title: Evaluation of an online platform for multiple sclerosis research: patient description, validation of severity scale, and exploration of BMI effects on disease course.
abstract: OBJECTIVE
  To assess the potential of an online platform, PatientsLikeMe.com (PLM), for research in multiple sclerosis (MS). An investigation of the role of body mass index (BMI) on MS disease course was conducted to illustrate the utility of the platform.
  
  
  METHODS
  First, we compared the demographic characteristics of subjects from PLM and from a regional MS center. Second, we validated PLM's patient-reported outcome measure (MS Rating Scale, MSRS) against standard physician-rated tools. Finally, we analyzed the relation of BMI to the MSRS measure.
  
  
  RESULTS
  Compared with 4,039 MS Center patients, the 10,255 PLM members were younger, more educated, and less often male and white. Disease course was more often relapsing remitting, with younger symptom onset and shorter disease duration. Differences were significant because of large sample sizes but small in absolute terms. MSRS scores for 121 MS Center patients revealed acceptable agreement between patient-derived and physician-derived composite scores (weighted kappa = 0.46). The Walking domain showed the highest weighted kappa (0.73) and correlation (rs = 0.86) between patient and physician scores. Additionally, there were good correlations between the patient-reported MSRS composite and walking scores and physician-derived measures: Expanded Disability Status Scale (composite rs = 0.61, walking rs = 0.74), Timed 25 Foot Walk (composite rs = 0.70, walking rs = 0.69), and Ambulation Index (composite rs = 0.81, walking rs = 0.84). Finally, using PLM data, we found a modest correlation between BMI and cross-sectional MSRS (rho = 0.17) and no association between BMI and disease course.
  
  
  CONCLUSIONS
  The PLM population is comparable to a clinic population, and its patient-reported MSRS is correlated with existing clinical instruments. Thus, this online platform may provide a venue for MS investigations with unique strengths (frequent data collection, large sample sizes). To illustrate its applicability, we assessed the role of BMI in MS disease course but did not find a clinically meaningful role for BMI in this setting.
authors.affiliation: Program in Translational NeuroPsychiatric Genomics, Department of Neurology, Institute for the Neurosciences, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
authors.forename: Riley
authors.initials: R
authors.lastname: Bove
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Secor
authors.forename: Brian C
authors.initials: BC
authors.lastname: Healy
authors.forename: Alexander
authors.initials: A
authors.lastname: Musallam
authors.forename: Timothy
authors.initials: T
authors.lastname: Vaughan
authors.forename: Bonnie I
authors.initials: BI
authors.lastname: Glanz
authors.forename: Emily
authors.initials: E
authors.lastname: Greeke
authors.forename: Howard L
authors.initials: HL
authors.lastname: Weiner
authors.forename: Tanuja
authors.initials: T
authors.lastname: Chitnis
authors.forename: Paul
authors.initials: P
authors.lastname: Wicks
authors.forename: Philip L
authors.initials: PL
authors.lastname: De Jager
mesh_terms: D015992:Body Mass Index; D003710:Demography; D015340:Epidemiologic Research Design; D006801:Humans; D020407:Internet; D009103:Multiple Sclerosis / Q000503:physiopathology*; D012720:Severity of Illness Index; D012984:Software; D016138:Walking / Q000502:physiology