Nie Guole, Zhang Honglong, Yan Jun, Xie Danna, Zhang Haijun, Li Xun
The First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, China.
Front Oncol. 2023 Feb 9;13:1114847. doi: 10.3389/fonc.2023.1114847. eCollection 2023.
Adenocarcinoma is one of the most common pathological types of gastric cancer. The aims of this study were to develop and validate prognostic nomograms that could predict the probability of cancer-specific survival (CSS) for gastric adenocarcinoma (GAC) patients at 1, 3, and 5 years.
In total, 7747 patients with GAC diagnosed between 2010 and 2015, and 4591 patients diagnosed between 2004 and 2009 from the Surveillance, Epidemiology, and End Results (SEER) database were included in this study. The 7747 patients were used as a prognostic cohort to explore GAC-related prognostic risk factors. Moreover, the 4591 patients were used for external validation. The prognostic cohort was also divided into a training and internal validation sets for construction and internal validation of the nomogram. CSS predictors were screened using least absolute shrinkage and selection operator regression analysis. A prognostic model was built using Cox hazard regression analysis and provided as static and dynamic network-based nomograms.
The primary site, tumor grade, surgery of the primary site, T stage, N stage, and M stage were determined to be independent prognostic factors for CSS and were subsequently included in construction of the nomogram. CSS was accurately estimated using the nomogram at 1, 3, and 5 years. The areas under the curve (AUCs) for the training group at 1, 3, and 5 years were 0.816, 0.853, and 0.863, respectively. Following internal validation, these values were 0.817, 0.851, and 0.861. Further, the AUC of the nomogram was much greater than that of American Joint Committee on Cancer (AJCC) or SEER staging. Moreover, the anticipated and actual CSS values were in good agreement based on decision curves and time-calibrated plots. Then, patients from the two subgroups were divided into high- and low-risk groups based on this nomogram. The survival rate of high-risk patients was considerably lower than that of low-risk patients, according to Kaplan-Meier (K-M) curves (<0.0001).
A reliable and convenient nomogram in the form of a static nomogram or an online calculator was constructed and validated to assist physicians in quantifying the probability of CSS in GAC patients.
腺癌是胃癌最常见的病理类型之一。本研究的目的是开发并验证能预测胃腺癌（GAC）患者1年、3年和5年癌症特异性生存（CSS）概率的预后列线图。
本研究纳入了监测、流行病学和最终结果（SEER）数据库中2010年至2015年诊断的7747例GAC患者，以及2004年至2009年诊断的4591例患者。7747例患者作为预后队列以探索GAC相关的预后危险因素。此外，4591例患者用于外部验证。预后队列还被分为训练集和内部验证集，用于列线图的构建和内部验证。使用最小绝对收缩和选择算子回归分析筛选CSS预测因子。使用Cox风险回归分析建立预后模型，并以基于静态和动态网络的列线图形式呈现。
确定原发部位、肿瘤分级、原发部位手术、T分期、N分期和M分期为CSS的独立预后因素，并随后纳入列线图的构建。使用列线图可准确估计1年、3年和5年的CSS。训练组1年、3年和5年的曲线下面积（AUC）分别为0.816、0.853和0.863。内部验证后，这些值分别为0.817、0.851和0.861。此外，列线图的AUC远大于美国癌症联合委员会（AJCC）或SEER分期的AUC。而且，基于决策曲线和时间校准图，预期和实际CSS值吻合良好。然后，根据该列线图将两个亚组的患者分为高风险组和低风险组。根据Kaplan-Meier（K-M）曲线，高风险患者的生存率显著低于低风险患者（<0.0001）。
构建并验证了以静态列线图或在线计算器形式的可靠且便捷的列线图，以协助医生量化GAC患者CSS的概率。
