多发性骨髓瘤中可测量的残留疾病 (MRD) 动态以及人工智能分析的克隆多样性的影响
J Martinez-Lopez1,2, N Lopez-Muñoz3, A Chari4
1Hematology Department, Hospital 12 de Octubre, Complutense University, CNIO, Madrid, Spain. jmarti01@ucm.es.
Blood cancer journal
|August 7, 2024
概括
在多发性骨髓瘤 (MM) 中使用下一代测序 (NGS) 的最小残留疾病 (MRD) 评估预测了更长的无进展生存期 (PFS). 更深入的MRD消极性和特定的MRD动态,由AI分析,显著改善患者的结果.
科学领域:
- 血液学 血液学 血液学
- 在瘤学瘤学.
- 分子诊断学 分子诊断
背景情况:
- 最小残留疾病 (MRD) 评估是多发性骨髓瘤 (MM) 存活的关键替代标记.
- 免疫球蛋白 (Ig) 基因的下一代测序 (NGS) 为MRD检测提供了一种敏感的方法.
研究的目的:
- 评估MRD深度和克隆多样性对大量MM患者队列临床结果的长期影响.
- 评估MRD动态的预测价值,由人工智能分类,用于疾病演变和患者预后.
主要方法:
- 在2008年至2020年期间在UCSF诊断的482名MM患者的回顾性分析.
- 使用Ig基因的NGS进行的MRD评估.
- 使用Kaplan-Meier方法分析的无进展生存 (PFS) 曲线;AI用于定义MRD动态类别.
主要成果:
- 在新诊断的MM患者和复发的MM患者中,至少一次达到MRD阴性 (10^-6) 与延长的PFS有关.
- 人工智能定义的MRD动态将患者分为具有始终负的 (A),下降的 (B) 或增加/稳定的克隆 (C) 的组;A和B组显示PFS明显长于C组.
- 在尚未复发的MRD阳性患者中,与复发患者相比,观察到更高的克隆多样性.
结论:
- 通过NGS进行的MRD评估是多发性骨髓瘤中PFS的强有力的预测因素.
- MRD 动态,特别是持续的消极性或下降,与改善的生存率有显著的相关性.
- 克隆多样性评估可以补充MRD状态,以提高MM管理中的结果预测.
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