Wuxi School of Medicine, Jiangnan University, Wuxi, 214122, Jiangsu, China.
Department of Oncology, Affiliated Hospital of Jiangnan University, Wuxi, 214122, Jiangsu, China.
Support Care Cancer. 2024 Nov 26;32(12):821. doi: 10.1007/s00520-024-09032-x.
Pain-fatigue-sleep disturbance symptom cluster (PFS) was common in patients with lung cancer and seriously affected the life quality of patients. However, the heterogeneity and subgroups of PFS were unclear in lung cancer patients after chemotherapy. This study was conducted to identify distinct subgroups of PFS in patients with lung cancer after chemotherapy, and explore the differences and risk factors of PFS subgroups.
Lung cancer patients after chemotherapy were recruited. Data were collected using the Chinese version of the Brief Pain Inventory, the Cancer Fatigue Scale, and the Pittsburgh Sleep Quality Index. The latent profile analysis (LPA) was used to identify the subgroups of PFS. Univariate analysis was used to identify the differences among all subgroups. Logistic regression and restricted cubic splines were used to investigate predictors of the PFS subgroups.
Based on LPA, 512 participants were divided into four subgroups (Class 1: low pain-fatigue-sleep disturbance; Class 2: moderate pain-moderate fatigue-low sleep disturbance, Class 3: low pain-high fatigue-high sleep disturbance, and Class 4: high pain-fatigue-sleep disturbance). The univariate analysis showed that gender, body mass index (BMI), Eastern Cooperative Oncology Group (ECOG) performance status, leukocyte, neutrophils, platelet, C-reactive protein, stress, anxiety, depression, and social support were associated with PFS. The logistic regression analysis revealed that patients in Class 2 and Class 3 were more likely to experience great stress than those in Class 1. Additionally, compared to Class 1, females, lower BMI, stress, anxiety, and depression were independent predictors of Class 4.
This study successfully identified subgroups of PFS in patients with lung cancer after chemotherapy. Based on the results of this study, medical workers can identify patients with high risks for PFS and conduct more targeted interventions to improve symptom management.
疼痛-疲劳-睡眠障碍症状群(PFS)在肺癌患者中较为常见,严重影响患者的生活质量。然而,化疗后肺癌患者的 PFS 异质性和亚组尚不明确。本研究旨在确定化疗后肺癌患者 PFS 的不同亚组,并探讨 PFS 亚组的差异和危险因素。
招募化疗后的肺癌患者。使用中文版简明疼痛量表、癌症疲乏量表和匹兹堡睡眠质量指数收集数据。采用潜在剖面分析(LPA)确定 PFS 的亚组。采用单因素分析比较所有亚组之间的差异。采用逻辑回归和限制三次样条分析探讨 PFS 亚组的预测因素。
基于 LPA,512 名参与者被分为 4 个亚组(第 1 组:低疼痛-疲劳-睡眠障碍;第 2 组:中度疼痛-中度疲劳-低睡眠障碍,第 3 组:低疼痛-高疲劳-高睡眠障碍,第 4 组:高疼痛-疲劳-睡眠障碍)。单因素分析显示,性别、体重指数(BMI)、东部肿瘤协作组(ECOG)体能状态、白细胞、中性粒细胞、血小板、C 反应蛋白、压力、焦虑、抑郁和社会支持与 PFS 相关。逻辑回归分析显示,第 2 组和第 3 组患者比第 1 组患者更有可能经历较大的压力。此外,与第 1 组相比,女性、较低的 BMI、压力、焦虑和抑郁是第 4 组的独立预测因素。
本研究成功确定了化疗后肺癌患者 PFS 的亚组。基于本研究的结果,医务人员可以识别出 PFS 风险较高的患者,并进行更有针对性的干预,以改善症状管理。