to 75.4%. In all but one clinic, sudden onset was more common than gradual.”
This “open access” paper contains a lot of detailed data, and I encourage you to read it if you wish (see reference #2).
The goal of the CDC group’s analysis “was to determine if differences in clinical practice resulted in different subgroups of patients,” Unger and colleagues stated.
The medical complexity of ME/CFS and the lack of objective diagnostic
tests presents challenges for case ascertainment in research and clinical
care. Heterogeneity is masked when studies report means or medians.
Presenting research data in a format that shows heterogeneity, such as
scatter plots or histograms, will help clarify the challenge. Variations in
patient demographics, co-morbid conditions, medications, and duration
of illness can all contribute to heterogeneity.
Despite the heterogeneity they detected in symptomology, these investigators found the same-old same-old ME/CFS patients: “predominately insured white women with a high level of education.”
They didn’t recruit any patients with severe ME/CFS who are too sick to travel to special clinics; patients of differing racial backgrounds; patients with varying levels of education; or patients of limited financial means, and they don’t seem to think that influences their study’s conclusion at all.
“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 [i.e., different specialty clinics] remains,” Unger et al. asserted. “Study designs that incorporate illness heterogeneity to shed light on underlying pathogenesis are needed.”
And, naturally, they have to obscure ME/CFS even more by giving a shout out to “post-acute infection syndromes,” including Long Covid. In fact, they assert that Long Covid patients “have striking heterogeneity in their illness profiles.” Similarly to ME/CFS, no specific suggestions of how to study Long Covid’s heterogeneity are provided.
But back to ME/CFS: “Relying on case-control study designs without the subgrouping or stratification of ME/CFS illness characteristics may limit the reproducibility of research findings and could obscure underlying mechanisms,” they warned. “Study designs that compare similarities and differences in ME/CFS, Long COVID, and other PAIS and begin to link biomarkers to symptom measures and subgroups may be needed.”
They make excuses for neglecting what some patients, physicians, and researchers consider to be a hallmark of ME/CFS: post-exertional malaise (PEM). While PEM “is considered to be characteristic of ME/CFS and is a required symptom in the 2015 IOM clinical case definition, methods to identify PEM are not standardized.”
They’re clearly unsure how important PEM is in ME/CFS diagnosis (and so am I), but they are certain that the oldest, and most controversial, description of ME/CFS criteria remains the best: the 1994 Fukada criteria. Unger and colleagues examined how many of their patient population met each of the three diagnostic criteria—1994 Fukada criteria, 2003 Canadian consensus criteria, and 2015 IOM criteria—used in their study:
“Table 11 shows the proportion of patients meeting each of the three case definition algorithms by site and overall,” Unger et al. explained. “For each site, the 1994 research algorithm was met by the highest proportion of patients (83.4% overall, range of 77.0–90.0), and the 2003 Canadian algorithm was met by the lowest proportion of patients (50.1% overall, range of 45.9–57.4).” (2)
Not so fast, said Dr. Leonard Jason, an intermittent but committed ME/CFS researcher.
“Readers could conclude that using the Fukuda empirical criteria is the best method for identifying patients with ME/CFS,” Jason wrote in the “Perspectives” section of MedpageToday. “However, the CDC continues to promote a case definition that does not require cardinal symptoms of ME/CFS, including post-exertional malaise, cognitive impairment, and unrefreshing sleep.” (7)
He also questioned the use of the Fukada criteria to diagnose patients.
“For context, in 1994, the CDC's Fukuda criteria were developed and used in research by investigators,” Jason explained. “In 2005, epidemiologist William Reeves, MD, MSc, and colleagues operationalized these criteria in what has been called the ‘Fukuda empirical criteria,’ for use not just in research but for actually diagnosing patients.”
Jason demonstrated how unhelpful the Fukada criteria are by describing a 2009 study he co-authored. He and his colleagues “found that these Fukuda empirical criteria selected some individuals with solely affective disorders, like major depressive disorder. Findings indicated that 38% of those with a sole diagnosis of a major depressive disorder were misclassified as meeting the Fukuda empirical case definition.” (7)
Continuing to apply the Fukada criteria in diagnosing patients will only create ambiguity and further slow understanding of and treatment development for people with ME/CFS, Jason argued.
