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VANCOUVER, BC—No correlation between interferon treatment and antidepressant use was observed in the multiple sclerosis (MS) population, a large-scale study presented at the 68th AAN Annual Meeting reported.
Using Explorys Enterprise Performance Management, a HIPAA-compliant depersonalized clinical database, Matthew M. Mirsky, MS, of the Mellen Center for Multiple Sclerosis Treatment and Research, Neurological Institute, Cleveland Clinic, Cleveland, OH, assessed the association of antidepressant use and disease modifying therapy (DMT) prescribed for multiple sclerosis.
A search of this database, which totals 50 million patients and spans 26 different healthcare systems, “produced a cohort of individuals diagnosed with MS in the past 3 years, on a specific DMT, who were then placed on any antidepressant,” Mirsky noted.
“Additionally, the antidepressant prevalence was tested in the MS population also on the following DMTs: interferon-B1a, interferon-B1b, combined interferon-B as ‘IFN,’ glatiramer acetate, natalizumab, fingolimod, and dimethyl fumarate,” he added. The data were then further analyzed by age and sex.
For those on MS DMTs, rate of antidepressant use ranged from 40.60% to 44.57%, he reported.
“The frequency of antidepressant use in women was highest for natalizumab (47.33%) and lowest for dimethyl fumarate (43.10%),” he added. Among males, IFN had the lowest antidepressant frequency, 32.14%.
In 5 out of 6 DMTs, antidepressant use peaked in the group 45–54 years of age; only natalizumab peaked among those 35–44 years of age.
For future use in the MS population, Mirsky validated the EPM database against the Pattern et al. 2008 study of antidepressant use in association with interferon and glatiramer acetate treatment in MS.
When compared to these data, “our observation that antidepressant use with all IFN is 41.61% matches up closely,” he reported. “In addition, our data confirm that this use is not more than with other DMTs used in MS.”
Limitations to the study include that the EPM database precludes statistical analysis on population counts and that cohorts are rounded to the nearest 10 for de-identification purposes.
