Accelerated clinical discovery using self-reported patient data collected online and a patient-matching algorithm

• Published in: Nature biotechnology Vol. 29; no. 5; pp. 411 - 414
• Main Authors: Wicks, Paul, Vaughan, Timothy E, Massagli, Michael P, Heywood, James
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.05.2011; Nature Publishing Group
• Subjects: 631/114/2401; 631/378/1689/1285; 692/700/565/1436; Agriculture; Algorithms; Amyotrophic lateral sclerosis; Amyotrophic Lateral Sclerosis - drug therapy; analysis; Bioinformatics; Biological and medical sciences; Biomedical and Life Sciences; Biomedical Engineering/Biotechnology; Biomedicine; Biotechnology; Care and treatment; Case-Control Studies; Clinical trials; Control algorithms; Drug therapy; Female; Fundamental and applied biological sciences. Psychology; General aspects; Health aspects; Humans; Internet; Life Sciences; Lithium; Lithium carbonate; Lithium Carbonate - blood; Lithium Carbonate - therapeutic use; Male; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Middle Aged; Observational studies; Online health care information services; Riluzole - administration & dosage; Risk Factors; Self Report; Sex Distribution; Treatment Outcome; United States; Drug; Data analysis; On line; Treatment; Efficiency; Patient; Amyotrophic lateral sclerosis; Lithium carbonate; Web site; Algorithm; Computational biology
• ISSN: 1087-0156; 1546-1696; 1546-1696
• DOI: 10.1038/nbt.1837

The experiences of patients who try drugs that aren't approved for their disease have the potential to be mined for insights into drug efficacy. Wicks et al . rapidly monitored the efficacy of lithium treatment for 149 patients with amyotrophic lateral sclerosis using an online data collection tool and a patient-matching algorithm. 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.