Objective:Autoimmune gastritis (AIG) is characterized by the loss of acid-secreting glands, resulting in hypochlorhydria and hypergastrinemia, conditions that significantly increase the risk of developing gastric neuroendocrine tumors (NETs) and gastric adenocarcinoma. In recent years, AIG has garnered increasing attention in both clinical and research settings. However, comprehensive studies on the clinical and endoscopic characteristics of AIG particularly cases complicated by gastric neoplastic lesions remain limited in China. This study aims to comprehensively summarize the clinical and endoscopic features of AIG and its associated gastric neoplastic lesions.Methods:A retrospective analysis was conducted using medical records from patients with AIG diagnosed at Sichuan Provincial People′s Hospital between 2019 and 2024. Data collected included demographic information, medical history, serological test results, imaging findings, and endoscopic observations. The clinical and endoscopic features of AIG patients with gastric NETs or epithelial-derived tumors were compared to those without gastric neoplastic lesions to identify potential risk factors and diagnostic indicators for tumor development in AIG.Results:A total of 72 patients with AIG were included, of whom 62.5% (45/72) were female, with an age range of 30 to 79 years old (mean age: 57±11 years). Parietal cell antibody (PCA) positivity was observed in 93.1% (67/72), intrinsic factor antibody (IFA) positivity in 45.8% (33/72), and Helicobacter pylori ( H. pylori) co-infection in 48.6% (35/72). Endoscopically, 84.7% (61/72) showed prominent corpus-dominant advanced atrophy; 47.2% (34/72) had sticky adherent mucus; and 41.7% (30/72) displayed residual oxyntic mucosa in the gastric body or fundus. Only 23.6% (17/72) had normal antrum mucosa, and just 16.7% (12/72) showed a circular wrinkle-like pattern. Gastric neoplastic lesions were identified in 35 patients (48.6%), including 15 cases (20.8%) with NETs and 20 cases (27.8%) with epithelial-derived tumors (four adenocarcinomas, three adenomas, and 13 cases of intraepithelial neoplasia). No significant differences were found between tumor and non-tumor groups in terms of age, gender, PCA/IFA positivity, gastrin levels, anemia status, folic acid, or serum iron levels. However, patients with NETs had significantly lower vitamin B 12 levels compared to those without tumors (183±111 ng/L vs. 323±159 ng/L, t=2.47, P=0.042). Additionally, AIG patients with NETs were more likely to be H.pylori-negative compared to both the non-tumor group (66.7% vs. 35.1%, χ2=5.26, P=0.072) and the epithelial-derived tumor group (66.7% vs. 30.0%, χ2=5.80, P=0.055). The incidence of reverse atrophy in the epithelial-derived tumor group was significantly lower than that in the non-tumor group (65.0% vs. 91.9%, χ2=6.49, P=0.011) and the NETs group (65.0% vs. 93.3%, χ2=3.90, P=0.048).? Conclusion:In AIG patients with NETs, serum vitamin B 12 levels are significantly reduced, suggesting that vitamin B 12 deficiency may be a key risk factor or clinical indicator for NET development in AIG. Furthermore, NETs are more frequently observed in AIG patients without H.pylori infection, while epithelial-derived tumors are more commonly associated with H.pylori co-infection.

Objective:Autoimmune gastritis (AIG) is characterized by the loss of acid-secreting glands, resulting in hypochlorhydria and hypergastrinemia, conditions that significantly increase the risk of developing gastric neuroendocrine tumors (NETs) and gastric adenocarcinoma. In recent years, AIG has garnered increasing attention in both clinical and research settings. However, comprehensive studies on the clinical and endoscopic characteristics of AIG particularly cases complicated by gastric neoplastic lesions remain limited in China. This study aims to comprehensively summarize the clinical and endoscopic features of AIG and its associated gastric neoplastic lesions.Methods:A retrospective analysis was conducted using medical records from patients with AIG diagnosed at Sichuan Provincial People′s Hospital between 2019 and 2024. Data collected included demographic information, medical history, serological test results, imaging findings, and endoscopic observations. The clinical and endoscopic features of AIG patients with gastric NETs or epithelial-derived tumors were compared to those without gastric neoplastic lesions to identify potential risk factors and diagnostic indicators for tumor development in AIG.Results:A total of 72 patients with AIG were included, of whom 62.5% (45/72) were female, with an age range of 30 to 79 years old (mean age: 57±11 years). Parietal cell antibody (PCA) positivity was observed in 93.1% (67/72), intrinsic factor antibody (IFA) positivity in 45.8% (33/72), and Helicobacter pylori ( H. pylori) co-infection in 48.6% (35/72). Endoscopically, 84.7% (61/72) showed prominent corpus-dominant advanced atrophy; 47.2% (34/72) had sticky adherent mucus; and 41.7% (30/72) displayed residual oxyntic mucosa in the gastric body or fundus. Only 23.6% (17/72) had normal antrum mucosa, and just 16.7% (12/72) showed a circular wrinkle-like pattern. Gastric neoplastic lesions were identified in 35 patients (48.6%), including 15 cases (20.8%) with NETs and 20 cases (27.8%) with epithelial-derived tumors (four adenocarcinomas, three adenomas, and 13 cases of intraepithelial neoplasia). No significant differences were found between tumor and non-tumor groups in terms of age, gender, PCA/IFA positivity, gastrin levels, anemia status, folic acid, or serum iron levels. However, patients with NETs had significantly lower vitamin B 12 levels compared to those without tumors (183±111 ng/L vs. 323±159 ng/L, t=2.47, P=0.042). Additionally, AIG patients with NETs were more likely to be H.pylori-negative compared to both the non-tumor group (66.7% vs. 35.1%, χ2=5.26, P=0.072) and the epithelial-derived tumor group (66.7% vs. 30.0%, χ2=5.80, P=0.055). The incidence of reverse atrophy in the epithelial-derived tumor group was significantly lower than that in the non-tumor group (65.0% vs. 91.9%, χ2=6.49, P=0.011) and the NETs group (65.0% vs. 93.3%, χ2=3.90, P=0.048).? Conclusion:In AIG patients with NETs, serum vitamin B 12 levels are significantly reduced, suggesting that vitamin B 12 deficiency may be a key risk factor or clinical indicator for NET development in AIG. Furthermore, NETs are more frequently observed in AIG patients without H.pylori infection, while epithelial-derived tumors are more commonly associated with H.pylori co-infection.

