Zhao Xu, Ma Ruijia, Shen Jiaxing, Xu Dingwen, Yang Zhe
Department of Clinic, School of Medicine, Yangzhou Polytechnic University, Yangzhou, China.
Department of Orthopaedics, Shanxi Provincial People's Hospital, Shanxi, China.
Eur J Pharmacol. 2025 Nov 5;1006:178187. doi: 10.1016/j.ejphar.2025.178187. Epub 2025 Sep 26.
Lecanemab, a monoclonal antibody that targets amyloid-beta aggregates, has emerged as a promising therapeutic for Alzheimer's disease (AD). AD is a progressive neurodegenerative disorder characterized by cognitive decline and amyloid pathology. Research on the use of lecanemab in treating AD has increased; however, no relevant bibliometric analyses have been conducted. To address this gap, this study employed bibliometric methods to search for the relevant literature and analyze research trends investigating AD and lecanemab.
We performed a literature search of the Web of Science core database for studies investigating AD and lecanemab, published from database inception up to April 3rd, 2025. After rigorous screening, Excel, VOSviewer, and CiteSpace were used to perform a bibliometric analysis of publications, citations, and collaboration networks among countries, institutions, and authors, along with cluster and burst analyses of keywords. Coremine was used for text mining entries significantly related to AD and lecanemab.
The number of studies published on AD and lecanemab has increased annually. The countries with the highest publication output were the United States, the United Kingdom, and China. The leading institutions that produced the most articles were Eisai Inc. (Bunkyo City, Tokyo, Japan), Uppsala University (Uppsala, Sweden), and Harvard Medical School (Boston, MA, USA). The top three authors were Lars Lannfelt, Shobha Dhadda, and Michio Kanekiyo. The most prolific journals included The Journal of Alzheimer's Disease, Alzheimer's and Dementia, and Ageing Research Reviews. The most cited article was "Lecanemab in Early Alzheimer's Disease," by Van Dyck et al., published in The New England Journal of Medicine in 2023, which has accrued 172 citations. The 10 most frequently occurring keywords were Alzheimer's disease, lecanemab, dementia, aducanumab, amyloid-beta, immunotherapy, tau, a-beta, mouse model, and donanemab. Text mining revealed that drugs, anatomical structures, chemical molecules, genes, diseases, and procedures were significantly associated with both AD and lecanemab.
The bibliometric and text mining analysis revealed trends in research investigating the correlation between lecanemab and AD. It analyzed the cooperation among countries, regions, and authors, highlighting recent research hotspots. These data offer objective insights for scientific research and clinical practice on lecanemab and AD. These findings provide a roadmap for prioritizing clinical trials, optimizing drug development strategies, and addressing knowledge gaps in amyloid-targeted therapies.
莱卡奈单抗是一种靶向淀粉样蛋白β聚集体的单克隆抗体，已成为治疗阿尔茨海默病（AD）的一种有前景的疗法。AD是一种以认知衰退和淀粉样蛋白病理为特征的进行性神经退行性疾病。关于使用莱卡奈单抗治疗AD的研究有所增加；然而，尚未进行相关的文献计量分析。为填补这一空白，本研究采用文献计量方法检索相关文献，并分析研究AD和莱卡奈单抗的研究趋势。
我们在科学网核心数据库中进行文献检索，以查找从数据库创建到2025年4月3日发表的关于AD和莱卡奈单抗的研究。经过严格筛选后，使用Excel、VOSviewer和CiteSpace对出版物、引文以及国家、机构和作者之间的合作网络进行文献计量分析，同时对关键词进行聚类和突现分析。使用Coremine进行文本挖掘，以找出与AD和莱卡奈单抗显著相关的条目。
关于AD和莱卡奈单抗的研究发表数量逐年增加。发表量最高的国家是美国、英国和中国。发表文章最多的主要机构是卫材株式会社（日本东京文京区）、乌普萨拉大学（瑞典乌普萨拉）和哈佛医学院（美国马萨诸塞州波士顿）。排名前三的作者是拉尔斯·兰费尔特、肖巴·达达和米吉奥·金清。发文量最多的期刊包括《阿尔茨海默病杂志》《阿尔茨海默病与痴呆》和《衰老研究评论》。被引用次数最多的文章是范·戴克等人于2023年发表在《新英格兰医学杂志》上的《早期阿尔茨海默病中的莱卡奈单抗》，已获得172次引用。出现频率最高的10个关键词是阿尔茨海默病、莱卡奈单抗、痴呆、阿杜卡单抗、淀粉样蛋白β、免疫疗法、tau蛋白、a-β、小鼠模型和多奈单抗。文本挖掘显示，药物、解剖结构、化学分子、基因、疾病和程序与AD和莱卡奈单抗均显著相关。
文献计量和文本挖掘分析揭示了研究莱卡奈单抗与AD之间相关性的研究趋势。它分析了国家、地区和作者之间的合作，突出了近期的研究热点。这些数据为莱卡奈单抗和AD的科研及临床实践提供了客观见解。这些发现为确定临床试验优先级、优化药物开发策略以及填补淀粉样蛋白靶向治疗的知识空白提供了路线图。
