Association of Inflammatory Cytokines With the Symptom Cluster of Pain, Fatigue, Depression, and Sleep Disturbance in Chinese Patients With Cancer

作者:Ji, Yan-Bo; Bo, Chun-Lu; Xue, Xiu-Juan; Weng, En-Ming; Gao, Guang-Chao; Dai, Bei-Bei; Ding, Kai-Wen; Xu, Cui-Ping*
来源:Journal of Pain and Symptom Management, 2017, 54(6): 843-852.
DOI:10.1016/j.jpainsymman.2017.05.003

摘要

Context. Pain, fatigue, depression, and sleep disturbance are common in patients with cancer and usually co-occur as a symptom cluster. However, the mechanism underlying this symptom cluster is unclear. Objectives. This study aimed to identify subgroups of cluster symptoms, compare demographic and clinical characteristics between subgroups, and examine the associations between inflammatory cytokines and cluster symptoms. Methods. Participants were 170 Chinese inpatients with cancer from two tertiary hospitals. Inflammatory markers including interleukin-6 (IL-6), interleukin-1 receptor antagonist, and tumor necrosis factor alpha were measured. Intergroup differences and associations of inflammatory cytokines with the cluster symptoms were examined with one-way analyses of variance and logistic regression. Results. Based on cluster analysis, participants were categorized into Subgroup 1 (all low symptoms), Subgroup 2 (low pain and moderate fatigue), or Subgroup 3 (moderate-to-high on all symptoms). The three subgroups differed significantly in Eastern Cooperative Oncology Group (ECOG) performance status, sex, residence, current treatment, education, economic status, and inflammatory cytokines levels (all P < 0.05). Compared with Subgroup 1, Subgroup 3 had a significantly poorer ECOG physical performance status and higher IL-6 levels, were more often treated with combined chemoradiotherapy, and were more likely to be rural residents. IL-6 and ECOG physical performance status were significantly associated with 1.246-fold (95% CI 1.114-1.396) and 31.831-fold (95% CI 6.017-168.385) increased risk of Subgroup 3. Conclusion. Our findings suggest that IL-6 levels are associated with cluster symptoms in cancer patients. Clinicians should identify patients at risk for more severe symptoms and formulate novel target interventions to improve symptom management.