Li Xiang, Fu Zhongxue, Zhang Jun, Xu Jinming, Wang Lianwei, Li Ke
Department of Gastrointestinal Surgery, Chongqing University FuLing Hospital, Chongqing, China.
Department of General Surgery, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Front Nutr. 2024 Nov 18;11:1438319. doi: 10.3389/fnut.2024.1438319. eCollection 2024.
The objectives of this study were to integrate the Prognostic Nutritional Index, Controlling Nutritional Status, and Nutritional Risk Index, into a novel Nutrition-combined Prognostic Index (NCPI), and to develop and validate a nomogram to predict overall survival (OS) in patients with gastric cancer (GC).
Data from 609 patients with GC, collected between January 1, 2017, and April 30, 2023, were retrospectively analyzed. Optimal cut-off values for nutritional parameters were determined using X-Tile software, and the Kaplan-Meier method applied for survival analysis. Univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses were conducted, and a nomogram for predicting OS in patients with GC constructed and validated.
Inferior nutritional status was strongly correlated with worse clinicopathologic features and prognosis of patients with GC. NCPI, body mass index, American Joint Committee on Cancer T stage, and lymph node ratio were identified as independent risk factors for OS. A nomogram including these factors predicted 1-, 3-, and 5-year OS, with training and validation set C-index values of 0.716 and 0.77, respectively. Calibration curves demonstrated that the predicted outcomes closely matched the actual results, and decision curve analysis highlighted the high practical value of the model.
The novel nutritional marker, NCPI, is closely associated with the clinicopathologic features and OS of patients with GC. The practical value of the NCPI-based nomogram was demonstrated and a web-based calculator developed.
本研究的目的是将预后营养指数、控制营养状况和营养风险指数整合为一种新的营养综合预后指数(NCPI),并开发和验证一种列线图以预测胃癌(GC)患者的总生存期(OS)。
回顾性分析了2017年1月1日至2023年4月30日期间收集的609例GC患者的数据。使用X-Tile软件确定营养参数的最佳截断值,并应用Kaplan-Meier方法进行生存分析。进行单因素、最小绝对收缩和选择算子以及多因素Cox回归分析,并构建和验证GC患者OS预测列线图。
营养状况较差与GC患者更差的临床病理特征和预后密切相关。NCPI、体重指数、美国癌症联合委员会T分期和淋巴结比率被确定为OS的独立危险因素。包含这些因素的列线图预测了1年、3年和5年OS,训练集和验证集的C指数值分别为0.716和0.77。校准曲线表明预测结果与实际结果密切匹配,决策曲线分析突出了该模型的高实用价值。
新的营养标志物NCPI与GC患者的临床病理特征和OS密切相关。证明了基于NCPI的列线图的实用价值并开发了基于网络的计算器。