Abstract:
OBJECTIVE:To generate a national multiple sclerosis (MS) prevalence estimate for the United States by applying a validated algorithm to multiple administrative health claims (AHC) datasets. METHODS:A validated algorithm was applied to private, military, and public AHC datasets to identify adult cases of MS between 2008 and 2010. In each dataset, we determined the 3-year cumulative prevalence overall and stratified by age, sex, and census region. We applied insurance-specific and stratum-specific estimates to the 2010 US Census data and pooled the findings to calculate the 2010 prevalence of MS in the United States cumulated over 3 years. We also estimated the 2010 prevalence cumulated over 10 years using 2 models and extrapolated our estimate to 2017. RESULTS:The estimated 2010 prevalence of MS in the US adult population cumulated over 10 years was 309.2 per 100,000 (95% confidence interval [CI] 308.1-310.1), representing 727,344 cases. During the same time period, the MS prevalence was 450.1 per 100,000 (95% CI 448.1-451.6) for women and 159.7 (95% CI 158.7-160.6) for men (female:male ratio 2.8). The estimated 2010 prevalence of MS was highest in the 55- to 64-year age group. A US north-south decreasing prevalence gradient was identified. The estimated MS prevalence is also presented for 2017. CONCLUSION:The estimated US national MS prevalence for 2010 is the highest reported to date and provides evidence that the north-south gradient persists. Our rigorous algorithm-based approach to estimating prevalence is efficient and has the potential to be used for other chronic neurologic conditions.
journal_name
Neurologyjournal_title
Neurologyauthors
Wallin MT,Culpepper WJ,Campbell JD,Nelson LM,Langer-Gould A,Marrie RA,Cutter GR,Kaye WE,Wagner L,Tremlett H,Buka SL,Dilokthornsakul P,Topol B,Chen LH,LaRocca NG,US Multiple Sclerosis Prevalence Workgroup.doi
10.1212/WNL.0000000000007035subject
Has Abstractpub_date
2019-03-05 00:00:00pages
e1029-e1040issue
10eissn
0028-3878issn
1526-632Xpii
WNL.0000000000007035journal_volume
92pub_type
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