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中国晚期癌症患者疲劳症状的网络分析

Network analysis of fatigue symptoms in Chinese patients with advanced cancer.

作者信息

Hu Huixiu, Zhao Yajie, Luo Huanhuan, Hao Yuqing, Wang Pei, Yu Lijuan, Sun Chao

机构信息

Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.

Department of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.

出版信息

Asia Pac J Oncol Nurs. 2024 Dec 14;12:100641. doi: 10.1016/j.apjon.2024.100641. eCollection 2025 Dec.

Abstract

OBJECTIVE

This study was aimed at investigating the network structures of fatigue symptoms in patients with advanced cancer, with a focus on identifying the central symptom-an aspect crucial for targeted and effective fatigue symptom management.

METHODS

In this cross-sectional study, patients with advanced cancer were recruited from the cancer treatment center of a tertiary hospital in China between January and December of 2022. Symptom occurrence and severity were assessed with the Cancer Fatigue Scale. Network analysis was conducted to explore the network structure and identify the core fatigue symptoms.

RESULTS

The study included 416 patients with advanced cancer. Lack of energy (2.25 ​± ​1.24), lack of interest in anything (2.20 ​± ​1.22), and lack of self-encouragement (2.03 ​± ​1.25) were the most severe fatigue symptoms and belonged to the affective fatigue dimension. In the overall network, reluctance (  ​= ​5.622), a heavy and tired body (  ​= ​5.424), and tiring easily (  ​= ​5.319) had the highest strength values. All these core symptoms were classified within the physical fatigue dimension and remained stable before and after adjustment for covariates.

CONCLUSIONS

This study identified reluctance, a heavy and tired body, and tiring easily as the core fatigue symptoms in patients with advanced cancer, thus providing valuable insight to help clinical nurses formulate more effective symptom management strategies. Future interventions could assess the efficacy of targeting the central symptom cluster in alleviating other symptoms and patient burden.

摘要

目的

本研究旨在调查晚期癌症患者疲劳症状的网络结构,重点是识别核心症状——这是针对性且有效地管理疲劳症状的关键方面。

方法

在这项横断面研究中,于2022年1月至12月期间从中国一家三级医院的癌症治疗中心招募晚期癌症患者。使用癌症疲劳量表评估症状的发生情况和严重程度。进行网络分析以探索网络结构并识别核心疲劳症状。

结果

该研究纳入了416例晚期癌症患者。精力不足(2.25 ± 1.24)、对任何事情缺乏兴趣(2.20 ± 1.22)和缺乏自我激励(2.03 ± 1.25)是最严重的疲劳症状,属于情感疲劳维度。在整体网络中,不情愿(β = 5.622)、身体沉重且疲惫(β = 5.424)和容易疲劳(β = 5.319)的强度值最高。所有这些核心症状都归类于身体疲劳维度,在对协变量进行调整前后保持稳定。

结论

本研究确定不情愿、身体沉重且疲惫和容易疲劳是晚期癌症患者的核心疲劳症状,从而为临床护士制定更有效的症状管理策略提供了有价值的见解。未来的干预措施可以评估针对核心症状群缓解其他症状和减轻患者负担的疗效。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/909d/11780119/d3d7f488bc57/gr1.jpg

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