宫颈癌患者焦虑、抑郁的影响因素及其预测模型构建-现代医学

宫颈癌患者焦虑、抑郁的影响因素及其预测模型构建

单位：南京医科大学附属妇产医院(南京市妇幼保健院) 妇科, 江苏南京 210000

分类号：R737.33

出版年·卷·期（页码）：2025·53·第一期（34-42）

摘要：

目的: 探讨宫颈癌患者发生焦虑、抑郁的危险因素，构建并验证其预测模型。方法: 回顾性收集2019年1月至2024年1月我院收治的妇科宫颈癌患者为研究对象，收集并记录患者的临床资料、问卷调查资料，根据是否发生焦虑、抑郁分为焦虑抑郁组159例，对照组79例。采用多元有序Logistic回归进行危险因素分析，根据结果初步构建预测模型，并采用ROC曲线进行模型验证。结果: 多因素回归分析显示，主要照顾者、临床分期、治疗方案、术后并发症、癌因性疲乏评分、希望评分、自我负担感受评分、睡眠质量评分、宫颈癌相关生活质量评分是宫颈癌患者发生焦虑、抑郁的影响因素(P<0.05)；风险预测模型经受试者工作特征(ROC)曲线验证，结果显示曲线下面积(AUC)为0.829、预测灵敏度为81.76%、特异度为91.03%。结论: 本研究风险预测模型具有良好的预测价值，有助于临床护理人员对高危患者做出校准及区分，有针对性地采取相应的护理对策，对临床预防宫颈癌患者发生焦虑、抑郁具有一定的价值。

Objective: To explore the risk factors of anxiety and depression in patients with cervical cancer, and to construct and validate a prediction model. Methods: Patients with cervical cancer admitted to our hospital between January 2019 and 2024 were selected and retrospectively analyzed. Clinical data from electronic medical record and questionnaire survey were collected and recorded. According to whether anxiety and depression occurred, patients were divided into anxiety group(159 cases) and control group(79 cases). Logistic regression was used for risk factor analysis，and the prediction model was constructed based on the results. Receiver operator characteristic(ROC)curve was used to validate the performance of the prediction model. Results: Multivariate analysis showed that the main caregivers, clinical stages, treatment regimen, post-operative complications, cancer fatigue score, Herth Hope Index Score, Self-Burden Perception score, Pittsburgh sleep quality index and functional assessment of cancer therapy-cervix score were the influencing factors(P<0.05). The area under the curve of the prediction model was 0.829 with the specificity and sensitivity of 81.76% and 91.03% respectively. Conclusion: The risk prediction model based on above-mentioned factors has a good predictive value for anxiety and depression in patients with cervical cancer, which can help clinical nurses to make intuitive evaluation for high-risk patients and take corresponding countermeasures.

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