Background: Patients with advanced cancer may experience symptom clusters during treatment (eg, fatigue, pain, sleep disturbance, depression). Understanding the characteristics and factors associated with symptom cluster classes among this patient population is essential for effective symptom management.
Objective: The aims of this study were to identify symptom cluster (fatigue-pain-sleep disturbance-depression) classes and explore influencing factors in patients with advanced cancer during the treatment.
Methods: A cross-sectional survey was conducted in an oncology department of a tertiary hospital in China from September 2020 to March 2021. Cancer patients (stage III/IV) 18 years or older completed the questionnaires on pain, fatigue, sleep disturbance, depression, physical activity, and exercise self-efficacy. Latent class analysis and multinomial logistic regression were used.
Results: Three hundred sixty-five patients who were male (65.2%) and younger than 60 years (59.5%) completed questionnaires. Three symptom cluster classes were identified: class 1 ("low symptom burden" class), class 2 ("fatigue-insomnia" class), and class 3 ("high symptom burden" class), with a percentage of 54.5%, 38.6%, and 6.8%, respectively. The quality-of-life score, introversion/extroversion, economic burden, Karnofsky Performance Status, albumin level, and exercise self-efficacy were significantly different among the 3 classes (P < .05).
Conclusion: Patients with advanced cancer were classified into 3 distinct classes, with class 1 having the best function. Results from this study reveal that Karnofsky Performance Status, albumin level, and exercise self-efficacy were significant factors for the latent classes of symptom cluster.
Implications For Practice: Exercise self-efficacy is important for personalized interventions and improving symptom management efficiency.
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| http://dx.doi.org/10.1097/NCC.0000000000001316 | DOI Listing |
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