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Background: Breast cancer patients with internal mammary lymph node (IMLN) metastasis have been shown to have poor prognosis, and the overall survival of patients was significantly different. The nomogram was developed to predict prognosis of IMLN metastasis in breast cancer patients who received neoadjuvant chemotherapy and divide the patients into different risk groups.Methods: This retrospective study included 218 breast cancer patients with IMLN metastasis who underwent neoadjuvant chemotherapy. Based on the multivariate Cox regression model, we determined independent prognostic factors in breast cancer patients with IMLN metastasis and developed a predictive nomogram using these factors. The discrimination and performance of the nomogram was assessed by C‐index, the calibration curves and decision curve analyses. Patients were stratified into the high- risk group and low-risk group based on the best cut-off risk score. The Kaplan-Meier analyses were performed between the two different risk groups to assess the predictive ability of the nomogram.Results: Menopausal status, clinical T stage, pathological Complete Response, axillary lymph node metastasis and Ki-67 were independent prognostic factors in breast cancer patients with IMLN metastasis. These prognostic factors were determined for the development of the nomogram. The C‐index of the nomogram was 0.77, which showed the nomogram provided good discernment. The calibration curves demonstrated optimal agreement between prediction by the nomogram and actual observation. The decision curve analyses further demonstrated that the nomogram had the best net benefits. The patients with IMLN metastasis were divided into high-risk group (total score ≥206.9733) and low-risk group (total score＜206.9733), and the risk group stratification confirmed that the nomogram had great capacity for distinguishing the prognosis. Conclusions: The nomogram was developed and validated to predict prognosis of IMLN metastasis in breast cancer patients with neoadjuvant chemotherapy. It might help clinicians to identify patients who need individualized treatment and active post-operative surveillance. However, it is necessary to further mine the unknown prognostic factors to optimize the nomogram, and more external validation is still required. |
