Case Reports usually involve just the one patient. When patients get together and join a social network their shared experiences could be used to evaluate research questions that would otherwise go unexplored or take time to answer. This is exactly what the website PatientsLikeMe claim to have done with the use of Lithium Carbonate in the treatment of Amyotrophic Lateral Sclerosis – a type of motorneurone disease – and they have published the work in Nature Biotechnology (1).
“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.”
The sample of patients from a particular social media website will, by definition, be self-selected. Perhaps such groups would be better at generating qualitative rather than quantitative information. However, this approach could be used to evaluate off-label uses of drugs.
It is an interesting technique but care should be taken in interpreting such observations and it would be good to see other examples of this type of study and more analysis of the case-control selection algorithm. Small effects may be missed without careful elimination of bias.