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Diagnostic Methods for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Systematic Review for a National Institutes of Health Pathways to Prevention WorkshopDiagnostic Methods for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome FREE

Elizabeth Haney, MD; M.E. Beth Smith, DO; Marian McDonagh, PharmD; Miranda Pappas, MA; Monica Daeges, BA; Ngoc Wasson, MPH; and Heidi D. Nelson, MD, MPH
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From Oregon Health & Science University and Providence Cancer Center, Providence Health and Services Oregon, Portland, Oregon.

Disclaimer: The findings and conclusions in this document are those of the authors, who are responsible for its content, and do not necessarily represent the views of the Agency for Healthcare Research and Quality (AHRQ). No statement in this report should be construed as an official position of AHRQ or the U.S. Department of Health and Human Services.

Acknowledgment: The authors thank the following individuals for their contributions to this project: Richard Bryant, MD, for providing expert consultation throughout the report; Andrew Hamilton, MLS, MS, for conducting literature searches; and Spencer Dandy, BS, for assistance with preparing this report (all are located at the Oregon Health & Science University). They also thank Suchitra Iyer, PhD, Task Order Officer at the Agency for Healthcare Research and Quality; Carmen Green, MD, National Institutes of Health (NIH) Working Group Chair; the NIH; the Technical Expert Panel; and reviewers of the draft report.

Financial Support: By the Agency for Healthcare Research and Quality (contract 290-2012-00014-i, task order 4), Rockville, Maryland.

Disclosures: Dr. Haney reports grants from the Agency for Healthcare Research and Quality during the conduct of the study. Ms. Daeges reports grants from the Agency for Healthcare Research and Quality during the conduct of this study. Authors not named here have disclosed no conflicts of interest. Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M15-0443.

Editors' Disclosures: Christine Laine, MD, MPH, Editor in Chief, reports that she has no financial relationships or interests to disclose. Darren B. Taichman, MD, PhD, Executive Deputy Editor, reports that he has no financial relationships or interests to disclose. Cynthia D. Mulrow, MD, MSc, Senior Deputy Editor, reports that she has no relationships or interests to disclose. Deborah Cotton, MD, MPH, Deputy Editor, reports that she has no financial relationships or interest to disclose. Jaya K. Rao, MD, MHS, Deputy Editor, reports that she has stock holdings/options in Eli Lilly and Pfizer. Sankey V. Williams, MD, Deputy Editor, reports that he has no financial relationships or interests to disclose. Catharine B. Stack, PhD, MS, Deputy Editor for Statistics, reports that she has stock holdings in Pfizer.

Requests for Single Reprints: Elizabeth Haney, MD, 3181 SW Sam Jackson Park Road, Mail Code BICC, Portland, OR 97239; e-mail, haneye@ohsu.edu.

Current Author Addresses: Drs. Haney, Smith, McDonagh, and Nelson; Ms. Pappas; Ms. Daeges; and Ms. Wasson: 3181 SW Sam Jackson Park Road, Mail Code BICC, Portland, OR 97239.

Author Contributions: Conception and design: E. Haney, M.E.B. Smith, M. McDonagh, H.D. Nelson.

Analysis and interpretation of the data: E. Haney, M.E.B. Smith, M. McDonagh, M. Pappas, N. Wasson, H.D. Nelson.

Drafting of the article: E. Haney, M.E.B. Smith, M. McDonagh, M. Pappas, H.D. Nelson.

Critical revision of the article for important intellectual content: E. Haney, M.E.B. Smith, M. McDonagh, H.D. Nelson.

Final approval of the article: E. Haney, M.E.B. Smith, M. McDonagh, M. Pappas, N. Wasson, H.D. Nelson.

Obtaining of funding: M.E.B. Smith, M. McDonagh, H.D. Nelson.

Administrative, technical, or logistic support: M. Pappas, N. Wasson.

Collection and assembly of data: E. Haney, M.E.B. Smith, M. Pappas, N. Wasson, H.D. Nelson.


Ann Intern Med. 2015;162(12):834-840. doi:10.7326/M15-0443
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Background: The diagnosis of myalgic encephalomyelitis (ME)/chronic fatigue syndrome (CFS) is based on clinical criteria, yet there has been no consensus regarding which set of criteria best identifies patients with the condition. The Institute of Medicine has recently proposed a new case definition and diagnostic algorithm.

Purpose: To review methods to diagnose ME/CFS in adults and identify research gaps and needs for future research.

Data Sources: MEDLINE, PsycINFO, and Cochrane databases (January 1988 to September 2014); clinical trial registries; and reference lists.

Study Selection: English-language studies describing methods of diagnosis of ME/CFS and their accuracy.

Data Extraction: Data on participants, study design, analysis, follow-up, and results were extracted and confirmed. Study quality was dual-rated by using prespecified criteria, and discrepancies were resolved through consensus.

Data Synthesis: Forty-four studies met inclusion criteria. Eight case definitions have been used to define ME/CFS; a ninth, recently proposed by the Institute of Medicine, includes principal elements of previous definitions. Patients meeting criteria for ME represent a more symptomatic subset of the broader ME/CFS population. Scales rating self-reported symptoms differentiate patients with ME/CFS from healthy controls under study conditions but have not been evaluated in clinically undiagnosed patients to determine validity and generalizability.

Limitations: Studies were heterogeneous and were limited by size, number, applicability, and methodological quality. Most methods were tested in highly selected patient populations.

Conclusion: Nine sets of clinical criteria are available to define ME/CFS, yet none of the current diagnostic methods have been adequately tested to identify patients with ME/CFS when diagnostic uncertainty exists. More definitive studies in broader populations are needed to address these research gaps.

