Feng Mengya, Kang Yihua, Li Sijia, Yang Dechun, Ren Shengnan, Tang Shicong, Mo Dan, Lei Hai
Department of Breast Surgery, The People's Hospital of Chuxiong Yi Autonomous Prefecture, No. 318 Lucheng South Road, Chuxiong, Yunnan 675000, China.
Department II of General Surgery, The People's Hospital of Chuxiong Yi Autonomous Prefecture, No. 318 Lucheng South Road, Chuxiong, Yunnan 675000, China.
Surg Open Sci. 2025 Apr 23;26:28-38. doi: 10.1016/j.sopen.2025.04.006. eCollection 2025 Jun.
To investigate the clinicopathological factors influencing lung and bone metastasis in breast cancer, and to further construct a nomogram model for predicting the risk of lung and bone metastasis in breast cancer patients at various time points, followed by a prognostic analysis.
The retrospective analysis included 200 patients with breast cancer, among whom 51 had lung metastases and 57 had bone metastases. The remaining 92 patients without metastases served as the control group. Baseline characteristics were analyzed using the chi-square test; COX univariate and multivariate analyses were applied to explore the influencing factors. A nomogram was constructed to predict the risk of individuals developing lung or bone metastasis at 1, 3, and 5 years. The predictive model was further validated by ROC curves and calibration curves, and decision curves were plotted to assess the clinical application value of the model.
Analysis revealed that age, BMI, tumor size, lymph node status, ER, PR, HER-2, and Ki67 significantly influenced lung metastasis (P < 0.05), while age, BMI, tumor size, lymph node status, ER, PR, and Ki67 significantly impacted bone metastasis (P < 0.05). The nomogram indicated that HER-2 negativity elevated the risk of breast cancer lung metastases. ROC curves were plotted for 1, 3, and 5 years, with AUC values and 95 % confidence intervals of 0.803 (67.42-93.15), 0.831 (75.93-90.29), and 0.854 (78.43-92.34) in the lung metastasis group, and 0.754 (55.15-95.66), 0.753 (64.91-85.71), and 0.777 (68.64-86.67) in the bone metastasis group, respectively. These results suggest that the model has a superior predictive efficacy and a high degree of predictive reliability. Additionally, the calibration curve demonstrated that the model is well-fitted, and the decision curve indicated that the model possesses clinical utility in practice.
Age, BMI, tumor size, lymph node status, ER, PR, and Ki67 significantly influence lung and bone metastasis in breast cancer. The nomogram developed in this study can evaluate the risk of lung or bone metastasis for individuals at 1, 3, and 5 years, predict prognosis, guide clinical individualized treatment, and bring more benefits, further improving the quality of life for patients. It demonstrates good predictive ability and clinical value.
The nomogram model constructed in this study can predict prognosis, guide clinical individualized treatment, and bring more benefits, further improving the quality of life for patients. It possesses good predictive ability and holds certain clinical predictive value.
探讨影响乳腺癌肺转移和骨转移的临床病理因素，并进一步构建列线图模型，以预测乳腺癌患者在不同时间点发生肺转移和骨转移的风险，随后进行预后分析。
回顾性分析200例乳腺癌患者，其中51例发生肺转移，57例发生骨转移。其余92例无转移患者作为对照组。采用卡方检验分析基线特征；应用COX单因素和多因素分析探讨影响因素。构建列线图以预测个体在1年、3年和5年发生肺或骨转移的风险。通过ROC曲线和校准曲线进一步验证预测模型，并绘制决策曲线以评估模型的临床应用价值。
分析显示，年龄、BMI、肿瘤大小、淋巴结状态、ER、PR、HER-2和Ki67对肺转移有显著影响（P<0.05），而年龄、BMI、肿瘤大小、淋巴结状态、ER、PR和Ki67对骨转移有显著影响（P<0.05）。列线图表明HER-2阴性会增加乳腺癌肺转移的风险。绘制了1年、3年和5年的ROC曲线，肺转移组的AUC值及95%置信区间分别为0.803（67.42 - 93.15）、0.831（75.93 - 90.29）和0.854（78.43 - 92.34），骨转移组分别为0.754（55.15 - 95.66）、0.753（64.91 - 85.71）和0.777（68.64 - 86.67）。这些结果表明该模型具有较高的预测效能和预测可靠性。此外，校准曲线表明模型拟合良好，决策曲线表明该模型在实际应用中具有临床实用性。
年龄、BMI、肿瘤大小、淋巴结状态、ER、PR和Ki67对乳腺癌肺转移和骨转移有显著影响。本研究构建的列线图可评估个体在1年、3年和5年发生肺或骨转移的风险，预测预后，指导临床个体化治疗并带来更多益处，进一步提高患者生活质量。它具有良好的预测能力和临床价值。
本研究构建的列线图模型可预测预后，指导临床个体化治疗并带来更多益处，进一步提高患者生活质量。它具有良好的预测能力并具有一定的临床预测价值。
