Department of General Surgery, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Rd, Zhengzhou, 450008, Henan, China.
Department of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China.
J Gastrointest Surg. 2022 Aug;26(8):1743-1756. doi: 10.1007/s11605-022-05408-8. Epub 2022 Jul 14.
There are few reports on disease-specific survival (DSS) prediction systems for resected gastric cancer (GC) patients. The aim of this study was to create a nomogram based on the log odds of the negative lymph node/T stage ratio (LONT) for individual risk prediction.
We applied the Surveillance, Epidemiology, and End Results (SEER) Program database released in 2021 to screen GC patients from 2010 to 2015. Using a competitive risk model, we plotted the cumulative risk curve of variables for gastric cancer-specific death and death from other causes at each time point. According to the minimum BIC, we constructed and assessed a nomogram for the 12-month, 36-month, and 60-month cumulative mortality probabilities assessed by time-dependent ROC curves (time-AUCs), the C-index, Brier scores, decision curve analysis (DCA), and calibration curves.
A total of 3895 patients were ultimately included and randomly assigned to two sets: the training set (n = 2726, 70%) and the validation set (n = 1169, 30%). The LONT was a remarkable independent predictor of gastric cancer-specific death (high versus low: 0.705, 95% CI 0.524-0.95, p = 0.021). The variables selected based on the minimum BIC were as follows: location, AJCC, AJCC.T, AJCC.N, radiotherapy, LONT.cat, and chemotherapy. According to the time-AUC, C-index, Brier score, DCA, and calibration curves, the nomogram risk score had excellent survival prediction ability for DSS.
A low LONT was associated with a high cumulative incidence of DSS. A prognostic nomogram model based on the LONT could effectively predict DSS for resectable GC patients.
关于可切除胃癌（GC）患者疾病特异性生存（DSS）预测系统的报道较少。本研究旨在基于负淋巴结/T 期比值（LONT）的对数几率创建一个列线图，用于个体风险预测。
我们应用 2021 年发布的监测、流行病学和最终结果（SEER）计划数据库，筛选 2010 年至 2015 年的 GC 患者。使用竞争风险模型，我们绘制了每个时间点胃癌特异性死亡和其他原因死亡变量的累积风险曲线。根据最小 BIC，我们构建并评估了时间依赖性 ROC 曲线（时间-AUC）、C 指数、Brier 评分、决策曲线分析（DCA）和校准曲线评估的 12 个月、36 个月和 60 个月累积死亡率概率的列线图。
最终共纳入 3895 例患者，并随机分为两组：训练集（n=2726，70%）和验证集（n=1169，30%）。LONT 是胃癌特异性死亡的显著独立预测因素（高 vs 低：0.705，95%CI 0.524-0.95，p=0.021）。基于最小 BIC 选择的变量如下：位置、AJCC、AJCC.T、AJCC.N、放疗、LONT.cat 和化疗。根据时间-AUC、C 指数、Brier 评分、DCA 和校准曲线，列线图风险评分对 DSS 具有出色的生存预测能力。
低 LONT 与 DSS 的累积发生率较高相关。基于 LONT 的预后列线图模型可有效预测可切除 GC 患者的 DSS。
