CENTER FOR COMMUNITY RESEARCH
Diagnostic Criteria for Myalgic
Encephalomyelitis/Chronic Fatigue
Syndrome
Leonard A. Jason
Center for Community Research
DePaul University
Presentation to the Institute of Medicine’s (IOM),
May 5, 2014
CENTER FOR COMMUNITY RESEARCH
What is the Natural History of ME/CFS?
What Are the Limits of Such Studies Presently?
• Very few studies in this area, particularly with best methodology
– prospective community-based samples
• Jason, Porter et al. (2011a, 2011b) examined the course of ME/CFS
over a ten year period of time for a prospective, random, communitybased, multi-ethnic sample
– There was relative stability over time on critical measures of disability, fatigue,
support, optimism and coping over time
– The rate of ME/CFS remained approximately the same over the ten year period
of time
– Post-exertional malaise best differentiated the ME/CFS group from the other
groups (control, Idiopathic chronic fatigue, Medical/Psychiatric reasons for
fatigue)
• This reaffirms the importance of this being a cardinal and critical symptom for ME/CFS.
– For unrefreshing sleep and impaired memory and concentration, 100% of the
ME/CFS group had these symptoms
• Similar to post-exertional malaise, these results support the idea that unrefreshing sleep
and impaired memory and concentration are core symptoms of ME/CFS
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I was asked: Do Certain Symptoms in ME/CFS
Appear to Cluster Together?
More Precisely: Are Data Available on What
Symptoms Covary and How
• In order to accurately diagnose an illness or
disease, it is important to have a reliable set of
criteria for clinicians
• Otherwise, it is possible that disagreements
about diagnostic decisions may arise because of
diagnostic unreliability
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Criterion Variance:
Classification of Patients’ Symptoms
into Diagnostic Categories
• Criterion variance constitutes the largest source of
diagnostic unreliability
• This typically occurs when an operationally explicit
set of criteria is not being utilized in the process of
diagnosing an illness
• Therefore, a case definition needs to specify the
core, cardinal features of ME/CFS
– In a recent systematic review, Brurberg, Fønhus, Larun,
Flottorp, and Malterud (2014) identified 20 case definitions
– Problem is that different case definitions specify different
symptoms
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Factor Analysis:
Can be used to Determine which
Symptoms Covary
• Factor analysis identifies latent dimensions
• Multiple factor analytic studies of
symptomatology have resulted in three to four
symptom factors
–
–
–
–
–
Nisenbaum, Reyes, Mawle, & Reeves, 1998
Friedberg, Dechene, McKenzie, & Fontanetta, 2000
Nisenbaum, Reyes, Unger, & Reeves, 2004
Arroll & Senior, 2009
Hickie et al., 2009
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Brown and Jason’s (2014) Study
Identified Three Factors
Pain
Autonomic
Neuroendocrine
Immune
Fatigue
PEM
Neurocognitive
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Interpretation of Brown et al. Study
• Two of the emergent factors were
– Neurological/Cognitive Dysfunction
– Post-Exertional Malaise
– fit well with previous literature indicating that these are two of the
cardinal symptom clusters of ME/CFS
• One factor was items from Neuroendocrine, Autonomic,
& Immune Dysfunction
– more difficult to interpret as it incorporates many symptom
clusters
• This suggests that there may be core, well-defined
symptom clusters such as cognitive impairment and
post-exertional malaise
– but also that there may be many other symptoms that are
experienced differently by patients
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Are There Any Short Screen Tools
That Have Been Validated for
ME/CFS?
