风险预测模型作为管理癌症相关疲劳的新兴趋势:系统性审查
Yun Zhang1, Linna Li1, Xia Li2
1West China School of Nursing, Sichuan University/Department of Nursing, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
Journal of advanced nursing
|December 15, 2024
概括
这项系统性审查发现,虽然与癌症相关的疲劳预测模型显示出希望,但大多数方法限制阻碍了临床使用. 未来的研究应该提高公平的精确护理的实用性和成本效益.
科学领域:
- 在瘤学瘤学.
- 生物统计学 生物统计学
- 基于证据的医学 基于证据的医学
背景情况:
- 与癌症相关的疲劳 (CRF) 显著影响患者的生活质量.
- 准确预测CRF对于及时干预和个性化护理至关重要.
- 现有的CRF风险预测模型需要进行系统的评估.
研究的目的:
- 系统地识别,描述和评估癌症相关疲劳的当前风险预测模型.
- 评估这些模型的方法质量和临床适用性.
主要方法:
- 对开发CRF风险预测模型的研究进行系统审查.
- 从创立到2024年9月,在七个数据库中进行了搜索.
- 使用预测模型偏差风险评估工具评估偏差风险和适用性.
主要成果:
- 包括18项研究,开发各种癌症 (如乳腺癌,肺癌) 的模型.
- 常见的预测因素包括焦虑,抑郁,年龄,化疗,睡眠质量和疼痛.
- 大多数模型显示出良好的预测性能,但方法上的限制 (例如,数据处理,变量失衡) 是普遍存在的,增加了偏差的风险.
结论:
- 与癌症相关的疲劳预测模型为改善管理和精确护理提供了潜力.
- 然而,重要的方法缺陷限制了它们目前的临床应用.
- 未来的研究必须优先考虑临床效用,预测准确性和成本效益,以确保公平的实施.
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