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Journal Articles European Journal of Human Genetics Year : 2020

Estimating cumulative point prevalence of rare diseases: analysis of the Orphanet database

Abstract

Abstract Rare diseases, an emerging global public health priority, require an evidence-based estimate of the global point prevalence to inform public policy. We used the publicly available epidemiological data in the Orphanet database to calculate such a prevalence estimate. Overall, Orphanet contains information on 6172 unique rare diseases; 71.9% of which are genetic and 69.9% which are exclusively pediatric onset. Global point prevalence was calculated using rare disease prevalence data for predefined geographic regions from the ‘Orphanet Epidemiological file’ ( http://www.orphadata.org/cgi-bin/epidemio.html ). Of the 5304 diseases defined by point prevalence, 84.5% of those analysed have a point prevalence of <1/1 000 000. However 77.3–80.7% of the population burden of rare diseases is attributable to the 4.2% ( n = 149) diseases in the most common prevalence range (1–5 per 10 000). Consequently national definitions of ‘Rare Diseases’ (ranging from prevalence of 5 to 80 per 100 000) represent a variable number of rare disease patients despite sharing the majority of rare disease in their scope. Our analysis yields a conservative, evidence-based estimate for the population prevalence of rare diseases of 3.5–5.9%, which equates to 263–446 million persons affected globally at any point in time. This figure is derived from data from 67.6% of the prevalent rare diseases; using the European definition of 5 per 10 000; and excluding rare cancers, infectious diseases, and poisonings. Future registry research and the implementation of rare disease codification in healthcare systems will further refine the estimates.
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inserm-04045409 , version 1 (24-03-2023)

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Stéphanie Nguengang Wakap, Deborah Lambert, Annie Olry, Charlotte Rodwell, Charlotte Gueydan, et al.. Estimating cumulative point prevalence of rare diseases: analysis of the Orphanet database. European Journal of Human Genetics, 2020, 28 (2), pp.165-173. ⟨10.1038/s41431-019-0508-0⟩. ⟨inserm-04045409⟩

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