The Facilitation of Clinical and Therapeutic Discoveries in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Related Diseases : Protocol for the You + ME Registry Research Platform
©Allison Ramiller, Kathleen Mudie, Elle Seibert, Sadie Whittaker. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 10.08.2022..
BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) 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, have transformed the understanding of many complex illnesses, such as 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: This study aims 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: We 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: As of September 30, 2021, the You + ME Registry had over 4200 geographically diverse participants (3033/4339, 69.9%, people with ME/CFS; 833/4339, 19.2%, post-COVID-19 people; and 473/4339, 10.9%, 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 the registry to a friend. Analyses of collected data are currently underway, and preliminary findings are expected in the near future.
CONCLUSIONS: The You + ME Registry is an invaluable resource because it integrates with a symptom-tracking app, as well as a biorepository, to provide a robust and rich data set that is available to qualified researchers. Accordingly, it facilitates collaboration that may ultimately uncover causes and help accelerate the development of therapies.
TRIAL REGISTRATION: ClinicalTrials.gov NCT04806620; https://clinicaltrials.gov/ct2/show/NCT04806620.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/36798.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:11 |
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| Enthalten in: |
JMIR research protocols - 11(2022), 8 vom: 10. Aug., Seite e36798 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Ramiller, Allison [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Revised 19.10.2022 published: Electronic ClinicalTrials.gov: NCT04806620 Citation Status PubMed-not-MEDLINE |
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| doi: |
10.2196/36798 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM343371367 |
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| 245 | 1 | 4 | |a The Facilitation of Clinical and Therapeutic Discoveries in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Related Diseases |b Protocol for the You + ME Registry Research Platform |
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| 500 | |a ClinicalTrials.gov: NCT04806620 | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a ©Allison Ramiller, Kathleen Mudie, Elle Seibert, Sadie Whittaker. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 10.08.2022. | ||
| 520 | |a BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) 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, have transformed the understanding of many complex illnesses, such as 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 | ||
| 520 | |a OBJECTIVE: This study aims 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 | ||
| 520 | |a METHODS: We 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 | ||
| 520 | |a RESULTS: As of September 30, 2021, the You + ME Registry had over 4200 geographically diverse participants (3033/4339, 69.9%, people with ME/CFS; 833/4339, 19.2%, post-COVID-19 people; and 473/4339, 10.9%, 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 the registry to a friend. Analyses of collected data are currently underway, and preliminary findings are expected in the near future | ||
| 520 | |a CONCLUSIONS: The You + ME Registry is an invaluable resource because it integrates with a symptom-tracking app, as well as a biorepository, to provide a robust and rich data set that is available to qualified researchers. Accordingly, it facilitates collaboration that may ultimately uncover causes and help accelerate the development of therapies | ||
| 520 | |a TRIAL REGISTRATION: ClinicalTrials.gov NCT04806620; https://clinicaltrials.gov/ct2/show/NCT04806620 | ||
| 520 | |a INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/36798 | ||
| 650 | 4 | |a Journal Article | |
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| 650 | 4 | |a chronic fatigue syndrome | |
| 650 | 4 | |a data acquisition source | |
| 650 | 4 | |a digital health | |
| 650 | 4 | |a health application | |
| 650 | 4 | |a long COVID | |
| 650 | 4 | |a longitudinal cohort study | |
| 650 | 4 | |a longitudinal health data | |
| 650 | 4 | |a mobile health | |
| 650 | 4 | |a myalgic encephalomyelitis/chronic fatigue syndrome | |
| 650 | 4 | |a patient powered | |
| 650 | 4 | |a postinfectious | |
| 650 | 4 | |a symptom-tracking app | |
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| 700 | 1 | |a Seibert, Elle |e verfasserin |4 aut | |
| 700 | 1 | |a Whittaker, Sadie |e verfasserin |4 aut | |
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