Jisheng Li1, Hejiang Yu2, Ling Peng3, Li Li1, Xiangling Wang1, Jing Hao1, Na Shao4. 1. Department of Medical Oncology, Cheeloo College of Medicine, Qilu Hospital, Shandong University, Jinan, Shandong, China. 2. Department of Oncology, Yunyang County People's Hospital, Yunyang, Chongqing, China. 3. Department of Respiratory Disease, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang Province, China. 4. Department of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
Abstract
BACKGROUND: Small-cell carcinoma is a relatively infrequent pathological variety of esophageal cancer. In this study, a novel nomogram model was developed to evaluate the cancer-specific survival (CSS) and overall survival (OS) of patients with primary esophageal small-cell carcinoma (ESmCC). MATERIALS AND METHODS: In total, 502 patients with primary ESmCC were identified based on data from 1973 to 2015 retrieved from the surveillance, epidemiology, and end results database. Clinical characteristics such as age at diagnosis, gender, race, site, tumor stage, surgery, radiotherapy, and chemotherapy were included for multivariate logistic analyses to predict CSS and OS. Nomogram models for the prediction of CSS and OS in ESmCC patients were tested with the concordance index (C-index) method and calibration curves. RESULTS: From our multivariate analyses, race, stage, chemotherapy, and radiotherapy, but not surgery, were significantly associated with the CSS of ESmCC patients, while age at diagnosis, stage, chemotherapy, and radiotherapy were significantly associated with their OS. Nomograms were developed using age at diagnosis, race, gender, stage, surgery, radiotherapy, and chemotherapy to predict the two survival measures; these nomograms were verified as accurate in predicting OS and CSS in ESmCC patients, with C-index values of 0.736 and 0.731, respectively. CONCLUSIONS: By utilizing easily accessible clinicopathological information, we established a simple but useful tool for predicting the CSS and OS of ESmCC patients that could help to make personalized clinical decisions for patients with this rare malignancy. Cancer-specific survival, esophageal small-cell carcinoma, nomogram, overall survival, surveillance, epidemiology, and end results.
BACKGROUND: Small-cell carcinoma is a relatively infrequent pathological variety of esophageal cancer. In this study, a novel nomogram model was developed to evaluate the cancer-specific survival (CSS) and overall survival (OS) of patients with primary esophageal small-cell carcinoma (ESmCC). MATERIALS AND METHODS: In total, 502 patients with primary ESmCC were identified based on data from 1973 to 2015 retrieved from the surveillance, epidemiology, and end results database. Clinical characteristics such as age at diagnosis, gender, race, site, tumor stage, surgery, radiotherapy, and chemotherapy were included for multivariate logistic analyses to predict CSS and OS. Nomogram models for the prediction of CSS and OS in ESmCC patients were tested with the concordance index (C-index) method and calibration curves. RESULTS: From our multivariate analyses, race, stage, chemotherapy, and radiotherapy, but not surgery, were significantly associated with the CSS of ESmCC patients, while age at diagnosis, stage, chemotherapy, and radiotherapy were significantly associated with their OS. Nomograms were developed using age at diagnosis, race, gender, stage, surgery, radiotherapy, and chemotherapy to predict the two survival measures; these nomograms were verified as accurate in predicting OS and CSS in ESmCC patients, with C-index values of 0.736 and 0.731, respectively. CONCLUSIONS: By utilizing easily accessible clinicopathological information, we established a simple but useful tool for predicting the CSS and OS of ESmCC patients that could help to make personalized clinical decisions for patients with this rare malignancy. Cancer-specific survival, esophageal small-cell carcinoma, nomogram, overall survival, surveillance, epidemiology, and end results.