河北医科大学学报 ›› 2021, Vol. 42 ›› Issue (8): 900-903,943.doi: 10.3969/j.issn.1007-3205.2021.08.008

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乳腺癌患者术后抑郁情绪的危险因素及临床预测模型的建立

  

  1. 1.河北省秦皇岛市妇幼保健院手术室,河北 秦皇岛 066000;2.河北省秦皇岛市第一医院乳腺外科,
    河北 秦皇岛 066000;3.河北大学附属医院胃肠外科,河北 保定 071000
  • 出版日期:2021-08-25 发布日期:2021-08-27
  • 作者简介:吴晓(1986-),男,河北秦皇岛人,河北省秦皇岛市妇幼保健院主管护师,医学学士,从事乳腺癌患者心理护理研究。
  • 基金资助:
    秦皇岛市科学技术研究与发展计划项目(201805A158)

Risk factors of postoperative depression in patients with breast cancer and establishment of clinical predictive model

  1. 1.Department of Operating Room, Maternal and Child Health Hospital of Qinhuangdao, Hebei Province, 
    Qinhuangdao 066000, China; 2.Department of Breast Surgery, the First People′s Hospital of 
    Qinhuangdao, Hebei Province, Qinhuangdao 066000, China; 3.Department of 
    Gastrointestinal Surgery, the Affiliated Hospital of Hebei University, 
    Hebei Province, Baoding 071000, China
  • Online:2021-08-25 Published:2021-08-27

摘要: 目的  探讨乳腺癌患者术后发生抑郁的危险因素,并建立预测模型,为临床工作提供参考。
方法   选取女性乳腺癌术后患者200例,采用抑郁自评量表和家庭支持自评量表对患者进行评估,并记录其年龄、文化程度、人均月收入、医保类型、婚姻状况、肿瘤分期以及手术方式。通过多因素Logistic回归分析确定乳腺癌患者术后发生抑郁的危险因素,并采用ROC曲线评估临床预测模型的价值。
结果  多因素Logistic回归分析显示年龄小、人均月收入低、未婚/离异/丧偶是乳腺癌患者术后发生抑郁的危险因素,而家庭支持程度好、肿瘤分期早则是保护因素。临床预测模型的截断值是-0.475,曲线下面积是0.856(95%CI:0.794~0.919)。
结论  以年龄、人均月收入、婚姻状况、家庭支持程度和肿瘤分期为预测因子建立的临床预测模型对乳腺癌患者术后抑郁的发生具有良好的预测价值。


关键词: 乳腺肿瘤, 抑郁, 危险因素

Abstract: Objective  To investigate the risk factors of postoperative depression in patients with breast cancer and to establish a predictive model, thereby providing reference for clinical work. 
Methods   A total of 200 female patients with breast cancer were enrolled in this study. The patients were evaluated by the self-rating depression scale and the family support self-rating scale, and their age, education level, monthly income per capita, type of medical insurance, marital status, tumor stage and mode of operation were recorded. Multivariate Logistic regression analysis was used to determine the risk factors of postoperative depression in patients with breast cancer, and ROC curve was used to evaluate the value of clinical predictive model. 
Results  Multivariate Logistic regression analysis showed that young age, low monthly income per capita, being unmarried/ divorced/widowed were risk factors for postoperative depression in patients with breast cancer, while good family support and early tumor stage were protective factors. The cutoff value of the clinical predictive model was -0.475, and the area under curve was 0.856(95%CI:0.794-0.919). 
Conclusion  The clinical predictive model based on age, monthly income per capita, marital status, family support and tumor stage has good predictive value for postoperative depression in patients with breast cancer.


Key words: breast neoplasms, depression, risk factors