Department of Radiotherapy, The First Affiliated Hospital of Weifang Medical College, Weifang, Shandong, China; Department of Radiotherapy, Weifang People's Hospital, Weifang, Shandong, China.
Department of Radiotherapy, The First Affiliated Hospital of Weifang Medical College, Weifang, Shandong, China; Department of Radiotherapy, Weifang People's Hospital, Weifang, Shandong, China.
Clin Breast Cancer. 2022 Oct;22(7):681-689. doi: 10.1016/j.clbc.2022.06.002. Epub 2022 Jun 26.
we aimed to develop an individualized survival prediction model for elderly locally advanced breast cancer (LABC) and stratify its risk to assist in the treatment and follow-up of patients.
Elderly LABC data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The best model was screened using Cox, least absolute shrinkage and selection operator (LASSO) and best subset regression to construct the nomogram. After internal and external validation of this model, risk stratification was established, and differences between risk groups were assessed using Kaplan-Meier method.
A total of 10,697 elderly LABC patients were divided into a training group (n = 7131) and a validation group (n = 3566) with a 5-year overall survival rate of 57.6% [confidence interval (CI): 56.4%-58.7%]. A nomogram was developed using age, marital status, histological grading, estrogen and progesterone receptors, surgery, radiation therapy, and chemotherapy as predictors. This model was evaluated and validated to perform well, with a discrimination index of 0.744 (95% CI: 0.734-0.753). Patients were divided into low, medium and high groups based on risk scores, and there was a significant difference in survival between the 3 groups.
The prognosis of elderly LABC was poor. The nomogram constructed based on prognostic factors could accurately predict the prognosis, which would provide a reference for treatment and follow-up.
我们旨在为老年局部晚期乳腺癌（LABC）患者开发一种个体化生存预测模型，并对其风险进行分层，以协助患者的治疗和随访。
从监测、流行病学和最终结果（SEER）数据库中提取老年 LABC 数据。使用 Cox、最小绝对收缩和选择算子（LASSO）和最佳子集回归筛选最佳模型，以构建列线图。对该模型进行内部和外部验证后，建立风险分层，并使用 Kaplan-Meier 方法评估风险组之间的差异。
共纳入 10697 例老年 LABC 患者，分为训练组（n=7131）和验证组（n=3566），5 年总生存率为 57.6%（置信区间：56.4%-58.7%）。使用年龄、婚姻状况、组织学分级、雌激素和孕激素受体、手术、放疗和化疗作为预测因子，建立了一个列线图。该模型经过评估和验证，表现良好，区分度指数为 0.744（95%置信区间：0.734-0.753）。根据风险评分将患者分为低、中、高组，3 组间生存差异有统计学意义。
老年局部晚期乳腺癌的预后较差。基于预后因素构建的列线图可以准确预测预后，为治疗和随访提供参考。
