Valdez, Ashley R, Hancock, Elizabeth E, Adebayo, Seyi et al. · Frontiers in pediatrics · 2018 · DOI
Researchers used insurance billing records and computer analysis to estimate how many Americans have ME/CFS. They found that between 1.7 and 3.4 million people in the U.S. may have been diagnosed with ME/CFS, making it more common than many people realize. The study also showed that ME/CFS costs patients far more in medical expenses than other serious diseases like lupus or multiple sclerosis.
This study provides quantitative evidence that ME/CFS is not rare but a relatively common condition affecting millions of Americans, challenging previous underestimates of prevalence. The finding that ME/CFS generates substantially higher healthcare costs than similarly serious neurological conditions highlights the significant disease burden and supports the need for greater clinical recognition and research investment.
This study does not establish what causes ME/CFS or prove that the conditions diagnosed as ME and CFS are biologically identical—in fact, it suggests CFS may represent a more heterogeneous group. It also cannot determine how many undiagnosed ME/CFS patients exist in the general population, as it only analyzes people who received a diagnosis in insurance records.
About the PEM badge: “PEM required” means post-exertional malaise was an explicit required diagnostic criterion for participant inclusion in this study — not that PEM was studied, observed, or discussed. Studies using criteria that do not require PEM (e.g. Fukuda, Oxford) are tagged “PEM not required”. How the atlas works →
The first block is for the primary paper and is the citation you should use in research work. The atlas-snapshot line only applies if you are specifically referring to this atlas’s reading of the paper on the date shown.
Primary citation
Valdez, Ashley R, Hancock, Elizabeth E, Adebayo, Seyi, Kiernicki, David J, Proskauer, Daniel, Attewell, John R, et al. (2018). Estimating Prevalence, Demographics, and Costs of ME/CFS Using Large Scale Medical Claims Data and Machine Learning.. Frontiers in pediatrics. https://doi.org/10.3389/fped.2018.00412
BibTeX
@article{mecfsatlas-valdez-2018-estimating-prevalence,
author = {Valdez, Ashley R and Hancock, Elizabeth E and Adebayo, Seyi and Kiernicki, David J and Proskauer, Daniel and Attewell, John R and Bateman, Lucinda and DeMaria, Alfred and Lapp, Charles W and Rowe, Peter C and Proskauer, Charmian},
title = {Estimating Prevalence, Demographics, and Costs of ME/CFS Using Large Scale Medical Claims Data and Machine Learning.},
journal = {Frontiers in pediatrics},
year = {2018},
doi = {10.3389/fped.2018.00412},
note = {PubMed: 30671425},
url = {https://www.mecfsatlas.com/evidence/valdez-2018-estimating-prevalence},
}Atlas snapshot reference
ME/CFS Atlas. Generator v1 / Scanner v1.4 / policy v0.1. Accessed 2026-05-30. https://www.mecfsatlas.com/evidence/valdez-2018-estimating-prevalence
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