Cui Xiang, Song Deba, Li Xiaoxu
Department of Thyroid and Breast Surgery, The First People's Hospital of Shangqiu, Shangqiu, China.
Front Oncol. 2021 Feb 8;10:636549. doi: 10.3389/fonc.2020.636549. eCollection 2020.
Triple-negative breast cancer (TNBC) is one of the most aggressive subtypes of breast cancer with poorest clinical outcomes. Patients of childbearing age have a higher probability of TNBC diagnosis, with more demands on maintenance and restoration of physical and psychosocial function. This study aimed to design effective and comprehensive nomograms to predict survival in these patients.
We used the SEER database to identify patients with TNBC aged between 18 and 45 and randomly classified these patients into a training (n=2,296) and a validation (n=2,297) cohort. Nomograms for estimating overall survival (OS) and breast cancer-specific survival (BCSS) were generated based on multivariate Cox proportional hazards models and competing-risk models in the training cohort. The performances of the nomograms were quantified in the validation cohort using calibration curves, time-dependent receiver operating characteristic (ROC) curves and Harrell's concordance index (C-index).
A total of 4,593 TNBC patients of childbearing age were enrolled. Four prognostic factors for OS and six for BCSS were identified and incorporated to construct nomograms. In the validation cohort, calibration curves showed excellent agreement between nomogram-predicted and actual survival data. The nomograms also achieved relatively high Harrell's C-indexes and areas under the time-dependent ROC curves for estimating OS and BCSS in both training and validation cohorts.
Independent prognostic factors were identified, and used to develop nomograms to predict OS and BCSS in childbearing-age patients with TNBC. These models could enable individualized risk estimation and risk-adapted treatment for these patients.
三阴性乳腺癌（TNBC）是侵袭性最强的乳腺癌亚型之一，临床预后最差。育龄期患者TNBC诊断概率更高，对身体及心理社会功能的维持和恢复有更多需求。本研究旨在设计有效且全面的列线图以预测这些患者的生存情况。
我们使用监测、流行病学和最终结果（SEER）数据库识别年龄在18至45岁之间的TNBC患者，并将这些患者随机分为训练队列（n = 2296）和验证队列（n = 2297）。基于训练队列中的多变量Cox比例风险模型和竞争风险模型生成了用于估计总生存期（OS）和乳腺癌特异性生存期（BCSS）的列线图。使用校准曲线、时间依赖性受试者工作特征（ROC）曲线和哈雷尔一致性指数（C指数）在验证队列中对列线图的性能进行量化。
共纳入4593例育龄期TNBC患者。确定了4个OS预后因素和6个BCSS预后因素，并将其纳入以构建列线图。在验证队列中，校准曲线显示列线图预测的生存数据与实际生存数据之间具有良好的一致性。列线图在训练队列和验证队列中估计OS和BCSS时，还获得了相对较高的哈雷尔C指数和时间依赖性ROC曲线下面积。
确定了独立的预后因素，并用于开发列线图以预测育龄期TNBC患者的OS和BCSS。这些模型能够为这些患者进行个体化风险评估和风险适应性治疗。
