Construction and validation of nomograms for predicting the prognosis of grade 3 endometrial endometrioid adenocarcinoma cancers: a SEER-based study

Most cases of endometrial adenocarcinoma (EAC) are diagnosed early and have a good prognosis; however, grade 3 (G3) EACs have poor outcomes. We retrospectively analyzed the data of 11,519 patients with G3 EACs registered between 2004 and 2015 in the Surveillance, Epidemiology, and End Results Program database and constructed a nomogram to guide clinicians in decision-making and accurate prediction of the prognosis. The caret package was used to divide samples into a training set and a validation set. Univariate and multivariate Cox regression analyses were performed, and a nomogram was constructed. A calibration curve was plotted, and a decision curve analysis was performed to verify the accuracy and clinical utility in both cohorts. The Cox regression analysis revealed that age, race, tumor size, number of lymph nodes resected, International Federation of Gynecology and Obstetrics stage, tumor/node stage, and adjuvant therapy were the prognostic factors for G3 EAC, and these were included in the nomogram. The area under the curve values of the training cohort for 1-, 3-, and 5-year were 0.832, 0.798, and 0.784, respectively for the overall survival (OS) group, and 0.858, 0.812, and 0.799, respectively for the cancer specific survival (CSS) group. A nomogram was constructed to predict the survival rate of patients with G3 EACs more accurately. The predictive nomogram will help clinicians manage patients with G3 EACs more effectively in terms of clinical prognosis.

绝大多数子宫内膜腺癌（endometrial adenocarcinoma, EAC）病例可在早期确诊且预后良好，但3级（G3）子宫内膜腺癌患者的预后较差。本研究回顾性分析了2004至2015年登记于监测、流行病学与最终结果（Surveillance, Epidemiology, and End Results, SEER）数据库的11519例3级子宫内膜腺癌患者的临床数据，并构建列线图以指导临床医师进行决策及精准预测患者预后。本研究采用Caret软件包将样本划分为训练集与验证集，开展单因素及多因素Cox回归分析并构建列线图；通过绘制校准曲线及决策曲线分析，验证了该模型在两个队列中的准确性与临床实用性。Cox回归分析结果显示，年龄、种族、肿瘤大小、切除淋巴结数目、国际妇产科联盟（International Federation of Gynecology and Obstetrics, FIGO）分期、肿瘤/淋巴结分期以及辅助治疗均为3级子宫内膜腺癌的预后影响因素，上述因素均被纳入列线图模型。训练队列中，总生存期（overall survival, OS）亚组的1年、3年、5年受试者工作特征曲线下面积（AUC）分别为0.832、0.798、0.784；癌症特异性生存期（cancer specific survival, CSS）亚组的对应值分别为0.858、0.812、0.799。本研究构建的列线图可更为精准地预测3级子宫内膜腺癌患者的生存率，该预测模型将有助于临床医师更有效地开展3级子宫内膜腺癌患者的临床预后管理工作。