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Network Analysis of Cancer Patients and Symptoms : Implications for Symptom Management and Treatment

Although many cancer patients experience multiple concurrent symptoms, most studies have focused on the analysis of single symptoms. Furthermore, the few studies that have analyzed how symptoms co-occur across patients have used methods such as factor analysis that have a priori assumptions of how the data is structured. To address these limitations, we used networks to visualize how 665 cancer patients reported 18 symptoms, and verified the results using appropriate quantitative methods. The results suggest that symptoms co-occur in a nested structure, where there is a small set of symptoms that co-occur in many patients, and larger inclusive sets of symptoms that co-occur among a few patients. These results (1) demonstrate how network analyses can reveal complex relationships between patients and symptoms while avoiding a priori assumptions, and (2) provide implications for cancer treatment and management that address complexities in symptom co-occurrence.