Jason’s commentary concluded: “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.” (7)
I’ll end with a note for our readers who are techies—or just anyone owning a cell phone: Hasn’t medical technology changed significantly in the last 30 years? Might that increased technological knowledge be used to further understanding of ME/CFS, as opposed to the 1994 Fukada criteria the CDC continues to push on investigators? AI, anyone?
BIBLIOGRAPHY
1. Walitt, B., Singh, K., LaMunion, S.R. et al. “Deep Phenotyping of Post-infectious Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Nat Commun 15, 907 (2024).
2. Elizabeth R. Unger, Jin-Mann S. Lin, Yang Chen, et al. “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.” J. Clin. Med. 2024, 13(5), 1369; https://doi.org/10.3390/jcm13051369
3. Anthony L. Komaroff. “Advances in Understanding the Pathophysiology of Chronic Fatigue Syndrome.” JAMA 2019, 322, 499–500.
4. Fukuda, K.; Straus, S.E.; Hickie, I.; Sharpe, M.C.; Dobbins, J.G.; Komaroff, A. “International Chronic Fatigue Syndrome Study Group. The chronic fatigue syndrome: A comprehensive approach to its definition and study.” Ann. Intern. Med. 1994, 121, 953–959.
5. Cortes, R.M.; Mastronardi, C.; Silva-Aldana, C.T.; Arcos-Burgos, M.; Lidbury, B.A. “Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.” J. Chronic Fatigue Syndr. 2003, 11, 7–115. [Canadian Consensus Criteria]
6. IOM (Institute of Medicine). “Beyond Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Redefining an Illness”; The National Academies Press: Washington, DC, USA, 2015; Available online: https://www.nap.edu/catalog/19012/beyond-myalgic-encephalomyelitischronic-fatigue-syndrome-redefining-an-illness (accessed on 21 February 2024).
7. Leonard Jason. “Be Wary of Flawed Diagnosis Criteria for ME/CFS—A new CDC-funded paper includes criteria that may be leading to inaccurate prevalence rates.” MedpageToday, March 20, 2024.
Oh, you mean like the AI that says George Washington was a black female, or that medieval European knights were Chinese? Sorry, but I'm unconvinced that you are going to get any better information about health from a Pharma stooge AI vs. a Pharma stooge doctor.... The technology is fancier now (with 'machine learning' etc) but at the end of the day, AI is just algorithms and algorithms are 'garbage in, garbage out' propositions. And if Pharma is doing the 'training' of the AI then I predict 99.9% garbage out.
Interesting that the 3 main symptoms of CFS are lack of good sleep, malaise after exertion, and cognitive impairment. Well, anyone who has gone without good sleep can tell you that it results in the other two. Just sayin'..... There's a reason sleep deprivation is used as a torture / mind scrambling device.
Also, those many symptoms remind of of Gulf War Syndrome, which was most likely caused by the horrible Anthrax Vaccine (and probably other vaccines and exposures too). I was in the military in a later period, but still was forced to get the Anthrax vaccine and a bunch of other ones. My health has been a challenge ever since.
Another thing it makes me think of: the horrible Ciprofloxacin antibiotics. These basically kill / maim the mitochondria, resulting in similar effects (fatigue and many others). I know that my mom had lots of UTIs, and they prescribed her Cipro antibiotics. So just a hunch, but I wonder how many of the CFS sufferers took Cipro antibiotics before their CFS started?
Of course the medical industry doesn't care about actual causes of problems or actual solutions, so I don't expect any of these obvious things to be investigated. Their 'answer' to Pharma-poison 'side' effects is always more Pharma poisons...
'Long' 'covid' is another one... how about 'long-term covid vaccine poisoning effects'?
This CDC study was initiated for a very specific reason. The Chronic Fatigue Syndrome Advisory Committee had just voted to convene a workshop of ME/CFS experts to endorse a case definition, using the Canadian Consensus Criteria as a starting point.
This threw HHS into a panic, as the last thing they wanted was for experts to agree on a rigorous case definition.
So, they launched this CDC study that was supposed to be gathering imperical evidence to help with a case definition. But the real reason was to prevent the CCC from being adopted.