A novel nomogram based on the prognostic nutritional index for predicting postoperative outcomes in patients with stage I-III gastric cancer undergoing robotic radical gastrectomy.

The inflammation and nutrition status are crucial factors influencing the outcome of patients with gastric cancer. This study aims to investigate the prognostic value of the preoperative prognostic nutritional index (PNI) in patients with stage I-III gastric cancer undergoing robotic radical gastrectomy combined with Enhanced Recovery after Surgery (ERAS), and further to create a clinical prognosis prediction model. 525 patients with stage I-III gastric cancer who underwent ERAS combined with RRG from July 2010 to June 2018 were included in this work, and were divided randomly into training and validating groups in a 7-to-3 ratio. The association between PNI and overall survival (OS) was assessed by Kaplan-Meier analysis and the log-rank test. Independent risk factors impacting postoperative survival were analyzed with the Cox proportional hazards regression model. A nomogram for predicting OS was constructed based on multivariate analysis, and its predictive performance was evaluated using Harrell's concordance index (C-index), calibration plots, ROC curve, decision curve analysis (DCA), and time-dependent ROC curve analysis. Survival analyses revealed the presence of a significant correlation between low preoperative PNI and shortened postoperative survival (P = 0.001). According to multivariate analysis, postoperative complications (P < 0.001), pTNM stage (II: P = 0.007; III: P < 0.001), PNI (P = 0.048) and lymph node ratio (LNR) (P = 0.003) were independent prognostic factors in patients undergoing ERAS combined with RRG. The nomogram constructed based on PNI, pTNM stage, complications, and LNR was superior to the pTNM stage model in terms of predictive performance. The C-indexes of the nomogram model were respectively 0.765 and 0.754 in the training and testing set, while AUC values for 1-year, 3-year, and 5-year OS were 0.68, 0.71, and 0.74 in the training set and 0.60, 0.67, and 0.72 in the validation set. Preoperative PNI is an independent prognostic factor for patients with stage I-III gastric cancer undergoing ERAS combined with robotic radical gastrectomy. Based on PNI, we constructed a nomogram for predicting postoperative outcomes of gastric cancer patients, which might be utilized clinically.

Shen D ，Zhou G ，Zhao J ，Wang G ，Jiang Z ，Liu J ，Wang H ，Deng Z ，Ma C ，Li J ... -  《Frontiers in Surgery》

[Establishment and validation of a predictive nomogram model for advanced gastric cancer with perineural invasion].

Liu SH ，Hou XY ，Zhang XX ，Liu GW ，Xin FJ ，Wang JG ，Zhang DL ，Wang DS ，Lu Y ... -  《-》

[Prognostic value of a predictive model comprising preoperative inflammatory response and nutritional indexes in patients with gastric cancer].

Wu LL ，Cai MZ ，Wang BG ，Deng JY ，Ke B ，Zhang RP ，Liang H ，Wang XN ... -  《-》

Clinical value and application of a novel nomogram containing inflammatory, nutritional and clinical markers in predicting overall survival of stage II/III gastric cancer patients after radical resection: a bi-centered retrospective study of 2,443 patient

We aimed to identify nutritional, inflammatory and clinical indicators associated with stage II/III gastric cancer in patients, and construct a nomogram model for accurate prediction of prognosis of patients. We retrospectively recruited stage II/III gastric cancer (GC) patients who underwent radical gastrectomy at Fudan University Shanghai Cancer Center, from 2012 to 2019. The patients were randomly divided into training and internal validation sets, and then the Maximum log-rank statistic method was used to determine the optimal cut-off value. Next, we performed univariate and multivariate Cox regression analyses to identify independent risk factors associated with overall survival (OS). These were subsequently used to develop a nomogram model. We validated this model in patients with stage II/III gastric cancer (from 2010 to 2019) at Guangxi Medical University Affiliated Tumor Hospital. A total of 2,443 patients met our inclusion criteria and were therefore included in our study. Patients from Fudan University Shanghai Cancer Center were randomly divided into training (n=1725) and internal validation (n=430) sets, while those from Guangxi Medical University Affiliated Tumor Hospital were used as the external validation set (n=288). Results from univariate and multivariate Cox regression analyses revealed that age (adjusted HR, 1.23; 95% CI, 1.05-1.44; P=0.012), TNM stage (adjusted HR, 3.62; 95% CI, 2.79-4.68; P<0.001), CEA (adjusted HR, 1.40; 95% CI, 1.14-1.71; P<0.001), CA199 (adjusted HR, 1.47; 95% CI, 1.21-1.79; P<0.001), and Prognostic Nutritional Index (PNI, adjusted HR, 0.81; 95% CI, 0.67-0.98; P=0.026) were independent prognostic factors for OS in the training set. The established nomogram model, with a C-index of 0.67, had 3- and 5-year Area under Curve (AUC) values of 0.719 and 0.714, respectively. Notably, the model effectively distinguished patients' OS in both the internal (P<0.001) and external (P<0.001) datasets. PNI is an independent prognostic factor for stage II/III GC patients after radical resection. The established novel nomogram model, based on nutritional, inflammatory and clinical indicators, can accurately and efficiently predict prognosis of stage II/III GC patients.

Liang S ，Wei C ，Tang L ，Gao J ，Yan W ，Wu J ，Long Z ，Wang Y ... -  《-》

[Establishment and verification of a prognostic nomogram for survival of tongue squamous cell carcinoma patients who underwent cervical dissection].

Su J ，Wang X ，Sun Z 《-》