Accepted for/Published in: JMIR Research Protocols
Date Submitted: Jan 26, 2022
Open Peer Review Period: Jan 26, 2022 - Mar 23, 2022
Date Accepted: Jun 5, 2022
Date Submitted to PubMed: Jul 11, 2022
(closed for review but you can still tweet)
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
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 [1,2] and multiple sclerosis [3,4], 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 make ME/CFS and other post-infection diseases widely understood, diagnosable, and treatable.
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.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.