| 汤雅洁,岳朝丽,许丽芬,徐齐宏,刘扣英.肺癌化疗患者癌因性疲乏影响因素及与生存质量、睡眠质量的关系研究[J].,2020,(22):4288-4292 |
| 肺癌化疗患者癌因性疲乏影响因素及与生存质量、睡眠质量的关系研究 |
| Investigation of Cancer-related Fatigue in Lung Cancer Patients Undergoing Chemotherapy and Its Relationship with Quality of Life and Sleep Quality |
| 投稿时间：2020-04-29 修订日期：2020-05-24 |
| DOI：10.13241/j.cnki.pmb.2020.22.019 |
| 中文关键词: 肺癌 化疗 癌因性疲乏 生存质量 睡眠质量 关系 影响因素 |
| 英文关键词: Lung cancer Chemotherapy Cancer-related fatigue Quality of life Sleep quality Relationship Influencing factors |
| 基金项目:国家自然科学基金项目（81800090） |
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| 中文摘要: |
| 摘要 目的：调查肺癌化疗患者癌因性疲乏情况，并分析癌因性疲乏与生存质量、睡眠质量的关系。方法：选取2017年3月至2019年11月期间我院收治的189例肺癌化疗患者。分别采用Piper疲乏修正量表（RPFS）评分、肺癌治疗功能评价系统（FACT-L）评分和匹兹堡睡眠质量指数（PSQI）评分对患者疲乏程度、生存质量和睡眠质量进行评价。采用Pearson检验分析癌因性疲乏与睡眠质量、生存质量的关系。采用单因素及多因素Logistic回归分析癌因性疲乏的影响因素。结果：共发放问卷189份，回收有效问卷182份，回收率为96.30%。182例肺癌化疗患者中，癌因性疲乏发生率为66.48%（121/182）。将发生癌因性疲乏的患者纳为疲乏组（n=121），未发生癌因性疲乏的患者纳为无疲乏组（n=61）。疲乏组FACT-L评分低于无疲乏组，PSQI评分高于无疲乏组（P<0.05）。Pearson相关性分析显示：RPFS评分与FACT-L评分呈负相关，而与PSQI评分呈正相关（P＜0.05）。单因素分析显示：无疲乏组与疲乏组组间比较，在文化程度、家庭月收入、血红蛋白、化疗次数、白细胞计数、临床分期、白蛋白方面比较差异均有统计学意义（P<0.05）。多因素Logistic回归分析显示：白细胞计数、家庭月收入、血红蛋白、文化程度、化疗次数、白蛋白、临床分期均为肺癌化疗患者癌因性疲乏的影响因素（P＜0.05）。结论：肺癌化疗患者癌因性疲乏越严重，其睡眠质量和生存质量越差，且癌因性疲乏的产生受多种因素的影响，临床实际中应尽可能针对癌因性疲乏的影响因素对患者进行干预。 |
| 英文摘要: |
| ABSTRACT Objective: To investigate cancer-related fatigue in lung cancer patients undergoing chemotherapy, and analyze the relationship between cancer-related fatigue and quality of life and sleep quality. Methods: 189 cases of lung cancer patients who were admitted to our hospital from March 2017 to November 2019 were selected. The clinical data of patients were collected by questionnaire. The fatigue degree of patients was evaluated by Piper Fatigue Scale (RPFS). The quality of life was evaluated by lung cancer treatment function evaluation system (FACT-L) score. Pittsburgh sleep quality index (PSQI) score was used to evaluate sleep quality. Pearson test was used to analyze the relationship between cancer-related fatigue and quality of life and sleep quality. The influencing factors of cancer-related fatigue were analyzed by univariate and multivariate Logistic regression. Results: A total of 189 questionnaires were distributed, and 182 valid questionnaires were recovered, with the recovery rate of 96.30%. In 182 cases of lung cancer patients undergoing chemotherapy, 121 cases developed cancer-related fatigue, the incidence of cancer-related fatigue was 66.48% (121/182). Patients with cancer-related fatigue were included as fatigue group (n=121), and patients without cancer-related fatigue were included as non fatigue group (n=61). The FACT-L score of fatigue group was lower than that of non fatigue group, and PSQI score was higher than that of non fatigue group (P<0.05). Pearson correlation analysis showed that RPFS score was negatively correlated with FACT-L score, but positively correlated with PSQI score (P<0.05). Univariate analysis showed that, there were significant differences in education level, family monthly income, hemoglobin, chemotherapy frequency, white blood cell count, clinical stage and albumin between the fatigue group and non fatigue group (P<0.05). Multivariate Logistic regression analysis showed that white blood cell count, family monthly income, hemoglobin, education level, chemotherapy frequency, albumin and clinical stage were the influencing factors of cancer-related fatigue in lung cancer patients undergoing chemotherapy (P<0.05). Conclusion: The generation of cancer-related fatigue in lung cancer patients undergoing chemotherapy is affected by a variety of factors, and the more severe the cancer-related fatigue is in patients, the worse their sleep quality and quality of life are. In clinical practice, intervention should be carried out for the influencing factors of cancer-related fatigue in patients as far as possible. |
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