乳腺癌患者焦虑轨迹预测模型的开发和验证:一项回顾性研究
Xia Li1, Ben-Kai Wei2, Fan Li1
1Department of Breast Surgery, the First People's Hospital of Lianyungang, The Affiliated Hospital of Xuzhou Medical University, Lianyungang, 222000, Jiangsu Province, People's Republic of China.
Psychology research and behavior management
|February 21, 2025
概括
这项研究开发了一种预测模型,以识别乳腺癌患者治疗后持久焦虑. 该模型使用基线数据指导个性化干预,以获得更好的患者结果.
科学领域:
- 在瘤学瘤学.
- 心理学 心理学 心理学
- 生物统计学 生物统计学
背景情况:
- 乳腺癌治疗可能会导致显著的短期焦虑.
- 了解焦虑轨迹对于及时的临床干预至关重要.
研究的目的:
- 开发和验证乳腺癌患者短期焦虑轨迹的预测模型.
- 为精确的临床干预利用基线特征和初始焦虑评分.
主要方法:
- 收集了424名乳腺癌患者的基线数据.
- 在治疗后的多个时间点使用自我评价焦虑量表 (SAS) 评分来评估焦虑.
- 开发并比较了后勤回归,随机森林和极端梯度增强模型.
主要成果:
- 确定了两个主要的焦虑轨迹:逐渐减少和持续的焦虑.
- 后勤回归 (LM) 模型显示出优异的预测性能 (ROC AUC 0.822).
- 决策曲线分析证实了预测模型的临床实用性.
结论:
- 乳腺癌患者治疗后存在明显的焦虑轨迹.
- 使用基线特征进行预测建模是可行的,并有助于干预.
- 需要进一步的研究来完善和实施这些模型.
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