目的 基于SEER数据库分析三阴性乳腺癌（TNBC）的预后,并建立Cox回归临床预测模型且进行内部验证。方法 使用SEER*Stat软件（8.4.2版）筛选2010—2015年诊断为TNBC的病例,进行单因素和Cox多因素回归以及向后逐步回归分析,明确与生存相关的独立危险因素,构建预测TNBC患者3年和5年癌症特异生存（CSS）率的Nomogram图,并用受试者工作特征曲线,Harrell’s一致性指数,临床预测模型校准曲线以及决策曲线对该模型进行评估及内部验证,以评估该模型的临床预测效能。结果 共筛选出符合纳入标准的TNBC患者5 564例,按照7∶3的比例随机拆分为训练集（n=3 894）和验证集（n=1 670）。通过单因素,多因素分析显示TNM分期、放射治疗、化学治疗以及手术和其他治疗的先后顺序是与TNBC患者CSS显著相关的独立危险因素（P<0.05）。利用上述预后相关因素建立Nomogram图模型。训练集的C-index为0.731（95%CI：0.712~0.749）,验证集的C-index为0.719（95%CI：0.688~0.749）,训练集和验证集3年和5年生存ROC曲线的曲线下面积均>0.7,区分度较好,且校准曲线拟合良好。结论 TNM分期、放射治疗、化学治疗以及手术和其他治疗的先后顺序是TNBC的独立预后因素,基于此建立的Nomogram图临床预测模型区分度、准确度以及临床适用性较好,能较好地预测TNBC患者的生存预后。

Objective To analyze the prognosis of triple negative breast cancer（TNBC）based on the SEER database,and to establish a Cox regression clinical prediction model with internal validation．Methods Cases diagnosed with TNBC from 2010 to 2015 were screened using SEER*Stat software（version 8.4.2）,and univariate and Cox multifactorial regression as well as backward stepwise regression analyses were performed to identify the independent risk factors associated with survival,and to construct a clinical prediction model for predicting the three- and five-year cancer specific survival（CSV）of TNBC patients．Survival（CSS）rates of TNBC patients at 3 and 5 years,and the model was evaluated and internally validated using the ROC curve,Harrell’s consistency index（C-index）,clinical prediction model calibration curve,and decision-making curve（DCA curve）to assess the predictive efficacy of the model for clinical prediction．Results A total of 5 564 TNBC patients meeting the inclusion criteria were screened and randomly split into a training set（n=3 894）and a validation set（n=1 670）according to a 7∶3 ratio．By univariate,multivariate analysis showed that T-stage,N-stage,M-stage,radiotherapy,chemotherapy,and the sequence of surgery and other treatments were independent risk factors significantly associated with CSS in TNBC patients．The above prognostic-related factors were utilized to build a Nomogram plot model．The C-index was 0.731（95%CI：0.712-0.749）for the training set and 0.719（95%CI：0.688-0.749）for the validation set,and the areas under the curves of the 3- and 5-year survival ROC curves of both the training and validation sets were >0.7,which was a good differentiation,and the calibration curves were well-fitted．Conclusions T-stage,N-stage,M-stage,radiotherapy,chemotherapy,and the sequence of surgery and other treatments are independent prognostic factors for TNBC,and the Nomogram clinical prediction model based on this has good differentiation,accuracy,and clinical utility,and can better predict the survival prognosis of TNBC patients．

  目的   基于SEER数据库分析三阴性乳腺癌（TNBC）的预后，并建立Cox回归临床预测模型且进行内部验证。方法   使用SEER*Stat软件（8.4.2版）筛选2010—2015年诊断为TNBC的病例，进行单因素和Cox多因素回归以及向后逐步回归分析，明确与生存相关的独立危险因素，构建预测TNBC患者3年和5年癌症特异生存（CSS）率的Nomogram图，并用受试者工作特征曲线，Harrell’s一致性指数，临床预测模型校准曲线以及决策曲线对该模型进行评估及内部验证，以评估该模型的临床预测效能。结果   共筛选出符合纳入标准的TNBC患者5 564例，按照7∶3的比例随机拆分为训练集（n=3 894）和验证集（n=1 670）。通过单因素，多因素分析显示TNM分期、放射治疗、化学治疗以及手术和其他治疗的先后顺序是与TNBC患者CSS显著相关的独立危险因素（P＜0.05）。利用上述预后相关因素建立Nomogram图模型。训练集的C-index为0.731（95%CI：0.712~0.749），验证集的C-index为0.719（95%CI：0.688~0.749），训练集和验证集3年和5年生存ROC曲线的曲线下面积均＞0.7，区分度较好，且校准曲线拟合良好。结论  TNM分期、放射治疗、化学治疗以及手术和其他治疗的先后顺序是TNBC的独立预后因素，基于此建立的Nomogram图临床预测模型区分度、准确度以及临床适用性较好，能较好地预测TNBC患者的生存预后。

    Objective  To analyze the prognosis of triple negative breast cancer（TNBC）based on the SEER database，and to establish a Cox regression clinical prediction model with internal validation．Methods  Cases diagnosed with TNBC from 2010 to 2015 were screened using SEER*Stat software（version 8.4.2），and univariate and Cox multifactorial  regression as well as backward stepwise regression analyses were performed to identify the independent risk factors associated with survival，and to construct a clinical prediction model for predicting the three- and five-year cancer specific survival（CSV）of TNBC patients．Survival（CSS）rates of TNBC patients at 3 and 5 years，and the model was evaluated and internally validated using the ROC curve，Harrell’s consistency index（C-index），clinical prediction model calibration curve，and decision-making curve（DCA curve）to assess the predictive efficacy of the model for clinical prediction．Results  A total of 5 564 TNBC patients meeting the inclusion criteria were screened and randomly split into a training set（n=3 894）and a validation set（n=1 670）according to a 7∶3 ratio．By univariate，multivariate analysis showed that T-stage，N-stage，M-stage，radiotherapy，chemotherapy，and the sequence of surgery and other treatments were independent risk factors significantly associated with CSS in TNBC patients．The above prognostic-related factors were utilized to build a Nomogram plot model．The C-index was 0.731（95%CI：0.712-0.749）for the training set and 0.719（95%CI：0.688-0.749）for the validation set，and the areas under the curves of the 3- and 5-year survival ROC curves of both the training and validation sets were ＞0.7，which was a good differentiation，and the calibration curves were well-fitted．Conclusions  T-stage，N-stage，M-stage，radiotherapy，chemotherapy，and the  sequence of  surgery and other treatments are independent prognostic factors for TNBC，and the Nomogram clinical prediction model based on this has good differentiation，accuracy，and clinical utility，and can better predict the survival prognosis of TNBC patients．