Yi Zhang 1 , Brock E Schroeder 1 , Piiha-Lotta Jerevall 2 , Amy Ly 2 , Hannah Nolan 2 , Catherine A Schnabel 3 , Dennis C Sgroi 2 . Show Affiliations »
Abstract
Purpose: 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).Experimental Design: Analysis was conducted in a well-annotated retrospective series of pN1 patients (N = 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. Results: 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 (n = 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-χ2 = 20.12; P < 0.0001). Addition of tumor size (ΔLR-χ2 = 13.29, P = 0.0003) and grade (ΔLR-χ2 = 12.72; P = 0.0004) significantly improved prognostic performance. BCI added significant prognostic information to tumor size (ΔLR-χ2 = 17.55; P < 0.0001); addition to tumor grade was incremental (ΔLR-χ2 = 2.38; P = 0.1) with considerable overlap between prognostic values (ΔLR-χ2 = 17.74).Conclusions: 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. Clin Cancer Res; 23(23); 7217-24. ©2017 AACR. ©2017 American Association for Cancer Research.
Purpose: 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 ).Experimental Design: Analysis was conducted in a well-annotated retrospective series of pN1 patients (N = 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. Results: 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 (n = 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-χ2 = 20.12; P < 0.0001). Addition of tumor size (ΔLR-χ2 = 13.29, P = 0.0003) and grade (ΔLR-χ2 = 12.72; P = 0.0004) significantly improved prognostic performance. BCI added significant prognostic information to tumor size (ΔLR-χ2 = 17.55; P < 0.0001); addition to tumor grade was incremental (ΔLR-χ2 = 2.38; P = 0.1) with considerable overlap between prognostic values (ΔLR-χ2 = 17.74).Conclusions: 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 . Clin Cancer Res; 23(23); 7217-24. ©2017 AACR. ©2017 American Association for Cancer Research.
Entities: Disease
Gene
Species
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Year: 2017
PMID: 28939745 DOI: 10.1158/1078-0432.CCR-17-1688
Source DB: PubMed Journal: Clin Cancer Res ISSN: 1078-0432 Impact factor: 12.531