The purpose of this article was to introduce the basic concepts,calculation methods,two examples and the implementation of SAS calculation methods related to the cluster analysis of disordered samples.The basic concepts included nominal variables,ordered variables,qualitative variables,interval variables ratio variables and distance.The calculation methods involved the first set of 15 distance calculation formulas and the Ward's method calculation formula for measuring the distance between two clusters of samples.The data in the two examples were"physical morphology data of 16-year-old boys from 27 ethnic minorities in China"and"labor health supervision data from 14 provinces and municipalities in China in 1995".Using SAS software,Cluster analysis of disordered samples was performed on the data from two instances,and the SAS output results were explained.

The purpose of the paper was to introduce the basic concepts,calculation methods,two examples and the implementation of SAS calculation methods related to the cluster analysis of disordered samples.The basic concepts included similarity,dissimilarity,metric and non metric type.The calculation methods involved the second set of distance methods(12 in total)for measuring the distance between two samples and the centroid method for measuring the distance between two clusters of samples.The data in the two examples were"survey data on the expenditure of farmers in 16 regions of China in 1982"and"measurement values of 13 sports events on two quantitative indicators".Using SAS software,cluster analysis of disordered samples was performed on the data from two instances,and the SAS output results were explained.

The purpose of this article was to introduce the basic concepts,calculation methods,two examples,and the implementation of SAS calculation methods related to the cluster analysis of disordered samples.The basic concepts included symmetric nominal variables,missing values,matching coefficients,and Hamann coefficients.The calculation method involved the third set of distance method(8 in total)and average linkage method.The data in the two examples were"survey data reflecting the air pollution conditions in 39 cities in the United States"and"population growth and decline data of stem borer in a certain area from 1962 to 1988".Using SAS software,Cluster analysis of disordered samples was performed on the data from two instances,and the SAS output results were explained.

The purpose of this article was to introduce the basic concepts,calculation methods,two examples and SAS implementation related to the multivariate multiple linear regression analysis.Basic concepts included multivariate multiple regression analysis,ordinary least squares,partial least squares,principal component analysis and canonical correlation analysis.The calculation methods involved data preparation and implementation steps.The data in the two examples were"measurement results of body morphology indicators and functional indicators of Han male students"and"measurement results of physical shape and health status indicators of two groups of subjects".With the help of SAS software,the multivariate multiple linear regression analysis was carried out on the data in the two examples,and an explanation was made for the output results of SAS.

The purpose of the paper was to introduce the basic concepts,calculation methods,two examples and SAS implementation related to the path analysis.Basic concepts included explicit variables and latent variables,direct effects and indirect effects,path diagrams,path models and path coefficients.The calculation methods involved the mathematical model and assumptions of path analysis,and the specific calculation in path analysis.The data in the two examples were"correlation coefficient matrix between 6 items including nurses'sense of organizational fairness and emotional intelligence"and"variance covariance matrix of family,school and student depression data".With the help of SAS software,the path analysis of the data in the two examples was carried out,and an explanation was made for the output results of SAS.

The purpose of this article was to introduce the basic concepts,calculation methods,two examples and the method of analyzing examples with SAS software related to the conjoint analysis.Basic concepts included utility and part-worth utility,relative importance weights,profiles and full profiles,orthogonal design and uniform design.The calculation methods involved the basic idea,basic model,calculation and implementation steps of part-worth utility.The two examples were"computer attributes and levels"and"tire attributes and levels".With the help of SAS software,the data in the two examples were analyzed by using the conjoint analysis,separately,and an explanation was given for the output results.

The purpose of the paper was to introduce the basic concepts,calculation methods,two examples and SAS implementation related to the qualitative data discrimination analysis.Basic concepts included qualitative and categorical variables,discriminant analysis,maximum likelihood method,prior probability and prior distribution,posterior probability and posterior distribution.The calculation methods involved the maximum likelihood discriminant method and Bayes formula discriminant approach.The data in the two examples were"the frequency of various types of appendicitis in each detail"and"the symptoms and signs of a patient".With the help of SAS software,the discriminant analysis was carried out on the data in the two examples,and an explanation was made for the output results of SAS.

The purpose of this article was to introduce the basic concepts,calculation methods,two examples related to the exploratory factor analysis,and how to implement calculations using SAS.Basic concepts included common factors and special factors,factor loadings,common factor variances and factor scree plots.The calculation methods involved the mathematical model of factor analysis,principal component method,principal factor method,centroid method and maximum likelihood method.The data in the two examples were"evaluation data of 31 provincial government portal websites"and"sources of basic construction investment in various regions across the country".With the help of SAS software,the exploratory factor analysis was conducted on the data in the two examples,and an explanation was given to the SAS output results.