Symptom cluster trajectories and sentinel symptoms during the first cycle of chemotherapy in patients with lung cancer

• Published in: European journal of oncology nursing : the official journal of European Oncology Nursing Society 2023-04, Vol.63, p.102282-102282, Article 102282
• Main Authors: Ju, Xiaodi, Bai, Jiayuan, She, Yiwei, Zheng, Rong, Xu, Xiuzhi, Wang, Wenru, Hong, Jingfang
• Format: Article
• Language: English
• Subjects: Cough; Fatigue; Humans; Longitudinal study; Lung cancer; Lung Neoplasms; Quality of Life; Sentinel symptom; Symptom cluster; Syndrome
• ISSN: 1462-3889; 1532-2122
• DOI: 10.1016/j.ejon.2023.102282

To investigate symptom severity, symptom cluster trajectories and sentinel symptoms during chemotherapy cycle 1 in patients with lung cancer. Patients with lung cancer were recruited to complete the MD Anderson Symptom Inventory (MDASI) and First Appearance of Symptoms Time Sheet daily during the first week of chemotherapy cycle 1. Latent class growth analysis was performed to examine symptom cluster trajectories. The Apriori algorithm combined with the time of the first appearance of symptoms after chemotherapy was used to determine the sentinel symptoms of each symptom cluster. A total of 175 lung cancer patients participated in the study. Five symptom clusters were identified: class 1 (difficulty remembering-numbness-hemoptysis-weight loss), class 2 (cough-expectoration-chest tightness-shortness of breath), class 3 (nausea-sleep disturbance-drowsiness-constipation), class 4 (pain-distress-dry mouth-sadness-vomiting), class 5 (fatigue-lack of appetite). Sentinel symptoms were found to be cough (class 2) and fatigue (class 5), while none were found for other symptom clusters. The trajectories of five symptom clusters were observed during the first week of chemotherapy cycle 1 and the sentinel symptoms of each cluster were explored. The study has important significance for the effective management of symptoms and the quality of nursing care for patients. At the same time, alleviating sentinel symptoms may reduce the severity of the whole symptom cluster, reducing medical resources and improving quality of life for lung cancer patients. •Exploring the symptom trajectory of patients with lung cancer during the first chemotherapy cycle.•Using a latent class growth analysis that explore the five symptom clusters.•The Apriori algorithm combined with the first occurrence time of symptoms was used to explore sentinel symptoms.