Biotheranostics, Inc., San Diego, California.
Massachusetts General Hospital, Department of Pathology, Boston, Massachusetts.
Clin Cancer Res. 2017 Dec 1;23(23):7217-7224. doi: 10.1158/1078-0432.CCR-17-1688. Epub 2017 Sep 22.
The study objective was to characterize the prognostic performance of a novel Breast Cancer Index model (BCIN), an integration of BCI gene expression, tumor size, and grade, specifically developed for assessment of distant recurrence (DR) risk in HR breast cancer patients with one to three positive lymph nodes (pN1). Analysis was conducted in a well-annotated retrospective series of pN1 patients ( = 402) treated with adjuvant endocrine therapy with or without chemotherapy using a prespecified model. The primary endpoint was time-to-DR. Results were determined blinded to clinical outcome. Kaplan-Meier estimates of overall (0-15 years) and late (≥5 years) DR, HRs, and 95% confidence interval (CIs) were estimated. Likelihood ratio statistics assessed relative contributions of prognostic information. BCIN classified 81 patients (20%) as low risk with a 15-year DR rate of 1.3% (95% CI, 0.0%-3.7%) versus 321 patients as high risk with a DR rate of 29.0% (95% CI, 23.2%-34.4%). In patients DR-free for ≥5 years ( = 349), the late DR rate was 1.3% (95% CI, 0.0%-3.7%) and 16.1% (95% CI, 10.6%-21.3%) in low- and high-risk groups, respectively. BCI gene expression alone was significantly prognostic (ΔLR-χ = 20.12; < 0.0001). Addition of tumor size (ΔLR-χ = 13.29, = 0.0003) and grade (ΔLR-χ = 12.72; = 0.0004) significantly improved prognostic performance. BCI added significant prognostic information to tumor size (ΔLR-χ = 17.55; < 0.0001); addition to tumor grade was incremental (ΔLR-χ = 2.38; = 0.1) with considerable overlap between prognostic values (ΔLR-χ = 17.74). The integrated BCIN identified 20% of pN1 patients with limited risk of recurrence over 15 years, in whom extended endocrine treatment may be spared. Ongoing studies will characterize combined clinical-genomic risk assessment in node-positive patients. .
研究目的是描述一种新型乳腺癌指数模型（BCIN）的预后性能，该模型是一种 BCI 基因表达、肿瘤大小和分级的综合指标，专门用于评估有 1-3 个阳性淋巴结（pN1）的 HR 乳腺癌患者远处复发（DR）风险。分析是在一组 well-annotated 回顾性 pN1 患者中进行的（=402），这些患者接受了辅助内分泌治疗，伴或不伴化疗，使用了预设模型。主要终点是 DR 时间。结果是盲法评估临床结果的。使用 Kaplan-Meier 估计总体（0-15 年）和晚期（≥5 年）DR、HR 和 95%置信区间（CI）。似然比统计评估了预后信息的相对贡献。BCIN 将 81 名患者（20%）归类为低风险，15 年 DR 率为 1.3%（95%CI，0.0%-3.7%），321 名患者为高风险，DR 率为 29.0%（95%CI，23.2%-34.4%）。在无 DR 持续≥5 年的患者中（=349），低危组的晚期 DR 率为 1.3%（95%CI，0.0%-3.7%），高危组为 16.1%（95%CI，10.6%-21.3%）。BCI 基因表达本身具有显著的预后意义（ΔLR-χ=20.12；<0.0001）。肿瘤大小（ΔLR-χ=13.29，=0.0003）和分级（ΔLR-χ=12.72；=0.0004）的加入显著改善了预后性能。BCI 为肿瘤大小增加了显著的预后信息（ΔLR-χ=17.55；<0.0001）；添加肿瘤分级具有增量作用（ΔLR-χ=2.38；=0.1），但预后值有很大重叠（ΔLR-χ=17.74）。综合 BCIN 确定了 20%的 pN1 患者在 15 年内复发风险有限，可以避免延长内分泌治疗。正在进行的研究将对阳性淋巴结患者的联合临床基因组风险评估进行描述。
