Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Feb 10;21(1):112.
doi: 10.1186/s12967-023-03946-6.

Symptom-based clusters in people with ME/CFS: an illustration of clinical variety in a cross-sectional cohort

Anouk W Vaes  1 , Maarten Van Herck  2   3   4 , Qichen Deng  2   3 , Jeannet M Delbressine  2   3 , Leonard A Jason  5 , Martijn A Spruit  2   3
Affiliations

Symptom-based clusters in people with ME/CFS: an illustration of clinical variety in a cross-sectional cohort

Anouk W Vaes et al. J Transl Med. .

Abstract

Background: Myalgic encephalomyelitis (ME)/chronic fatigue syndrome (CFS) is a complex, heterogenous disease. It has been suggested that subgroups of people with ME/CFS exist, displaying a specific cluster of symptoms. Investigating symptom-based clusters may provide a better understanding of ME/CFS. Therefore, this study aimed to identify clusters in people with ME/CFS based on the frequency and severity of symptoms.

Methods: Members of the Dutch ME/CFS Foundation completed an online version of the DePaul Symptom Questionnaire version 2. Self-organizing maps (SOM) were used to generate symptom-based clusters using severity and frequency scores of the 79 measured symptoms. An extra dataset (n = 252) was used to assess the reproducibility of the symptom-based clusters.

Results: Data of 337 participants were analyzed (82% female; median (IQR) age: 55 (44-63) years). 45 clusters were identified, of which 13 clusters included ≥ 10 patients. Fatigue and PEM were reported across all of the symptom-based clusters, but the clusters were defined by a distinct pattern of symptom severity and frequency, as well as differences in clinical characteristics. 11% of the patients could not be classified into one of the 13 largest clusters. Applying the trained SOM to validation sample, resulted in a similar symptom pattern compared the Dutch dataset.

Conclusion: This study demonstrated that in ME/CFS there are subgroups of patients displaying a similar pattern of symptoms. These symptom-based clusters were confirmed in an independent ME/CFS sample. Classification of ME/CFS patients according to severity and symptom patterns might be useful to develop tailored treatment options.

Keywords: Chronic fatigue syndrome; Clusters; ME/CFS; Myalgic encephalomyelitis; Symptoms.

PubMed Disclaimer

Conflict of interest statement

MAS reports grants from Netherlands Lung Foundation, Stichting Astma Bestrijding, AstraZeneca, TEVA, Chiesi and Boehringer Ingelheim; consultancy fees from AstraZeneca and Boehringer Ingelheim for advisory boards, all outside the submitted work. No other disclosures were reported.

Figures

Fig. 1
Fig. 1
Proportional Venn diagrams and UpSet plots showing the overlap of different ME/CFS case definitions in the Dutch (a) and US (b) ME/CFS population. The different case definitions are displayed as horizontal bars on the lower left corner of the UpSet plot. Paired intersections are displayed as black dots; gray dots indicate the case definitions that are not part of the intersection. Black lines connecting 2 or more black dots indicate which case definitions form the intersections. The heights of the vertical bars indicate the intersection size (number of number of patients with indicated case definitions)
Fig. 2
Fig. 2
Symptom-based clusters using self-organizing maps. All clusters of patients are displayed in the direction of left to right and bottom to top. Each hexagon represents a cluster, and the number within a hexagon shows the number of patients in the cluster. The x-axis and y-axis indicate the number of clusters, starting from 0. In particular, coordinate (0,0) corresponds to Cluster 1, coordinate (1,0) corresponds to Cluster 2, etc. The 13 clusters including at least 10 patients are shown in purple. a Symptom-based clusters in Dutch ME/CFS population. b Connection between symptom-based clusters. The blue hexagons represent the clusters. The colors in the regions containing the red lines indicate the distances between clusters: darker colors represent larger distances (less similarity between the two clusters), lighter colors represent smaller distances (more similarity between the two clusters). c Symptom-based clusters in US population
See this image and copyright information in PMC

References

    1. https://blogs.cdc.gov/global/2020/05/12/cdc-team-takes-me-cfs-around-the.... Accessed 24 Oct 2022.
    1. Lim EJ, Son CG. Review of case definitions for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) J Transl Med. 2020;18(1):289. doi: 10.1186/s12967-020-02455-0. - DOI - PMC - PubMed
    1. Conroy K, Bhatia S, Islam M, Jason LA. Homebound versus bedridden status among those with myalgic encephalomyelitis/chronic fatigue syndrome. Healthcare. 2021;9(2):106. doi: 10.3390/healthcare9020106. - DOI - PMC - PubMed
    1. Pemberton S, Cox DL. Experiences of daily activity in chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) and their implications for rehabilitation programmes. Disabil Rehabil. 2014;36(21):1790–1797. doi: 10.3109/09638288.2013.874503. - DOI - PubMed
    1. Falk Hvidberg M, Brinth LS, Olesen AV, Petersen KD, Ehlers L. The health-related quality of life for patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) PLoS ONE. 2015;10(7):e0132421. doi: 10.1371/journal.pone.0132421. - DOI - PMC - PubMed