• Regardless of which case definition is used
– it is critical to assess symptoms in a standardized way
to reduce reliability issues
• such as the Wagner’s CFS Symptom Inventory
• By using a consistent set of items on a
questionnaire or measure, as well as cut off
points for defining whether a threshold has been
met for symptom criteria
– clinicians will be able to examine the same illness
constructs among all their participants or patients
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Not Easy Determine Whether a Patient
Meets a ME/CFS Case Definition
• Some investigators have found that over 90% of
those with CFS Fukuda also meet the ME/CFS
Canadian Clinical criteria (Fluge et al., 2011)
whereas others have found the rates closer to
50% (Pheby et al. 2011)
– This variability suggests that different investigators
might be using different scoring rules for diagnosing
ME/CFS using the Canadian Clinical criteria
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DePaul Symptom Questionnaire
(DSQ) (Jason et al., 2010)
• Developed to provide a structured approach to
gathering standardized information and to allow
investigators to determine whether or not a
patient meets the diagnostic criteria
• After completing the DSQ, algorithm determines
if a patient meets case definitions including:
– Myalgic Encephalomyelitis/Chronic Fatigue Syndrome
(ME/CFS; Carruthers et al., 2003)
– Myalgic Encephalomyelitis (ME-ICC; Carruthers et al.,
2011
– Chronic fatigue syndrome (CFS; Fukuda et al., 1994)
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Psychometric Properties of the DSQ
• Good to excellent test-retest reliability
(correlation coefficients for items on the DSQ)
– Suggests that the overall instrument is a reliable
measure for examining symptoms and illness
constructs within the patient community
• Brown & Jason (2014) indicates excellent
internal consistency reliability
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Dissemination
• The DSQ is now being used in countries around the
world, including Canada, Mexico, Iran, England,
Norway, and France
• Being used data collection efforts with the CFIDS
Association Biobank, CDC multi-site study, Chronic
Fatigue Initiative
• It is also being used in efforts to document specific
vision-related abnormalities among patients
– (Hutchinson, Maltby, Badham, & Jason, in press)
• A group of Iranian investigators are currently
examining other psychometric properties of this
instrument.
• Specialty Clinic in Vancouver using DSQ all new
patients
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Need Standardized Use of Measures
• Allow for a well-defined characterization of a
patient’s illness
• Thus, clinicians will be able to better determine
when examining those with ME, ME/CFS, and/or
CFS
• Ultimately identify and work with more
homogenous samples
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DSQ Freely Available
• The DePaul Symptom Questionnaire is officially
in the REDCap Shared Library
– https://redcap.vanderbilt.edu/consortium/library/searc
h.php
• If your institution does not subscribe to REDCap,
you can access the DSQ using this link
– https://redcap.is.depaul.edu/surveys/?s=tRxytSPVVw
CENTER FOR COMMUNITY RESEARCH
In Terms of the Validated Questionnaires and
Tools Used for the Diagnosis of ME/CFS,
How Do Patients with ME/CFS Compare to
Other “Sick" Controls?
• ME/CFS is an illness as debilitating as Type II
diabetes mellitus, congestive heart failure,
Multiple Sclerosis, end-stage renal disease
– Anderson & Ferrans (1997); Buchwald, Pearlman,
Umali, Schmaling, & Katon (1996)
CENTER FOR COMMUNITY RESEARCH
What Types of “Sick" Controls Have
Been Used in the Past in Your or
Others' Work?
What Work Is In Progress?
• One longitudinal study of youth after developing mono, they
those who recovered and who did not were followed up at 6,
12, and 24 months.
– Jason, Katz et al. (2013) found that days spent in bed since mono,
along with autonomic symptoms, were associated with postinfectious ME/CFS at 6 months
• Need include physically active and inactive healthy controls
– Such studies could help us explore whether deconditioning is
associated with ME/CFS and the major outcome measures
• Studies of exercise deconditioning using careful case-control
structures have not been able to explain ME/CFS on the basis
of exercise deconditioning
– Bazelmans, Bleijenberg, van der Meer, & Folgering, (2001); Bruno
(2004); van der Werf et al. (2000)
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We Can Distinguish Between
ME/CFS and Major Depressive
Disorder
• Using Discriminant Function Analysis
– 100% participants were classified correctly as having
ME/CFS or Depressive Disorder
• Predictors
– Percent of time fatigue was reported
– post-exertional malaise
– unrefreshing sleep
