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在早期乳腺癌患者中,CanAssist乳腺检测和PREDICT在线工具对复发风险预测的比较

Rajeev Kumar¹, Garima Daga¹, Prerit Sharma²

¹Surgical Oncology, Breast Services, Rajiv Gandhi Cancer Institute and Research Centre, New Delhi, IND.

|February 13, 2025

概括

作为一个多标志物预后工具,CanAssist乳腺 (CAB) 测试为早期乳腺癌 (EBC) 患者提供了比PREDICT在线工具更准确的风险评估. CAB更好地识别低风险患者,优化基于瘤生物学的治疗决策.

科学领域:

在瘤学瘤学.
生物标志物研究生物标志物研究
癌症预后癌症预后

背景情况:

准确的预后对于早期乳腺癌 (EBC) 治疗决策至关重要.
多标记测试和在线工具可用于风险评估.
对比不同预后方法的疗效对于临床实践至关重要.

研究的目的:

将基于免疫组织化学的CanAssist乳房 (CAB) 测试与在线预后工具PREDICT在EBC患者中的风险分层性能进行比较.
评估CAB和PREDICT之间的风险评估的一致性和差异.
确定CAB是否提供优质的预后信息,以优化EBC的治疗.

主要方法:

分析了2017年5月至2022年6月期间接受治疗的130名EBC患者的队列.
使用CanAssist乳房 (CAB) 测试和PREDICT在线工具进行了风险分层.
两种方法之间的一致性是使用kappa系数进行评估的.

主要成果:

与PREDICT (46%) 相比,CAB确定了显著更高比例的低风险患者 (61%).
CAB将28%的3级瘤分为低风险,而PREDICT将所有3级瘤分为高风险.
在使用CAB进行风险评估时,治疗遵守率高达89%.

结论:

与EBC患者的PREDICT工具相比,CanAssist乳房 (CAB) 测试提供了增强和相关的预后信息.
基于瘤生物学,CAB的风险分层是独立于年龄和临床参数的,有助于优化HR+/HER2-EBC的治疗.
通过提供更细致的风险评估,CAB证明了更精确的患者管理的潜力.

关键词:

可以帮助乳房.乳腺癌的早期发展雌激素和孕激素受体的受体她的2/neu是负的激素受体阳性激素受体阳性卡帕相关系数.卡帕相关系数.在线预测工具在线预测工具预测预测预测预测

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