Department of General Surgery, The First Affiliated Hospital of Shandong First Medical University, Jinan, 250100, China.
Department of General Surgery, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, 266000, China.
Clin Transl Oncol. 2024 Apr;26(4):1001-1011. doi: 10.1007/s12094-023-03340-0. Epub 2023 Nov 24.
To establish a nomogram for predicting the overall survival (OS) in patients with gastric cancer (GC) based on inflammatory, nutritional and pathological factors.
GC patients underwent curative gastrectomy from January 2012 to June 2017 in our hospital were included, and were classified into training set and validation set with a ratio of 7:3. Then variables associated with OS were analyzed using univariate and multivariate Cox regression analysis. Nomograms predicting OS were built using variables from multivariable Cox models. Finally, Kaplan-Meier curve and Log-rank test were also conducted to analyze the 1-yr, 3-yr and 5-yr OS to validate the efficiency of risk stratification of the nomogram.
A total of 366 GC patients were included. After univariate and multivariate Cox regression analysis, age (HR = 1.52, 95% CI = 1.01-2.30, P = 0.044), CA50 (HR = 1.90, 95% CI = 1.12-3.21, P = 0.017), PNI (HR = 1.65, 95% CI = 1.13-2.39, P = 0.009), SII (HR = 1.46, 95% CI = 1.03-2.08, P = 0.036), T stage (HR = 2.26, 95% CI = 1.01-5.05, P = 0.048; HR = 7.24, 95% CI = 3.64-14.40, P < 0.001) were independent influencing factors on the survival time of GC patients. Five factors including CEA, prognostic nutritional index (PNI), systemic immune-inflammation index (SII), ln (tumor size), T stage, and N stage were identified and entered the nomogram, which showed good discrimination and calibration in both sets. On internal validation, 1-yr, 3-yr and 5-yr nomogram demonstrated a good discrimination with an area under the ROC curve (AUC) of 0.77, 0.84 and 0.86, respectively. The AUC for 1-yr, 3-yr and 5-yr nomogram in validation set was 0.77, 0.79 and 0.81, respectively. The OS in low risk group of training cohort and validation cohort was significantly higher than that of intermediate risk group and high risk group, respectively.
We established a nomogram based on PNI, SII and pathological factors for predicting OS in GC patients. In addition, its efficiency was validated by validation set and stratified analysis.
基于炎症、营养和病理因素，建立预测胃癌患者总生存期（OS）的列线图。
纳入 2012 年 1 月至 2017 年 6 月在我院接受根治性胃切除术的胃癌患者，按照 7:3 的比例分为训练集和验证集。采用单因素和多因素 Cox 回归分析与 OS 相关的变量。使用多变量 Cox 模型中的变量构建预测 OS 的列线图。最后，通过 Kaplan-Meier 曲线和 Log-rank 检验分析 1 年、3 年和 5 年 OS，以验证列线图的风险分层效率。
共纳入 366 例胃癌患者。经过单因素和多因素 Cox 回归分析，年龄（HR=1.52，95%CI=1.01-2.30，P=0.044）、CA50（HR=1.90，95%CI=1.12-3.21，P=0.017）、PNI（HR=1.65，95%CI=1.13-2.39，P=0.009）、SII（HR=1.46，95%CI=1.03-2.08，P=0.036）、T 分期（HR=2.26，95%CI=1.01-5.05，P=0.048；HR=7.24，95%CI=3.64-14.40，P<0.001）是影响胃癌患者生存时间的独立影响因素。CEA、预后营养指数（PNI）、全身免疫炎症指数（SII）、ln（肿瘤大小）、T 分期和 N 分期这 5 个因素被确定并纳入列线图，在两组中均显示出良好的区分度和校准度。内部验证显示，1 年、3 年和 5 年列线图的 AUC 分别为 0.77、0.84 和 0.86。验证集的 1 年、3 年和 5 年 AUC 分别为 0.77、0.79 和 0.81。训练集和验证集低危组的 OS 明显高于中危组和高危组。
我们基于 PNI、SII 和病理因素建立了一个预测胃癌患者 OS 的列线图。此外，通过验证集和分层分析验证了其效率。
