Supplementary Material for: A Prognostic Model for Survival in Patients with Gastric Signet-Ring Cell Carcinoma

Background: The objective of our study was to develop a nomogram to predict overall survival (OS) and cancer-specific survival (CSS) in patients with gastric signet ring cell carcinoma (GSRCC). Patients and Methods: A total of 3408 GSRCC patients between 1975 and 2017 were screened from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into training and validation cohorts. Univariate and multivariate Cox analyses were conducted to identify independent prognostic factors for the construction of a nomogram. The performance of the model was then assessed by the concordance index (C-index), calibration plot and area under the receiver operating characteristic (ROC) curve (AUC). Then, the novel nomogram was further assessed by 64 GSRCC patients from our hospital as the external cohort. Results: We identified age, tumor lymph node metastasis (TNM) staging system, surgery and chemotherapy as significant independent elements of prognosis. On this basis, a nomogram was constructed, with a C-index of OS in the training and validation cohorts of 0.763 (95% CI: 0.751–0.774) and 0.766 (95% CI: 0.748–0.784) and a C-index of CSS of 0.765 (95% CI: 0.753–0.777) and 0.773 (95% CI: 0.755–0.791), respectively. The AUCs of the nomogram for predicting 2- and 5-year OS were 0.848 and 0.885, respectively, and those for predicting CSS were 0.854 and 0.899, respectively, demonstrating the excellent predictive value of the constructed nomogram compared to the traditional AJCC staging system. Similar results were also observed in both the internal and external validation sets. Conclusion: The nomogram provided an accurate tool to predict OS and CSS in patients with GSRCC, which can assist clinicians in making predictions about individual patient survival.

研究背景：本研究旨在构建一列线图（nomogram），用于预测胃印戒细胞癌（gastric signet ring cell carcinoma，GSRCC）患者的总生存期（overall survival，OS）与肿瘤特异性生存期（cancer-specific survival，CSS）。
患者与方法：从监测、流行病学与最终结果（Surveillance, Epidemiology, and End Results，SEER）数据库中筛选1975年至2017年间的3408例GSRCC患者，并随机分为训练队列与验证队列。采用单因素与多因素Cox回归分析筛选独立预后因素，以此构建列线图。随后通过一致性指数（concordance index，C-index）、校准曲线及受试者工作特征曲线（receiver operating characteristic，ROC）下面积（AUC）评估模型性能。另纳入本院64例GSRCC患者作为外部验证队列，进一步验证该新型列线图的效能。
结果：本研究筛选出年龄、肿瘤-淋巴结-转移（TNM）分期系统、手术治疗与化疗为显著独立预后因素。基于此构建的列线图，其在训练队列与验证队列中的OS一致性指数分别为0.763（95%置信区间：0.751~0.774）与0.766（95%置信区间：0.748~0.784），CSS一致性指数分别为0.765（95%置信区间：0.753~0.777）与0.773（95%置信区间：0.755~0.791）。该列线图预测2年与5年OS的AUC分别为0.848与0.885，预测2年与5年CSS的AUC分别为0.854与0.899，相较传统美国癌症联合委员会（AJCC）分期系统，展现出更优异的预测价值。内部与外部验证集均得到了一致的结果。
结论：本研究所构建的列线图可精准预测GSRCC患者的OS与CSS，能够辅助临床医师实现个体化的患者生存期预测。