Dataset Information

Bibliometric Analysis of the Top-Cited Publications and Research Trends for Stereotactic Body Radiotherapy.

ABSTRACT:

Objective

This study aims to analyze the 100 most cited papers and research trends on stereotactic body radiotherapy (SBRT).

Methods

We used Web of Science to identify the 100 most frequently cited papers on SBRT on September 29, 2021 and extracted the following data: publication year, source title, country/region, organization, total citations, and average number of citations per year. The research type and research domain were classified independently by the authors. Then we carried out a bibliometric analysis to determine the trends in research on SBRT.

Results

These 100 papers were cited a total of 26,540 times, and the median number of citations was 190 (range, 138-1688). "Stereotactic body radiation therapy for inoperable early stage lung cancer" by Timmerman et al. had the highest number of total citations (1688 times). International Journal of Radiation Oncology, Biology, Physics published the largest number of papers (37 papers), followed by Journal of Clinical Oncology (13 papers). The USA contributed the most papers (67 papers), followed by Canada (18 papers). Primary lung cancer (33 papers, 10,683 citations) and oligometastases (30 papers, 7,147 citations) were the most cited research areas.

Conclusions

To the best of our knowledge, this is the first bibliometric analysis of the most frequently cited papers on SBRT. Our results provide insight into the historical development of SBRT and important advances in its application to cancer treatment. Early-stage non-small-cell lung cancer and oligometastases were the most cited research areas in the top 100 publications on SBRT, and SBRT combined with immunotherapy was a hot topic in the past few years. This study is helpful for researchers to identify the most influential papers and current research hotspots on SBRT.

SUBMITTER: Liu Y

PROVIDER: S-EPMC8677697 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundPublications regarding the 100 top-cited articles in a given discipline are common, but studies reporting the association between article topics and their citations are lacking. Whether or not reviews and original articles have a higher impact factor than case reports is a point for verification in this study. In addition, article topics that can be used for predicting citations have not been analyzed. Thus, this study aims to METHODS:: We searched PubMed Central and downloaded 100 top-cited abstracts in the journal Medicine (Baltimore) since 2011. Four article types and 7 topic categories (denoted by MeSH terms) were extracted from abstracts. Contributors to these 100 top-cited articles were analyzed. Social network analysis and Sankey diagram analysis were performed to identify influential article types and topic categories. MeSH terms were applied to predict the number of article citations. We then examined the prediction power with the correlation coefficients between MeSH weights and article citations.ResultsThe citation counts for the 100 articles ranged from 24 to 127, with an average of 39.1 citations. The most frequent article types were journal articles (82%) and comparative studies (10%), and the most frequent topics were epidemiology (48%) and blood and immunology (36%). The most productive countries were the United States (24%) and China (23%). The most cited article (PDID = 27258521) with a count of 135 was written by Dr Shang from Shandong Provincial Hospital Affiliated to Shandong University (China) in 2016. MeSH terms were evident in the prediction power of the number of article citations (correlation coefficients = 0.49, t = 5.62).ConclusionThe breakthrough was made by developing dashboards showing the overall concept of the 100 top-cited articles using the Sankey diagram. MeSH terms can be used for predicting article citations. Analyzing the 100 top-cited articles could help future academic pursuits and applications in other academic disciplines.