Primary Funding Source: Agency for Healthcare Research and Quality. (PROSPERO: CRD42014009779)


The terms myalgic encephalomyelitis (ME) and chronic fatigue syndrome (CFS) have been used to describe a debilitating multisystemic condition characterized by chronic, disabling fatigue and various other symptoms. The term CFS was introduced in the 1980s after research failed to identify a clear viral association with what was previously labeled chronic Epstein–Barr virus syndrome (14). Other terms, such as postviral fatigue syndrome and chronic fatigue immune dysfunction syndrome, were also used in attempts to associate the syndrome with possible underlying causes (12, 56). Although the most recent international consensus report advocates moving away from the term CFS in favor of the term ME to better reflect an underlying disease process involving widespread inflammation and neuropathology (78), experts do not agree about these mechanisms and the cause of CFS remains unclear.

A recent Institute of Medicine (IOM) report proposes a name, systemic exertion intolerance disease (SEID), that describes the central elements of the disease. The report focuses on the adverse effect that physical, cognitive, or emotional exertion can have on patients with this condition and acknowledges that this is a complex and severe disorder for which specific causes are not yet proven (9).

The diagnosis of ME/CFS is based on clinical criteria that attempt to distinguish it from other conditions that also present with fatigue. Eight published case definitions have been used since the first one established by the Centers for Disease Control and Prevention (CDC) in 1988 (2), and the IOM proposed a ninth in February 2015 (9). All include persistent fatigue not attributable to a known underlying medical condition, as well as additional clinical signs and symptoms that do not all need to be present to establish the diagnosis (10). However, there has been no consensus about which, if any, of these clinical criteria should be considered the reference standard. The variations in case definitions imply that they may describe different conditions and lead to different diagnoses, complicating ME/CFS research and clinical care. For example, depending on the case definition, prevalence rates of ME/CFS in the United States range from 0.3% to 2.5% (1, 1112).

This systematic review is part of a larger report to inform a research agenda for the National Institutes of Health (NIH) 2014 Pathways to Prevention Workshop, an evidence-based methodology workshop (13). The purpose of this systematic review was to evaluate and compare studies of methods to diagnose ME/CFS, identify limitations of current studies, and determine needs for future research.

Key questions guiding this review were developed in collaboration with the NIH ME/CFS Working Group following a standard protocol, including input from key informants and a technical expert panel, registration in the PROSPERO database for systematic reviews (14), and posting on an Agency for Healthcare Research and Quality (AHRQ) public Web site. Key questions concerned describing clinical methods for diagnosing ME/CFS and evaluating their concordance and accuracy, describing variations in diagnostic methods by patient subgroups, and identifying consequences of diagnosis for patients. This article focuses on the published case definitions and on the concordance and accuracy of methods for diagnosis of ME/CFS. A technical report details the methods and includes an analytic framework, search strategies, and additional evidence tables (13).

Data Sources and Searches

A research librarian searched electronic databases to identify relevant articles published between January 1988 (year of the first case definition) and September 2014: MEDLINE (Ovid), PsycINFO, the Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, and the National Health Sciences Economic Evaluation. Searches were supplemented by references identified from additional sources, including reference lists and experts.

Study Selection

English-language studies of adults with ME/CFS as defined by any of the established case definitions, and those for whom ME/CFS was a diagnostic consideration, were eligible for inclusion. For this review, we use the combined term "ME/CFS" when referring to the condition in general, and we use the individual terms to represent study populations fulfilling specific sets of clinical criteria defined as ME or CFS. Studies of diagnostic tests or case definitions were included if they were conducted in clinical settings or settings applicable to clinical practice settings; we excluded studies of inpatients or institutionalized individuals. We also excluded studies of disease cause and studies that reported the diagnosis of specific symptoms of ME/CFS (for example, postexertional malaise).

We included studies that 1) compared case definitions (for example, Fukuda/CDC, Canadian, International) and provided measures of agreement or 2) tested the ability of the method to identify patients with ME/CFS by using 1 of the case definitions as a reference standard and reported at least 1 of the specified outcomes. Because there is no single accepted definition for ME/CFS and therefore no "gold standard," any of the case definitions published since 1988 were accepted as reference standards. Included outcomes of diagnostic accuracy were sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, c-statistic, receiver-operating characteristic curve and area under the receiver-operating characteristic curve, net reclassification index, and concordance. Studies of any design were included if they described potential harms from diagnosis, such as psychological harms, labeling, risk from diagnostic tests, and misdiagnosis. These studies are included in the full report (13).

Two investigators independently evaluated each study to determine inclusion eligibility. Disagreement was resolved by consensus, with a third investigator making the final decision as needed.

Data Extraction and Quality Assessment

An investigator abstracted details of the patient population, study design, setting, inclusion and exclusion criteria, population characteristics, sample size, case definition for diagnosis, and results. A second investigator reviewed extracted data for accuracy and completeness. Investigators rated the quality (risk of bias) of the individual studies on the basis of criteria adapted from the Agency for Healthcare Research and Quality (AHRQ) Methods Guide for Medical Test Reviews (15). A second investigator reviewed ratings, and disagreements were resolved by consensus with a third investigator as needed. Quality and strength of evidence ratings were assessed for all studies of diagnostic test accuracy (comparison of a diagnostic test to a reference standard) but could not be assessed for other studies with descriptive, cross-sectional, and case series designs.

Data Synthesis and Analysis

Studies of diagnostic tests could not be combined in a quantitative meta-analysis because of heterogeneity of patient populations, study designs, reported outcomes, and reference standards. Therefore, data were synthesized qualitatively with attention to such factors as patient characteristics and risk of bias.

Role of the Funding Source

The AHRQ funded the review, and a working group convened by the NIH helped develop the review's scope and key questions. Neither had a role in study selection, quality assessment, or synthesis. The investigators are solely responsible for the content.

Among the 6175 abstracts identified by searches and additional papers identified through other sources, 44 studies met inclusion criteria (Appendix Figure). These included 8 studies describing case definitions (Table) (2, 57, 1619), 22 evaluating diagnostic tests (Appendix Tables 1 and 2) (1, 10, 2039), and 14 describing consequences of diagnosis (Appendix Table 3) (11, 4052). The new IOM case definition was also included for completeness (bringing the total to 9 available case definitions), even though it was published after the literature search dates.

