Qi Wei-Xiang, Cao Lu, Xu Cheng, Zhao Shengguang, Chen Jiayi
Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.
Cancer Manag Res. 2021 Apr 23;13:3517-3527. doi: 10.2147/CMAR.S292233. eCollection 2021.
To establish and validate a nomogram for predicting prognosis of breast cancer patients with pN0-1 who were treated with mastectomy and without adjuvant radiotherapy.
The LASSO regression was performed to identify predictors of breast cancer-specific survival (BCSS), local regional recurrence (LRR) and distant metastasis (DM). Model performance was evaluated by the concordance index (C-index) and calibration plot.
The 5-year BCSS, LRR and DM rates for the entire cohort were 98%, 2% and 4%, respectively. LASSO regression analysis found that pathological T stage, number of positive LN, grade and Ki-67 were significant predictors for both BCSS and DM-free survival, while number of resected LN and PR status were predictors for DM-free survival. In addition, number of positive LN was the only significant predictor for developing LRR. The C-indexes for the 5-year BCSS and DM nomograms were 0.81 and 0.78 in the training data set, 0.65 and 0.70 in the testing set and 0.72 and 0.69 in the external validation set, respectively.
Our prognostic nomograms accurately predict 5-year BCSS and DM-free survival in post-mastectomy breast cancer without adjuvant radiotherapy, which provides a useful tool to identify high-risk patients who could benefit from additional adjuvant therapy.
建立并验证一种列线图,用于预测接受乳房切除术且未接受辅助放疗的pN0-1期乳腺癌患者的预后。
采用LASSO回归分析来确定乳腺癌特异性生存(BCSS)、局部区域复发(LRR)和远处转移(DM)的预测因素。通过一致性指数(C指数)和校准图评估模型性能。
整个队列的5年BCSS、LRR和DM发生率分别为98%、2%和4%。LASSO回归分析发现,病理T分期、阳性淋巴结数量、分级和Ki-67是BCSS和无远处转移生存的显著预测因素,而切除淋巴结数量和PR状态是无远处转移生存的预测因素。此外,阳性淋巴结数量是发生LRR的唯一显著预测因素。5年BCSS和DM列线图在训练数据集的C指数分别为0.81和0.78,在测试集为0.65和0.70,在外部验证集为0.72和0.69。
我们的预后列线图能够准确预测接受乳房切除术后且未接受辅助放疗的乳腺癌患者的5年BCSS和无远处转移生存情况,这为识别可能从额外辅助治疗中获益得高危患者提供了一个有用的工具。