Abstract:
Background: ME/CFS (Myalgic Encephalomyelitis / Chronic Fatigue Syndrome) is a chronic, complex, heterogeneous disease that affects millions and lacks both diagnostics and treatments. Big data, or the collection of vast quantities of data that can be mined for information, has transformed the understanding of many complex illnesses like cancer and multiple sclerosis, by dissecting heterogeneity, identifying subtypes, and enabling the development of personalized treatments. It is possible that big data can reveal the same for ME/CFS.
Objective: To describe the protocol for the You + ME Registry, present preliminary results related to participant enrollment and satisfaction, and discuss the limitations of the registry as well as next steps.
Methods: Solve M.E. developed and launched the You + ME Registry to collect longitudinal health data from people with ME/CFS, people with Long COVID (LC) and control volunteers using rigorous protocols designed to harmonize with other groups collecting data from similar groups of people.
Results: The Registry now has over 4,200 geographically-diverse participants (3,033 people with ME/CFS, 833 post-COVID, and 473 control volunteers) with an average of 72 new people registered every week. It has qualified as “great” using a Net Promotor Score, indicating registrants are likely to recommend to a friend. Analyses of collected data are currently underway and preliminary findings are expected in the near future.
Conclusions: The Registry is an invaluable resource because it integrates with a symptom tracking app, as well as a biorepository, to provide a robust and rich dataset that is available to qualified researchers. Accordingly, it facilitates collaboration that may ultimately uncover causes and help accelerate the development of therapies.
International registered report: DERR1-10.2196/36798.
Source: Ramiller A, Mudie K, Seibert E, Whittaker S. The Facilitation of Clinical and Therapeutic Discoveries in Myalgic Encephalomyelitis/ Chronic Fatigue Syndrome and Related Diseases: A Protocol for the You + ME Registry Research Platform. JMIR Res Protoc. 2022 Jun 5. doi: 10.2196/36798. Epub ahead of print. PMID: 35816681. https://pubmed.ncbi.nlm.nih.gov/35816681/ https://preprints.jmir.org/preprint/36798/accepted (Full study available as PDF file)