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Appendix Figure.

Summary of evidence search and selection.

* Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects, Health Technology Assessment, National Health Sciences Economic Evaluation Database, and Cochrane Database of Systematic Reviews.

† Identified from such sources as reference lists, hand searches, and suggestions by experts.

‡ Studies that provided data and contributed to the body of evidence were considered "included."

§ Studies included for the treatment key questions are reported elsewhere (13).

|| The Institute of Medicine case definition (9) is an additional case definition, which was released subsequent to the search.

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Table Jump PlaceholderTable. Comparisons of Symptoms Using Different Case Definitions 
Table Jump PlaceholderAppendix Table 1. Included Studies of Methods Used to Diagnose Myalgic Encephalomyelitis/Chronic Fatigue Syndrome 
Table Jump PlaceholderAppendix Table 2. Included Studies Evaluating the Concordance of Different Diagnostic Criteria and Comparisons Between Populations 
Table Jump PlaceholderAppendix Table 3. Included Studies of Harms of Diagnosis 
Methods for Diagnosing ME/CFS

Nine case definitions using clinical criteria have been developed to identify patients with ME/CFS and help clinicians distinguish ME/CFS from other conditions that present with fatigue (Table) (2, 57, 9, 1619). Although most case definitions require that other conditions be excluded before ME/CFS is diagnosed, no studies compared strategies for ruling out alternative diagnoses or specifically defined which conditions should be ruled out. The IOM case definition, published in February 2015, incorporates required elements of fatigue, postexertional malaise, and sleep disturbance, along with cognitive impairment or orthostatic hypotension (9). The Oxford case definition incorporates the fewest symptoms (new onset of fatigue with impairment of physical and mental function), suggesting that it includes patients who would not meet other criteria for ME/CFS (19).

Concordance of Methods for Diagnosing ME/CFS

Seven studies compared symptoms of patients with ME/CFS diagnosed by using different case definitions and found that symptoms varied depending on the clinical criteria used (Appendix Table 1) (1, 10, 2024). In general, populations defined by ME or ME/CFS criteria had more severe symptoms or more functional impairment than those defined by CFS criteria alone (1, 10, 2024).

Three studies enrolling a total of 6087 patients compared symptoms of patients with CFS identified by the 1994 CDC criteria with symptoms of patients without CFS (healthy controls; other fatigued patients; and patients with psychiatric, rheumatologic, and other chronic diseases) (2527). In general, patients without CFS were less impaired than those with CFS, although results varied. In 1 study, patients with CFS and multiple sclerosis had similar scores on the 36-item Short-Form Survey (SF-36) on physical function, vitality, and social function scales (27).

Accuracy of Measures for Diagnosing ME/CFS

Nine studies evaluated methods to discriminate ME/CFS from other conditions by using 1 of the published case definitions as a reference standard (Appendix Tables 2 and 4) (2937). One study met criteria for good quality (30), 7 for fair quality (3137), and 1 for poor quality (29). Several studies used the same or very similar study populations to report different outcomes, most commonly recruiting from CFS self-help groups (3436) or community samples (3233). Major limitations of studies included small size (<50 participants) (29, 3436), recruitment from specialty clinics only (30), lack of blinding to the reference standard result (2936), and comparing cases with primarily healthy or nonfatigued controls (29, 31, 3336).

Table Jump PlaceholderAppendix Table 4. Measures Used as Diagnostic Tests for ME/CFS 

By using computerized modeling to identify key symptoms, 3 studies found that symptom-based instruments had high sensitivity and specificity for identifying patients who meet 1 of the ME/CFS case definitions (Appendix Table 2) compared with healthy controls (3031, 37).

Another study randomly assigned a broad spectrum of 198 participants with fatigue (including patients with systemic lupus erythematosus, fibromyalgia, and CFS defined by Oxford criteria) to derivation or validation cohorts (30). Participants completed symptom questionnaires, and the symptoms with the highest sensitivity and specificity for CFS were selected to develop and evaluate computer-generated classification criteria to distinguish patients with CFS from the other patients. Four methods of classification were tested in the derivation cohort, and for each algorithm, the sensitivity, specificity, and accuracy were determined in the validation cohort. A strategy that included 24 symptoms, the artificial neural network, had good discriminative ability (sensitivity, 0.95; specificity, 0.85; accuracy, 0.90) (30). This study met criteria for good quality because it included a broad spectrum of patients with conditions considered to be competing diagnoses for ME/CFS and included a validation cohort.

An evaluation of responses to the DePaul Symptom Questionnaire from 515 patients with CFS and 176 controls used K-means clustering to distinguish patients with fewer symptoms from those with more symptoms, who presumably had CFS (37). After testing of 4 methods of clustering, the unsupervised thresholding model was used to assign a diagnostic label to each participant, and the diagnosis assigned by each of 3 different clinical criteria (1994 CDC [CFS], Canadian [ME/CFS], and 2011 International [ME]) was compared with the assigned diagnostic label. Then, the individual symptoms were ranked by predictive value and compared with the 3 case definitions and the use of all 54 DePaul Symptom Questionnaire symptoms.

Results indicated that model accuracy obtained by using the top 11 ranked symptoms was better than that obtained with all 54 DePaul Symptom Questionnaire symptoms or the 1994 CDC (CFS), Canadian (ME/CFS), and 2011 International (ME) criteria (90.2%, 82.3%, 83.8%, 84.1%, and 78.7%, respectively). The top-ranked symptoms corresponded to fatigue, exertional malaise, sleep disturbance, cognitive impairment, and myalgias. This study met criteria for fair quality because it lacked a validation group, but it included a relatively large, broad spectrum of participants.

