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

Abstract

Background: One of the goals of the Multi-site Clinical Assessment of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (MCAM) study was to evaluate whether clinicians experienced in diagnosing and caring for patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) recognized the same clinical entity. Methods: We enrolled participants from seven specialty clinics in the United States. We used baseline data (n = 465) on standardized questions measuring general clinical characteristics, functional impairment, post-exertional malaise, fatigue, sleep, neurocognitive/autonomic symptoms, pain, and other symptoms to evaluate whether patient characteristics differed by clinic. Results: We found few statistically significant and no clinically significant differences between clinics in their patients' standardized measures of ME/CFS symptoms and function. Strikingly, patients in each clinic sample and overall showed a wide distribution in all scores and measures. Conclusions: Illness heterogeneity may be an inherent feature of ME/CFS. Presenting research data in scatter plots or histograms will help clarify the challenge. 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.

Keywords: common data elements (CDEs); heterogeneity; multi-site study; myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS); patient characteristics; site difference.

Figure 1

Distribution of age at enrollment by site (A through G) and overall mean. The boxplots display the five-number summary: minimum, first quartile (Q1), median, third quartile (Q3), and maximum. The central rectangle spans from the first quartile to the third quartile (the interquartile range), a green segment inside the rectangle shows the median, the red diamond shows the mean, and the vertical lines (sometimes referred to as whiskers) are extended to the extrema of the distribution in the data set.

Figure 2

Distribution of age at diagnosis by site (A through G). The boxplots display the five-number summary: minimum, first quartile (Q1), median, third quartile (Q3), and maximum. The central rectangle spans from the first quartile to the third quartile (the interquartile range), a green segment inside the rectangle shows the median, the red diamond shows the mean, and the vertical lines (sometimes referred to as whiskers) are extended to the extrema of the distribution in the data set.

Figure 3

Agreement in classification by case definition algorithm. Venn diagram showing the overlap in classification by case definition algorithm. The number that did not fulfil any of the algorithms is shown in the background. Note: Data exclude 16 participants with insufficient information to determine all classifications.

Figure 4

Histograms of CDC Inventory Scores by clinic. Frequency of CDC Symptom Inventory scores (frequency X severity) is shown by score groups 0 (not present), 1–4, 5–8, 9–12, and 13–16 (highest scores) for each clinic (A–G, shown by colors noted at the bottom of the figure).

Figure 4

Histograms of CDC Inventory Scores by clinic. Frequency of CDC Symptom Inventory scores (frequency X severity) is shown by score groups 0 (not present), 1–4, 5–8, 9–12, and 13–16 (highest scores) for each clinic (A–G, shown by colors noted at the bottom of the figure).