基于竞争风险模型的浸润性乳腺癌全乳切除预后影响因素分析

Prognostic factors of patients with invasive breast cancer undergoing total mastectomy based on the competing risk model

目的利用竞争风险模型分析浸润性乳腺癌(IBC)全乳切除患者的预后影响因素,绘制列线图进行患者生存率的个体化预测。方法提取SEER数据库中诊断为IBC并行全乳切除手术患者的临床资料,基于竞争风险模型的单因素及多因素分析预后影响因素,绘制列线图预测患者术后3年及5年的生存率,采用C-index、ROC曲线及校准曲线验证预测能力。结果纳入全乳切除手术的IBC患者129808例;多因素分析结果显示,年龄、种族、婚姻状况、组织学分级、T分期、N分期、M分期、ER状态、PR状态、分子亚型、放疗及化疗为患者独立的预后影响因素;利用预后影响因素绘制列线图,3年、5年的C-index分别为0.853、0.823,ROC曲线AUC值分别为0.821、0.818,校准曲线显示预测与实际情况拟合良好。结论竞争风险模型能够有效识别IBC全乳切除患者的预后影响因素,以此为依据绘制的列线图具有良好的预测性能,可为临床医生评估患者预后及制定个体化治疗方案提供依据。

Objective To analyze the prognostic factors of patients with invasive breast cancer(IBC)undergoing total mastectomy by using a competing risk model,and to draw a nomogram for individualized prediction of survival rate.Methods The clinical data of patients with a diagnosis of IBC and total mastectomy were extracted from the SEER database,and the prognostic factors were determined by univariate and multivariate analysis based on the competing risk model.The nomogram was made to predict the 3-year and 5-year survival rate of patients after the operation,and C-index,ROC curve and calibration curve were used to validate the predictability.Results Totally 129808 IBC patients who underwent total mastectomy were included.Univariate and multivariate analysis indicated that the independent prognostic factors were age,race,marital status,histological grade,T stage,N stage,M stage,ER status,PR status,molecular subtype,radiotherapy and chemotherapy.The nomogram was drawn using prognostic factors,the C-index at 3 and 5 years was 0.853 and 0.823,and the AUC value of the ROC curve at 3 and 5 years was 0.821 and 0.818,respectively.The calibration curve showed excellent fit between prediction and actual situation.Conclusion The competing risk model can effectively identify the prognostic factors of IBC patients with total mastectomy,and the nomogram based on the model shows excellent predictive performance,which can provide foundation for clinicians to assess patient prognosis and develop individualized treatment plans.