In another study of 368 patients and 452 controls, the Schedule of Fatigue and Anergia for CFS Scale was developed by using a composite set of criteria as a reference standard and specific symptoms from 4 symptom checklists (31). Latent class analysis was used to select 10 symptoms having the highest correlation to CFS-like fatigue; then, a composite score was tested to determine sensitivity and specificity. The 10 symptoms included fatigue, exertional malaise, myalgias, cognitive difficulties (including poor concentration, poor memory, speech difficulties), poor sleep, and headaches. A total score of 3 to 4 out of 4 had a sensitivity of 81% for the 3-class solution and a specificity of 100%. This study met criteria for fair quality because patients were recruited from specialty clinics rather than from a broader population and because it lacked a validation cohort.

Variation in Diagnostic Testing According to Subgroups

Three studies evaluated diagnostic tests in subgroups of patients with ME/CFS (28, 3839). Compared with patients younger than 25 years, patients older than 50 were more impaired, had lower self-efficacy, and had worse scores on the Fatigue Impact Scale, Chalder Fatigue Scale, Hospital Anxiety and Depression Scale–Depression subscale, and SF-36 (28). Likewise, older patients had lower resting heart rates, higher left ventricular ejection time, and lower baroreflex sensitivity (ability to maintain blood pressure) than younger patients.

Two studies of the same population evaluated the ability of self-reported function scales to predict recovery from cardiopulmonary exercise testing in patients with CFS defined by 1994 CDC (CFS) criteria and nondisabled sedentary controls (3839). The SF-36 subscales of physical function, role-physical, bodily pain, general health, vitality, and social functioning identified patients with failure to recover at 1 day; the subscales role-emotional, vitality, and bodily pain identified those with failure to recover at 1 week (38). Having 3 or more symptoms of postexertional malaise optimally distinguished between patients with CFS and controls (39).

Of the 8 previously published sets of clinical criteria for ME and/or CFS, case definitions for ME and ME/CFS identify patients with more impairment, lower functioning, and more severe symptoms than the CFS-alone case definitions. The new IOM case definition incorporates principal elements of previous definitions, and the association of these elements to ME/CFS is supported by modeling studies (31, 37). None of the case definitions or other diagnostic methods has been adequately tested to determine how well they differentiate patients with ME/CFS from patients with other conditions. Although some symptom-based instruments discriminate patients with ME/CFS from healthy controls, their utility in differentiating patients with diagnostic uncertainty remains inconclusive because they have not been widely tested in broad spectrums of patients. The few studies that evaluated how diagnostic tests vary by patient subgroups were inconclusive.

The clinical applicability of current research on diagnostic methods for ME/CFS is limited in several ways. All case definitions require the exclusion of competing diagnoses before assigning a ME/CFS diagnosis, yet no studies evaluated strategies for the evaluation and assignment of alternative diagnoses. In addition, most studies were designed as descriptive studies and enrolled healthy or nonfatigued participants as controls. Studies evaluated whether tests distinguished ME/CFS from these types of controls, but not the essential clinical question of whether the test could distinguish ME/CFS from other fatiguing illnesses. Only 1 study included participants with overlapping symptoms and tested a strategy for diagnosis in both a derivation and a validation cohort; and only 2 studies evaluated a diagnostic test by using control groups of fatigued or other chronically ill patients (30). In addition, studies used varying case definitions as the reference standard precluding comparisons across studies. Finally, many studies recruited participants from specialty clinics, potentially reflecting more severe disease, or site-dependent or local practices, limiting generalizability to other patients with ME/CFS. Consistent with a prior systematic review (53), no studies identified specific patients with identifiable causes.

Future research should be based on a standard case definition, or a set of reference standards, to allow comparison of results across studies. The IOM has provided a consensus case definition that could serve this purpose. Consensus groups and researchers should consider retiring the Oxford case definition because it differs from the other case definitions and is the least restrictive, probably including individuals with other overlapping conditions. The new IOM case definition and algorithm provide a starting place for future studies of diagnostic testing.

Future studies evaluating the capability of diagnostic methods for ME/CFS should include a broad range of patients with conditions that require clinical distinction from ME/CFS, such as fibromyalgia and depression. Moreover, studies should report how well a particular method distinguishes ME/CFS from other conditions by using standard performance measures, such as concordance, sensitivity, and specificity. Studies should report findings according to important features of ME/CFS, such as postexertional malaise, neurocognitive status, and autonomic function, to identify subgroups that may respond differently to specific treatments. Collaborative groups could consider establishing an international ME/CFS registry that would track the natural history of patients to determine which set of clinical criteria best identifies patients for whom no alternative diagnosis will be found with subsequent testing, and for whom the diagnosis of ME/CFS will continue to be appropriate over time. Given the devastating effect of this condition on patients and families, researchers should involve patients and advocates in trial planning and development so that future research is relevant and meaningful to those affected by ME/CFS.

In conclusion, 9 sets of clinical criteria are used to define ME/CFS, yet none of the current diagnostic methods have been adequately tested to identify patients with ME/CFS when diagnostic uncertainty exists. More definitive studies in broader populations are needed to address these research gaps.

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Jason L, Brown M, Evans M, Anderson V, Lerch A, Brown A, et al. Measuring substantial reductions in functioning in patients with chronic fatigue syndrome. Disabil Rehabil. 2011; 33:589-98.
PubMed
CrossRef
 
Gaab J, Engert V, Heitz V, Schad T, Schürmeyer TH, Ehlert U. Associations between neuroendocrine responses to the Insulin Tolerance Test and patient characteristics in chronic fatigue syndrome. J Psychosom Res. 2004; 56:419-24.
PubMed
CrossRef
 
Gaab J, Hüster D, Peisen R, Engert V, Schad T, Schürmeyer TH, et al. Low-dose dexamethasone suppression test in chronic fatigue syndrome and health. Psychosom Med. 2002; 64:311-8.
PubMed
CrossRef
 
Gaab J, Rohleder N, Heitz V, Engert V, Schad T, Schürmeyer TH, et al. Stress-induced changes in LPS-induced pro-inflammatory cytokine production in chronic fatigue syndrome. Psychoneuroendocrinology. 2005; 30:188-98.
PubMed
CrossRef
 
