Dear Editor,Burkitt lymphoma (BL) is a highly aggressive form of non-Hodgkin lymphoma that predominantly affects young males. The age-standardized incidence rates (ASIRs) of BL show significant variation, with disparities ranging from three- to five-fold across different continents [1]. This variation is most pronounced in equatorial Africa, where the incidence rates exceed 4 cases per million person-years between 10°N to 10°S latitude, making BL endemic to this region [2, 3].

亲爱的编辑，伯基特淋巴瘤（BL）是一种高度侵袭性的非霍奇金淋巴瘤，主要影响年轻男性。BL的年龄标准化发病率（ASIR）显示出显着差异，不同大陆的差异从三到五倍不等（1）。这种变化在赤道非洲最为明显，在10°N至10°S纬度之间，发病率超过每百万人年4例，使BL在该地区流行[2，3]。

Survival outcomes for BL are influenced by multiple factors, including disease stage, geographic location, ethnicity, and treatment approaches [4, 5].Annual data from 1990 to 2021 on incident cases, prevalent cases, deaths, and disability-adjusted life years (DALYs) of BL, as well as ASIRs, age-standardized prevalence rates (ASPRs), age-standardized mortality rates (ASMRs), and age-standardized DALY rates (ASDRs), were obtained using the Global Health Data Exchange (GHDx) query tool (http://ghdx.healthdata.org/gbd-results-tool).

BL的生存结果受多种因素影响，包括疾病分期，地理位置，种族和治疗方法[4，5]。使用全球健康数据交换（GHDx）查询工具获得了1990年至2021年关于BL事件、流行病例、死亡和残疾调整生命年（DALYs）的年度数据，以及ASIR、年龄标准化患病率（ASPR）、年龄标准化死亡率（ASMRs）和年龄标准化DALY率（ASDRs）(http://ghdx.healthdata.org/gbd-results-tool)。

Socioeconomic data, comprising the Socio-Demographic Index (SDI) [6] for 2021, the Universal Health Coverage Index (UHCI) [7] values for 2019, and the Human Development Index (HDI) [8] were also collected. The estimated annual percentage change (EAPC) was used to summarize changes in age-standardized rates (ASRs) over time.

还收集了社会经济数据，包括2021年的社会人口指数（SDI）、2019年的全民健康覆盖指数（UHCI）和人类发展指数（HDI）。估计的年度百分比变化（EAPC）用于总结年龄标准化率（ASR）随时间的变化。

Joinpoint regression analysis was applied to detect shifts in trends and identify critical points of change. To explore the relationship between EAPCs and socioeconomic factors, Spearman correlation analyses were conducted. Additionally, we performed a decomposition analysis focusing on the contributions of age structure, epidemiologic changes, and population size.

应用连接点回归分析来检测趋势的变化并确定变化的关键点。为了探索EAPCs与社会经济因素之间的关系，进行了Spearman相关分析。此外，我们进行了分解分析，重点是年龄结构，流行病学变化和人口规模的贡献。

Finally, using the Bayesian APC (BAPC) model [9], we projected the absolute numbers, rate.

最后，使用贝叶斯APC（BAPC）模型（9），我们预测了绝对数字，速率。

Data availability

数据可用性

Data were obtained from the Global Health Data Exchange (GHDx) query tool (http://ghdx.healthdata.org/gbd-results-tool).

数据来自全球健康数据交换（GHDx）查询工具(http://ghdx.healthdata.org/gbd-results-tool)。

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Download referencesAcknowledgementsWe highly appreciate the works of the Global Burden of Disease Study 2021 collaborators. This study was funded by Jiangsu Key Research and Development Project of Social Development (2019638).Author informationAuthor notesThese authors contributed equally: Ying Wang, Ziyuan Shen.Authors and AffiliationsDepartment of Personnel, Jiangsu Province (Suqian) Hospital, Suqian, 223800, Jiangsu, ChinaYing WangDepartment of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221006, Jiangsu, ChinaZiyuan Shen & Wei SangDepartment of Public Health, Affiliated Wuxi Fifth Hospital of Jiangnan University, Wuxi, 214000, Jiangsu, ChinaChenlu HeDepartment of Public Health, The Fifth People’s Hospital of Wuxi, Wuxi, 214000, Jiangsu, ChinaChenlu HeDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USAXing XingResearch Center of Health Policy and Health Management, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, ChinaZaixiang TanBlood Diseases Institute, Xuzhou Medical University, Xuzhou, 221006, Jiangsu, ChinaWei SangAuthorsYing WangView author publicationsYou can also search for this author in.

下载参考文献致谢我们高度赞赏2021年全球疾病负担研究合作者的工作。本研究由江苏省社会发展重点研究发展项目（2019638）资助。作者信息作者注意到这些作者做出了同样的贡献：王颖，沈子元。作者和所属单位江苏省（宿迁）医院人事科，江苏宿迁223800，中国王颖徐州医科大学附属医院血液科，江苏徐州221006，中国沈紫源和魏桑江南大学附属无锡第五医院公共卫生科，江苏无锡214000，江苏无锡第五人民医院公共卫生科，江苏无锡214000，中国陈璐生物统计学系，约翰·霍普金斯大学彭博公共卫生学院，马里兰州巴尔的摩21205，USAXing XingResearch Center of Health Policy and Health Management，徐州中国医科大学，徐州，221004，江苏，徐州医科大学血液病研究所，徐州，221006，江苏，中国卫桑Authorsing WangView作者出版物您也可以在中搜索这位作者。

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PubMed Google ScholarContributionsZT and WS revised the manuscript; YW wrote the first version of the manuscript; ZS, CH, and XX performed data analysis.Corresponding authorCorrespondence to

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Reprints and permissionsAbout this articleCite this articleWang, Y., Shen, Z., He, C. et al. Global, regional, and national burden of Burkitt lymphoma from 1990 to 2021 and predictions to 2030: a systematic analysis for the Global Burden of Disease Study 2021.

转载和许可本文引用本文Wang，Y.，Shen，Z.，He，C.等人，《1990年至2021年伯基特淋巴瘤的全球，地区和国家负担以及2030年的预测：2021年全球疾病负担研究的系统分析》。

Blood Cancer J. 14, 154 (2024). https://doi.org/10.1038/s41408-024-01138-zDownload citationReceived: 24 July 2024Revised: 29 August 2024Accepted: 02 September 2024Published: 09 September 2024DOI: https://doi.org/10.1038/s41408-024-01138-zShare this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard.

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