Abstract:

Objective To identify distinct subgroups of breast cancer patients who were experiencing differential symptom burdens, and to analyze the risk indicators for patients with high symptom burdens. Methods A cross-sectional study design was used, and fatigue, anxiety, depression and sleep disturbance were reported by patients of a tertiary hospital in Shanghai from January 2016 to January 2017. Latent Class Model（LCM） was used to identify the characteristics of potential patient subgroups who were experiencing differential symptom burdens, and Multinominal logistic regression was conducted to identify risk indicators for patients with high-risk symptom burdens. Results 3 latent classes of symptoms were identified, which were named as “high symptom burden class”, “high psychological-related symptom burden class” and “low symptom burden class” according to the symptom characteristics of patients in different classes, accounting for 25. 0%, 19. 7% and 55. 3%, respectively. Compared to patients in the low symptom burden class, patients in the high symptom burden class reported significantly lower quality of life scores（F=55. 499, P<0. 001）. Patients in the “high symptom burden class” were characterized by significantly lower level of exercise self-efficacy（OR=0. 949, P=0. 019）, while patients in the “high psychological-related symptom burden class” were characterized by personality traits of intermediate type（OR=6. 189, P=0. 007）, no breast cancer resection（OR=4. 718, P=0. 020）, and low exercise self-efficacy level（OR=0. 926, P=0. 002）. Conclusion Distinct subgroups of patients with different symptom characters were identified, and quality of life for patients with high-risk symptom burdens were significantly poorer, while exercise self-efficacy can be used as one of the important risk indicators for recognition of high-risk patient groups. For symptom management of breast cancer patients in the future, patients should be assigned into different class memberships, so that subgroups with high symptom burden can be located and person-centered intervention tailored to an individual’s symptom cluster can be offered.

Key words: Breast Cancer, Symptom Management, Latent Class Model, Predictors, Nursing Care

摘要：

目的 探讨乳腺癌患者化疗期间症状群内部特征,并分析高症状特征患者的风险指标。方法 采用横断面研究,于2016年1月—2017年1月选取上海市某三级甲等医院228例乳腺癌患者作为研究对象,收集乳腺癌患者化疗期间疲乏、焦虑、抑郁、睡眠障碍相关自我报告症状,基于潜类别模型探讨该症状群的潜在类别,并探索不同类别间的区分指标。结果 乳腺癌患者化疗期疲乏-焦虑-抑郁-睡眠障碍症状群表现为3种不同的类别,分别命名为“高症状组”“高心理症状组”和“低症状组”,占比依次为25.0%、19.7%、55.3%。相比于“低症状组”,前两组生活质量得分较低,差异有统计学意义（F=55.499,P<0.001）。锻炼自我效能是区分和预测“高症状组”的独立指标（OR=0.949,P=0.019）;“高心理症状组”预测指标分别是中间型性格特点（OR=6.189,P=0.007）、未接受过乳腺癌切除术（OR=4.718,P=0.020）及较低的锻炼自我效能（OR=0.926,P=0.002）。结论 乳腺癌患者化疗期间症状群存在明显不同的分类特征,“高症状组”的生活质量较低,锻炼自我效能是其重要预测因子。后续对于乳腺癌患者的症状管理应根据不同患者的症状特征,给予针对性的干预。

关键词: 乳腺癌, 症状管理, 潜类别模型, 预测指标, 护理