Zhang Shuairan, Liu Yang, Jiao Zihan, Li Zenan, Wang Jin, Li Ce, Qu Xiujuan, Xu Ling
Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China.
Front Oncol. 2021 Mar 5;11:603031. doi: 10.3389/fonc.2021.603031. eCollection 2021.
Gastric signet ring cell carcinoma (GSRCC) is a rare disease associated with poor prognosis. A prognostic nomogram was developed and validated in this study to assess GSRCC patients' overall survival (OS).
Patients diagnosed with GSRCC from the Surveillance, Epidemiology, and End Results (SEER) database (2004-2016) and the First Hospital of China Medical University (CMU1h) were enrolled in this retrospective cohort study. Univariate and multivariate COX analysis was used to determine independent prognostic factors to construct the prognostic nomogram. Predictions were evaluated by the C-index and calibration curve. In addition, the receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and Kaplan-Meier analysis were employed to assess the clinical utility of the survival prediction model.
Patients were classified into two cohorts. We randomly divided patients in the SEER database and CMU1h cohort into a training group (n=3068, 80%) and a validation group (n=764, 20%). Age, race, T stage, N stage, M stage, therapy, and tumor size were significantly associated with the prognosis of GSRCC patients. On this basis, a nomogram was constructed, with a C-index in the training and the validation cohorts at 0.772 (95% CI: 0.762-0.782) and 0.774 (95% CI: 0.752-0.796), respectively. The accuracy of the generated nomogram was verified through calibration plots. Similarly, compared with the traditional AJCC staging system, the results of the area under curve (AUC) calculated by ROC, DCA, and Kaplan-Meier curves, demonstrated a good predictive value of the constructed nomogram, compared to the traditional AJCC staging system.
In the present study, seven independent prognostic factors of GSRCC were screened out. The established nomogram models based on seven variables provided a visualization of each prognostic factor's risk and assisted clinicians in predicting the 1-, 3-, and 5-year OS of GSRCC.
胃印戒细胞癌（GSRCC）是一种罕见疾病，预后较差。本研究开发并验证了一种预后列线图，以评估GSRCC患者的总生存期（OS）。
本回顾性队列研究纳入了来自监测、流行病学和最终结果（SEER）数据库（2004 - 2016年）以及中国医科大学附属第一医院（CMU1h）诊断为GSRCC的患者。采用单因素和多因素COX分析确定独立预后因素，以构建预后列线图。通过C指数和校准曲线评估预测效果。此外，采用受试者工作特征（ROC）曲线、决策曲线分析（DCA）和Kaplan - Meier分析来评估生存预测模型的临床实用性。
患者被分为两个队列。我们将SEER数据库和CMU1h队列中的患者随机分为训练组（n = 3068，80%）和验证组（n = 764，20%）。年龄、种族、T分期、N分期、M分期、治疗方式和肿瘤大小与GSRCC患者的预后显著相关。在此基础上构建了列线图，训练队列和验证队列的C指数分别为0.772（95%CI：0.762 - 0.782）和0.774（95%CI：0.752 - 0.796）。通过校准图验证了所生成列线图的准确性。同样，与传统的美国癌症联合委员会（AJCC）分期系统相比，ROC、DCA和Kaplan - Meier曲线计算的曲线下面积（AUC）结果表明，与传统AJCC分期系统相比，所构建的列线图具有良好的预测价值。
在本研究中，筛选出了GSRCC的七个独立预后因素。基于七个变量建立的列线图模型直观显示了每个预后因素的风险，并辅助临床医生预测GSRCC患者1年、3年和5年的总生存期。
