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김희준 ( Kim Hee-Jun ) -
배선형 ( Bae Sun-Hyoung ) -
박진희 ( Park Jin-Hee ) -
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Abstract
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Purpose: This study aimed to understand the knowledge structure and trends in research on cancer-relatedcognitive impairment (CRCI) in patients with non-central nervous system (non-CNS) cancer through text networkanalysis and topic modeling.
Methods: From 2011 to 2021, studies on CRCI in patients with non-CNS cancerregistered in databases including Ovid-MEDLINE, EMBASE, Cochrane, CINAHL, CENTRAL, and PsycInfo, wereextracted and cleaned into words using Python’s natural language toolkit package. Text network analysis wasperformed using the NetworkX library, and topic modeling analysis based on the latent Dirichlet allocationalgorithm was carried out using the Gensim library.
Results: In total, 24,030 keywords were extracted from theabstracts of 490 selected papers, of which “chemotherapy,” “breast cancer,” and “quality of life” showed highfrequency and centrality. As a result of the topic modeling analysis, four subject groups were derived, includingcognitive impairment due to chemotherapy, breast cancer and cognitive impairment, factors related to cognitiveimpairment, and symptom experience.
Conclusion: These findings will help cancer researchers to understand thetrends and insights of research on CRCI in patients with non-CNS cancer and suggest important areas anddirections for future studies.
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KeyWords
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Bibliometrics, Chemotherapy-Related Cognitive Impairment, Neoplasm, Social Network Analysis
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원문 및 링크아웃 정보
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등재저널 정보
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