Hao Chen1, Can-Tong Liu2, Chao-Qun Hong3, Ling-Yu Chu4, Xin-Yi Huang4, Lai-Feng Wei2, Yi-Wei Lin2, Li-Ru Tian1, Yu-Hui Peng5, Yi-Wei Xu6. 1. State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, PR China. 2. Department of Clinical Laboratory Medicine, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, PR China; Precision Medicine Research Center, Shantou University Medical College, Shantou, Guangdong, PR China. 3. Department of Oncological Laboratory Research, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, PR China. 4. Precision Medicine Research Center, Shantou University Medical College, Shantou, Guangdong, PR China. 5. Department of Clinical Laboratory Medicine, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, PR China; Precision Medicine Research Center, Shantou University Medical College, Shantou, Guangdong, PR China; Department of Oncological Laboratory Research, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, PR China. 6. Department of Clinical Laboratory Medicine, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, PR China; Precision Medicine Research Center, Shantou University Medical College, Shantou, Guangdong, PR China; Guangdong Esophageal Cancer Institute, Shantou University Medical College, Shantou, Guangdong, PR China. Electronic address: yiwei512@126.com.
Abstract
OBJECTIVES: Small cell carcinoma of the esophagus (SCCE) is a rare type of esophageal cancer, and the parameters for prediction of SCCE outcome are unclear. This study aimed to construct a nomogram to predict the outcome of SCCE. METHODS: Patients who underwent treatments at the Sun Yat-Sen University Cancer Center were recruited and divided randomly into training and validation cohorts (61 and 32 patients, respectively). A Cox regression analysis was utilized to identify independent prognostic factors to establish a nomogram and predict overall survival (OS) and disease-free survival (DFS). RESULTS: Information on pretreatment nutritional candidate hemoglobin and inflammation-related neutrophil-to-lymphocyte ratio and platelet count were entered into the nomogram. In the training cohort, the concordance index of the nomogram for OS was 0.728, higher than that obtained by tumor/node/metastasis staging (0.614; P = 0.014). A significant difference was observed in the nomogram for DFS (0.668 vs tumor/node/metastasis stage: 0.616; P = 0.014). Similar results were found in the validation group. The decision curve analysis, net reclassification improvement, and integrated discrimination improvement showed moderate improvement of the nomogram in predicting survival. Based on the cut point calculated according to the constructed nomogram, the high-risk group had poorer OS and DFS than the low-risk group in both cohorts (all P < 0.05). Moreover, the DFS of patients receiving surgery in the high-risk group was better than that of patients receiving single radiation therapy or chemotherapy (P = 0.0111). CONCLUSIONS: A nomogram based on nutrition- and inflammation-related indicators was developed to predict the survival of patients with SCCE.
OBJECTIVES: Small cell carcinoma of the esophagus (SCCE) is a rare type of esophageal cancer, and the parameters for prediction of SCCE outcome are unclear. This study aimed to construct a nomogram to predict the outcome of SCCE. METHODS: Patients who underwent treatments at the Sun Yat-Sen University Cancer Center were recruited and divided randomly into training and validation cohorts (61 and 32 patients, respectively). A Cox regression analysis was utilized to identify independent prognostic factors to establish a nomogram and predict overall survival (OS) and disease-free survival (DFS). RESULTS: Information on pretreatment nutritional candidate hemoglobin and inflammation-related neutrophil-to-lymphocyte ratio and platelet count were entered into the nomogram. In the training cohort, the concordance index of the nomogram for OS was 0.728, higher than that obtained by tumor/node/metastasis staging (0.614; P = 0.014). A significant difference was observed in the nomogram for DFS (0.668 vs tumor/node/metastasis stage: 0.616; P = 0.014). Similar results were found in the validation group. The decision curve analysis, net reclassification improvement, and integrated discrimination improvement showed moderate improvement of the nomogram in predicting survival. Based on the cut point calculated according to the constructed nomogram, the high-risk group had poorer OS and DFS than the low-risk group in both cohorts (all P < 0.05). Moreover, the DFS of patients receiving surgery in the high-risk group was better than that of patients receiving single radiation therapy or chemotherapy (P = 0.0111). CONCLUSIONS: A nomogram based on nutrition- and inflammation-related indicators was developed to predict the survival of patients with SCCE.