Prognostic analysis and nomogram establishment in patients with early esophageal cancer receiving endoscopic therapy: a population-based study

Author:

Sun Danping1,Yi Jun12,Gong Lingqi3,Wu Yu42,Liu Xiaowei526ORCID

Affiliation:

1. Department of Gastroenterology, Xiangya Hospital, Central South University, Changsha, Hunan, China

2. Hunan International Scientific and Technological Cooperation Base of Artificial Intelligence Computer Aided Diagnosis and Treatment for Digestive Disease, Changsha, Hunan, China

3. Department of Gastroenterology, Hunan Provincial People’s Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China

4. Department of Gastroenterology, Xiangya Hospital, Central South University, No. 87 Xiangya Road, Kaifu District, Changsha, Hunan 410000 China

5. Department of Gastroenterology, Xiangya Hospital, Central South University, No. 87 Xiangya Road, Kaifu District, Changsha, Hunan 410000, China

6. National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan, China

Abstract

Background: The growing numbers of early esophageal cancer (EEC) have increased the demand for endoscopic therapy. Objectives: To clarify the influential factors for the prognosis of patients with EEC receiving endoscopic surgery, and to construct a nomogram to evaluate the prognostic value of endoscopic therapy. Design: Prognostic analysis study. Methods: Clinical data of EEC patients who received endoscopic therapy between 2004 and 2015 were collected from the Surveillance, Epidemiology, and End Results database and used to construct the nomogram. The prognosis was analyzed by R language; the nomogram was constructed by Cox survival analysis; and the accuracy of the nomogram was verified by C index and the receiver operating characteristic (ROC) and calibration curves. X-Tile software was used to stratify the risk of patients. Results: Our study constructed the nomogram of the prognosis of patients with EEC treated by endoscopic surgery, including 1118 patients and 5 independent prognostic factors of esophageal cancer-specific survival. The C index and the area under the ROC curve (AUC) of the training and verification cohorts were all >0.75. The calibration curve also reflected the good consistency of the model in predicting survival. Significant difference in the risk of patients from different stratifications with the same T staging existed, and the model had a better C index than that of the T staging. Conclusion: Our study reports potential influential factors affecting the prognosis of EEC patients who received endoscopic therapy and establishes a reliable nomogram to predict the risk and prognosis, which has certain advantages compared with traditional TNM staging system.

Funder

Appropriate Technology Promotion Project of National Clinical Research Center for Geriatric Disorders

Hunan International Scientific and Technological Cooperation Base of Artificial Intelligence Computer Aided Diagnosis and Treatment for Digestive Disease

Publisher

SAGE Publications

Subject

Gastroenterology

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