Jin JZ, Liang X, Liu SP, Wang RL, Zhang QW, Shen YF, Li XB. Association between autoimmune gastritis and gastric polyps: Clinical characteristics and risk factors. World J Gastrointest Oncol 2025; 17(1): 92908 [DOI: 10.4251/wjgo.v17.i1.92908]
Corresponding Author of This Article
Xiao-Bo Li, MD, PhD, Doctor, Professor, Department of Gastroenterology, Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Institute of Digestive Diseases, No. 160 Pujian Road, Pudong New Area, Shanghai 200127, China. lxb196911@163.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Jing-Zheng Jin, Division of Gastroenterology and Hepatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
Jing-Zheng Jin, Xiao Liang, Shu-Peng Liu, Qing-Wei Zhang, Yu-Feng Shen, Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Diseases, Shanghai 200001, China
Xiao Liang, Shu-Peng Liu, Qing-Wei Zhang, Division of Gastroenterology and Hepatology, Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
Rui-Lan Wang, Division of Gastroenterology and Hepatology, Sichuan Armed Police Corps Hospital, Leshan 610041, Sichuan Province, China
Yu-Feng Shen, Division of Gastroenterology and Hepatology, NHC Key Laboratory of Digestive Diseases, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
Xiao-Bo Li, Department of Gastroenterology, Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Institute of Digestive Diseases, Shanghai 200127, China
Co-corresponding authors: Yu-Feng Shen and Xiao-Bo Li.
Author contributions: Jin JZ, Liang X, and Liu SP contributed equally to this research, Jin JZ and Liang X are the co-first authors of this manuscript. Jin JZ and Liang X conceptualized the study and authored the manuscript; Liu SP played a key role in designing the analysis plans; Wang RL were responsible for data collection and provided technical support throughout the research; Zhang QW, Shen YF, and Li XB also made equal contributions to the study; Zhang QW, Shen YF, and Li XB meticulously reviewed, proofread the manuscript, and suggested valuable improvements, they are the co-corresponding authors of this manuscript. All authors reviewed and approved the final version of the manuscript.
Supported bythe Health Technology Project of Pudong New District Health Commission, No. PW2020D-12.
Institutional review board statement: This study received approval from the Institutional Ethics Committee of Renji Hospital, Shanghai Jiao Tong University, School of Medicine, Approval No. LY2024-141-B.
Informed consent statement: The informed consent was waived by the Institutional Ethics Committee of Renji Hospital, Shanghai Jiao Tong University, School of Medicine.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Xiao-Bo Li, MD, PhD, Doctor, Professor, Department of Gastroenterology, Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Institute of Digestive Diseases, No. 160 Pujian Road, Pudong New Area, Shanghai 200127, China. lxb196911@163.com
Received: February 10, 2024 Revised: August 23, 2024 Accepted: September 11, 2024 Published online: January 15, 2025 Processing time: 306 Days and 4.2 Hours
Abstract
BACKGROUND
The relationship between autoimmune gastritis (AIG) and gastric polyps (GPs) is not well understood.
AIM
To explore the clinical characteristics and risk factors of AIG with GPs in patients.
METHODS
This double center retrospective study included 530 patients diagnosed with AIG from July 2019 to July 2023. We collected clinical, biochemical, serological, and demographic data were of each patient. Logistic regression analyses, both multivariate and univariate, were conducted to pinpoint independent risk factors for GPs in patients with AIG patients. Receiver operating characteristic curves were utilized to establish the optimal cutoff values, sensitivity, and specificity of these risk factors for predicting GPs in patients with AIG.
RESULTS
Patients with GPs had a higher median age than those without GPs [61 (52.25-69) years vs 58 (47-66) years, P = 0.006]. The gastrin-17 levels were significantly elevated in patients with GPs compared with those without GPs [91.9 (34.2-138.9) pmol/mL vs 60.9 (12.6-98.4) pmol/mL, P < 0.001]. Additionally, the positive rate of parietal cell antibody (PCA) antibody was higher in these patients than in those without GPs (88.6% vs 73.6%, P < 0.001). Multivariate and univariate analyses revealed that PCA positivity [odds ratio (OR) = 2.003, P = 0.017], pepsinogen II (OR = 1.053, P = 0.015), and enterochromaffin like cells hyperplasia (OR = 3.116, P < 0.001) were significant risk factors for GPs, while pepsinogen I was identified as a protective factor.
