Department of Medical Ultrasound, Fudan University Shanghai Cancer Center, No 270, Dong'an Road, Xuhui District, Shanghai, 200032, China.
Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
Eur Radiol. 2022 Oct;32(10):6575-6587. doi: 10.1007/s00330-022-08910-4. Epub 2022 Jun 27.
This study aimed to incorporate clinicopathological, sonographic, and mammographic characteristics to construct and validate a nomogram model for predicting disease-free survival (DFS) in patients with triple-negative breast cancer (TNBC).
Patients diagnosed with TNBC at our institution between 2011 and 2015 were retrospectively evaluated. A nomogram model was generated based on clinicopathological, sonographic, and mammographic variables that were associated with 1-, 3-, and 5-year DFS determined by multivariate logistic regression analysis in the training set. The nomogram model was validated according to the concordance index (C-index) and calibration curves in the validation set.
A total of 636 TNBC patients were enrolled and divided into training cohort (n = 446) and validation cohort (n = 190). Clinical factors including tumor size > 2 cm, axillary dissection, presence of LVI, and sonographic features such as angular/spiculated margins, posterior acoustic shadows, and presence of suspicious lymph nodes on preoperative US showed a tendency towards worse DFS. The multivariate analysis showed that no adjuvant chemotherapy (HR = 6.7, 95% CI: 2.6, 17.5, p < 0.0005), higher axillary tumor burden (HR = 2.7, 95% CI: 1.0, 7.1, p = 0.045), and ≥ 3 malignant features on ultrasound (HR = 2.4, CI: 1.1, 5.0, p = 0.021) were identified as independent prognostic factors associated with poorer DFS outcomes. In the nomogram, the C-index was 0.693 for the training cohort and 0.694 for the validation cohort. The calibration plots also exhibited excellent consistency between the nomogram-predicted and actual survival probabilities in both the training and validation cohorts.
Clinical variables and sonographic features were correlated with the prognosis of TNBCs. The nomogram model based on three variables including no adjuvant chemotherapy, higher axillary tumor load, and more malignant sonographic features showed good predictive performance for poor survival outcomes of TNBC.
• The absence of adjuvant chemotherapy, heavy axillary tumor load, and malignant-like sonographic features can predict DFS in patients with TNBC. • Mammographic features of TNBC could not predict the survival outcomes of patients with TNBC. • The nomogram integrating clinicopathological and sonographic characteristics is a reliable predictive model for the prognostic outcome of TNBC.
本研究旨在结合临床病理、超声和乳腺 X 线摄影特征，构建并验证三阴性乳腺癌（TNBC）患者无病生存（DFS）的预测列线图模型。
回顾性分析 2011 年至 2015 年在我院诊断为 TNBC 的患者。通过多变量逻辑回归分析，在训练集中确定与 1 年、3 年和 5 年 DFS 相关的临床病理、超声和乳腺 X 线摄影变量，生成列线图模型。在验证集中，根据一致性指数（C-index）和校准曲线对列线图模型进行验证。
共纳入 636 例 TNBC 患者，分为训练队列（n = 446）和验证队列（n = 190）。临床因素包括肿瘤大小>2cm、腋窝清扫术、存在脉管内肿瘤侵犯（LVI），以及术前超声的声像图特征，如角度/刺状边缘、后方声影和可疑淋巴结，均显示出与 DFS 不良相关的趋势。多因素分析显示，无辅助化疗（HR = 6.7，95%CI：2.6，17.5，p < 0.0005）、较高的腋窝肿瘤负荷（HR = 2.7，95%CI：1.0，7.1，p = 0.045）和超声检查≥3 个恶性特征（HR = 2.4，CI：1.1，5.0，p = 0.021）是与较差 DFS 结局相关的独立预后因素。在列线图中，训练队列的 C-index 为 0.693，验证队列的 C-index 为 0.694。校准图也显示，训练和验证队列中，列线图预测的生存概率与实际生存概率之间具有极好的一致性。
临床变量和超声特征与 TNBC 的预后相关。基于无辅助化疗、较高的腋窝肿瘤负荷和更多恶性超声特征这三个变量的列线图模型，对 TNBC 患者的不良生存结局具有良好的预测性能。
无辅助化疗、腋窝肿瘤负荷较重和恶性超声特征可预测 TNBC 患者的 DFS。
TNBC 的乳腺 X 线摄影特征不能预测患者的生存结局。
整合临床病理和超声特征的列线图是预测 TNBC 预后结局的可靠预测模型。
