Multiple sclerosis prevalence in the United States commercially insured population
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Abstract
Objective: To estimate the US commercially insured multiple sclerosis (MS) annual prevalence from 2008 to 2012.
Methods: The study was a retrospective analysis using PharMetrics Plus, a nationwide claims database for over 42 million covered US representative lives. Annual point prevalence required insurance eligibility during an entire year. Our primary annual MS identification algorithm required 2 inpatient claims coded ICD-9 340 or 3 outpatient claims coded ICD-9 340 or 1 MS-indicated disease-modifying therapy claim. Age-adjusted annual prevalence estimates were extrapolated to the US population using US Census data.
Results: The 2012 MS prevalence was 149.2 per 100,000 individuals (95% confidence interval 147.6–150.9). Prevalence was consistent over 2008–2012. Female participants were 3.13 times more likely to have MS. The highest prevalence was in participants aged 45–49 years (303.5 per 100,000 individuals [295.6–311.5]). The East Census region recorded the highest prevalence (192.1 [188.2–196.0]); the West Census region recorded the lowest prevalence (110.7 [105.5–116.0]). The US annual 2012 MS extrapolated population was 403,630 (387,445–419,833).
Conclusions: MS prevalence rates from a representative commercially insured database were higher than or consistent with prior US estimates. For further accuracy improvement of US prevalence estimates, results should be confirmed after validation of MS identification algorithms, and should be expanded to other US populations, including the government-insured and the uninsured.
GLOSSARY
- CI=
- confidence interval;
- COMIRB=
- Colorado Multiple Institute Review Board;
- DMT=
- disease-modifying therapy;
- ICD-9=
- International Classification of Diseases–9;
- MS=
- multiple sclerosis
Footnotes
Go to Neurology.org for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.
- Received July 22, 2015.
- Accepted in final form December 1, 2015.
- © 2016 American Academy of Neurology
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