title: Psychiatric diagnoses, medication and risk for disability pension in multiple sclerosis patients; a population-based register study.
abstract: BACKGROUND
  Psychiatric comorbidity is common among multiple sclerosis (MS) patients. The majority of MS patients of working ages are on disability pension. The aims of this study were to chart the prevalences of psychiatric diagnoses and medications among MS patients of working ages, and to investigate their association with the risk for future disability pension.
  
  
  METHODS
  This nationwide, population-based prospective cohort study includes 10,750 MS patients and 5,553,141 non-MS individuals who in 2005 were aged 17-64 years. Psychiatric diagnoses and medications were identified using nationwide registers. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated adjusting for socio-demographics. Furthermore, a survival analysis with five-year follow-up was performed among the 4,571 MS patients not on disability pension in 2005, with psychiatric diagnoses and medication as risk factors, and disability pension as the outcome.
  
  
  RESULTS
  Among MS patients, 35% had been prescribed psychiatric medication compared to 10% of non-MS individuals, adjusted OR 3.72 (95% CI 3.57 to 3.88). Ten percent of MS patients had received a psychiatric diagnosis, compared to 5.7% of non-MS individuals, OR 1.82 (95% CI 1.71 to 1.94). Serotonin reuptake inhibitors (SSRIs), were the most commonly prescribed drugs (17%) among MS patients, while depression (4.8%) was the most common psychiatric diagnosis. In the survival analysis, MS patients with any psychiatric diagnosis had a hazard ratio (HR) of 1.83 (95% CI 1.53 to 2.18) for disability pension compared to other MS patients. MS patients with any psychiatric drug prescription had a HR for disability pension of 2.09 (95% CI 1.84 to 2.33).
  
  
  CONCLUSIONS
  Psychiatric diagnoses and medications are common among MS patients and adversely affect risk for disability pension. This highlights the importance of correct diagnosis and management of psychiatric comorbidity, in a clinical as well as in a societal perspective.
authors.affiliation: Division of Psychiatry, Department of Clinical Neuroscience, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
authors.forename: Philip
authors.initials: P
authors.lastname: Brenner
authors.affiliation: Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Kristina
authors.initials: K
authors.lastname: Alexanderson
authors.affiliation: Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Charlotte
authors.initials: C
authors.lastname: Björkenstam
authors.affiliation: Division of Neuro, Department of Clinical Neuroscience, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
authors.forename: Jan
authors.initials: J
authors.lastname: Hillert
authors.affiliation: Division of Psychiatry, Department of Clinical Neuroscience, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
authors.forename: Jussi
authors.initials: J
authors.lastname: Jokinen
authors.affiliation: Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Ellenor
authors.initials: E
authors.lastname: Mittendorfer-Rutz
authors.affiliation: Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Petter
authors.initials: P
authors.lastname: Tinghög
mesh_terms: D000293:Adolescent; D000328:Adult; D015331:Cohort Studies; D016001:Confidence Intervals; D006233:Persons with Disabilities / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000188:drug therapy / Q000453:epidemiology* / Q000523:psychology*; D016017:Odds Ratio; D010415:Pensions / Q000706:statistics & numerical data*; D016016:Proportional Hazards Models; D012042:Registries / Q000706:statistics & numerical data*; D012307:Risk Factors; D013548:Sweden / Q000453:epidemiology; D055815:Young Adult
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