From malnutrition to multimodal care: a bibliometric and knowledge mapping analysis of frailty research in cancer

Abstract

Background – Frailty and malnutrition are highly prevalent, interrelated syndromes in cancer that significantly impact treatment tolerance, clinical outcomes, and quality of life. Despite rapid growth in research over the past two decades, the structure, evolution, and emerging frontiers of this field remain unclear. This study presents a comprehensive bibliometric and knowledge-mapping analysis of global research on frailty and nutrition in cancer, using data from the Web of Science Core Collection (WoSCC) and Scopus databases, to identify major contributors, research hotspots, and future trends. Methods – Publications related to frailty and nutrition in cancer from 2005 to 2025 were retrieved from WoSCC and Scopus on September 30, 2025. Bibliometric and knowledge mapping were analyzed using CiteSpace, VOSviewer, and bibliometrix. Results – A total of 2, 887 publications were identified, showing a substantial surge in output after 2020, with projections indicating a peak around 2032. The field is currently dominated by research in oncology, biochemistry, and rehabilitation disciplines. Recent studies emphasize the development of standardized diagnostic criteria, mechanistic insights, and multimodal management strategies. Keyword burst and trend analyses identified several emerging frontiers including cholesterol blood level, lymph node metastasis, short physical performance battery (SPPB), liver disease, and mini nutritional assessment short-form (MNA-SF). Conclusion – Global research on frailty and nutrition in cancer has evolved from descriptive epidemiology to evidence-based, precision, and integrative frameworks combining clinical nutrition, geriatric oncology, and rehabilitation science. Current research hotspots emphasize prehabilitation, multimodal interventions, and the integration of functional, metabolic, and imaging markers into personalized care. Future directions should focus on developing predictive models, digital health-enabled assessments, and multicenter translational collaborations to improve early detection, optimize interventions, and inform patient-centered, policy-driven cancer care strategies.