Zhang Guangwen, Wang Xinle, Cheng Chen, Wang Shiming, Guo Yujun
First Clinical Medical College of Shanxi Medical University, Taiyuan, 030001, Shanxi, China.
Department of Breast Surgery, First Hospital of Shanxi Medical University, Taiyuan, 030001, Shanxi, China.
Discov Oncol. 2025 May 23;16(1):876. doi: 10.1007/s12672-025-02732-8.
Young triple negative breast cancer (YTNBC) patients often face poor survival outcomes. Given the high-risk nature of YTNBC, there is an urgent need for tools that can accurately predict patient outcomes and guide personalized treatment strategies. Prognostic models, particularly those in the form of nomograms, have gained popularity in oncology for their ability to integrate multiple clinical variables to estimate individual patient survival. Our study aimed to investigate independent prognostic factors in YTNBC patients and develop a nomogram to predict OS, thereby helping patients choose a better therapeutic approach.
Patients diagnosed with YTNBC between January 2010 and December 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled and randomly divided into training and validation cohorts at a ratio of 7:3. Univariate and multivariate Cox analyses were conducted to identify significant factors associated with prognosis, which were then used to construct a nomogram for predicting 1-, 3-, and 5-year OS.
Nine survival predictors (marital status, tumor grade, AJCC stage, T stage, N stage, M stage, surgery, bone metastases, brain metastases) were selected for nomogram construction. The concordance indexes (C-index), in the training and validation cohorts were 0.749 and 0.745, respectively. The nomogram model demonstrated good calibration, and time-dependent receiver operating characteristic (ROC) curves confirmed its superiority for clinical utility. Additionally, Kaplan-Meier survival curves of various independent prognostic factors validated the model.
The novel nomogram serves as a reliable tool for predicting survival, aiding clinicians in identifying high-risk patients and devising individualized treatments.
年轻三阴性乳腺癌（YTNBC）患者的生存结局往往较差。鉴于YTNBC的高风险性质，迫切需要能够准确预测患者预后并指导个性化治疗策略的工具。预后模型，尤其是列线图形式的模型，因其能够整合多个临床变量以估计个体患者生存情况而在肿瘤学领域受到欢迎。我们的研究旨在调查YTNBC患者的独立预后因素并开发一种列线图来预测总生存期（OS），从而帮助患者选择更好的治疗方法。
纳入2010年1月至2015年12月期间在监测、流行病学和最终结果（SEER）数据库中诊断为YTNBC的患者，并按7:3的比例随机分为训练组和验证组。进行单因素和多因素Cox分析以确定与预后相关的显著因素，然后用于构建预测1年、3年和5年OS的列线图。
选择九个生存预测因素（婚姻状况、肿瘤分级、美国癌症联合委员会（AJCC）分期、T分期、N分期、M分期、手术、骨转移、脑转移）用于列线图构建。训练组和验证组的一致性指数（C指数）分别为0.749和0.745。列线图模型显示出良好的校准，并且时间依赖性受试者工作特征（ROC）曲线证实了其在临床应用中的优越性。此外，各种独立预后因素的Kaplan-Meier生存曲线验证了该模型。
这种新型列线图是预测生存的可靠工具，有助于临床医生识别高危患者并制定个体化治疗方案。