– confusion/disorientation
– shortness of breath
– severity self-reproach (BDI)
• Hawk, Jason, Torres-Harding (2006)
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Jason et al. (1997) compared
ME/CFS to MS and Lupus
• Early version of our scale differentiates patients with
ME/CFS from those who are healthy
– it is less likely to distinguish ME/CFS from other autoimmune
diseases (especially Lupus)
• We will soon be recruiting larger samples of controls with
MS and Lupus, to see how they differ from those with
ME/CFS using the DSQ
• We recommend a two-stage research design with
– 1) a screening instrument with good sensitivity
– 2) medical assessments of ME/CFS positives from stage 1 to
deal with the specificity problem
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Extreme Care with Low Prevalence
Illnesses
• Based on epidemiological evidence, in a sample of
100,000, there would be approximately 420 cases of
ME/CFS
• According to Bayes' theorem
– If a case definition had a 95% rate of sensitivity and
95% specificity
• would identify 399 of the 420 ME/CFS cases
• Identify 4,979 individuals who did not have ME/CFS but
were identified as having it
CENTER FOR COMMUNITY RESEARCH
Need Define What Counts as a
Symptom
• Many questionnaires have measured severity
but not frequency, and both need to be
considered
– Some symptoms are very severe, but if they occur
rarely, they are less likely to be considered a problem
• Also, many investigators consider mild severity
as a cut off point, this decision can lead to
including too many individuals into the case
definition
DePaul Symptom Questionnaire:
Frequency and Severity scales for each symptom
Scale:
Frequency:
Severity:
0
1
2
3
4
None
of the time
A little
of the time
About half
of the time
Most
of the time
All
of the time
Symptom not
present
Mild
Moderate
Severe
Very severe
CENTER FOR COMMUNITY RESEARCH
DePaul Symptom Questionnaire:
Frequency and Severity scales for each symptom
Frequency and Severity Scores of at least 1:
Scale:
Frequency:
Severity:
0
1
2
3
4
None
of the time
A little
of the time
About half
of the time
Most
of the time
All
of the time
Symptom not
present
Mild
Moderate
Severe
Very severe
CENTER FOR COMMUNITY RESEARCH
Fatigue
100%
100%
Percentage of CFS and Controls with Frequency and Severity Scores >=1
(Fukuda Criteria)
Unrefreshing
Sleep
99%
Post-Exertional Malaise
99%
96%
Memory & Concentration Problems
98%
95%
95%
97%
95%
95%
Muscle
Pain
96%
94%
93%
90%
90%
90%
Headaches
Joint
Pain
86%
Sore
Throat
81%
Tender
Lymph
Nodes
81%
80%
70%
50%
65%
65%
60%
56%
55%
51%
49%
44%
40%
39%
37%
30%
20%
21%
19%
17%
22%
18%
13%
10%
9%
7%
6%
0%
CFS
CFS
Control
Control
Misclassifications of Fukuda et al. (1994) CFS
33.7% of controls would meet Fukuda symptom
requirements when including participants who report
frequency and severity scores of 1 or greater
CENTER FOR COMMUNITY RESEARCH
DePaul Symptom Questionnaire:
Frequency and Severity scales for each symptom
Frequency and Severity Scores of at least 2:
Scale:
Frequency:
Severity:
0
1
2
3
4
None
of the time
A little
of the time
About half
of the time
Most
of the time
All
of the time
Symptom not
present
Mild
Moderate
Severe
Very severe
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Percentage of
of CFS
CFS and
and Controls
Controls with
with Frequency
Frequency and
and Severity
Severity Scores
Scores >=1
>=2
Percentage
(Fukuda Criteria)
Criteria)
(Fukuda
Unrefreshing
Fatigue
Sleep
Fatigue Unrefreshing
100%
99%
100%
Sleep
100%
96%
92%
Post-Exertional Malaise
99%
96%
Memory & Concentration Problems
98%
95%
95%
97%
95%
95%
Post-Exertional Malaise
96%
94%
86%
90%
Memory & Concentration Problems
85%
83%
83%
80%
73%
69%
86%
68%
65%
Headaches
55%
Tender
Lymph
Nodes
50%
56%
51%
49%
81%
64%
65%
55%
Tender
Lymph
Nodes
Joint
Pain
73%
69%
Sore
Throat
81%
66%
60%
60%
Joint
Pain
Muscle
Pain
80%
80%
70%
70%
Headaches
93%
90%
90%
90%
50%
50%
Muscle
Pain
44%
40%
40%
Sore
Throat
44%
39%
37%
31%
30%
30%
20%
20%
16%
17%
10%
10%
18%
13%
12%
10%
7%
0%
0%
22%
21%
19%
7%
7%
2%
7%
4%
5%
4%
7%
2%
CFS
CFS
CFS
9%
2%
7%
5%
Control
Control
Control
2%
1%
6%
0%
Canadian Clinical ME/CFS (2003) criteria
• Six or more months of fatigue
• One symptom from each of the following categories:
–
–
–
–
Post-Exertional Malaise
Sleep Dysfunction
Neurocognitive Impairments
Pain
• One symptom from two of the following categories:
– Autonomic
– Neuroendocrine
– Immune
CENTER FOR COMMUNITY RESEARCH
Percentage of CFS and Controls with Frequency and Severity Scores >=2
(ME/CFS Symptoms)
100%
Sleep
90%
PEM
Neurocognitive
80%
Pain
Immune, Neuroendocrine, &
Autonomic symptoms have
lower prevalence
70%
60%
Immune
Neuroendocrine
Autonomic
50%
40%
30%
20%
10%
0%
CFS
Control
CENTER FOR COMMUNITY RESEARCH
Are There Any Data on How Patients of
Different Ethnic/ Socio-Economic Backgrounds
Present?
