Comparative study of treatment options and construction nomograms to predict survival for early-stage esophageal cancer: a population-based study. (3rd June 2021)

• Record Type: Journal Article
• Authors: Jia, Ran; Xiao, Wanyi; Zhang, Hongdian; Yu, Zhentao
• Is Part Of: Scandinavian journal of gastroenterology. Volume 56:Number 6(2021)
• Page Start: 635
• Page End: 646
• Publication Date: 2021-06-03
• Subjects: Esophageal cancer; nomogram; early-stage; treatment option; Gastroenterology -- Periodicals; Digestive organs -- Diseases -- Periodicals; 616.33
• DOI: 10.1080/00365521.2021.1910997
• Languages: English
• ISSNs: 0036-5521

Abstract

Abstract: Background: The aim of this study was to investigate the impact of several common treatment options on the long-term survival of patients with early-stage esophageal cancer and to construct nomograms for survival prediction. Method: This study was performed using the Surveillance, Epidemiology and End Results (SEER) database (2004–2015) on patients with early-stage (pT1N0M0) esophageal cancer who underwent endoscopic local therapy (ET), radiotherapy (RT), esophagectomy (ES) or neoadjuvant therapy (NT). Multivariate Cox regression was used to explore which factors influenced patient survival, and these factors were then incorporated into propensity sore matching (PSM) and the construction of nomogram plots. Kaplan-Meier analysis was used to compare whether there was a difference in long-term survival between the other three treatments and esophagectomy. Result: Data from 4184 patients were included in this study. Multivariate Cox regression analysis showed that age, grade, marital status, and treatment method were independent factors affecting survival. After matching, Kaplan-Meier analysis showed that the ET group had better CSS than the ES group, but no difference in OS, while the NT and RT groups had worse OS and CSS than the ES group. In the nomogram prediction model, the c-indexes of the training and validation cohorts were 0.805 and 0.794, respectively. Additionally the ROC curve (5-year AUC = 0.877) and DCA curve showed that the model had a good predictive effect. Conclusion: For early-stage esophageal cancer, the results of this study showed that ET is not inferior to ES. Based on the independent factors affecting prognosis identified in the study, we constructed and validated a predictive model for predicting long-term survival in patients with early-stage esophageal cancer.