Zhao Huimin, Yan Haoxiang, Chen Lianju, Li Yafei
Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Department of Dermatology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Transl Cancer Res. 2023 Apr 28;12(4):965-979. doi: 10.21037/tcr-23-484.
For clinical workers, disease-specific death is a better indicator of tumor severity. Breast cancer is the most prevalent malignancy in women. Luminol type B breast cancer is one of the biggest threats to women's health, and few studies have paid attention to its specific death. Early recognition of luminol type B breast cancer allows clinicians to assess the prognosis and develop more optimal treatment plans.
In this study, the basic information of luminal B population, clinical and pathological characteristics, treatment regimen and survival data were collected from the SEER database. The patients were randomly divided into a training group and a validation group. The single-factor and multi-factor competitive risk models were used to analyze the independent influencing factors of tumor-specific death, and the predictive nomogram based on the competitive risk model was constructed. The consistency index (C-index) and calibration curves over time were used to evaluate the accuracy of the predicted nomograms.
This study included a total of 30,419 luminal B patient. The median follow-up period was 60 (IQR: 44-81) months. Among the 4,705 deaths during the follow-up period, 2,863 patients died specifically, accounting for 60.85% of the deaths. The independent predictive factors of cancer-specific mortality were: married, primary site, grade, stage, the primary site of operation, radiotherapy, chemotherapy, metastasis (lymph node, bone, brain, liver, lung), and Estrogen Receptor and Progesterone Receptor status. In the training cohort, the C-index of the predictive nomogram was 0.858, and the area under the receiver operating characteristic curve (AUC) for the first, third, and fifth years was 0.891, 0.864, and 0.845. The C-index of the validation cohort was 0.862, and the AUC for the first, third, and fifth years was 0.888, 0.872, and 0.849. The calibration curves of the training and validation cohorts showed that the predicted probability of the model was very consistent with the actual probability. And the 5-year survival rate according to the traditional survival analysis was 9.49%, while the 5-year specific mortality rate was only 8.88%.
The luminal B competing risk model we established has ideal accuracy and calibration.
对于临床工作者而言，疾病特异性死亡是肿瘤严重程度的更好指标。乳腺癌是女性中最常见的恶性肿瘤。B型 luminal 乳腺癌是对女性健康的最大威胁之一，很少有研究关注其特异性死亡情况。早期识别B型 luminal 乳腺癌可使临床医生评估预后并制定更优化的治疗方案。
在本研究中，从SEER数据库收集luminal B人群的基本信息、临床和病理特征、治疗方案及生存数据。将患者随机分为训练组和验证组。采用单因素和多因素竞争风险模型分析肿瘤特异性死亡的独立影响因素，并构建基于竞争风险模型的预测列线图。使用一致性指数（C指数）和随时间变化的校准曲线评估预测列线图的准确性。
本研究共纳入30419例luminal B患者。中位随访期为60（四分位间距：44 - 81）个月。在随访期间的4705例死亡患者中，2863例患者死于特异性原因，占死亡人数的60.85%。癌症特异性死亡率的独立预测因素为：婚姻状况、原发部位、分级、分期、手术原发部位、放疗、化疗、转移（淋巴结、骨、脑、肝、肺）以及雌激素受体和孕激素受体状态。在训练队列中，预测列线图的C指数为0.858，第一年、第三年和第五年的受试者工作特征曲线下面积（AUC）分别为0.891、0.864和0.845。验证队列的C指数为0.862，第一年、第三年和第五年的AUC分别为0.888、0.872和0.849。训练和验证队列的校准曲线表明模型的预测概率与实际概率非常一致。根据传统生存分析的5年生存率为9.49%，而5年特异性死亡率仅为8.88%。
我们建立的luminal B竞争风险模型具有理想的准确性和校准度。