Are There Any Differences in Terms of Their
Presentation or Course of Illness?
• Few studies have examined these questions
• Most research has been on Caucasian samples
CENTER FOR COMMUNITY RESEARCH
Data from a Community-Based
Sample
Jason, Taylor, Kennedy et al. (2001)
Symptoms experienced more severely by Minority
participants
100
90
80
70
60
Severity
Rating
Minority
Caucasian
50
40
30
20
10
0
Sore throat
Postexertional
Malaise
Headaches
Symptom
Unrefreshing
Sleep
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Song, Jason, & Taylor(1999) Examined
Sociodemographic Differences
• Examined fatigue across African American,
Caucasian, Latino and Asian American samples
• Latinos who were female, older, and of lower
SES reported the highest relative severity of
fatigue
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Women Latinas Highest Fatigue
Female
13.44
13.50
Male
13.10
13.00
Mean Fatigue
13.00
12.50
12.90
12.49
12.38
12.29
12.00
12.00
11.50
11.00
African Americans
Caucasians
Latinos
Racial/ethnic Groups
Asian Americans
CENTER FOR COMMUNITY RESEARCH
Among Latinos, Highest Fatigue
Found Among Those Older and
Lower SES
Latinos
Younger 50%
13.4
Older 50%
13.22
13.2
13
12.91
12.80
Mean Fatigue
12.8
12.6
12.4
12.23
12.2
12
11.8
11.6
Lower 50%
Upper 50%
SES
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In What Ways Are Community-Based
Patients Different from Those Recruited
From Referral/ Specialty Centers?
• Issue not been well explored
• Almost all studies of samples with patients with
ME/CFS have relied on referrals from physicians
or health facilities
CENTER FOR COMMUNITY RESEARCH
Jason, Plioplys et al. (2003) Compared Individuals
Diagnosed with ME/CFS in a Community-Based
Sample to Patients with ME/CFS Who Were
Recruited From Tertiary-Care
• Significantly more minorities in the Community
versus Tertiary samples
• Within the ME/CFS-Community sample, 45% were white, 16%
were Black, 29% were Latino, and 10% were other
• In the ME/CFS-Tertiary sample 93% were white, 5% were
Black, 1% were Latino and 1% were other
• However, symptom criteria were significantly higher
among Tertiary as compared with the Community
samples
– memory and concentration problems, 96% vs 74%
– sore throat, 76% vs 45%
– tender lymph nodes, 65% vs 45%
CENTER FOR COMMUNITY RESEARCH
Thoughts on the recent IOM with Gulf
War Veterans
• In their review of factor-analytic studies, key
question is whether the factor structure varies
among compared populations
• As the report stated, that question is most
appropriately posited as a formal statistical test
– the probability of observing the differences between the
factor structures in the samples is estimated under the null
hypothesis that the factor structures are the same in the
two populations
• Unfortunately, almost all existing studies of factorstructure differences have failed to test the
hypothesis directly
– none have used structural equation models
CENTER FOR COMMUNITY RESEARCH
Issues Needing Resolution
• Reduce criterion variance by deciding which case
definition to use
– Facilitate clinicians identify patients similar core symptoms
• Specify what instrument to use to measure the symptoms
– Develop algorithms to help determine whether a patient meets
the case definition
• Encourage research on ways to better operationalize key
elements of the case definition
–
–
–
–
Define Onset
Define Substantial Reductions
Define Lifelong fatigue
Define Time Period for Symptoms (6 months, 1 month, 1 week,
today)
– Define Cutoffs for Frequency and Severity of Symptoms
2013
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Illness Timeline:
Level of Functioning over Time
100
90
80
70
60
50
40
30
Health significantly
deteriorating
20
Chronic Bronchitis
10
0
CENTER FOR COMMUNITY RESEARCH
Future Directions
• In the critical decisions before your committee
– Collect and share data from patient groups, clinicians, NIH,
CDC, IACFS/ME using quantitative and qualitative
methods to inform an interactive and transparent process
– This will help secure the participation of key stakeholders
• Learn from experiences of other diseases which
developed infrastructures to oversee refinements of
case definition criteria
– Recommend the development of an ongoing, flexible,
adaptive system that encourages clinical trials, research,
incorporation of new findings into the case definition
CENTER FOR COMMUNITY RESEARCH
References
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Anderson, J. S., & Ferrans, C. E. (1997). The quality of life of persons with chronic fatigue syndrome. Journal of Nervous
Mental Disorders, 185, 359-367.
