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Updated: Jun 21, 2025

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An R-Based Landscape Validation of a Competing Risk Model
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开发和验证临床风险评分名录仪,用于预测5mg/L以上的伏利可纳的最低度:一项回顾性队列研究
Mengyuan Xie1,2, Manxue Jiang1,2, Jian Xu1,2
1Department of Pharmacy, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
Journal of chemotherapy (Florence, Italy)
|July 9, 2024
概括
这项研究确定了诸如年龄,体重,CYP2C19基因型和专蛋白等关键因素,这些因素可以预测高可纳 (VRC) 血水平. 一种名目录模型有助于早期查风险高的VRC毒性患者.
科学领域:
- 药理学 药理学是指药理学的学科.
- 临床药房 临床药房
- 治疗药物监测 治疗药物监测
背景情况:
- 抗真菌药物沃里康纳 (VRC) 的治疗指数很窄,需要仔细监测.
- 高血RC (>5 mg/L) 度可能导致毒性,需要确定预测因素.
- 开发一个预测模型可以帮助优化VRC剂量和患者管理.
研究的目的:
- 调查与血度 (> 5 mg/L) 升高的伏利康纳相关的因素.
- 开发和验证用于预测高VRC血水平的临床风险评分编号.
- 为风险患者群体提供早期识别和干预的工具.
主要方法:
- 对接受voriconazole的221名患者的临床数据进行了回顾性分析.
- 随机将患者分为培训 (70%) 和验证 (30%) 队列.
- 单变量和二进制物流回归以确定独立的风险因素;使用AUC和决策曲线分析构建和验证名ogram.
主要成果:
- 年龄,体重,CYP2C19基因型和血清白蛋白被确定为VRC血度> 5 mg/L的独立预测因素.
- 诺莫格拉姆模型表现出良好的预测性能,AUC值为0.841 (训练) 和0.802 (验证).
- 决策曲线分析表明,开发的名图表具有良好的临床适用性.
结论:
- 一个整合年龄,体重,CYP2C19基因型和专蛋白的诺姆图有效预测高子度的血.
- 这种预测工具可以帮助临床医生在早期查和及时干预VRC毒性风险患者.
- 诺米图作为个性化沃里可纳治疗管理的宝贵参考.
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