Clinical Nomogram for Predicting Survival Outcomes in Early Mucinous Breast Cancer

Background
The features related to the prognosis of patients with mucinous breast cancer (MBC) remain controversial. We aimed to explore the prognostic factors of MBC and develop a nomogram for predicting survival outcomes.
Methods
The Surveillance, Epidemiology, and End Results (SEER) database was searched to identify 139611 women with resectable breast cancer from 1990 to 2007. Survival curves were generated using Kaplan-Meier methods. The 5-year and 10-year cancer-specific survival (CSS) rates were calculated using the Life-Table method. Based on Cox models, a nomogram was constructed to predict the probabilities of CSS for an individual patient. The competing risk regression model was used to analyse the specific survival of patients with MBC.
Results
There were 136569 (97.82%) infiltrative ductal cancer (IDC) patients and 3042 (2.18%) MBC patients. Patients with MBC had less lymph node involvement, a higher frequency of well-differentiated lesions, and more estrogen receptor (ER)-positive tumors. Patients with MBC had significantly higher 5 and10-year CSS rates (98.23 and 96.03%, respectively) than patients with IDC (91.44 and 85.48%, respectively). Univariate and multivariate analyses showed that MBC was an independent factor for better prognosis. As for patients with MBC, the event of death caused by another disease exceeded the event of death caused by breast cancer. A competing risk regression model further showed that lymph node involvement, poorly differentiated grade and advanced T-classification were independent factors of poor prognosis in patients with MBC. The Nomogram can accurately predict CSS with a high C-index (0.816). Risk scores developed from the nomogram can more accurately predict the prognosis of patients with MBC (C-index = 0.789) than the traditional TNM system (C-index = 0.704, P< 0.001).
Conclusions
Patients with MBC have a better prognosis than patients with IDC. Nomograms could help clinicians make more informed decisions in clinical practice. The competing risk regression model, as a more rational model, is recommended for use in the survival analysis of patients with MBC in the future.

研究背景
粘液性乳腺癌（mucinous breast cancer, MBC）患者预后相关的影响因素仍存在争议。本研究旨在探讨MBC患者的预后因素，并构建用于预测其生存结局的列线图（nomogram）。

方法
检索监测、流行病学与最终结果（Surveillance, Epidemiology, and End Results, SEER）数据库，纳入1990年至2007年间的139611例可手术切除乳腺癌女性患者。采用Kaplan-Meier法绘制生存曲线，通过寿命表法计算5年及10年癌症特异性生存（cancer-specific survival, CSS）率。基于Cox模型构建列线图，以预测个体患者的CSS发生概率；同时采用竞争风险回归模型分析MBC患者的特异性生存情况。

结果
本队列共纳入浸润性导管癌（infiltrative ductal cancer, IDC）患者136569例（占97.82%），MBC患者3042例（占2.18%）。与IDC患者相比，MBC患者的淋巴结受累比例更低，高分化病变占比更高，雌激素受体（estrogen receptor, ER）阳性肿瘤占比也更高。MBC患者的5年及10年CSS率分别为98.23%和96.03%，显著高于IDC患者的91.44%和85.48%。单因素及多因素分析结果显示，MBC是预后较好的独立影响因素。对于MBC患者而言，非乳腺癌相关死亡事件的发生率高于乳腺癌相关死亡事件。竞争风险回归模型进一步证实，淋巴结受累、低分化程度及高级别T分期是MBC患者预后不良的独立影响因素。该列线图的一致性指数（C-index）达0.816，可精准预测CSS发生概率；基于该列线图构建的风险评分，相比传统TNM分期系统（C-index=0.704，P<0.001），可更精准地预测MBC患者的预后（C-index=0.789）。

结论
MBC患者的预后优于IDC患者。列线图可辅助临床医师在临床实践中做出更合理的决策。竞争风险回归模型作为更具合理性的分析模型，建议未来应用于MBC患者的生存分析研究。