Dataset Information

A scientometric analysis of neuroblastoma research.

ABSTRACT:

Background

Thousands of research articles on neuroblastoma have been published over the past few decades; however, the heterogeneity and variable quality of scholarly data may challenge scientists or clinicians to survey all of the available information. Hence, holistic measurement and analyzation of neuroblastoma-related literature with the help of sophisticated mathematical tools could provide deep insights into global research performance and the collaborative architectonical structure within the neuroblastoma scientific community. In this scientometric study, we aim to determine the extent of the scientific output related to neuroblastoma research between 1980 and 2018.

Methods

We applied novel scientometric tools, including Bibliometrix R package, biblioshiny, VOSviewer, and CiteSpace IV for comprehensive science mapping analysis of extensive bibliographic metadata, which was retrieved from the Web of ScienceTM Core Collection database.

Results

We demonstrate the enormous proliferation of neuroblastoma research during last the 38?years, including 12,435 documents published in 1828 academic journals by 36,908 authors from 86 different countries. These documents received a total of 316,017 citations with an average citation per document of 28.35?±?7.7. We determine the proportion of highly cited and never cited papers, "occasional" and prolific authors and journals. Further, we show 12 (13.9%) of 86 countries were responsible for 80.4% of neuroblastoma-related research output.

Conclusions

These findings are crucial for researchers, clinicians, journal editors, and others working in neuroblastoma research to understand the strengths and potential gaps in the current literature and to plan future investments in data collection and science policy. This first scientometric study of global neuroblastoma research performance provides valuable insight into the scientific landscape, co-authorship network architecture, international collaboration, and interaction within the neuroblastoma community.

SUBMITTER: Martynov I

PROVIDER: S-EPMC7260742 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A scientometric analysis of neuroblastoma research.

Martynov Illya I Klima-Frysch Jessica J Schoenberger Joachim J

BMC cancer 20200529 1

<h4>Background</h4>Thousands of research articles on neuroblastoma have been published over the past few decades; however, the heterogeneity and variable quality of scholarly data may challenge scientists or clinicians to survey all of the available information. Hence, holistic measurement and analyzation of neuroblastoma-related literature with the help of sophisticated mathematical tools could provide deep insights into global research performance and the collaborative architectonical structur ...[more]

PMID: 32471384

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Project description:Background:With the development of new magnetic resonance imaging (MRI) techniques, an increasing number of articles have been published regarding hepatocellular carcinoma magnetic resonance imaging (HCCMRI) in the past decade. However, few studies have statistically analyzed these published articles. In this study, we aim to systematically evaluate the scientific outcomes of HCCMRI research and explore the research hotspots from 2008 to 2017. Methods:The included articles regarding HCCMRI research from 2008 to 2017 were downloaded from the Web of Science Core Collection and verified by two experienced radiologists. Excel 2016 was used to analyze the literature data, including the publication years and journals. CiteSpace V was used to perform co-occurrence analyses for authors, countries/regions and institutions and to generate the related collaboration network maps. Reference co-citation analysis (RCA) and burst keyword detection were also performed using CiteSpace V to explore the research hotspots in the past decade. Results:A total of 835 HCCMRI articles published from 2008 to 2017 were identified. Journal of Magnetic Resonance Imaging published the most articles (79 publications, 9.46%). Extensive cooperating relationship were observed among countries/regions and among authors. South Korea had the most publications (199 publications, 21.82%), followed by the United States of America (USA) (190 publications, 20.83%), Japan (162 publications, 17.76%), and the People's Republic of China (148 publications, 16.23%). Among the top 10 co-cited authors, Bruix J (398 citations) was ranked first, followed by Llovet JM (235 citations), Kim YK (170 citations) and Forner A (152 citations). According to the RCA, ten major clusters were explored over the last decade; "LI-RADS data system" and "microvascular invasion" (MVI) were the two most recent clusters. Forty-seven burst keywords with the highest citation strength were detected over time. Of these keywords, "microvascular invasion" had the highest strength in the last 3 years. The LI-RADS has been constantly updated with the latest edition released in July 2018. However, the LI-RADS still has limitations in identifying certain categories of lesions by conceptual and non-quantitative probabilistic methods. Plenty of questions still need to be further answered such as the difference of diagnostic efficiency of each major/ancillary imaging features. Preoperative prediction of MVI of HCC is very important to therapeutic decision-making. Some parameters of Gd-EOB-DTPA-enhanced MRI were found to be useful in prediction of MVI, however, with a high specificity but a very low sensitivity. Comprehensive predictive model incorporating both imaging and clinical variables may be the more preferable in prediction of MVI of HCC. Conclusions:HCCMRI-related publications displayed a gradually increasing trend from 2008 to 2017. The USA has a central position in collaboration with other countries/regions, while South Korea contributed the most in the number of publications. Of the ten major clusters identified in the RCA, the two most recent clusters were "LI-RADS data system" and "microvascular invasion", indicative of the current HCCMRI research hotspots.

Dataset Information

A scientometric analysis of neuroblastoma research.

Background

Methods

Results

Conclusions

Publications

A scientometric analysis of neuroblastoma research.

Similar Datasets

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