ObjectivePatients with lung cancer often experience interrelated symptoms such as fatigue, pain, and sleep disturbances during chemotherapy, forming a core symptom cluster that significantly impacts daily functioning, treatment experience, and quality of life. Currently, evidence on non-pharmacological management of this core symptom cluster is scattered, and there is a lack of standardized, patient- and caregiver-friendly guidance tools that are easy to understand and implement. This patient guideline aims to provide decision support for self-management of the core symptom cluster in patients undergoing chemotherapy for lung cancer. MethodsGuided by evidence-based methodology, qualitative interviews and on-site questionnaire surveys were conducted to identify the health-related needs of stakeholders. Domestic and international guideline websites, relevant professional association websites, and comprehensive databases were systematically searched according to the inclusion and exclusion criteria. The included literature was evaluated for quality, and recommendations were extracted, integrated, and graded to form a summary of the best evidence. Based on the identified health issues and evidence summary, preliminary recommendations for the patient guideline were developed. The recommendations were then revised through two rounds of Delphi expert consultation, and consensus was reached on the strength of recommendations, forming the final version of the patient guideline. ResultsThe patient guideline covered four major sections: screening and assessment of core symptom clusters, daily management, intervention measures, and timing of referral. The core content included nine aspects: screening of core symptom clusters, assessment, lifestyle habits, dietary interventions, sleep environment, exercise interventions, psychological interventions, Traditional Chinese Medicine interventions, and referral indications. In total, the guidelines addressed 16 health issues and provided 25 recommendations. ConclusionThe development process of this patient guideline is rigorous and fully considered the needs of patients. Expert review concludes that the recommendations are highly feasible and appropriate.
ObjectiveTo explore the dynamic evolution trajectory of symptom clusters and the influencing factors among lung cancer patients during their first chemotherapy cycle, so as to provide evidence for precise and stratified symptom management. MethodsA convenience sampling method was adopted. Incident lung cancer patients were recruited from the Cancer Hospital, Chinese Academy of Medical Sciences between December 2025 and April 2026. Longitudinal surveys were conducted at 1 day before the first chemotherapy, and on days 1, 3, 5 and 7 after chemotherapy using the general information questionnaire, the Chinese version of the M. D. Anderson Symptom Inventory-Lung Cancer Module (MDASI-LC), and the Charlson Comorbidity Index (CCI). Exploratory factor analysis was used to identify the composition of symptom clusters at different time points. Latent class mixed models (LCMM) were applied to fit the developmental trajectories of symptom clusters. The least absolute shrinkage and selection operator (LASSO) regression was used for variable screening, followed by multivariate logistic regression to analyze the influencing factors of each trajectory class. ResultsA total of 133 patients were enrolled, including 97 males and 36 females, aged 37-78 (62.54±9.27) years. Five symptom clusters were identified: respiratory symptom cluster, cough-expectoration symptom cluster, chemotherapy-related symptom cluster, gastrointestinal symptom cluster and psychological symptom cluster. All symptom clusters exhibited significant dynamic changes throughout the first chemotherapy cycle (P<0.05). Trajectory analysis revealed 2 to 3 trajectory subtypes for symptom clusters with marked heterogeneity. Most symptom clusters peaked on days 3 to 5 after chemotherapy. Multivariate logistic regression analysis, with the low-level trajectory group as reference, showed that pathological type (P<0.001) and medical insurance type [OR=0.022, 95%CI (0.000, 0.976), P=0.049] were associated with membership of respiratory symptom cluster trajectories; household per capita monthly income [OR=3.102, 95%CI (1.183, 8.129), P=0.021] and chemotherapy regimen [OR=0.306, 95%CI (0.098, 0.959), P=0.042] were associated with membership of cough-expectoration symptom cluster trajectories; smoking amount [OR=1.039, 95%CI (1.003, 1.075), P=0.011] and clinical stage [OR=0.209, 95%CI (0.045, 0.977), P=0.047] were associated with membership of gastrointestinal symptom cluster trajectories; CCI [OR=0.342, 95%CI (0.131, 0.897), P=0.029] was associated with membership of psychological symptom cluster trajectories. ConclusionSymptom clusters in lung cancer patients demonstrate obvious dynamic evolutionary characteristics and individual heterogeneity during the first chemotherapy cycle. Days 3 to 5 post-chemotherapy serve as the critical window for symptom monitoring and intervention. Medical staff should implement individualized stratified management in consideration of patients’ pathological type, economic status, comorbidity burden and treatment regimen to realize precise early warning and timely intervention of symptoms.