Risk Models Based On Populations In High-Risk Areas of Oesophageal Cancer In China For Improving The Oesophageal Cancer Diagnosis Rate

Background: To improve the diagnostic efficiency of early oesophageal cancer, it is of great significance to develop an effective risk prediction model. This study aimed to identify a high-risk population with oesophageal squamous cell carcinoma (ESCC) based on a population screening model. Methods: : From 120 target townships randomly selected from 150 villages selected in Nanchong City, Sichuan Province, China, from Jan 2016 to Sep 2019, a total of 6409 subjects were screened. Each patient underwent standard endoscopy and narrow band imaging (NBI) and iodine staining indicator biopsies to evaluate oesophageal cancer and precancerous lesions. Before endoscopy, the subjects completed a questionnaire about ESCC risk factors. Variables were evaluated by univariate analysis, and variables significantly related to ESCC were extracted by using a logistic regression model. We used the Akaike information criterion to develop the final model structure and the coding form of variables with multiple metrics. We developed two sets of models to define severe dysplasia and above (SDA) and moderate dysplasia and above (MDA) as prognostic events, respectively. Results: : The areas under the receiver operating characteristic curve (AUROC) were0.896 (95%CI, 0.888-0.903) and 0.825 (95% CI, 0.816-0.835) for our SDA and MDA models, respectively. MDA-related and SDA-related factors included age, sex, cigarette smoking, alcohol drinking, pharyngeal foreign body sensation, swallowing obstruction, pain behind the sternum, and discomfort behind the breastbone. Conclusions: : we developed an easy-to-use model to identify individuals with high risk of dysplasia or oesophageal cancer in high-risk areas of oesophageal cancer in China.