Unveiling the multi-dimensional frailty network among older cancer survivors in China: A network analysis study
Journal of Geriatric Oncology(2024)
Abstract
Introduction
Frailty has a significant impact on the overall quality of life of older cancer survivors, but the relationships among frailty symptoms are not well understood. This study aims to explore the specific associations among multidimensional symptoms of frailty among older cancer survivors by employing network analysis to provide supportive evidence for targeted interventions in the future.
Materials and Methods
Data were obtained by cluster sampling from three large Grade-A tertiary hospitals in Shandong Province, China, and collected through face-to-face interviews by trained investigators. We included patients who were diagnosed with a solid malignant tumor at the age of 60 years or older. Frailty indicators were measured by the Groningen Frailty Indicator (GFI) and analyzed primarily through network analysis, including network estimation, centrality, and stability analysis. The relative importance of a node in a network was tested by centrality analyses, and Spearman correlations were applied to estimate the relationships between symptom pairs (symptom score) and symptom clusters (standardized symptom score) in the symptom network. In terms of centrality, the indexes of strength, closeness, and betweenness were adopted to measure the importance of nodes.
Results
Five hundred and eight older cancer survivors were included, with an average age of 68.4 years (standard deviation [SD] = 5.4), and a higher proportion were male (n = 307[60.4%]). The prevalence of frailty among older cancer survivors was 58.9% (n = 299), with a mean GFI score of 4.46 (SD = 2.87). The strongest edge was between “dressing and undressing” and “going to the toilet” (r = 0.58). The nodes with the higher strength centrality were “going to the toilet” (rS=1.09), “walking around outside” (rS=0.97), and “part of social network” (rS=0.96); and the nodes with the higher closeness centrality were “mark physical fitness” (rC=0.005), “calm and relaxed” (rC=0.005), and “nervous or downhearted” (rC=0.005).
Discussion
This study demonstrated that older cancer survivors in China have a high prevalence of frailty, with self-care and social participation-related symptoms playing a key role in the multidimensional network of frailty symptoms. Psychological symptoms can rapidly influence other symptoms within this network. Therefore, prioritizing psychological symptoms in the assessment of older adults with cancer is essential for effective frailty management.
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Key words
Older,Cancer survivors,Frailty,Network analysis
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