ArticleDiscover oncology2026
Early chemotherapy symptom clusters predict quality of life and treatment adherence in lung cancer patients.
Article in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeTo identify symptom clusters in lung cancer (LC) patients during the early chemotherapy interval and evaluate their predictive value for quality of life (QoL) and treatment adherence.
methodsA total of 256 LC patients receiving chemotherapy during October 2022-October 2024 were included. Symptoms were assessed using the Chinese version of the MD Anderson Symptom Inventory-Lung Cancer module (MDASI-LC), and QoL using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30) during the early interval. Treatment adherence was quantified as relative dose intensity (RDI). Exploratory factor analysis (EFA) was employed to identify symptom clusters. Multiple linear regression analyses were conducted to examine the clusters' independent predictive effects on global health status/QoL and RDI.
resultsEFA identified four symptom clusters: somatic (drowsiness, fatigue, pain, numbness/tingling), psychological (distress, sadness, sleep disturbance), respiratory (coughing, expectoration, shortness of breath), and gastrointestinal (nausea, poor appetite, vomiting). Regression analysis revealed that the respiratory (β = -0.380, P < 0.001), psychological (β = -0.244, P < 0.001), and somatic (β = -0.175, P = 0.001) clusters were independent negative predictors of global health status/QoL. Furthermore, the respiratory (β = -0.354, P < 0.001) and somatic (β = -0.133, P = 0.012) clusters independently predicted lower RDI.
conclusionRespiratory, psychological, and somatic clusters present during the early chemotherapy interval are independent risk factors for reduced QoL and chemotherapy adherence in LC patients. Early systematic assessment and targeted management of these clusters are crucial to improve patient experience and support treatment integrity.
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