Symptom Network Analysis in Patients Undergoing Chemotherapy for Colorectal Cancer: A Cross-Sectional Study.

[OBJECTIVE] This study aimed to construct a symptom network in patients diagnosed with colorectal cancer (CRC) undergoing chemotherapy, thereby providing a theoretical framework for optimizing symptom management strategies.

[METHODS] A cross-sectional survey was conducted among 261 patients with CRC receiving chemotherapy across five tertiary care hospitals in Shanghai, selected through convenience sampling. Network analysis was applied to construct the symptom network and to determine centrality indices, including strength centrality. Model accuracy and stability were evaluated using nonparametric bootstrapping techniques.

[RESULTS] Symptom prevalence ranged from 5.4% to 85.8%, with severity scores ranging from 0.51±1.44 to 4.83±3.23. Fatigue was associated with the highest severity score. Depression ( = 2.188), nausea ( = 1.290), and anorexia ( = 1.223) demonstrated the highest strength centrality values. The constructed network model exhibited high accuracy and stability, as indicated by narrow confidence intervals and Correlation Stability (CS) coefficients exceeding 0.25.

[CONCLUSION] This study is among the first to apply network analysis to chemotherapy-related symptom interactions and potential mechanisms in CRC, highlighting central targets for intervention. These findings may inform more precise and efficient symptom management approaches in oncology care.