乳腺癌患者接受化疗的症状集群研究:潜伏类分析和同时网络分析
Guangting Chang1, Xiaoyuan Lin1, Meijiao Qin1
1School of Nursing, Guangdong Pharmaceutical University, Guangzhou, China.
Asia-Pacific journal of oncology nursing
|July 8, 2024
概括
这项研究在接受化疗的乳腺癌患者中确定了两个症状负担子组. "恐慌感"和"紧张或疼痛"是核心症状,为化疗症状管理提供了有针对性的干预措施.
科学领域:
- 在瘤学瘤学.
- 心理社会瘤学
- 癌症症状管理 癌症症状管理
背景情况:
- 乳腺癌的化疗往往导致复杂的症状集群.
- 了解患者子组和核心症状对于有效管理至关重要.
研究的目的:
- 探索症状集群,并确定接受化疗的乳腺癌患者的核心症状.
- 根据症状负担和相关因素区分子组.
- 为症状管理提供有针对性的干预措施提供信息.
主要方法:
- 在中国佛山市对292名乳腺癌患者进行横截面调查.
- 使用隐性类分析 (LCA) 识别症状子组.
- 采用网络分析来确定子组内的核心症状.
主要成果:
- 出现了两个不同的子组:高症状负担 (72.3%) 和低症状负担 (27.7%).
- 社会经济因素 (教育,收入,工作状态) 和睡眠时间与子组成员关系密切.
- 发现的核心症状是"恐慌感" (全样本,2级) 和"压力或疼痛" (1级).
结论:
- 症状集群和核心症状,如恐惧,快乐,紧张和疼痛在患者子组之间有所不同.
- 研究结果可以为乳腺癌患者在化疗期间的个性化症状管理策略提供指导.
相关概念视频
Cancer Survival Analysis
340
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
340
Comparing the Survival Analysis of Two or More Groups
175
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
175


