Siyuan Liang1,2, Chuanyi Wei3, Liping Tang4, Jie Gao3, Wenbin Yan1,5, Jiangchun Wu1,6, Ziwen Long1,2, Yanong Wang1,2. 1. Department of Oncology, Shanghai Medical College, Fudan University Shanghai 200032, China. 2. Department of Gastric Surgery, Fudan University Shanghai Cancer Center, Fudan University Shanghai 200032, China. 3. Department of Gastrointestinal Surgery, Affiliated Tumor Hospital, Guangxi Medical University Nanning 530021, Guangxi, China. 4. Department of Rehabilitation Medicine, Pudong New District Gongli Hospital Shanghai 200032, China. 5. Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Fudan University Shanghai 200032, China. 6. Department of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Fudan University Shanghai 200032, China.
Abstract
OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. AJTR
OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. AJTR
Authors: Arved Weimann; Marco Braga; Franco Carli; Takashi Higashiguchi; Martin Hübner; Stanislaw Klek; Alessandro Laviano; Olle Ljungqvist; Dileep N Lobo; Robert Martindale; Dan L Waitzberg; Stephan C Bischoff; Pierre Singer Journal: Clin Nutr Date: 2017-03-07 Impact factor: 7.324