ArticleOrphanet journal of rare diseases2023
Sources of variation in estimates of Duchenne and Becker muscular dystrophy prevalence in the United States.
Article in Orphanet journal of rare diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Prequalification of genome-based newborn screening for severe childhood genetic diseases through federated training based on purifying hyperselection.American journal of human genetics · 2024Article
- Latent factors underlying the symptoms of adult-onset myotonic dystrophy type 1 during the clinical course.Orphanet journal of rare diseases · 2024Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundDirect estimates of rare disease prevalence from public health surveillance may only be available in a few catchment areas. Understanding variation among observed prevalence can inform estimates of prevalence in other locations. The Muscular Dystrophy Surveillance, Tracking, and Research Network (MD STARnet) conducts population-based surveillance of major muscular dystrophies in selected areas of the United States. We identified sources of variation in prevalence estimates of Duchenne and Becker muscular dystrophy (DBMD) within MD STARnet from published literature and a survey of MD STARnet investigators, then developed a logic model of the relationships between the sources of variation and estimated prevalence.
resultsThe 17 identified sources of variability fell into four categories: (1) inherent in surveillance systems, (2) particular to rare diseases, (3) particular to medical-records-based surveillance, and (4) resulting from extrapolation. For the sources of uncertainty measured by MD STARnet, we estimated each source's contribution to the total variance in DBMD prevalence. Based on the logic model we fit a multivariable Poisson regression model to 96 age-site-race/ethnicity strata. Age accounted for 74% of the variation between strata, surveillance site for 6%, race/ethnicity for 3%, and 17% remained unexplained.
conclusionVariation in estimates derived from a non-random sample of states or counties may not be explained by demographic differences alone. Applying these estimates to other populations requires caution.
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