Symptom clusters in breast cancer patients, post-chemotherapy: Prevalence, severity, and network analysis approaches

Abstract

Background: Breast cancer patients undergoing chemotherapy experience multiple symptoms that cluster together, exacerbating their overall distress and impacting their quality of life. Understanding the structure and interactions of these symptom clusters can guide more effective supportive care interventions.

Materials and Methods: A descriptive cross-sectional design was employed. This study employed network analysis to investigate the composition and structure of symptom clusters among breast cancer patients undergoing chemotherapy in selected hospitals in Delta State, Nigeria. 139 participants who had undergone chemotherapy within the past 12 weeks. Data on symptom prevalence and severity were collected using the Memorial Symptom Assessment Scale (MSAS). Symptom clustering was analysed using Principal Component Analysis (PCA), and network analysis was conducted in R (version 4.3.1) to identify key symptom interactions, using EBICglasso for network estimation.

Results: The findings showed that pain was the most prevalent symptom (80%). Lack of energy (69.5%), difficulty sleeping (63.8%), and pain (62.2%) were the most severe symptoms. Among others, difficulty swallowing (8.7%) and vomiting (6.2%) were the least severe. A symptom network analysis identified three clusters: constitutional, gastrointestinal-epithelial, and psychological. Lack of energy emerged as the most central symptom, strongly connected to drowsiness, pain, difficulty sleeping, nausea, and difficulty concentrating.

Conclusion: The study highlights fatigue as a key driver of symptom co-severity, emphasising the need for multidimensional symptom management strategies. Interventions targeting fatigue, cognitive impairments, and psychological distress may help improve patient outcomes and quality of life. Further longitudinal studies are recommended to explore symptom progression over time.