由人工智能检测到的癌症进展引发的临床试验通知:随机试验
Tali Mazor1, Karim S Farhat2, Pavel Trukhanov1
1Knowledge Systems Group, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts.
JAMA network open
|April 21, 2025
概括
人工智能驱动的通知瘤学家关于基因组匹配的临床试验并没有增加患者入学率. 未来用于癌症临床试验的AI应用需要更广泛的范围,而不仅仅是治疗变化预测.
科学领域:
- 在瘤学瘤学.
- 临床试验管理 临床试验管理
- 人工智能在医学中的应用
背景情况:
- 从历史上看,成人癌症患者参加临床试验的比例仍然很低 (<10%).
- 计算工具存在于患者试验匹配,但仅限于需要新治疗的患者.
- 人工智能 (AI) 可以从成像报告中检测癌症进展.
研究的目的:
- 为了确定是否通知瘤学家关于针对AI检测癌症进展的患者的基因组定向临床试验,增加了试验参与率.
- 评估人工智能驱动的警报对临床试验招生率的影响.
主要方法:
- 一个单一中心的随机试验,涉及在精密瘤学数据库中具有固体瘤的患者.
- 患者被随机分为2:1的干预组 (AI检测到瘤学家的进展警报) 或对照组 (没有警报).
- 主要结局是参加任何治疗性临床试验.
主要成果:
- 干预没有显著影响临床试验招生率 (2.20%对2.03%,P=.41).
- 在确定为试验准备的患者或开始新系统治疗的患者中,在招募中没有发现显著差异.
- 人工智能驱动的通知没有改善治疗临床试验的入学率.
结论:
- 促使瘤学家使用人工智能识别的基因组匹配试验来发现癌症进展并没有提高招生率.
- 未来用于优化癌症临床试验招生的人工智能工具应该考虑超出治疗变化预测的更广泛应用.
- 人工智能可能需要针对不同的患者群体或结合额外的预测因素来增加试验参与.
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