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通过临床相关指标预测ER阳性,HER2阴性乳腺癌的预后模型

Xinming Song¹, Pintian Wang¹, Ruiling Feng¹

¹Department of Oncology, The First Affiliated Hospital of Shantou University Medical College, No. 57, Changping Road, Jinping District, Shantou, 515041, Guangdong, China.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico

|September 15, 2023

概括

这项研究确定了预测ER阳性,HER2阴性乳腺癌患者无病生存 (DFS) 和整体生存 (OS) 的关键因素. 开发的诺米图准确地根据风险对患者进行分层,有助于个性化治疗策略,以获得更好的结果.

科学领域:

在瘤学瘤学.
基因组学就是基因组学.
生物统计学生物统计学

背景情况:

雌激素受体阳性 (ER阳性),HER2阴性乳腺癌构成一个重要的亚型.
准确的预后对于定制治疗策略和改善患者治疗结果至关重要.
确定无病生存期 (DFS) 和整体生存期 (OS) 的可靠预测因素至关重要.

研究的目的:

调查与ER阳性,HER2阴性乳腺癌患者中DFS和OS相关的临床病理变量.
开发和验证用于预测个体患者风险的诺姆图.
加强个性化的风险评估和治疗规划.

主要方法:

对585名 (发展) 和291名 (外部验证) ER阳性,HER2阴性乳腺癌患者的回顾性分析.
利用单变量和多变量考克斯回归分析来识别DFS和OS的独立预测因素.
生成的风险评分 (RS-OS和RS-DFS) 和验证的名录表表现.

主要成果:

病态阶段,光线亚型和临床阶段是DFS的重要预测因素.
临床阶段和内分泌治疗被确定为OS的独立预测因素.
卡普兰-梅尔曲线在低风险患者群体和高风险患者群体中显示了显著更长的DFS和OS.

结论:

结合独立预测因子的诺姆图成功开发出来,可以预测DFS和OS.
这些名录有效地将患者分为不同的预后类别.
在内部和外部验证队列中,开发的名录表显示出强大的性能.

关键词:

没有疾病的生存率.有ER阳性/HER2乳腺癌的患者.诺莫格拉姆斯 (Nomograms) 是一个名字.总体生存率总体生存率

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