Relationship between the magnitude of symptoms and the quality of life: a cluster analysis of lung cancer patients in Brazil.

Objective: Lung cancer patients often experience profound physical and psychosocial changes as a result of disease progression or treatment side effects. Fatigue, pain, dyspnea, depression, and sleep disturbances appear to be the most common symptoms in such patients. The objective of the present study was to examine the prevalence of symptoms in lung cancer patients in order to identify subgroups (clusters) of patients, grouped according to the magnitude of the symptoms, as well as to compare the quality of life among the identified subgroups.

Methods: A cross-sectional study involving agglomerative hierarchical clustering. A total of 50 lung cancer patients were evaluated in terms of their demographic characteristics and their scores on three quality of life questionnaires, namely the 30-item European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ-C30), the Functional Assessment of Cancer Therapy-Lung, and the Medical Outcomes Study 36-item Short-form Survey. The cluster analysis took into account the magnitude of the most prevalent symptoms as assessed by the EORTC QLQ-C30 symptom scale scores; those symptoms were fatigue, pain, dyspnea, and insomnia.

Results: Three clusters (subgroups)_of patients were identified on the basis of the magnitude of the four most prevalent symptoms. The three subgroups of patients were as follows: patients with mild symptoms (n = 30; 60%); patients with moderate symptoms (n = 14; 28%); and patients with severe symptoms (n = 6; 12%). The subgroup of patients with severe symptoms had the worst quality of life, as assessed by the total scores and by the integrated domains of all three instruments.

Conclusions: This study highlights the importance of symptom cluster assessment as an important tool to assess the quality of life of patients with chronic diseases, such as lung cancer.