Based on data from the surveillance， epidemiology， and end results （SEER） database， breast cancer patients between 2010 and 2016 were analyzed retrospectively. The factors affecting the overall survival rate of male breast cancer were screened and modeled by univariate and multivariate Cox regression analysis. The Nomogram prediction model was performed by R software. Using the C-index， calibration curves were used to evaluate the consistency and predictive ability of the Nomogram prediction model.

3 029 patients with breast cancer were included. Molecular subtypes Luminal A， Luminal B， HER2 overexpressing and triple negative breast cancer accounted for 84.9%， 12.1%， 0.9% and 2.1%. Multivariate Cox regression analysis showed that age （P < 0.001）， marital status （P = 0.001）， histologic grade（P < 0.001）， type of surgery （P < 0.001）， tumor invasion and spread （P = 0.026）， T staging （P < 0.001）， molecular subtype （P < 0.001）， tumor size （P = 0.001）， and bone metastasis （P = 0.024） were independent prognostic factors for the overall survival. A Nomogram predictive model was established based on the significant clinicopathological parameters obtained by multivariate Cox regression to evaluate the competitive risk affecting overall survival and to quantify survival differences. The internal verification results of the Nomogram prediction model show that the C-index was 7.477 （95% CI： 0.722 ~ 0.772）， and the correction curves of 3 years and 5 years show that the line diagram had good prediction ability.

Nomogram model has good prediction ability and can be used as a tool for prognosis monitoring of male breast cancer patients.

本研究通过回顾性分析SEER数据库2010年至2016年男性乳腺癌患者的临床资料，采用单因素和多因素Cox回归分析影响男性乳腺癌患者根治术后预后的独立因素，并基于独立预后因素绘制Nomogram预测模型。

共3 029例男性乳腺癌患者纳入本研究，分子分型Luminal A型、Luminal B型、HER-2过度表达型、Basal-like型（三阴性乳腺癌）占比分别为84.9％，12.1％，0.9％，2.1％。采用单因素和多因素Cox回归分析，结果显示年龄（P < 0.001）、婚姻状况（P = 0.001）、分化程度（P < 0.001）、肿瘤大小（P = 0.001）、肿瘤浸润和扩散程度（P = 0.026）、T分期（P < 0.001）、分子分型（P < 0.001）、骨转移（P = 0.024）、手术类型（P < 0.001）是男性乳腺癌患者总生存期的独立预后因素。将多因素Cox回归分析得到的显著临床病理参数建立Nomogram预测模型来评估影响患者总生存期的竞争性风险和量化生存差异。Nomogram预测模型的内部验证结果表明，一致性指数（C-index）为0.747（95% CI：0.722 ~ 0.772），并且3年、5年生存率的校正曲线显示列线图预测能力较好。

男性乳腺癌患者Nomogram预测模型具有较好的预测能力，可作为男性乳腺癌患者预后监测的一种评价工具。