School of Public Health, Weifang Medical University, 7166# Baotong West Street, Weifang, Shandong 261053, China; Office of the President, Shandong Cancer Prevention and Treatment Institute (Shandong Cancer Hospital), Cancer Hospital Affiliated to Shandong First Medical University (Shandong Academy of Medical Sciences), Jinan, Shandong 250117, China.
Office of the President, Shandong Cancer Prevention and Treatment Institute (Shandong Cancer Hospital), Cancer Hospital Affiliated to Shandong First Medical University (Shandong Academy of Medical Sciences), Jinan, Shandong 250117, China.
J Affect Disord. 2024 Feb 15;347:327-334. doi: 10.1016/j.jad.2023.11.061. Epub 2023 Nov 20.
Depressed mood affects a significant number of patients with cancer, and can impair their quality of life and interfere with successful treatment. Our study aims to create a predictive model for identifying high-risk groups of depressed mood in cancer patients, offering a theoretical support for preventing depressed mood in these individuals.
The China Health and Retirement Longitudinal Study (CHARLS) provided the data for this research, which used CES-D as a tool to identify individuals with depressed mood. Influencing factors of depressed mood in cancer patients was analyzed using a binary logistic regression model. Using the Harvard Cancer Index, we classified the high-risk patients for depressed mood.
In present study, 52.96 % of cancer patients met criteria for depressed mood based on the CES-D. Significant correlations were found between depressed mood and factors such as gender, self-rated health, sleep duration, exercise, satisfaction with family, residence, education, life satisfaction, and medical insurance. Utilizing the Harvard Cancer Index, we classified patients into five risk levels for depressed mood, revealing a significant variation in the number of depressive patients across these levels (x=99.82, P < 0.05). Notably, the incidence of depressed mood increased with the risk level among cancer patients (x=103.40, P < 0.05).
Lack of data on tumor typing and subgroups makes it unlikely to explore the specifics of depressed mood in patients with various types of cancer.
The determinants of depressed mood in cancer patients are multi-dimensional. The Harvard Cancer Index may be helpful in identifying high-risk populations.
抑郁情绪影响着大量癌症患者，会降低他们的生活质量，并干扰治疗的成功进行。我们的研究旨在建立一个预测模型，以识别癌症患者中抑郁情绪的高危人群，为这些个体预防抑郁情绪提供理论支持。
本研究采用中国健康与养老追踪调查（CHARLS）的数据，使用 CES-D 量表来识别抑郁情绪患者。采用二项逻辑回归模型分析癌症患者抑郁情绪的影响因素。利用哈佛癌症指数（Harvard Cancer Index）对抑郁情绪高危患者进行分类。
本研究中，52.96%的癌症患者根据 CES-D 标准符合抑郁情绪标准。抑郁情绪与性别、自评健康、睡眠时间、运动、家庭满意度、居住地、教育程度、生活满意度和医疗保险等因素显著相关。利用哈佛癌症指数，我们将患者分为五个抑郁情绪风险水平，发现这些水平之间抑郁患者的数量存在显著差异（x=99.82，P<0.05）。值得注意的是，癌症患者的抑郁情绪发生率随着风险水平的增加而增加（x=103.40，P<0.05）。
缺乏肿瘤类型和亚组的数据，使得我们不太可能探讨不同类型癌症患者抑郁情绪的具体情况。
癌症患者抑郁情绪的决定因素是多维度的。哈佛癌症指数可能有助于识别高危人群。