Watson SP, Ruskin AS, Simonis V, Jason LA, Sunnquist M, Furst JD. Identifying defining aspects of chronic fatigue syndrome via unsupervised machine learning and feature selection. International Journal of Machine Learning & Computing. 2014; 4:133-8.
CrossRef
 
Davenport TE, Stevens SR, Baroni K, Van Ness JM, Snell CR. Reliability and validity of Short Form 36 Version 2 to measure health perceptions in a sub-group of individuals with fatigue. Disabil Rehabil. 2011; 33:2596-604.
PubMed
CrossRef
 
Davenport TE, Stevens SR, Baroni K, Van Ness M, Snell CR. Diagnostic accuracy of symptoms characterising chronic fatigue syndrome. Disabil Rehabil. 2011; 33:1768-75.
PubMed
CrossRef
 
Jason LA, Taylor RR. Measuring attributions about chronic fatigue syndrome. J Chronic Fatigue Syndr. 2001; 8:31-40.
CrossRef
 
Asbring P, Närvänen AL. Women's experiences of stigma in relation to chronic fatigue syndrome and fibromyalgia. Qual Health Res. 2002; 12:148-60.
PubMed
CrossRef
 
Assefi NP, Coy TV, Uslan D, Smith WR, Buchwald D. Financial, occupational, and personal consequences of disability in patients with chronic fatigue syndrome and fibromyalgia compared to other fatiguing conditions. J Rheumatol. 2003; 30:804-8.
PubMed
 
Deale A, Wessely S. Diagnosis of psychiatric disorder in clinical evaluation of chronic fatigue syndrome. J R Soc Med. 2000; 93:310-2.
PubMed
 
Dickson A, Knussen C, Flowers P. Stigma and the delegitimation experience: an interpretative phenomenological analysis of people living with chronic fatigue syndrome. Psychol Health. 2007; 22:851-67.
CrossRef
 
Green J, Romei J, Natelson BH. Stigma and chronic fatigue syndrome. J Chronic Fatigue Syndr. 1999; 5:63-95.
CrossRef
 
Guise J, McVittie C, McKinlay A. A discourse analytic study of ME/CFS (Chronic Fatigue Syndrome) sufferers' experiences of interactions with doctors. J Health Psychol. 2010; 15:426-35.
PubMed
CrossRef
 
Jason LA, Taylor RR, Stepanek Z, Plioplys S. Attitudes regarding chronic fatigue syndrome: the importance of a name. J Health Psychol. 2001; 6:61-71.
PubMed
CrossRef
 
Brimmer DJ, Maloney E, Devlin R, Jones JF, Boneva R, Nagler C, et al. A pilot registry of unexplained fatiguing illnesses and chronic fatigue syndrome. BMC Res Notes. 2013; 6:309.
PubMed
CrossRef
 
Devasahayam A, Lawn T, Murphy M, White PD. Alternative diagnoses to chronic fatigue syndrome in referrals to a specialist service: service evaluation survey. JRSM Short Rep. 2012; 3:4.
PubMed
CrossRef
 
Lawn T, Kumar P, Knight B, Sharpe M, White PD. Psychiatric misdiagnoses in patients with chronic fatigue syndrome. JRSM Short Rep. 2010; 1:28.
PubMed
CrossRef
 
Newton JL, Mabillard H, Scott A, Hoad A, Spickett G. The Newcastle NHS Chronic Fatigue Syndrome Service: not all fatigue is the same. J R Coll Physicians Edinb. 2010; 40:304-7.
PubMed
CrossRef
 
Woodward RV, Broom DH, Legge DG. Diagnosis in chronic illness: disabling or enabling—the case of chronic fatigue syndrome. J R Soc Med. 1995; 88:325-9.
PubMed
 
Brurberg KG, Fønhus MS, Larun L, Flottorp S, Malterud K. Case definitions for chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME): a systematic review. BMJ Open. 2014; 4:e003973.
PubMed
CrossRef
 
Beck AT, Steer RA, Carbin MG. Psychometric properties of the Beck Depression Inventory: twenty-five years of evaluation. Clin Psychol Rev.. 1988; 8:77-100.
CrossRef
 
Brown M, Kaplan C, Jason L. Factor analysis of the Beck Depression Inventory-II with patients with chronic fatigue syndrome. J Health Psychol.. 2012; 17:799-808.
PubMed
CrossRef
 
Chalder T, Berelowitz G, Pawlikowska T, Watts L, Wessely S, Wright D, et al. Development of a fatigue scale. J Psychosom Res.. 1993; 37:147-53.
PubMed
CrossRef
 
Morriss RK, Wearden AJ, Mullis R. Exploring the validity of the Chalder Fatigue scale in chronic fatigue syndrome. J Psychosom Res.. 1998; 45:411-7.
PubMed
CrossRef
 
Cella M, Chalder T. Measuring fatigue in clinical and community settings. J Psychosom Res.. 2010; 69:17-22.
PubMed
CrossRef
 
Hickie I, Lloyd A, Hadzi-Pavlovic D, Parker G, Bird K, Wakefield D. Can the chronic fatigue syndrome be defined by distinct clinical features? Psychol Med.. 1995; 25:925-35.
PubMed
CrossRef
 
Hickie I, Lloyd A, Wakefield D, Parker G. The psychiatric status of patients with the chronic fatigue syndrome. Br J Psychiatry. 1990; 156:534-40.
PubMed
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Hawk C, Jason LA, Torres-Harding S. Reliability of a chronic fatigue syndrome questionnaire. J Chronic Fatigue Syndr.. 2007; 13:41-66.
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Figures

Grahic Jump Location
Appendix Figure.

Summary of evidence search and selection.

* Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects, Health Technology Assessment, National Health Sciences Economic Evaluation Database, and Cochrane Database of Systematic Reviews.

† Identified from such sources as reference lists, hand searches, and suggestions by experts.

