A Prospective Validation Cohort Study of a Prediction Model on Non-sentinel Lymph Node Involvement in Early Breast Cancer.

BACKGROUND:Early breast cancer with one or two sentinel lymph nodes (SLNs) may omit axillary lymph node dissection (ALND) if followed by radiotherapy. However, only less than one-third of the patients have positive non-SLNs and can truly benefit from radiotherapy. Before any regional treatment decision, the risk of non-SLN metastasis must be identified. The authors previously developed a predictive model for non-SLN involvement using CK19 mRNA and contrast-enhanced ultrasound (CEUS) score in a training set. They designed a further study to evaluate the predictive effect using the model prospectively in a validation set of one or two involved SLNs. METHODS:This study identified early breast cancer patients at Zhejiang Cancer Hospital from July 2017 to June 2018. The CK19 mRNA tested by quantitative real-time polymerase chain reaction and CEUS scores were collected before surgery. Patients with one or two involved SLNs were enrolled and underwent ALND. The estimated percentage of non-SLN involvement was calculated by the authors' model formula and the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram. The false-negative rates, predictive accuracy, and area under curve (AUC) were compared between two predictive models. RESULTS:The study enrolled 235 patients, and 35.36% (83/235) of them had non-SLN involvement. The authors' model had a false-negative rate of 6% and an accuracy of 94.9%. The AUC was 0.952 (95% confidence interval [CI] 0.922-0.982), which was significantly higher than that of the MSKCC model at all three cutoff value levels. CONCLUSION:The authors' model, using CK19 mRNA and the CEUS score, showed the potential predictive value of non-SLNs before surgery for early breast cancer patients. CLINICALTRIALS REGISTRY:NCT02992067, NCT03280134.

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