Article2021

Ten Years of the Cohort Biobank: Bibliometric Outcomes

Deqing Wu · Susu Wang · Chunping Hu · Chonghuai Yan · Meiqin Wu

9 citations0/0 files storedBiopreservation and Biobanking

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scientometrics and bibliometrics research Health, Environment, Cognitive Aging Diverse Approaches in Healthcare and Education Studies

Abstract

Background: 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. Materials and Methods: 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. Results: 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. Conclusions: 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.

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References

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