‡ Studies that provided data and contributed to the body of evidence were considered "included."

§ Studies included for the treatment key questions are reported elsewhere (13).

|| The Institute of Medicine case definition (9) is an additional case definition, which was released subsequent to the search.

Grahic Jump Location

Tables

Table Jump PlaceholderTable. Comparisons of Symptoms Using Different Case Definitions 
Table Jump PlaceholderAppendix Table 1. Included Studies of Methods Used to Diagnose Myalgic Encephalomyelitis/Chronic Fatigue Syndrome 
Table Jump PlaceholderAppendix Table 2. Included Studies Evaluating the Concordance of Different Diagnostic Criteria and Comparisons Between Populations 
Table Jump PlaceholderAppendix Table 3. Included Studies of Harms of Diagnosis 
Table Jump PlaceholderAppendix Table 4. Measures Used as Diagnostic Tests for ME/CFS 

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PubMed
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Jason LA, Evans M, Brown A, Brown M, Porter N, Hunnell J, et al. Sensitivity and specificity of the CDC empirical chronic fatigue syndrome case definition. Psychology. 2010; 1:9-16.
CrossRef
 
Jason L, Brown M, Evans M, Anderson V, Lerch A, Brown A, et al. Measuring substantial reductions in functioning in patients with chronic fatigue syndrome. Disabil Rehabil. 2011; 33:589-98.
PubMed
CrossRef
 
Gaab J, Engert V, Heitz V, Schad T, Schürmeyer TH, Ehlert U. Associations between neuroendocrine responses to the Insulin Tolerance Test and patient characteristics in chronic fatigue syndrome. J Psychosom Res. 2004; 56:419-24.
PubMed
CrossRef
 
Gaab J, Hüster D, Peisen R, Engert V, Schad T, Schürmeyer TH, et al. Low-dose dexamethasone suppression test in chronic fatigue syndrome and health. Psychosom Med. 2002; 64:311-8.
PubMed
CrossRef
 
Gaab J, Rohleder N, Heitz V, Engert V, Schad T, Schürmeyer TH, et al. Stress-induced changes in LPS-induced pro-inflammatory cytokine production in chronic fatigue syndrome. Psychoneuroendocrinology. 2005; 30:188-98.
PubMed
CrossRef
 
Watson SP, Ruskin AS, Simonis V, Jason LA, Sunnquist M, Furst JD. Identifying defining aspects of chronic fatigue syndrome via unsupervised machine learning and feature selection. International Journal of Machine Learning & Computing. 2014; 4:133-8.
CrossRef
 
Davenport TE, Stevens SR, Baroni K, Van Ness JM, Snell CR. Reliability and validity of Short Form 36 Version 2 to measure health perceptions in a sub-group of individuals with fatigue. Disabil Rehabil. 2011; 33:2596-604.
PubMed
CrossRef
 
Davenport TE, Stevens SR, Baroni K, Van Ness M, Snell CR. Diagnostic accuracy of symptoms characterising chronic fatigue syndrome. Disabil Rehabil. 2011; 33:1768-75.
PubMed
CrossRef
 
Jason LA, Taylor RR. Measuring attributions about chronic fatigue syndrome. J Chronic Fatigue Syndr. 2001; 8:31-40.
CrossRef
 
Asbring P, Närvänen AL. Women's experiences of stigma in relation to chronic fatigue syndrome and fibromyalgia. Qual Health Res. 2002; 12:148-60.
PubMed
CrossRef
 
Assefi NP, Coy TV, Uslan D, Smith WR, Buchwald D. Financial, occupational, and personal consequences of disability in patients with chronic fatigue syndrome and fibromyalgia compared to other fatiguing conditions. J Rheumatol. 2003; 30:804-8.
PubMed
 
Deale A, Wessely S. Diagnosis of psychiatric disorder in clinical evaluation of chronic fatigue syndrome. J R Soc Med. 2000; 93:310-2.
PubMed
 
Dickson A, Knussen C, Flowers P. Stigma and the delegitimation experience: an interpretative phenomenological analysis of people living with chronic fatigue syndrome. Psychol Health. 2007; 22:851-67.
CrossRef
 
Green J, Romei J, Natelson BH. Stigma and chronic fatigue syndrome. J Chronic Fatigue Syndr. 1999; 5:63-95.
CrossRef
 
Guise J, McVittie C, McKinlay A. A discourse analytic study of ME/CFS (Chronic Fatigue Syndrome) sufferers' experiences of interactions with doctors. J Health Psychol. 2010; 15:426-35.
PubMed
CrossRef
 
Jason LA, Taylor RR, Stepanek Z, Plioplys S. Attitudes regarding chronic fatigue syndrome: the importance of a name. J Health Psychol. 2001; 6:61-71.
PubMed
CrossRef
 
Brimmer DJ, Maloney E, Devlin R, Jones JF, Boneva R, Nagler C, et al. A pilot registry of unexplained fatiguing illnesses and chronic fatigue syndrome. BMC Res Notes. 2013; 6:309.
PubMed
CrossRef
 
Devasahayam A, Lawn T, Murphy M, White PD. Alternative diagnoses to chronic fatigue syndrome in referrals to a specialist service: service evaluation survey. JRSM Short Rep. 2012; 3:4.
PubMed
CrossRef
 
Lawn T, Kumar P, Knight B, Sharpe M, White PD. Psychiatric misdiagnoses in patients with chronic fatigue syndrome. JRSM Short Rep. 2010; 1:28.
PubMed
CrossRef
 
Newton JL, Mabillard H, Scott A, Hoad A, Spickett G. The Newcastle NHS Chronic Fatigue Syndrome Service: not all fatigue is the same. J R Coll Physicians Edinb. 2010; 40:304-7.
PubMed
CrossRef
 
Woodward RV, Broom DH, Legge DG. Diagnosis in chronic illness: disabling or enabling—the case of chronic fatigue syndrome. J R Soc Med. 1995; 88:325-9.
PubMed
 
