BACKGROUND: Lung cancer has become the leading cause of cancer-related deaths in China, and patients often experience multiple symptoms and substantial discomfort. Understanding and managing concurrent symptoms of patients with lung cancer are crucial during perichemotherapy. OBJECTIVE: To determine the types and components of symptom clusters according to the severity dimension and to understand how they change over time during perichemotherapy in a homogeneous population of patients with lung cancer. METHODS: Patients were recruited using convenience sampling. The Chinese version of the MD Anderson Symptom Inventory and the revised lung cancer module were used to measure multiple symptoms at the following 3 separate points: 2 weeks before chemotherapy (T1), chemotherapy cycle 1 (T2), and chemotherapy cycle 4 (T3). Symptom clusters were identified by exploratory factor analysis. RESULTS: A total of 144 patients with non-small cell lung cancer participated in the study. Six symptom clusters were identified at the 3 time points. Among the 6 symptom clusters, 3 symptom clusters remained stable at all time points, and differences were found in symptom clusters before and after chemotherapy. CONCLUSIONS: Symptom clusters can change during perichemotherapy, showing some stability and differences over time. IMPLICATIONS FOR PRACTICE: An improved understanding of symptom cluster trajectories in patients with lung cancer may facilitate effective assessment, prevention, and management of multiple concurrent symptoms. These findings will help clinicians to develop predictive interventions and reduce the symptom burden of patients undergoing chemotherapy.
BACKGROUND:Lung cancer has become the leading cause of cancer-related deaths in China, and patients often experience multiple symptoms and substantial discomfort. Understanding and managing concurrent symptoms of patients with lung cancer are crucial during perichemotherapy. OBJECTIVE: To determine the types and components of symptom clusters according to the severity dimension and to understand how they change over time during perichemotherapy in a homogeneous population of patients with lung cancer. METHODS:Patients were recruited using convenience sampling. The Chinese version of the MD Anderson Symptom Inventory and the revised lung cancer module were used to measure multiple symptoms at the following 3 separate points: 2 weeks before chemotherapy (T1), chemotherapy cycle 1 (T2), and chemotherapy cycle 4 (T3). Symptom clusters were identified by exploratory factor analysis. RESULTS: A total of 144 patients with non-small cell lung cancer participated in the study. Six symptom clusters were identified at the 3 time points. Among the 6 symptom clusters, 3 symptom clusters remained stable at all time points, and differences were found in symptom clusters before and after chemotherapy. CONCLUSIONS: Symptom clusters can change during perichemotherapy, showing some stability and differences over time. IMPLICATIONS FOR PRACTICE: An improved understanding of symptom cluster trajectories in patients with lung cancer may facilitate effective assessment, prevention, and management of multiple concurrent symptoms. These findings will help clinicians to develop predictive interventions and reduce the symptom burden of patients undergoing chemotherapy.