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

Rui Xie,1,* Xiao-Xin Gu,1,2,* Yin Wang1 1School of Nursing, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People’s Republic of China; 2Department of Health Education, School of International Medical Technology, Shanghai Sanda University, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yin Wang, School of Nursing, Shanghai University of Traditional Chinese Medicine, 1200 CaiLun Road, Pudong New District, Shanghai, 201203, People’s Republic of China, Tel +8618019315493, Email [email protected]: 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 (rstrength = 2.188), nausea (rstrength = 1.290), and anorexia (rstrength = 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.Keywords: chemotherapy, colorectal cancer, network analysis, symptom management, symptom network

Publication Details

Journal
Dove Medical Press (Taylor and Francis Group)
Published
2025-12-07
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Dove Medical Press (Taylor and Francis Group)
Mental Health Research Topics
article

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

article en

Abstract

Rui Xie,1,* Xiao-Xin Gu,1,2,* Yin Wang1 1School of Nursing, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People’s Republic of China; 2Department of Health Education, School of International Medical Technology, Shanghai Sanda University, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yin Wang, School of Nursing, Shanghai University of Traditional Chinese Medicine, 1200 CaiLun Road, Pudong New District, Shanghai, 201203, People’s Republic of China, Tel +8618019315493, Email [email protected]: 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 (rstrength = 2.188), nausea (rstrength = 1.290), and anorexia (rstrength = 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.Keywords: chemotherapy, colorectal cancer, network analysis, symptom management, symptom network

Dove Medical Press (Taylor and Francis Group)
Openalex Percentile: Top 32%
Mental Health Research Topics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Symptom Network Analysis in Patients Undergoing Chemotherapy for Colorectal Cancer: A Cross-Sectional Study · Dove Medical Press (Taylor and Francis Group) (2025) | TGRS Research Map | TGRS