Brurberg KG, Fønhus MS, Larun L, Flottorp S, Malterud K. Case definitions for chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME): a systematic review. BMJ Open. 2014; 4:e003973.
PubMed
CrossRef
 
Beck AT, Steer RA, Carbin MG. Psychometric properties of the Beck Depression Inventory: twenty-five years of evaluation. Clin Psychol Rev.. 1988; 8:77-100.
CrossRef
 
Brown M, Kaplan C, Jason L. Factor analysis of the Beck Depression Inventory-II with patients with chronic fatigue syndrome. J Health Psychol.. 2012; 17:799-808.
PubMed
CrossRef
 
Chalder T, Berelowitz G, Pawlikowska T, Watts L, Wessely S, Wright D, et al. Development of a fatigue scale. J Psychosom Res.. 1993; 37:147-53.
PubMed
CrossRef
 
Morriss RK, Wearden AJ, Mullis R. Exploring the validity of the Chalder Fatigue scale in chronic fatigue syndrome. J Psychosom Res.. 1998; 45:411-7.
PubMed
CrossRef
 
Cella M, Chalder T. Measuring fatigue in clinical and community settings. J Psychosom Res.. 2010; 69:17-22.
PubMed
CrossRef
 
Hickie I, Lloyd A, Hadzi-Pavlovic D, Parker G, Bird K, Wakefield D. Can the chronic fatigue syndrome be defined by distinct clinical features? Psychol Med.. 1995; 25:925-35.
PubMed
CrossRef
 
Hickie I, Lloyd A, Wakefield D, Parker G. The psychiatric status of patients with the chronic fatigue syndrome. Br J Psychiatry. 1990; 156:534-40.
PubMed
CrossRef
 
Broadbent DE, Cooper PF, FitzGerald P, Parkes KR. The Cognitive Failures Questionnaire (CFQ) and its correlates. Br J Clin Psychol.. 1982; 21 (Pt 1):1-16.
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Letters

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Information on ME and Post Viral Fatigue Syndrome might mislead
Posted on June 21, 2015
Ellen M Goudsmit, PhD
Retired
Conflict of Interest: None Declared
As someone who has studied myalgic encephalomyelitis (ME) and chronic fatigue syndrome (CFS) since the 1980s, I appreciate the work completed by The National Institutes of Health Pathways to Prevention Workshops on what is now known as ME/CFS. Unfortunately, some of the information in the two reviews is inaccurate, incomplete and misleading (1,2). For example, in the report on diagnostic methods, the reviewers included the London criteria for ME but gave details in the table based on a version written by a layperson, rather than the four individuals cited in their reference (3). Moreover, they did not consider the updated criteria for ME (4), although one of the authors had emailed the panel on two separate occasions during the consultation phase to alert them to their existence.

The second review (2) encourages further research on subgroups and outcomes other than fatigue and function but did not identify one of the few controlled studies which had employed such a design (5). For instance, in the Appendix, Table 1 lists the programme evaluated by Goudsmit and colleagues under ‘counseling and behavioural therapies’, and describes the treatment as ‘counseling’. It also states that patients were selected using the Oxford criteria, that the duration of follow-up was six months and that the outcomes were function and fatigue.

In fact, the trial evaluated a physician-led multi-component programme comprising medical care, information on the illness, diet and relaxation, as well as advice on activity management and some counselling (5). It was conducted in the naturalistic setting of an NHS hospital clinic, patients were diagnosed using criteria for post-viral fatigue syndrome as well as the Oxford criteria, and data were available for a number of symptoms including cognitive impairment, as well as other variables. Fatigue improved as noted in the review but the latter did not convey that 82% of the patients rated themselves as ‘better’, that 23% were well enough to be discharged at six months and that the improvements were maintained at 1 year. Given the missing details, the study’s rating as ‘poor’ is understandable.

The reviewers concluded that “more definitive studies comparing participants meeting different case definitions, including ME... are needed to fill research gaps”. It was therefore disappointing that they did not recognise the positive aspects of a study that used a different case definition and assessed a range of symptoms, not just fatigue.

1. Haney E, Smith MEB, McDonagh M, Pappas M, Daeges M, Wasson N, et al. Diagnostic methods for myalgic encephalomyelitis/chronic fatigue syndrome: A systematic review for a National Institutes of Health Pathways to Prevention Workshop. Ann Intern Med. 2015;162: 834-40. [PMID: 26075754] doi:10.7326/M15-0443

2. Smith MEB, Haney E, McDonagh M, Pappas M, Daeges M, Wasson N, et al. Treatment of myalgic encephalomyelitis/chronic fatigue syndrome: A systematic review for a National Institutes of Health Pathways to Prevention Workshop. Ann Intern Med. 2015;162:841-
50. [PMID: 26075755] doi:10.7326/M15-0114

3. Dowsett E, Goudsmit E, Macintyre A, Shepherd C. London Criteria for myalgic encephalomyelitis. In: Report from The National Task Force on Chronic Fatigue Syndrome (CFS), Post Viral Fatigue Syndrome (PVFS), Myalgic Encephalomyelitis (ME). Westcare. 1994. 96-98. Available from: http://www.actionforme.org.uk/Resources/Action%20for%20ME/Documents/get-informed/national%20task%20force.pdf

4. Goudsmit E, Shepherd C, Dancy CP, Howes S. ME: Chronic fatigue syndrome or a distinct clinical entity? Health Psychol Update. 2009;18(1):26-33. Available from:
http://shop.bps.org.uk/publications/publications-by-subject/health/health-psychology-update-vol-18-no-1-2009.html

5. Goudsmit EM, Ho-Yen DO, Dancey CP. Learning to cope with chronic illness. Efficacy of a multi-component treatment for people with chronic fatigue syndrome. Patient Educ Couns. 2009;77:231–6. [PMID: 19576714 ] doi:10.1016/j.pec.2009.05.015

Ellen M Goudsmit PhD FBPsS

Comment
Posted on July 6, 2015
James Webster, MD, MS, MACP
Feinberg School of Medicine of Northwestern University
Conflict of Interest: None Declared
​As recommended by Haney et. al. (1) the diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is best made using nine sets of "inadequately tested" clinical criteria. These are quite non-specific symptoms and there are no associated positive laboratory findings. Thus it is not surprising that most physicians have problems with the diagnosis much less with the difficult diffuse treatment approaches (2) for this entity.

