Department of Gastroenterology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China.
School of Public Health, Shanghai Jiao Tong University, Shanghai, China.
Biopreserv Biobank. 2021 Aug;19(4):269-279. doi: 10.1089/bio.2020.0096. Epub 2021 Jan 15.
Cohort studies with biobanks that use strict quality standards are essential requirements, not only for the development of new diagnostic and prognostic markers, but also for improving the understanding of pathophysiology of disease development, which have drawn an increasing amount of attention over the past decades. However, a bibliometric analysis of the global research on cohort biobanks is rare. The objective of this study was to evaluate the origin, current trend, and research hotspots of cohort biobanks. We searched the Web of Science Core Collection (WoSCC) with "biobank" and "cohort" as the topic words to retrieve English language articles published from 2009 to 2018. The CiteSpace 5.5.R2 was used to perform the cooperation network analysis, key words co-occurrence and burst detection analysis, and reference co-citation analysis. The number of publications on cohort biobanks has increased over the past decade. Tai Hing Lam from the Department of Community Medicine, University of Hong Kong, was found to be the most productive researcher in this field. The percentage of publications in England (38.30%) was the highest all over the world. Risk, biobank, meta-analysis, cohort, disease, and so on were the most frequent keywords. Metabolic syndrome was the strongest burst keyword in this field, followed by Hong Kong, Guangzhou biobank cohort and personalized medicine. Moreover, of all the references for 932 articles included in the study, the article titled "UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age" published in PLoS Med by Sudlow et al., was the most frequently co-cited reference in this field. The largest cluster was labeled as Guangzhou biobank cohort study. This study provides an insight into cohort biobanks and the valuable information for biobankers to identify new perspectives on potential collaborators and cooperative countries/territories.
队列研究与生物库相结合,采用严格的质量标准,不仅是开发新的诊断和预后标志物的必要条件,也是提高对疾病发展病理生理学理解的必要条件,这在过去几十年中引起了越来越多的关注。然而,对全球队列生物库研究进行文献计量分析的情况很少。本研究的目的是评估队列生物库的起源、当前趋势和研究热点。
我们使用“生物库”和“队列”作为主题词,在 Web of Science Core Collection (WoSCC) 中进行检索,以检索 2009 年至 2018 年发表的英文文章。使用 CiteSpace 5.5.R2 进行合作网络分析、关键词共现和突发检测分析以及参考文献共被引分析。过去十年,队列生物库的出版物数量有所增加。来自香港大学社区医学系的 Tai Hing Lam 被发现是该领域最具生产力的研究人员。全世界出版物中,英国(38.30%)的比例最高。风险、生物库、荟萃分析、队列、疾病等是最常见的关键词。代谢综合征是该领域最强的突发关键词,其次是香港、广州生物库队列和个性化医学。此外,在所研究的 932 篇文章中,Sudlow 等人在 PLoS Med 上发表的题为“英国生物库:一种识别中老年多种复杂疾病病因的开放获取资源”的文章是该领域被引用最多的参考文献。最大的聚类被标记为广州生物库队列研究。
本研究深入了解了队列生物库,为生物库管理者提供了有价值的信息,有助于确定潜在的合作者和合作国家/地区的新视角。