Analysis of research on metabolic syndrome in cancer survivors using topic modeling and social network analysis

Abstract

This study aimed to identify the relationships between the keywords of research on metabolic syndrome in cancer survivors and the entire knowledge research structure, through topic extraction from a macro perspective. From six electronic databases, 918 studies published between 1996 and 2019 were identified and reviewed, and 365 were included. Keyword network analysis and topic modeling were applied to examine the studies. In keyword network analysis, “obesity,” “treatment,” “breast cancer,” “body mass index,” and “prostate cancer” were the major keywords, whereas “obesity” and “breast” were the dominant keywords and ranked high in frequency, degree centrality, and betweenness centrality. In topic modeling, five clustered topics emerged, namely metabolic syndrome component, post CTX(chemotherapy) sequence, prostate-specific antigen-sensitive plot, lifestyle formation, and insulin fluctuation. Topic 2, post CTX sequence, showed the highest salience in earlier studies, but this has decreased over time, and the themes of the studies have also broadened. This study may provide critical basic data for determining the changing trends of research on metabolic syndrome in cancer survivors and for predicting the direction of future research through the visualization of the effects and interactions between the major keywords in research on metabolic syndrome in cancer survivors.