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卵巢癌术后患者合并抑郁的影响因素

Influencing Factors of Depression in Patients with Postoperative Ovarian Cancer

  • 摘要:
    目的 探讨卵巢癌术后患者抑郁症状的患病率,并从临床特征、心理及实验室指标多维度系统分析其影响因素。
    方法 采用横断面研究方法,纳入235例卵巢癌术后患者。使用患者健康问卷(PHQ-9)评估抑郁状况,并采用广泛性焦虑障碍量表(GAD-7)、匹兹堡睡眠质量指数(PSQI)、欧洲癌症研究与治疗组织生活质量核心问卷(EORTC QLQ-C30)、ECOG体能状态评分等工具,收集患者的人口社会学资料、临床病理特征及心理社会数据。检测外周血肿瘤标志物(CA125)、血常规、淋巴细胞亚群及血清细胞因子水平。采用单因素分析和多因素二元Logistic回归模型进行统计分析。
    结果 卵巢癌术后患者抑郁患病率为39.15%(92/235)。单因素分析显示,ECOG评分≥2分、疼痛、焦虑、睡眠质量、整体生活质量、生活满意度、肿瘤复发、累计化疗次数≥6次,以及CA125、NLR、NAR和血红蛋白水平均与抑郁相关(均P<0.05)。多因素二元Logistic回归分析结果显示,焦虑、睡眠效率、入睡时间、ECOG评分、认知功能及生活满意度是抑郁的独立危险因素(P<0.05)。实验室指标在多因素模型中未显示为独立影响因素。
    结论 卵巢癌术后患者抑郁受生理、心理、社会多因素共同影响。临床应重点关注伴有焦虑、睡眠障碍、体能状态差及生活满意度低的患者,实施早期筛查,并采取整合症状管理、心理支持与社会关怀的综合干预策略。

     

    Abstract:
    Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators.
    Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis.
    Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model.
    Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

     

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