癌症患者化疗诱导的恶心和吐的风险预测模型:系统性审查
Yongjian Wang1, Ruishuang Zheng1, Yunting Wu1
1Department of Hepatobiliary Oncology, Tianjin Medical University Cancer Hospital and Institute, National Clinical Research Centre for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Centre for Cancer, Tianjin, China.
International journal of nursing studies
|May 3, 2025
概括
这一系统性审查发现,虽然化疗诱导的恶心和吐 (CINV) 预测模型显示出希望,但大多数都有方法上的缺陷. 深森林模型,考虑到肌素清除和年龄等因素,表现良好,但需要进一步验证.
科学领域:
- 在瘤学瘤学.
- 临床预测建模临床预测建模
- 证据综合 证据综合
背景情况:
- 化疗诱导的恶心和吐 (CINV) 对癌症患者和医疗保健系统构成重大负担.
- 现有的CINV风险预测模型往往缺乏明确的方法质量和适用性评估.
- 本研究解决了对当前CINV预测模型进行全面评估的需求.
研究的目的:
- 系统地审查和批判性地评估现有的癌症患者中CINV风险预测模型.
- 在不同的建模方法中识别CINV的常见和新预测因素.
- 评估这些预测模型的方法质量和潜在适用性.
主要方法:
- 在多个数据库 (PubMed,Embase,Web of Science等) 中进行系统搜索. 在2024年10月1日之前进行.
- 包含62个CINV预测模型的17项研究使用PROBAST和CHARMS工具进行了批判性评估.
- 数据提取和偏差风险评估由两位作者独立进行.
主要成果:
- 与传统模型相比,深森林模型表现出更好的区分和校准.
- 深森林模型确定的主要预测因素包括肌素清除率,年龄,性别,预期性恶心和吐以及抗治疗方案.
- 研究中常见的预测因素是年龄,化疗方案,之前的CINV发作和性别.
- 所有纳入的研究都呈现出高偏差风险,主要是由于参与者和分析领域的报告不佳.
- 九项研究对其开发的模型的适用性提出了担忧.
结论:
- 关于CINV预测模型的研究仍在发展,预测器的共同点和变异已被确定.
- 尽管性能可接受,但大多数CINV模型都存在方法限制,缺乏外部验证.
- 未来的研究应该遵循TRIPOD的指导方针,并优先考虑更大的样本大小和多中心外部验证,以提高模型的稳定性.
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