Li Xingchen, Fan Yuan, Dong Yangyang, Cheng Yuan, Zhou Jingyi, Wang Zhiqi, Li Xiaoping, Wang Jianliu
Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.
Beijing Key Laboratory of Female Pelvic Floor Disorders Diseases, Beijing, China.
Front Med (Lausanne). 2020 Dec 23;7:614629. doi: 10.3389/fmed.2020.614629. eCollection 2020.
The present study was aimed at developing nomograms estimating the overall survival (OS) and cancer-specific survival (CSS) of endometrial cancer (EC)-affected patients. We retrospectively collected 145,445 EC patients between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors were identified via univariate and multivariate Cox analyses. These risk factors were used to establish nomograms to predict 3- and 5-year OS and CSS rates. Internal and external data were used for validation. The predictive accuracy and discriminative ability were measured by using concordance index (C-index) and risk group stratification. A total of 63,510 patients were collected and randomly assigned into the training cohort ( = 42,340) and the validation cohort ( = 21,170). Age at diagnosis, marital status, tumor size, histologic type, lymph node metastasis, tumor grade, and clinical stage were identified as independent prognostic factors for OS and CSS ( < 0.05 according to multivariate Cox analysis) and were further used to construct the nomograms. The area under the receiver operating characteristics (ROC) curve was greater than that of International Federation of Gynecology and Obstetrics (FIGO) staging system for predicting OS (0.83 vs. 0.73, < 0.01) and CSS (0.87 vs. 0.79, < 0.01) in the training cohort. The stratification into different risk groups ensured a significant distinction between survival curves within different FIGO staging categories. We constructed and validated nomograms that accurately predicting OS and CSS in EC patients. The nomograms can be used for estimating OS and CSS of individual patients and establishing their risk stratification.
本研究旨在开发列线图，以估计子宫内膜癌（EC）患者的总生存期（OS）和癌症特异性生存期（CSS）。我们回顾性收集了2004年至2015年间来自监测、流行病学和最终结果（SEER）数据库的145445例EC患者。通过单因素和多因素Cox分析确定独立预后因素。这些危险因素用于建立列线图，以预测3年和5年的OS和CSS率。使用内部和外部数据进行验证。通过一致性指数（C-index）和风险组分层来衡量预测准确性和鉴别能力。总共收集了63510例患者，并将其随机分为训练队列（n = 42340）和验证队列（n = 21170）。诊断时年龄、婚姻状况、肿瘤大小、组织学类型、淋巴结转移、肿瘤分级和临床分期被确定为OS和CSS的独立预后因素（多因素Cox分析P < 0.05），并进一步用于构建列线图。在训练队列中，预测OS的受试者工作特征（ROC）曲线下面积大于国际妇产科联盟（FIGO）分期系统（0.83对0.73，P < 0.01），预测CSS的ROC曲线下面积也大于FIGO分期系统（0.87对0.79，P < 0.01）。分层为不同风险组确保了不同FIGO分期类别内生存曲线之间的显著差异。我们构建并验证了能够准确预测EC患者OS和CSS的列线图。这些列线图可用于估计个体患者的OS和CSS并建立其风险分层。
