Abstracts

Rationale: PatientsLikeMe (PLM) is a free online platform allowing patients with life-changing conditions to share their disease characteristics and outcomes and learn how to improve their care by peer-peer interactions. The wealth of data collected may also allow research activities for a better understanding of the disease burden, treatment pathways and their impact on patients lives. The Epilepsy community was launched in the US in January 2010, and a first data export occurred in March. The objective of this analysis is to describe the main characteristics of this preliminary sample and to compare them with Pharmetrics - a claims database representative of the US commercially insured epileptic patient population. Methods: The PLM epilepsy community allows subjects with epilepsy to record their own characteristics (eg socio-demographics, diagnostic and medical history) and monitor their treatment-related data and outcomes. A survey participation system was built to facilitate longitudinal entry of widely used Patient Reported Outcomes instruments (QOLIE-31, HADS, EQ-5D) alongside treatments, symptoms, and weekly seizure frequency and severity. Pharmetrics has been used to allow comparison with the PLM sample. Patients from the Pharmetrics database who had been diagnosed (clinician reported) with epilepsy and continuously enrolled in Nov-Dec 2008 were selected (N=32 983). Results: As of March 2010, 1034 users had registered to the PLM Epilepsy community and 761 (73.6%) reported being diagnosed with epilepsy which constitutes the PLM sample selected for this analysis (69.5% females; mean age 36 years; mean duration since diagnosis 17.2 years; Table 1). When comparing PLM with Pharmetrics, mean age appeared similar (mean age: 36 years in both samples), although age distribution differed with a higher proportion of subjects aged 20-50 years for PLM (limited number of children). The proportion of females in the PLM sample was higher (70% in the PLM sample vs 54% in Pharmetrics). The distribution of seizure types showed a slightly larger proportion of patients with Unknown seizure type in the patient-reported PLM source. Treated patients in PLM were more often on polytherapy compared with Pharmetrics. When comparing antiepileptic drug (AED) use, newer AEDs tended to be over-represented in PLM. Conclusions: Analysis of this preliminary PLM sample shows that compared with Pharmetrics, the PLM Epilepsy community tends to provide an over-representation of i) females; ii) 20-50 years old (reflecting the general characteristics of online users); iii) subjects on polytherapy; and iv) on newer AEDs. These trends illustrate potential self-referral bias. The number of users is expected to increase substantially in the coming months. The representativeness of the PLM Epilepsy population will be re-evaluated as sample size increases. The large number of patients expected and wealth of data collected through this real-life setting will allow further analysis of this epilepsy population segment. UCB-sponsored