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Incidence and prevalence estimates in myasthenia gravis have varied widely. Recent studies based on administrative health data have large sample sizes but lack rigorous validation of MG cases, and have not examined the North American population. Our aim was to explore trends in MG incidence and prevalence for the years 1996–2013 in the province of Ontario, Canada (population 13.5 million). We employed a previously validated algorithm to identify MG cases. Linking with census data allowed for the calculation of crude- and age/sex-standardized incidence and prevalence rates for the years 1996–2013. The regional distribution of MG cases throughout the province was examined. Mean age at the first myasthenia gravis encounter was 60.2 ± 17.1 years. In 2013, there were 3611 prevalent cases in Ontario, and the crude prevalence rate was 32.0/100,000 population. Age- and sex-standardized prevalence rates rose consistently over time from 16.3/100,000 (15.4–17.1) in 1996 to 26.3/100,000 (25.4–27.3) in 2013. Standardized incidence rates remained stable between 1996 (2.7/100,000; 95% CL 2.3–3.0) and 2013 (2.3/100,000; 2.1–2.6). Incidence was highest in younger women and older men, and geographic variation was evident throughout the province. In conclusion, this large epidemiological study shows rising myasthenia gravis prevalence with stable incidence over time, which is likely reflective of patients living longer, possibly due to improved disease treatment. Our findings provide accurate information on the Canadian epidemiology of myasthenia gravis and burden for health care resources planning for the province, respectively. [ABSTRACT FROM AUTHOR]

Introduction: Incidence and prevalence estimates for myasthenia gravis (MG) have varied widely, and the ability of administrative health data (AHD) records to accurately identify cases of MG is yet to be ascertained. The goal of the current study was to validate an algorithm to identify patients with MG in Ontario, Canada using AHD - thereby enabling future disease surveillance., Methods: A reference standard population was established using automated key word searching within EMRALD (Electronic Medical Record Administrative data Linked Database) and chart review of potential cases. AHD algorithms were generated and tested against the reference standard. The data was used to calculate MG prevalence rates., Results: There were 123,997 eligible adult patients, and 49 patients had definite MG (forming the reference standard). An algorithm requiring: (1 hospital discharge abstract with MG listed as a reason for hospitalization or a comorbid condition), or (5 outpatient MG visits and 1 relevant diagnostic test, within 1 year), or (3 pyridostigmine prescriptions, within 1 year) identified MG with sensitivity = 81.6%, specificity = 100%, positive predictive value = 80.0% and negative predictive value = 100%. The population prevalence within our cohort was 0.04%., Conclusions: This novel validation method demonstrates the feasibility of using administrative health data to identify patients with myasthenia gravis among the Ontario population., (© 2015 S. Karger AG, Basel.)