title: Adherence to the immunomodulatory drugs for multiple sclerosis: contrasting factors affect stopping drug and missing doses.
abstract: BACKGROUND
  Long-term immunomodulatory drug (IMD) treatment is now common in multiple sclerosis (MS). However, predictors of adherence are not well understood; past studies lacked lifestyle factors such as alcohol use and predictors of missed doses have not been evaluated. We examined both levels of non-adherence-stopping IMD and missing doses.
  
  
  METHODS
  This longitudinal prospective study followed a population-based cohort (n = 199) of definite MS patients in Southern Tasmania (January 2002 to April 2005, source population 226 559) every 6 months. Baseline factors (demographic, clinical, psychological and cognitive) affecting adherence were examined by logistic regression and a longitudinal analysis (generalized estimating equation (GEE)).
  
  
  RESULTS
  Of the 97 patients taking an IMD (mean follow-up = 2.4 years), 73% (71/97) missed doses, with 1 in 10 missing > 10 doses in any 6-month period. Missed doses were positively associated with alcohol amount consumed per session (p = 0.008). A history of missed doses predicted future missed doses (p < 0.0005). Over one-quarter (27/97) stopped their current IMD, which was associated with lower education levels (p = 0.032) and previous relapses (p = 0.05). No cognitive or psychological test predicted adherence.
  
  
  CONCLUSIONS
  There were few strong predictors of missed doses, although people with MS consuming more alcoholic drinks per session are at a higher risk of missing doses. Divergent factors influenced the two levels of non-adherence indicating the need for a multifaceted approach to improving IMD adherence. In addition, missed doses should be assessed and incorporated into clinical trial design and clinical practice as poor adherers could impact on clinical outcomes.
authors.affiliation: Faculty of Medicine (Neurology), University of British Columbia, Canada. tremlett@interchange.ubc.ca
authors.forename: Helen
authors.initials: H
authors.lastname: Tremlett
authors.forename: Ingrid
authors.initials: I
authors.lastname: Van der Mei
authors.forename: Fotini
authors.initials: F
authors.lastname: Pittas
authors.forename: Leigh
authors.initials: L
authors.lastname: Blizzard
authors.forename: Glenys
authors.initials: G
authors.lastname: Paley
authors.forename: Terence
authors.initials: T
authors.lastname: Dwyer
authors.forename: Bruce
authors.initials: B
authors.lastname: Taylor
authors.forename: Anne-Louise
authors.initials: AL
authors.lastname: Ponsonby
mesh_terms: D000328:Adult; D000368:Aged; D000428:Alcohol Drinking / Q000009:adverse effects* / Q000453:epidemiology; D015331:Cohort Studies; D004522:Educational Status; D005260:Female; D005500:Follow-Up Studies; D005544:Forecasting; D006801:Humans; D007155:Immunologic Factors / Q000627:therapeutic use*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000188:drug therapy*; D010349:Patient Compliance; D011446:Prospective Studies; D012008:Recurrence; D011795:Surveys and Questionnaires; D013648:Tasmania / Q000453:epidemiology
chemical_list: D007155:Immunologic Factors