背景:一些指南建议使用不同的分类器来确定HR+HER2-乳腺癌患者的复发风险(ROR)和治疗决策。然而,在拉丁美洲(LA)患者中仍缺乏其有用性的数据。我们的目的是评估真实世界LA队列中不同ROR分类器的比较预后和预测性能。
方法:乳腺癌分子谱研究(MPBCS)是一项LA病例队列研究,随访5年。第一阶段和第二阶段,接受辅助激素治疗和/或化疗的临床淋巴结阴性HR+HER2-患者(n=340),进行了分析。随时间变化的接受者-操作者特征-曲线下面积,使用单变量和多变量Cox比例风险回归(CPHR)模型比较了几种风险生物标志物的预后表现.具有相互作用模型的多变量CPHR测试了选定风险分类器的预测能力。
结果:在此队列中,基于转录组的分类器,如复发评分(RS),EndPredict(EP风险和EPClin),和PAM50复发风险评分(ROR-S和ROR-PC)对淋巴结阴性患者的预后表现(单变量C指数0.61-0.68,校正C指数0.77-0.80,高和低风险之间的校正风险比[HR]:4.06-9.97)优于传统分类器Ki67和诺丁汉预后指数(单变量C指数0.53-0.59,校正C-72-85),1.54.RS(在某种程度上,EndoPredict)还显示了淋巴结阴性患者化疗获益的预测能力(相互作用P分别为.0200和.0510)。
结论:总之,我们可以证明大多数基于转录组的风险分类器的临床有效性,以及它们在异质性中优于基于临床和免疫组织化学的方法,真实世界节点阴性HR+HER2-MPBCS队列。
BACKGROUND: Several guidelines recommend the use of different classifiers to determine the risk of recurrence (ROR) and treatment decisions in patients with HR+HER2- breast cancer. However, data are still lacking for their usefulness in Latin American (LA) patients. Our aim was to evaluate the comparative
prognostic and predictive performance of different ROR classifiers in a real-world LA cohort.
METHODS: The Molecular Profile of Breast Cancer Study (MPBCS) is an LA case-cohort study with 5-year follow-up. Stages I and II, clinically node-negative HR+HER2- patients (n = 340) who received adjuvant hormone therapy and/or chemotherapy, were analyzed. Time-dependent receiver-operator characteristic-area under the curve, univariate and multivariate Cox proportional hazards regression (CPHR) models were used to compare the
prognostic performance of several risk biomarkers. Multivariate CPHR with interaction models tested the predictive ability of selected risk classifiers.
RESULTS: Within this cohort, transcriptomic-based classifiers such as the recurrence score (RS), EndoPredict (EP risk and EPClin), and PAM50-risk of recurrence scores (ROR-S and ROR-PC) presented better
prognostic performances for node-negative patients (univariate C-index 0.61-0.68, adjusted C-index 0.77-0.80, adjusted hazard ratios [HR] between high and low risk: 4.06-9.97) than the traditional classifiers Ki67 and Nottingham
Prognostic Index (univariate C-index 0.53-0.59, adjusted C-index 0.72-0.75, and adjusted HR 1.85-2.54). RS (and to some extent, EndoPredict) also showed predictive capacity for chemotherapy benefit in node-negative patients (interaction P = .0200 and .0510, respectively).
CONCLUSIONS: In summary, we could prove the clinical validity of most transcriptomic-based risk classifiers and their superiority over clinical and immunohistochemical-based methods in the heterogenous, real-world node-negative HR+HER2- MPBCS cohort.