Yang Qiuyu, Xi Liangchen, Huang Mudan, Zhang Haosheng, Zhou Fangzheng
Department of Radiation Oncology, Shenzhen Luohu People's Hospital (The Third Affiliated Hospital of Shenzhen University), No.47, Youyi Road, Luohu District, Shenzhen, 518001, Guangdong, China.
Sci Rep. 2025 Jul 1;15(1):21666. doi: 10.1038/s41598-025-05738-y.
Triple-negative breast cancer (TNBC) represents a subtype of breast cancer with a poor prognosis because of limited treatment options at present. Therefore, this study aimed to use nomograms to forecast the prognosis of patients with triple-negative invasive ductal carcinoma of the breast (TN-IDC) undergoing neoadjuvant chemotherapy (NCT). 3573 TNBC patients from the SEER database who received NCT between 2010 and 2015 were selected and randomized in 7:3 into the training or the testing group. Then, nomograms for overall survival (OS) and cancer-specific survival (CSS) of the two groups were created via univariate and multivariate analyses. Consistency index (C-index), calibration curve, and area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA) were employed to evaluate the reliability and accuracy of the model. As demonstrated by univariate and multivariate Cox regression analyses, 8 indicators (AJCC_M, AJCC_N, AJCC_T, positive lymph nodes [LNs] and the number of positive LNs, liver metastases, response to NCT, and radical surgery) were incorporated in the nomogram. The results indicated that the C-index of the OS prediction model was 0.776 for the training group and 0.779 for the testing group. In the training group, the AUC for forecasting 1-, 3-, and 5-year OS was 0.840, 0.822, and 0.817, respectively; in the testing group, the AUC was 0.889, 0.821, and 0.813, respectively. The C-index of the CSS prediction model was 0.790 for the training group and 0.789 for the testing group. In the training group, the AUC for forecasting 1-, 3-, and 5-year CSS was 0.853, 0.829, and 0.827, respectively; in the testing group, the AUC was 0.887, 0.800, and 0.820, respectively. Both C-index and AUC of OS and CSS prediction models were above or close to 0.8, indicating good predictability of the model. DCA consistently indicated that using the nomogram for OS and CSS prediction yielded favorable net clinical benefit, and the nomogram outperformed the AJCC TNM staging system in decision-making. T2-4 (maximum tumor diameter > 2 cm or invasion of the chest wall/skin), N3, M1, liver metastasis, incomplete remission after chemotherapy, and breast-conserving surgery were prognostic risk factors in TN-IDC patients receiving NCT. Higher T stage (T3-4, maximum tumor diameter > 5 cm or invasion of the chest wall/skin), N stage (N3), liver metastasis, non-remission (NR) after NCT, and positive LNs after chemotherapy were linked to worse OS and CSS. After NCT, the number of positive LNs ≥ 4 and NR for lesion exhibited the greatest impact on OS and CSS.
三阴性乳腺癌（TNBC）是乳腺癌的一种亚型，由于目前治疗选择有限，其预后较差。因此，本研究旨在使用列线图预测接受新辅助化疗（NCT）的三阴性浸润性导管癌（TN-IDC）患者的预后。从SEER数据库中选取了2010年至2015年间接受NCT的3573例TNBC患者，并按7:3随机分为训练组或测试组。然后，通过单因素和多因素分析创建了两组的总生存（OS）和癌症特异性生存（CSS）列线图。采用一致性指数（C-index）、校准曲线、受试者操作特征曲线下面积（AUC）、决策曲线分析（DCA）来评估模型的可靠性和准确性。单因素和多因素Cox回归分析表明，8个指标（AJCC_M、AJCC_N、AJCC_T、阳性淋巴结[LNs]及阳性LNs数量、肝转移、对NCT的反应和根治性手术）被纳入列线图。结果显示，OS预测模型在训练组的C-index为0.776，在测试组为0.779。在训练组中，预测1年、3年和5年OS的AUC分别为0.840、0.822和0.817；在测试组中，AUC分别为0.889、0.821和0.813。CSS预测模型在训练组的C-index为0.790，在测试组为0.789。在训练组中，预测1年、3年和5年CSS的AUC分别为0.853、0.829和0.827；在测试组中，AUC分别为0.887、0.800和0.820。OS和CSS预测模型的C-index和AUC均高于或接近0.8，表明模型具有良好的预测性。DCA一致表明，使用列线图进行OS和CSS预测产生了良好的净临床效益，并且在决策方面列线图优于AJCC TNM分期系统。T2-4（最大肿瘤直径>2 cm或侵犯胸壁/皮肤）、N3、M1、肝转移、化疗后未完全缓解和保乳手术是接受NCT的TN-IDC患者的预后危险因素。较高的T分期（T3-4，最大肿瘤直径>5 cm或侵犯胸壁/皮肤）、N分期（N3）、肝转移、NCT后未缓解（NR）以及化疗后阳性LNs与较差的OS和CSS相关。NCT后，阳性LNs数量≥4且病变NR对OS和CSS的影响最大。
