Economic burden of Huntington’s disease: A systematic review

疾病 科克伦图书馆 医学 亨廷顿病 梅德林 间接成本 疾病负担 中国 系统回顾 医疗保健 环境卫生 老年学 家庭医学 荟萃分析 地理 业务 政治学 经济增长 病理 经济 会计 法学 考古
作者
Pooja Gokhale,Lorenzo Villa‐Zapata
出处
期刊:Journal of Huntington's disease [IOS Press]
标识
DOI:10.1177/18796397251319209
摘要

Background Huntington's disease (HD) is an autosomal dominant neurodegenerative disease, characterized by progressive motor, cognitive, and psychiatric symptoms. The disease poses a significant social and economic burden. Objective This systematic review aims to characterize the global economic burden by analyzing the direct, indirect, and total costs associated with HD. Methods A comprehensive literature search was conducted across PubMed/MEDLINE, Web of Science, and Cochrane Library from inception to June 2024. The titles and abstracts were screened independently by two reviewers and full-text, English-language articles assessing direct, indirect, and/or total costs of HD were included. The costs were converted to annual costs in 2024 United States Dollars (USD). Results Out of the initial 608 de-duplicated articles, 19 full-text articles were included. The articles spanned 44 years, from 1980 to 2024. The studies covered a total of 15 countries. Annual costs in 2024 USD ranged significantly by region: Americas ($2542-$90,515), Europe ($40,000-$215,020), Asia ($1915-$7132), and Oceania ($3678-$8721). The highest costs were reported in Norway ($171,842) and the UK ($215,020), while Asian countries reported substantially lower costs (China: $6469; South Korea: $6305; Taiwan: $1915-$7132). Conclusions The global economic burden of HD varies substantially across regions, influenced by prevalence rates, healthcare systems, and reporting methodologies. Study limitations include heterogeneous cost reporting methods, potential underestimation in cost conversions, and lack of disease severity stratification. Standardizing cost-of-illness study methodologies and developing specific quality assessment tools would enhance cross-study comparability and improve resource allocation globally.
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