Journal: Journal of Neurology
Authors: Rebecca Persson, Sally Lee, Marianne Ulcickas Yood, Michael Wagner, Neil Minton, Steve Niemcryk, Anders Lindholm, Amber Evans, Susan Jick
NLM Citation: Persson R, Lee S, Yood MU, Wagner M, Minton N, Niemcryk S, Lindholm A, Evans A, Jick S. Multi-database study of multiple sclerosis: identification, validation and description of MS patients in two countries. J Neurol. 2019 May;266(5):1095-1106. doi: 10.1007/s00415-019-09238-8. Epub 2019 Feb 18. PMID: 30778708; PMCID: PMC6469671.
Abstract
Objective: To describe the resources and methods used to identify and validate multiple sclerosis (MS) and match non-MS patients in each of the two databases, and to characterize their demographics, comorbidities and concomitant medications.
Methods: This study was conducted in two separate electronic medical databases, the United States Department of Defense (DOD) military health care system and the United Kingdom’s Clinical Practice Research Datalink (CPRD) GOLD. We identified patients with a first recorded diagnosis of MS in 2001-2016 (CPRD) or 2004-2017 (DOD) and matched non-MS patients using algorithms appropriate to each database. We describe patient symptoms, comorbidities, and medication use at the time of the MS diagnosis and compared them to the non-MS cohort.
Results: We identified 8695 patients with MS and 86,934 matched non-MS patients in the DOD database and 6932 patients with MS and 68,526 matched non-MS patients in CPRD GOLD. Most MS patients were female (around 70%) and were diagnosed before age 60 (88%). MS patients had higher prevalence of depression and other psychiatric conditions at MS diagnosis compared to non-MS patients. Epilepsy, fractures and infections were also more common. MS patients had many expected symptoms and treatments documented in their records prior to the MS diagnosis.
Conclusion: These results are consistent between the two databases, as well as with previous studies of MS. Future analyses of these patients’ experience after MS diagnosis will provide valuable insights into disease and treatment patterns in relation to risk of chronic diseases and mortality.
Keywords: Comorbidities; Multiple sclerosis; Prevalence; Validation.
