A prediction model for early systemic recurrence in breast cancer using a molecular diagnostic analysis of sentinel lymph nodes: A large-scale, multicenter cohort study

利用前哨淋巴结分子诊断分析预测乳腺癌早期系统性复发的模型:一项大规模多中心队列研究

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Abstract

BACKGROUND: The one-step nucleic acid amplification (OSNA) assay can quantify the cytokeratin 19 messenger RNA copy number as a proxy for sentinel lymph node (SN) metastasis in breast cancer. A large-scale, multicenter cohort study was performed to determine the prognostic value of the SN tumor burden based on a molecular readout and to establish a model for the prediction of early systemic recurrence in patients using the OSNA assay. METHODS: SN biopsies from 4757 patients with breast cancer were analyzed with the OSNA assay. The patients were randomly assigned to the training or validation cohort at a ratio of 2:1. On the basis of the training cohort, the threshold SN tumor burden value for stratifying distant recurrence was determined with Youden's index; predictors of distant recurrence were investigated via multivariable analyses. Based on the selected predictors, a model for estimating 5-year distant recurrence-free survival was constructed, and predictive performance was measured with the validation cohort. RESULTS: The prognostic cutoff value for the SN tumor burden was 1100 copies/μL. The following variables were significantly associated with distant recurrence and were used to construct the prediction model: SN tumor burden, age, pT classification, grade, progesterone receptor, adjuvant cytotoxic chemotherapy, and adjuvant anti-human epidermal growth factor receptor 2 therapy. The values for the area under the curve, sensitivity, specificity, and accuracy of the prediction model were 0.83, 63.4%, 81.7%, and 81.1%, respectively. CONCLUSIONS: Using the OSNA assay, the molecular readout-based SN tumor burden is an independent prognostic factor for early breast cancer. This model accurately predicts early systemic recurrence and may facilitate decision-making related to treatment.

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