Author:
Chen Yuqian,Dang Yini,Sang Huaiming,Wang Xiaoyong,Chen Meihong,Lu Daiwei,Zhang Guoxin
Abstract
Abstract
Objective
To establish and validate a model to determine the progression risk of gastric low-grade intraepithelial neoplasia (LGIN).
Methods
A total of 705 patients with gastric LGIN at the endoscopy center of Jiangsu Provincial People's Hospital during January 2010 and August 2017 were retrospectively reviewed. Basic clinical and pathological information were recorded. According to the time sequence of the initial examination, the first 605 patients were enrolled in the derivation group, and the remaining 100 patients were used in the validation group. SPSS 19 software was used as statistical analysis to determine independent risk factors for progression of LGIN of the stomach and to establish a risk model. The ROC was used to verify the application value of the predictive model.
Results
Univariate and multivariate analysis suggested that sex, multiple location, congestion, ulceration and form were independent risk factors for prolonged or advanced progression in patients with LGIN. Based on this, a predictive model is constructed: P = ex/(1 + ex) X = − 10.399 + 0.922 × Sex + 1.934 × Multiple Location + 1.382 × Congestion + 0.797 × Ulceration + 0.525 × Form. The higher of the P value means the higher risk of progression. The AUC of the derivation group and validation group were 0.784 and 0.766, respectively.
Conclusion
Sex, multi-site, hyperemia, ulcer and morphology are independent risk factors for the prolongation or progression of patients with gastric LGIN. These factors are objective and easy to obtain data. Based on this, a predictive model is constructed, which can be used in management of patients. The model can be used to identify high-risk groups in patients with LGIN that may progress to gastric cancer. Strengthening follow-up or endoscopic treatment to improve the detection rate of early cancer or reduce the incidence of gastric cancer can provide a reliable basis for the treatment of LGIN.
Funder
National Natural Science Foundation of China
Jiangsu medical leading talent and innovation team
Jiangsu Province "333"project
Jiangsu Standard Diagnosis and Treatment Research for Key Disease
Publisher
Springer Science and Business Media LLC