基于SEER数据库构建和验证男性乳腺癌预后模型
Construction and validation of a prognostic model for male breast cancer based on the SEER database
苏小涵 1谭巧 1曾姣 1程攀科 2侯令密1
作者信息
- 1. 川北医学院附属医院甲状腺乳腺外科(四川南充 637001);四川省医学影像重点实验室(四川南充 637000)
- 2. 四川省医学科学院/四川省人民医院/电子科技大学附属医院/心血管病研究所·心血管内科(成都 610072)
- 折叠
摘要
目的 探究男性乳腺癌(male breast cancer,MBC)患者的预后因素,构建MBC患者生存预后列线图并预测 3 年和 5 年生存率.方法 纳入监测、流行病学和最终结果(Surveillance,Epidemiology,and End Results,SEER)癌症登记数据库的MBC患者,同时纳入川北医学院附属医院、遂宁市中心医院和德阳市人民医院的MBC患者,获取患者完整的临床基线资料及生存信息.以SEER数据库中患者数据作为训练集,3 家医院中的患者数据作为验证集,通过单因素和多因素Cox回归分析确定与总生存期(overall survival,OS)相关的独立预后因素,并构建预测MBC患者 3 年及 5 年生存率的列线图,运用校准曲线、一致性指数(CI)、受试者工作特征曲线(ROC)和决策分析曲线来评估模型的准确程度和实际应用价值.结果 共纳入 3 387 名MBC患者,其中训练集 3 307 例,验证集 80 例.通过对训练集进行单因素和多因素Cox回归分析后发现,诊断年龄、组织学分级、T分期、N分期、M分期、孕激素受体状态、手术、化疗和放疗是影响MBC患者OS的独立预后因素.将这些因素纳入并构建列线图模型并进行验证,训练集CI为0.711,验证集CI为0.787.训练集中,3年OS的AUC为0.744,5年OS的AUC为0.720;验证集中,3年OS的AUC为0.835,5年OS的AUC为0.858.ROC曲线表明模型区分能力较好,校准曲线显示模型预测性能良好,决策分析曲线表明模型的临床应用价值较高.结论 开发的列线图为预测MBC患者的预后提供了一种可靠且实用的方法,有助于个性化治疗决策,改善患者的治疗效果.
Abstract
Objective To explore the prognostic factors of male breast cancer(MBC)patients,and construct a survival prognostic nomogram for MBC patients,and predict the 3-year and 5-year overall survival rates.Methods Patients from the Surveillance,Epidemiology,and End Results(SEER)cancer registry database were included,along with MBC patients from the Affiliated Hospital of North Sichuan Medical College,Suining Central Hospital,and Deyang People's Hospital.Clinical baseline data and survival information of the patients were obtained.The data of patients from the SEER database served as the training coherent,and the data of patients from 3 hospitals as the validation coherent.Independent prognostic factors for the overall survival(OS)of MCB patients were determined by univariate and multivariate Cox regression analysis.A nomogram predicting 3-year and 5-year survival rates for MBC patients was constructed based on the independent prognostic factors,and its accuracy and practical application value were assessed using calibration curves,the concordance index(C-index),receiver operating characteristic curves(ROC),and decision curve analysis(DCA).Results A total of 3,387 MBC patients were included,3,307 patients were in training coherent and 80 patients were in validation coherent.After univariate and multivariate Cox regression analysis of the training set,it was found that diagnostic age,histological grade,TNM stage,prgesterone receptor status,surgery,chemotherapy,and radiotherapy were the independent prognostic factors for MBC.These factors were incorporated into the nomogram model and validated,with a C-index of 0.711 for the training set and 0.787 for the external validation set.In the training set,the nomogram showed an AUC of 0.744 for 3-year OS and an AUC of 0.720 for 5-year OS;in the validation set,the nomogram showed an AUC of 0.835 for 3-year OS and an AUC of 0.858 for 5-year OS.The ROC curve indicated good discriminative ability of the model,the calibration curve showed good predictive performance,and the DCA curve indicated high clinical utility of the model.Conclusion The nomogram provides a reliable and practical method for predicting the prognosis of MBC patients,aiding in personalized treatment decisions and thereby improving patient outcomes.
关键词
男性乳腺癌/列线图/SEER数据库/预后Key words
Male breast cancer/Nomogram/SEER database/Prognosis引用本文复制引用
基金项目
国家自然科学基金青年科学基金项目(32000967)
四川省自然科学基金面上项目(2022NSFSC0775)
出版年
2024
国家科技期刊平台
NSTL
万方数据