使用现实世界的数据来确定儿科患者急性化疗的发泄性
L Lee Dupuis1,2,3, Terrence Lo2, Martin Yi1
1Child Health Evaluative Sciences, Research Institute, The Hospital for Sick Children, Toronto, ON, Canada.
JCO clinical cancer informatics
|November 17, 2025
概括
这项研究使用电子健康记录数据对儿科患者的化疗疗程emetogenicity进行了分类. 结果提供了直接的儿科证据,以改善接受化疗的儿童的抗emetic选择.
科学领域:
- 儿科瘤学 儿科瘤学
- 临床药理学 临床药理学
背景情况:
- 化学疗法的直接儿科数据是稀缺的,这导致了抗选择的不确定性.
- 目前的抗选择框架缺乏特定的儿科证据.
研究的目的:
- 为了对儿科患者的化疗方案的急性emetogenicity进行分类.
- 使用电子健康记录 (EHR) 数据来分类化疗引起的吐 (CINV).
主要方法:
- 从接受化疗的儿科患者 (0-18岁) 的电子病历数据的回顾性分析.
- 数据包括化疗和抗药的使用,以及吐事件.
- 化学疗法疗法的emetogenicity被使用修订后的框架对抗emetics进行了调整.
主要成果:
- 分类了25种化疗方案的 emetogenicity: 7 种高度, 5 中等, 10 种低, 3 种最小的 emetogenic.
- 为19种治疗方案提供了新的儿科 emetogenicity 数据.
- 针对几种疗法,确定了儿科和成人 emetogenicity 分类之间的差异.
结论:
- 一种新的EHR数据提取方法为化疗 emetogenicity 分类提供了直接的儿科证据.
- 提高发性确定性有助于在儿科瘤学中有效选择抗发药物.
- 这种方法可以扩展到多机构研究,以获得更广泛的分类.
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