ObjectiveTo generate a national multiple sclerosis (MS) prevalence estimate for the United States by applying a validated algorithm to multiple administrative health claims (AHC) datasets.MethodsA 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.ResultsThe 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.ConclusionThe 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.

ObjectiveTo develop a valid algorithm for identifying multiple sclerosis (MS) cases in administrative health claims (AHC) datasets.MethodsWe used 4 AHC datasets from the Veterans Administration (VA), Kaiser Permanente Southern California (KPSC), Manitoba (Canada), and Saskatchewan (Canada). In the VA, KPSC, and Manitoba, we tested the performance of candidate algorithms based on inpatient, outpatient, and disease-modifying therapy (DMT) claims compared to medical records review using sensitivity, specificity, positive and negative predictive values, and interrater reliability (Youden J statistic) both overall and stratified by sex and age. In Saskatchewan, we tested the algorithms in a cohort randomly selected from the general population.ResultsThe preferred algorithm required ≥3 MS-related claims from any combination of inpatient, outpatient, or DMT claims within a 1-year time period; a 2-year time period provided little gain in performance. Algorithms including DMT claims performed better than those that did not. Sensitivity (86.6%–96.0%), specificity (66.7%–99.0%), positive predictive value (95.4%–99.0%), and interrater reliability (Youden J = 0.60–0.92) were generally stable across datasets and across strata. Some variation in performance in the stratified analyses was observed but largely reflected changes in the composition of the strata. In Saskatchewan, the preferred algorithm had a sensitivity of 96%, specificity of 99%, positive predictive value of 99%, and negative predictive value of 96%.ConclusionsThe performance of each algorithm was remarkably consistent across datasets. The preferred algorithm required ≥3 MS-related claims from any combination of inpatient, outpatient, or DMT use within 1 year. We recommend this algorithm as the standard AHC case definition for MS.

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Our objective was to describe racial and ethnic differences of amyotrophic lateral sclerosis (ALS) in distinct geographic locations around the United States (U.S.). ALS cases for the period 2009–2011 were identified using active case surveillance in three states and eight metropolitan areas. Of the 5883 unique ALS cases identified, 74.8% were white, 9.3% were African-American/black, 3.6% were Asian, 12.0% were an unknown race, and 0.3% were marked as some other race. For ethnicity, 77.5% were defined as non-Hispanic, 10.8% Hispanic, and 11.7% were of unknown ethnicity. The overall crude average annual incidence rate was 1.52 per 100,000 person-years and the rate differed by race and ethnicity. The overall age-adjusted average annual incidence rate was 1.44 per 100,000 person-years and the age-adjusted average incidence rates also differed by race and ethnicity. Racial differences were also found in payer type, time from symptom onset to diagnosis, reported El Escorial criteria, and age at diagnosis.In conclusion, calculated incidence rates demonstrate that ALS occurs less frequently in African-American/blacks and Asians compared to whites, and less frequently in Hispanics compared to non-Hispanics in the U.S. A more precise understanding of racial and ethnic variations in ALS may help to reveal candidates for further studies of disease etiology and disease progression.

ObjectiveConsiderable gaps exist in knowledge regarding the prevalence of neurologic diseases, such as multiple sclerosis (MS), in the United States. Therefore, the MS Prevalence Working Group sought to review and evaluate alternative methods for obtaining a scientifically valid estimate of national MS prevalence in the current health care era.MethodsWe carried out a strengths, weaknesses, opportunities, and threats (SWOT) analysis for 3 approaches to estimate MS prevalence: population-based MS registries, national probability health surveys, and analysis of administrative health claims databases. We reviewed MS prevalence studies conducted in the United States and critically examined possible methods for estimating national MS prevalence.ResultsWe developed a new 4-step approach for estimating MS prevalence in the United States. First, identify administrative health claim databases covering publicly and privately insured populations in the United States. Second, develop and validate a highly accurate MS case-finding algorithm that can be standardly applied in all databases. Third, apply a case definition algorithm to estimate MS prevalence in each population. Fourth, combine MS prevalence estimates into a single estimate of US prevalence, weighted according to the number of insured persons in each health insurance segment.ConclusionsBy addressing methodologic challenges and proposing a new approach for measuring the prevalence of MS in the United States, we hope that our work will benefit scientists who study neurologic and other chronic conditions for which national prevalence estimates do not exist.

Our objective was to develop state and metropolitan area-based surveillance projects to describe the characteristics of those with ALS and to assist with evaluating the completeness of the National ALS Registry. Because the literature suggested that ethnic/racial minorities have lower incidence of ALS, three state and eight metropolitan areas were selected to over-represent ethnic/racial minorities to have a sufficient number of minority patients. Project activities relied on reports from medical providers and medical records abstraction. The project areas represented approximately 27% of the U.S. population. The combined racial and ethnic distribution of these areas is 64.4% white, 16.0% African-American, 6.7% Asian, and 28.3% Hispanic. Most neurologists did not diagnose or provide care for ALS patients. The number of unique patients reported was close to expected (5883 vs. 6673). Age and gender distribution of patients was similar to the literature. The crude average annual incidence rate was 1.52 per 100,000 person-years, CI 1.44–1.61, and the 2009 prevalence rate was 3.84 per 100,000 population, CI 3.70–3.97. In conclusion, this study represents the largest number of clinically diagnosed ALS patients reported by neurologists in the U.S. Comparison of these data with those in the National ALS Registry will help evaluate the completeness of administrative databases.

IntroductionLimited epidemiological data on amyotrophic lateral sclerosis (ALS) exist in defined geographic areas in the United States.MethodsNeurologists submitted case reports for patients under their care between January 1, 2009, and December 31, 2011, who met the El Escorial criteria. Diagnosis was confirmed for a sample of cases by the consulting neurologist. Death certificate data were used for supplemental case identification.ResultsThe 248 reported cases were most likely to be 50–69 years old, men, white, and non-Hispanic. The total crude average annual incidence rate was 1.46 per 100,000 person-years.ConclusionsThe reported demographic characteristics were consistent with previously published findings. The crude annual incidence was slightly lower than the expected rate of 1.6 but was within the range reported previously (0.7–2.5). These findings help quantify the burden of ALS in the United States.

Objective: The majority of cases of the fatal neurodegenerative disease amyotrophic lateral sclerosis (ALS) are of unknown etiology. A proportion of these cases are likely to be attributable to contaminant exposures, although the specific environmental etiology of ALS remains largely a mystery. Certain forms of the neurotoxic metal mercury readily cross into the central nervous system. Fish is a dietary source of methylmercury, but also of beneficial components, such as omega-3 polyunsaturated fatty acids. Prior work using clinic-based studies of toenails and hair as keratinous biomarkers of exposure suggest elevated mercury levels in ALS patients compared with controls. We sought to validate this relationship in a U.S. case-control comparison of mercury levels in nail clippings. Methods: We performed trace element analysis using inductively coupled plasma mass spectrometry (ICP-MS) on the nail clippings of n ¼ 70 female, geographically representative ALS patients from the National ALS Biorepository and compared them to n ¼ 210 age-matched controls from a set of n ¼ 1216 nationally distributed controls from the Sister and Two Sister Studies. Results: Compared to the lowest quartile of nail mercury, moderate levels were associated with decreased risk of ALS (P ¼ 4.18e-6). However, the odds of having nail mercury levels above the 90th percentile were 2.3-fold higher among ALS patients compared with controls (odds ratio (OR) ¼ 2.3, 95% confidence interval 1.10-4.58, adjusted for age and smoking status). Conclusion: This finding suggests that excessive mercury exposure may be associated with the neurodegenerative health of aging populations.