Department of Pathology and Laboratory Medicine, Emory University, 1364 Clifton Road, Suite H175, Atlanta, GA, 30322, USA.
Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA.
Breast Cancer Res Treat. 2018 Sep;171(2):303-313. doi: 10.1007/s10549-018-4832-9. Epub 2018 Jun 15.
The eighth edition of AJCC cancer staging manual incorporated biomarker status into the prognostic staging group (PSG). We used data from National Cancer Database (NCDB) to validate and improve the PSG.
All patients had surgery and at least some systemic treatment (endocrine therapy, chemotherapy or HER2 targeted therapy). Information from 420,520 patients was assessed for potential predictors of overall survival (OS), including age at diagnosis (age), tumor grade (G), hormonal receptor and HER2 status, and presence of lymph vascular invasion (LVI), stratified by stage or sub-stages. Based on the multivariate Cox analyses, we built different point systems to predict OS and evaluated the different point systems by Akaike's information criterion (AIC), Harrell's concordance index (C-index), and Uno's concordance index.
Age, G, hormonal receptor and HER2 status, LVI and being TNBC were significantly associated with OS (all P < 0.0001). Three staging systems were correlated with OS: system 1 was the conventional anatomic TNM staging; system 2 included TNM, age, G, hormonal receptor, HER2, and LVI; system 3 included TNM, age, G, TNBC versus non-TNBC, and LVI. System 3 (C-index; 0.7316; AIC: 488138.91) achieved the best balance between predictive performance and goodness-of-fit to the NCDB data as compared to system 2 (C-index: 0.7325; AIC: 498087.73) and system 1 (C-index: 0.716; AIC: 688536.49).
The new PSG is a better staging system than the conventional anatomic TNM system. Grouping breast cancer into TNBC versus non-TNBC may be simpler while retaining similar accuracy as using ER/PR/HER2 status to predict OS.
第八版 AJCC 癌症分期手册将生物标志物状态纳入了预后分期组(PSG)。我们使用国家癌症数据库(NCDB)的数据来验证和改进 PSG。
所有患者均接受了手术和至少一种全身治疗(内分泌治疗、化疗或 HER2 靶向治疗)。评估了 420520 名患者的信息,以确定总生存(OS)的潜在预测因素,包括诊断时的年龄(age)、肿瘤分级(G)、激素受体和 HER2 状态以及淋巴血管侵犯(LVI)的存在,按分期或亚分期分层。基于多变量 Cox 分析,我们构建了不同的评分系统来预测 OS,并通过赤池信息量准则(AIC)、哈雷尔一致性指数(C-index)和宇野一致性指数评估了不同的评分系统。
年龄、G、激素受体和 HER2 状态、LVI 和三阴性乳腺癌(TNBC)与 OS 显著相关(均 P<0.0001)。三个分期系统与 OS 相关:系统 1 是传统的解剖学 TNM 分期;系统 2 包括 TNM、年龄、G、激素受体、HER2 和 LVI;系统 3 包括 TNM、年龄、G、TNBC 与非 TNBC 以及 LVI。与系统 2(C-index:0.7325;AIC:498087.73)和系统 1(C-index:0.716;AIC:688536.49)相比,系统 3(C-index:0.7316;AIC:488138.91)在预测性能和与 NCDB 数据的拟合度之间达到了更好的平衡。
新的 PSG 是比传统解剖学 TNM 系统更好的分期系统。将乳腺癌分为 TNBC 与非 TNBC 可能更简单,同时保留使用 ER/PR/HER2 状态预测 OS 的类似准确性。