Xueping Wang1, Minjie Mao1, Shihao Zhu2, Shan Xing1, Yiling Song1, Lin Zhang3, Peidong Chi4. 1. Department of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China. 2. Department of Etiology and Carcinogenesis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China. 3. Department of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China. zhanglin@sysucc.org.cn. 4. Department of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China. chipeidong126@126.com.
Abstract
INTRODUCTION: Gastric cancer (GC) is the fifth most common cancer worldwide, and every year approximately 950,000 individuals are diagnosed worldwide. Our study aimed to establish an effective nomogram to predict the prognosis of GC based on inflammation biomarkers. METHODS: We retrospectively analysed GC patients from the Sun Yat-sen University Cancer Center. The nomogram was developed with a primary cohort (n = 1067), and 537 patients were included in the validation cohort. The univariate survival analyses included 19 biomarkers. RESULTS: The multivariate analysis showed that tumour stage, metastasis stage and C-reactive protein (CRP), albumin (ALB), carcinoembryonic antigen (CEA) and carbohydrate antigen-199 (CA199) levels as well as the lymphocyte (LYM) count were independent risk factors for the prognosis of GC patients. The nomogram was based on the above factors. In the primary cohort, the nomogram had a concordance index (C-index) of 0.825 (95% CI 0.796-0.854), which was higher than the C-index of the AJCC TNM stage and that of the other biomarkers (CEA and CA199). The calibration plot suggested good agreement between the actual and nomogram-predicted overall survival (OS) probabilities, and the decision curve analyses showed that the nomogram model had a higher overall net benefit in predicting OS than the AJCC TNM stage. Moreover, we divided the patients into the following three distinct risk groups for OS based on the nomogram points: low, middle and high risk. The differences in OS rates were significant among the subgroups (P < 0.001). CONCLUSION: A novel nomogram integrated with inflammatory prognostic factors was proposed, which is highly predictive of OS in GC patients.
INTRODUCTION:Gastric cancer (GC) is the fifth most common cancer worldwide, and every year approximately 950,000 individuals are diagnosed worldwide. Our study aimed to establish an effective nomogram to predict the prognosis of GC based on inflammation biomarkers. METHODS: We retrospectively analysed GC patients from the Sun Yat-sen University Cancer Center. The nomogram was developed with a primary cohort (n = 1067), and 537 patients were included in the validation cohort. The univariate survival analyses included 19 biomarkers. RESULTS: The multivariate analysis showed that tumour stage, metastasis stage and C-reactive protein (CRP), albumin (ALB), carcinoembryonic antigen (CEA) and carbohydrate antigen-199 (CA199) levels as well as the lymphocyte (LYM) count were independent risk factors for the prognosis of GC patients. The nomogram was based on the above factors. In the primary cohort, the nomogram had a concordance index (C-index) of 0.825 (95% CI 0.796-0.854), which was higher than the C-index of the AJCC TNM stage and that of the other biomarkers (CEA and CA199). The calibration plot suggested good agreement between the actual and nomogram-predicted overall survival (OS) probabilities, and the decision curve analyses showed that the nomogram model had a higher overall net benefit in predicting OS than the AJCC TNM stage. Moreover, we divided the patients into the following three distinct risk groups for OS based on the nomogram points: low, middle and high risk. The differences in OS rates were significant among the subgroups (P < 0.001). CONCLUSION: A novel nomogram integrated with inflammatory prognostic factors was proposed, which is highly predictive of OS in GC patients.
Authors: Roheena Z Panni; Alexandra G Lopez-Aguiar; Jingxia Liu; George A Poultsides; Flavio G Rocha; William G Hawkins; Steven M Strasberg; Nikolaos A Trikalinos; Shishir Maithel; Ryan C Fields Journal: J Surg Oncol Date: 2019-07-24 Impact factor: 3.454