Brown, A., & Jason, L.A. (2014). Validating a measure of myalgic encephalomyelitis/chronic fatigue syndrome
symptomatology.. Manuscript under review.
Brurberg, K.G., Fønhus, M.S., Larun, L., Flottorp, S., & Malterud, K. (2014). (CFS/ME): a systematic review
syndrome/myalgic encephalomyelitis BMJ Open 2014 4:e003973
Buchwald, D., Pearlman, T., Umali, J., Schmaling, K., & Katon, W. (1996). Functional status in patients with chronic fatigue
syndrome, other fatiguing illnesses, and healthy individuals. American Journal of Medicine, 101, 364–370.
Hawk, C., Jason, L.A., & Torres-Harding, S. (2006). Differential diagnosis of chronic fatigue syndrome and major depressive
disorder. International Journal of Behavioral Medicine, 13, 244-251.
Hutchinson, C.V., Maltby, J., Badham, S.P., & Jason, L.A. (in press). Vision-related symptoms as a clinical feature of
Chronic Fatigue Syndrome/Myalgic Encephalomyelitis? Evidence from the DePaul Symptom
Questionnaire. British Journal of Ophthalmology. doi:10.1136/bjophthalmol-2013-304439
Jason, L. A., Brown, A., Evans, M., Sunnquist, M., & Newton, J. L. (2013). Contrasting chronic fatigue syndrome versus
myalgic encephalomyelitis/chronic fatigue syndrome. Fatigue: Biomedicine, Health & Behavior, 1(3), 168-183.
Jason, L.A., Katz, B.Z., Shiraishi, Y., Mears, C.J., Im, Y., Taylor, R.R. (2014). Predictors of post-infectious chronic fatigue
syndrome in adolescents. Health Psychology and Behavioral Medicine: An Open Access Journal, 2, 41–51.
Jason, L.A., Plioplys, A.V., Torres-Harding, S., & Corradi, K. (2003). Comparing symptoms of chronic fatigue syndrome in a
community-based versus tertiary care sample. Journal of Health Psychology, 8, 459-464.
Jason, L.A., Porter, N., Hunnell, J., Brown, A., Rademaker, A., & Richman, J.A. (2011a). A natural history study of chronic
fatigue syndrome. Rehabilitation Psychology, 56, 32-42. PMCID: PMC3171164
Jason, L.A., Porter, N., Hunnell, J., Rademaker, A., & Richman, J.A. (2011b). CFS prevalence and risk factors over time.
Journal of Health Psychology, 16, 445-456. PMCID: PMC3166209
Jason, L.A., Ropacki, M.T., Santoro, N.B., Richman, J.A., Heatherly, W., Taylor, R.R., Ferrari, J.R., Haney-Davis, T.M.,
Rademaker, A., Dupuis, J., Golding, J., Plioplys, A.V., & Plioplys, S. (1997). A screening instrument for Chronic Fatigue
Syndrome: Reliability and validity. Journal of Chronic Fatigue Syndrome, 3, 39-59.
Jason, L.A., Taylor, R.R., Kennedy, C.L., Harding, S.T., Song, S., Johnson, D., Chimata, R. (2001). Subtypes of chronic
fatigue syndrome: A review of findings. Journal of Chronic Fatigue Syndrome, 8, 1-21
Jason, L.A., Taylor, R.R., Kennedy, C.L., Jordan, K., Song, S., Johnson, D., & Torres, S. (2000). Chronic fatigue syndrome:
Sociodemographic subtypes in a community-based sample. Evaluation and the Health Professions, 23, 243-263.
Song, S., Jason, L.A., Taylor, R.R., Torres-Harding, S.R., Helgerson, J., & Witter, E. (2002). Fatigue severity among African
Americans: Gender and age interactions. Journal of Black Psychology, 28, 53-65.
Song, S., Jason, L.A., & Taylor, R.R. (1999). The relationship between ethnicity and fatigue in a community-based sample.
Journal of Gender, Culture, and Health, 4, 255-268.