实施基于规则的算法,以找到符合癌症临床试验条件的患者
Nina A Bickell1, Benjamin May2, Ihor Havrylchuk3
1Institute for Health Equity Research, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, United States.
JAMIA open
|November 19, 2024
概括
正则表达式 (RegEx) 可以简化癌症临床试验的患者识别. 这种方法减少了手动审查,提高了试验招生效率和包容性.
科学领域:
- 在瘤学瘤学.
- 生物信息学是一种生物信息学.
- 临床信息学 临床信息学
背景情况:
- 将患者与癌症临床试验相匹配是复杂的.
- 手动审查患者数据的资格是耗时的,容易产生偏见.
- 有效的患者鉴定对于及时的临床试验招生至关重要.
研究的目的:
- 探索正则表达式 (RegEx) 的使用,以自动化患者识别和分类.
- 简化将患者与相关癌症临床试验相匹配的过程.
- 评估RegEx在确定患者资格标准方面的准确性.
主要方法:
- 从NCI的临床试验搜索API中提取了资格标准.
- 收集患者数据,包括癌症类型,阶段和生物标志物状态.
- 应用RegEx以前性地识别和分类多个癌症中心和医院的合格患者.
- 将RegEx准确度与手动审查进行验证.
主要成果:
- 在治疗决策点识别患者时,RegEx显示了92%的真负率.
- 患者鉴定的真实阳性率为53%.
- 癌症分期的准确性在67%至95%之间,而受体/生物标志物状态则在76%至86%之间.
结论:
- RegEx显著减少了手动检查患者数据的需要.
- 这种方法提高了临床试验招生效率和包容性.
- 在资源有限或数据敏感的环境中,RegEx特别有利.
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