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Symptom cluster among cancer survivors from a nationally representative survey: a network analysis
Zhen Zhang1,2, Jiahui Lao3, Mingming Liu2
1School of Nursing and Rehabilitation, Cheeloo College of Medicine, Shandong University, Jinan, China.
Purpose:
To identify the symptom cluster among cancer survivors and examine their subgroup differences via network analysis based on nationally representative data.
Methods:
This cross-sectional study included 2966 survivors participating in the 2020 National Health Interview Survey (NHIS). Participants self-reported the presence of 14 symptoms capturing four clusters (physical, somatic, sleep, and psychologic problems). Network analysis models were used to reveal the relationships between symptoms and those interactions. Network comparison tests were applied to compare subgroups.
Results:
The core symptoms of the symptom cluster were fatigue (Bet = 33, Clo = 0.0067, Str = 0.9397), pain (Bet = 11, Clo = 0.0060, Str = 0.9226), wake up well rested (Bet = 25, Clo = 0.0057, Str = 0.8491), and anxiety (Bet = 5, Clo = 0.0043, Str = 0.9697) among cancer survivors. The core symptoms, network structure, and global strength were invariant between time since diagnoses (< 2 years vs. ≥ 2 years) or between numbers of cancers (1 vs. ≥ 2), yet varied between the comorbidity group and non-comorbidity group (≥ 1 vs. 0).
Conclusions:
Fatigue would be a potential target for alleviating other symptoms through a negative feedback loop of other related symptoms of cancer survivors. In particular, cancer survivors with other chronic diseases should be the focus of attention and strengthen targeted intervention.
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