PO.SHP01.01 · 科学与健康政策

在撒哈拉以南非洲建立数据驱动的肿瘤研究生态系统:Medserve-LUTH癌症中心(MLCC)研究单元的经验

Establishing a data-driven oncology research ecosystem in sub-Saharan Africa: The Medserve-LUTH Cancer Centre (MLCC) research unit experience

海报缩略图:在撒哈拉以南非洲建立数据驱动的肿瘤研究生态系统:Medserve-LUTH癌症中心(MLCC)研究单元的经验
编号 3687 展板 14 时间 4/20 02:00–05:00 区域 Section 39 主讲 Adedayo Joseph, MD
分会场 Science and Health Policy 1
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作者与单位 Authors & Affiliations

Adedayo Joseph1, Anthonia Sowunmi2, Muhammad Habeebu2, Bolanle Adegboyega2, Adewumi Alabi2, Eben A. Aje2, Temitope Andero2, Godwin Uwagba2, Chidiebere Agbakwuru2, Bukola Oshikanlu2, Ayodeji O. Ojetunde2, Samuel Adeneye2, Nusirat Adedewe2, Michelle Mangongolo2

1Lagos University Teaching Hospital, Nigeria, Nigeria,2Medserve-LUTH Cancer Centre, Lagos University Teaching Hospital, Lagos, Nigeria

摘要 Abstract

中文摘要
背景:可持续的癌症研究能力对于推进中低收入国家(LMICs)循证肿瘤学至关重要。历史上,非洲对全球癌症研究产出的贡献不足2%,这主要归因于基础设施不足、数据系统分散以及临床研究培训有限。Medserve-LUTH癌症中心(MLCC)研究单元于2020年在尼日利亚拉各斯成立,被设计为高诊疗量临床环境中的转化研究中心,旨在通过协调的临床研究、数据科学整合和劳动力发展来弥合这一差距。 方法:MLCC研究单元实施学术-产业混合模式,纳入电子数据采集、方案驱动的登记系统和跨学科培训。该单元支持覆盖所有肿瘤专科领域的研究者发起研究和多中心研究,并共同聚焦于放射肿瘤学。新兴的创新领域包括儿科放射肿瘤学、大分割放疗和经济导航。分析了包括在研研究、研究人员、合作伙伴关系和产出在内的关键运营指标,以评估2020年至2025年间的增长和影响。 结果:自成立以来,MLCC研究单元已支持73项正在进行或已完成的研究,涵盖临床、运营和实施研究。团队已从2人扩展到14名受过培训的人员,包括5名研究助理、7名研究助手和2名实习生。与超过18个国家的机构建立了合作伙伴关系,并与207个以上国际学术伙伴建立了被动合作,促进了数据共享和联合发表。已产出127篇同行评审稿件和118篇会议摘要。MLCC产生的研究数据已为区域文献、放疗政策讨论、区域临床试验(例如HYPOAfrica、ARETTA)以及国家和区域儿科肿瘤方案做出贡献。2021年启动了内部质量保证审计的整合,以提高数据完整性。 结论:MLCC研究单元表明,结构化、本地主导的肿瘤研究生态系统在与临床工作流程相契合、并得到数字基础设施和能力建设项目支持的情况下,能够在LMIC情境中蓬勃发展。该模式为在撒哈拉以南非洲发展可持续的癌症研究能力提供了一个可复制的框架,将本地数据生成与全球癌症控制优先事项联系起来。
查看英文原文 English abstract
Background: Sustainable cancer research capacity is critical to advancing evidence-based oncology in low- and middle-income countries (LMICs). Historically, Africa has contributed less than 2% of global cancer research output, largely due to inadequate infrastructure, fragmented data systems, and limited clinical research training. The Medserve-LUTH Cancer Centre (MLCC) Research Unit, established in 2020 in Lagos, Nigeria, was designed as a translational research hub within a high-volume clinical environment to bridge this gap through coordinated clinical studies, data science integration, and workforce development. Methods: The MLCC Research Unit implements a hybrid academic-industry model incorporating electronic data capture, protocol-driven registries, and cross-disciplinary training. The unit supports investigator-initiated and multicentre studies across all oncologic speciality areas, with a common focus on radiation oncology. Emerging areas of innovation have included pediatric radiation oncology, hypofractionated radiotherapy and financial navigation. Key operational metrics including active studies, research personnel, partnerships, and outputs were analysed to assess growth and impact between 2020 and 2025. Results: Since inception, the MLCC Research Unit has supported 73 ongoing or completed studies spanning clinical, operational, and implementation research. The team has expanded from 2 to 14 trained personnel, including 5 research associates, 7 research assistants and 2 interns. Collaborative partnerships were established with institutions in over 18 countries, and passive collaborations with 207+ international academic partners, facilitating data sharing and joint publications. 127 peer-reviewed manuscripts and 118 conference abstracts have been produced. Research data generated at MLCC have contributed to regional literature, radiotherapy policy discussions, regional clinical trials (e.g., HYPOAfrica, ARETTA), and national and regional pediatric oncology protocols. Integration of internal quality-assurance audits was initiated in 2021 to improve data completeness. Conclusion: The MLCC Research Unit demonstrates that structured, locally led oncology research ecosystems can thrive in LMIC contexts when aligned with clinical workflow and supported by digital infrastructure and capacity-building programs. This model offers a replicable framework for developing sustainable cancer research capacity across sub-Saharan Africa, linking local data generation to global cancer control priorities.
利益披露 Disclosure
A. Joseph, None.. A. Sowunmi, None.. M. Habeebu, None.. B. Adegboyega, None.. A. Alabi, None.. E. A. Aje, None.. T. Andero, None.. G. Uwagba, None.. C. Agbakwuru, None.. B. Oshikanlu, None.. A. O. Ojetunde, None.. S. Adeneye, None.. N. Adedewe, None.. M. Mangongolo, None.

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