Accelerated clinical discovery using self-reported patient data collected online and a patient-matching algorithm
Abstract
Patients with serious diseases may experiment with drugs that have not received regulatory approval. Online patient communities structured around quantitative outcome data have the potential to provide an observational environment to monitor such drug usage and its consequences. Here we describe an analysis of data reported on the website PatientsLikeMe by patients with amyotrophic lateral sclerosis (ALS) who experimented with lithium carbonate treatment. To reduce potential bias owing to lack of randomization, we developed an algorithm to match 149 treated patients to multiple controls (447 total) based on the progression of their disease course. At 12 months after treatment, we found no effect of lithium on disease progression. Although observational studies using unblinded data are not a substitute for double-blind randomized control trials, this study reached the same conclusion as subsequent randomized trials, suggesting that data reported by patients over the internet may be useful for accelerating clinical discovery and evaluating the effectiveness of drugs already in use.
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Researchers using observational data from a patient platform found that lithium therapy had no impact on amyotrophic lateral sclerosis disease progression, a result later confirmed by randomized trials.
“For example, researchers using observational data housed on such a platform found that lithium therapy had no impact on amyotrophic lateral sclerosis disease progression, later confirmed by subsequent randomized trials.13”
From Social Media and Clinical Care: Ethical, Professional, and Social Implications (2013) · cites this paper as [13]
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- Authors
- Wicks, P., Vaughan, T. E., Massagli, M. P., & Heywood, J.
- Affiliations
- PatientsLikeMe (United States) (US)
- Corresponding author
- Wicks, Paul
- Venue
- Nature Biotechnology
- Published
- 2011-04-24
- Volume
- 29
- Issue
- 5
- Pages
- 411-414
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- OpenAlex
- W2163560143
- Cited by
- 362
- References
- 28
- Citations by year
- 2026: 4 · 2025: 12 · 2024: 6 · 2023: 13 · 2022: 17 · 2021: 17 · 2020: 13 · 2019: 21 · 2018: 32 · 2017: 23 · 2016: 25 · 2015: 46 · 2014: 51 · 2013: 37 · 2012: 33
- FWCI
- 26.75
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Neurology › Amyotrophic Lateral Sclerosis Research
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Toxicology › Pharmacovigilance and Adverse Drug Reactions
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- amyotrophic lateral sclerosis, lithium carbonate, off-label drug use, patient-reported outcomes, online patient communities, PatientsLikeMe, disease progression, drug efficacy
- MeSH terms
- Algorithms, Amyotrophic Lateral Sclerosis, Female, Humans, Male, Middle Aged, Risk Factors, Case-Control Studies, Lithium Carbonate, Treatment Outcome, Sex Distribution, Riluzole, Internet, Self Report
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