​In a large, but admittedly convenience, sample of patients with the symptoms outlined (1) for ME/CFS the experience was that the overlap with the diagnosis of major depression and persistent (formerly dysphoric) depressive disorder (DSM V, 300.4) was huge. For these illnesses there are diagnostic criteria and proven effective therapies which were used to benefit a number of these latter patients. The differential diagnosis of ME/CFS and depressive disorders is difficult, but not impossible (3). The patients with the symptoms of depression and ME/CFS do indeed have real illnesses (4), but to ignore clear psychiatric possibilities and aspects, including the potential for a therapeutic trial, does them a great disservice.


1. Haney E, Smith MEB, McDonagh M, et al. Diagnostic methods for myalgic encephalomyelitis/chronic fatigue syndrome: A systematic review for a national institutes of health pathways to prevention workshop. Ann Intern Med. 2015:162:834-840.


2. Smith MEB, Haney E, McDonagh M, et al. Treatment of myalgic encephalomyelitis/chronic fatigue syndrome. A systematic review for a national institutes of health pathways to prevention workshop. Ann Intern Med. 2015;162:841-850.

3. Hawk C, Jason LA, Torres-Harding S. Int J Behav Med. 2006;13:244-51

4. Komaroff AL. Myalgic encephalomyelitis/chronic fatigue syndrome: A real illness. Ann Intern Med. 2015;162:871-872.





Author's Response
Posted on February 23, 2016
M.E. Beth Smith, DO, MCR, Marian McDonagh, PharmD
Oregon Health & Science University
Conflict of Interest: None Declared
In Response: We thank Dr. Goudsmit for her comments. She indicated that we had not identified her study but in fact it was identified and reviewed. Eligible outcomes were reported. We considered studies that recruited participants who fulfilled one of the case definitions for CFS, ME, or ME/CFS. Although her study may have considered additional criteria, it met our inclusion based on use of the Oxford criteria. Our review considered interventions in the categories of medications, complementary and alternative treatments, counseling and behavioral therapies, and exercise. Her study was considered in the category of counseling and behavioral therapies. The types of interventions in this category were broad and varied. We elected to categorize these as cognitive behavioral therapy (CBT), counseling including learning coping and self-sufficiency strategies, pragmatic rehabilitation, and supportive listening. The intervention in her study was multifactorial and included elements of CBT, education, and medical care. The lack of formalized CBT did not allow us to compare it to other interventions in that category, and the psycho-educative approach seemed more aligned with other studies in the counseling category.

When calling for additional outcomes in future research, we are referring to outcomes universal to the patient population such as post-exertional malaise and harms of interventions rather than individual symptoms such as pain, anxiety, depression. Standardized criteria are used to evaluate each study’s risk of bias or quality as outlined in the appendix. The design of Dr. Goudsmit’s study (pre-post) placed it at high risk of bias, which was reflected in its quality rating.

A matter of confusion and disappointment
Posted on February 25, 2016
EM Goudsmit PHD FBPsS
Formerly Visiting Research fellow UEL, UK.
Conflict of Interest: None Declared
I wish to thank Dr Smith and her colleagues for responding to my letter written in June 2015. Unfortunately, the delay seems to have confused the writers and consequently, they did not deal with the issues I raised.

My old eyes may be deceiving me but my copy of the response seems to suggest that I had complained that my study had not been included. From my original comment: " ... in the Appendix, Table 1 lists the programme evaluated by Goudsmit and colleagues under ‘counseling and behavioural therapies’, and describes the treatment as ‘counseling’. It also states that patients were selected using the Oxford criteria, that the duration of follow-up was six months and that the outcomes were function and fatigue."

What I focused on were the factual errors relating to the ME research criteria (London criteria of 1993 and 2009). The team reviewed the criteria published in the Westcare report, which, despite the references, were not authored by me or any other scientist she cited. NB If you click on the pdf for those criteria, you will not find any authors listed and it's a mystery why I was linked to what I and others consider was nonsense. The latest ME criteria (2009) which the team overlooked, are not.

Re quality. Pre-2000, many studies used alternative criteria for post-viral fatigue syndrome, and the trial I described was one of these. I would have given the study a brownie point for using sound criteria to select a more homogenous sample. And I would also have acknowledged the external validity because it was conducted in a hospital setting, as opposed to a well resourced research clinic.

As for the 'pre-post' comment, I'd note that all evaluations of interventions I'm aware of are 'pre-post', so I am mystified at the comment that "The design of Dr. Goudsmit’s study (pre-post) placed it at high risk of bias, which was reflected in its quality rating." The point missed is that a significant number in the Goudsmit et al trial were well enough to be discharged at six months (i.e. after one and a half hours clinic attendance). Isn't that what physicians want to know? Good outcomes in the real world?

I see many refer to ME/CFS but they do not know that the ME stands for. And how it differs from CFS. 'Malaise' is a vague lay term for something subjective and difficult to measure. It's why it has been criticised and is being dropped by specialists (in favour of PENE etc, as described in the article). The 2009 ME criteria provides an objective measure to assess criterion 1, which takes some of the guesswork out of diagnosis. I find it strange that none of the authors were interested.

Finally, to focus on fatigue and post-exertional malaise is a little like a cancer study which assesses the primary tumour and tiredness and ignores the secondaries and nausea. There's more to ME/CFS than fatigue and malaise. I am so disappointed, both with the original paper and the response. Good science depends on precision to detail. It's the least that we, and patients, deserve.
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