ABSTRACT
BACKGROUND: Data are limited for mortality and comorbidities in patients with multiple sclerosis (MS). OBJECTIVES: Compare mortality rates and event rates for comorbidities in MS (n=15,684) and non-MS (n=78,420) cohorts from the US Department of Defense (DoD) database. METHODS: Comorbidities and all-cause mortality were assessed using the database. Causes of death (CoDs) were assessed through linkage with the National Death Index. Cohorts were compared using mortality (MRR) and event (ERR) rate ratios. RESULTS: All-cause mortality was 2.9-fold higher in the MS versus non-MS cohort (MRR, 95% confidence interval [CI]: 2.9, 2.7-3.2). Frequent CoDs in the MS versus non-MS cohort were infectious diseases (6.2, 4.2-9.4), diseases of the nervous (5.8, 3.7-9.0), respiratory (5.0, 3.9-6.4) and circulatory (2.1, 1.7-2.7) systems and suicide (2.6, 1.3-5.2). Comorbidities including sepsis (ERR, 95% CI: 5.7, 5.1-6.3), ischemic stroke (3.8, 3.5-4.2), attempted suicide (2.4, 1.3-4.5) and ulcerative colitis (2.0, 1.7-2.3), were higher in the MS versus non-MS cohort. The rate of cancers was also higher in the MS versus the non-MS cohort, including lymphoproliferative disorders (2.2, 1.9-2.6) and melanoma (1.7, 1.4-2.0). CONCLUSIONS: Rates of mortality and several comorbidities are higher in the MS versus non-MS cohort. Early recognition and management of comorbidities may reduce premature mortality and improve quality of life in patients with MS.
Subject(s)
Multiple Sclerosis/epidemiology , Adolescent , Adult , Cause of Death , Cohort Studies , Comorbidity , Databases, Factual , Female , Humans , Male , Middle Aged , Military Personnel/statistics & numerical data , Multiple Sclerosis/drug therapy , United States/epidemiology , United States Department of Defense/statistics & numerical data , Young AdultABSTRACT
Have you noticed when you browse a book, journal, study report, or product label how your eye is drawn to figures more than to words and tables? Statistical graphs are powerful ways to transparently and succinctly communicate the key points of medical research. Furthermore, the graphic design itself adds to the clarity of the messages in the data. The goal of this paper is to provide a mechanism for selecting the appropriate graph to thoughtfully construct quality deliverables using good graphic design principles. Examples are motivated by the efforts of a Safety Graphics Working Group that consisted of scientists from the pharmaceutical industry, Food and Drug Administration, and academic institutions.
