Mining online social network data for biomedical research: A comparison of clinicians' and patients' perceptions about amyotrophic lateral sclerosis treatments

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Background: While only one drug is known to slow the progress of amyotrophic lateral sclerosis (ALS), numerous drugs can be used to treat its symptoms. However, very few randomized controlled trials have assessed the efficacy, safety, and side effects of these drugs. Due to this lack of randomized controlled trials, consensus among clinicians on how to treat the wide range of ALS symptoms and the efficacy of these treatments is low. Given the lack of clinical trials data, the wide range of reported symptoms, and the low consensus among clinicians on how to treat those symptoms, data on the prevalence and efficacy of treatments from a patient's perspective could help advance the understanding of the symptomatic treatment of ALS. Objective: To compare clinicians' and patients' perspectives on the symptomatic treatment of ALS by comparing data from a traditional survey study of clinicians with data from a patient social network. Methods: We used a survey of clinicians' perceptions by Forshew and Bromberg as our primary data source and adjusted the data from PatientsLikeMe to allow for comparisons. We first extracted the 14 symptoms and associated top four treatments listed by Forshew and Bromberg. We then searched the PatientsLikeMe database for the same symptom-treatment pairs. The PatientsLikeMe data are structured and thus no preprocessing of the data was required. Results: After we eliminated pairs with a small sample, 15 symptom-treatment pairs remained. All treatments identified as useful were prescription drugs. We found similarities and discrepancies between clinicians'and patients'perceptions of treatment prevalence and efficacy. In 7 of the 15 pairs, the differences between the two groups were above 10%. In 3 pairs the differences were above 20%. Lorazepam to treat anxiety and quinine to treat muscle cramps were among the symptom-treatment pairs with high concordance between clinicians' and patients' perceptions. Conversely, amitriptyline to treat labile emotional effect and oxybutynin to treat urinary urgency displayed low agreement between clinicians and patients. Conclusions: Assessing and comparing the efficacy of the symptomatic treatment of a complex and rare disease such as ALS is not easy and needs to take both clinicians' and patients' perspectives into consideration. Drawing a reliable profile of treatment efficacy requires taking into consideration many interacting aspects (eg, disease stage and severity of symptoms) that were not covered in the present study. Nevertheless, pilot studies such as this one can pave the way for more robust studies by helping researchers anticipate and compensate for limitations in their data sources and study design. © Carlos Nakamura, Mark Bromberg, Shivani Bhargava, Paul Wicks, Qing Zeng-Treitler.




Nakamura, C., Bromberg, M., Bhargava, S., Wicks, P., & Zeng-Treitler, Q. (2012). Mining online social network data for biomedical research: A comparison of clinicians’ and patients’ perceptions about amyotrophic lateral sclerosis treatments. In Journal of Medical Internet Research (Vol. 14).

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