CONCLUSION
PCA positivity and enterochromaffin like cells hyperplasia are significant risk factor for the development of GPs in patients with AIG. Elevated gastrin-17 levels may also play a role in this process. These findings suggest potential targets for further research and therapeutic intervention in managing GPs in patients with AIG.
Core Tip: In this double-center retrospective study, we explore the clinical characteristics and risk factors associated with autoimmune gastritis (AIG) and gastric polyps in 530 patients diagnosed with AIG from July 2019 to July 2023. The study found that higher age, elevated gastrin-17 levels, and higher positivity rates of parietal cell antibody antibodies were significantly associated with the presence of gastric polyps in AIG patients. Through univariate and multivariate analyses, parietal cell antibody positivity, elevated pepsinogen II levels, and enterochromaffin like cells hyperplasia were identified as significant risk factors.
Citation: Jin JZ, Liang X, Liu SP, Wang RL, Zhang QW, Shen YF, Li XB. Association between autoimmune gastritis and gastric polyps: Clinical characteristics and risk factors. World J Gastrointest Oncol 2025; 17(1): 92908
Gastric polyps (GPs) are protrusions that form within the stomach’s mucosal or submucosal layers. They are typically asymptomatic and are often detected incidentally during routine endoscopic examinations. While most GPs are benign, there is a potential for some to harbor dysplasia, which can progress to invasive cancer. The prevalence of GPs varies among sources, with several high-powered studies, reporting rates between 2% to 6% in patients undergoing endoscopy[1,2]. The most commonly observed types of GPs include gastric hyperplastic polyps (GHPs), characterized by significant foveolar hyperplasia; fundic gland polyps (FGPs), which are marked by dilated and irregularly budding fundic glands primarily composed of parietal cells, with a smaller proportion of chief cells. Additionally, adenomatous polyps, which are associated with low-grade glandular dysplasia[3-6], and gastric neuroendocrine neoplasms (gNENs), which are well-differentiated epithelial tumors arising from neuroendocrine cells within the gastric mucosa, can also present as submucosal lesions with specific patterns[7]. All these types can produce a mucosal or submucosal protrusion that appears as a GP[8].
GPs almost never occur in normal gastric mucosa. The majority of GPs are found incidentally during endoscopic investigations, and not fully the exact mechanism behind the formation of GHPs remains unclear[9]. However, their development is thought to be associated with chronic inflammation, commonly linked to atrophic gastritis and Helicobacter pylori (H. pylori) infection[10,11]. Prolonged use of proton pump inhibitors (PPIs) may lead to hypergastrinemia, which is associated with the development of both FGPs and GHPs[12,13]. The primary risk factors for adenoma development include age and chronic irritation or inflammation of the tissue, which can lead to intestinal metaplasia. This metaplasia increase the risk of malignant transformation, often linked to acquired mutations in genes such as p53 and Ki-67[14,15].
Autoimmune gastritis (AIG) is a chronic organ-specific atrophic gastritis, that is not self-limiting. Endoscopic examination reveals atrophy is typically confined to the body and fundus mucosa of the stomach, sparing the gastric antrum[16]. The disease is characterized by self-reactive T cells, and activated B cells that produce antibodies (PCA) and anti-intrinsic factor antibodies (IFAs). This immune response leads to the destruction of parietal cells, which impairs intrinsic factor secretion, resulting in disorders of iron and vitamin B12 absorption[17]. The destruction of parietal and chief cells results in the replacement of gastric glands with either connective tissue or a different type of epithelial tissue[18]. This process results in lowered hydrochloric acid production, decreased blood levels of pepsinogen I (PG-I), and elevated gastrin levels[19]. Intestinal metaplasia of the gastric mucosa is a precursor to gastric adenoma and adenocarcinoma, according to the Correa cascade, and patients with AIG have an elevated risk of developing gastric adenocarcinoma compared to the general population[20]. Moreover, hypergastrinemia resulting from reduced stomach acid can lead to enterochromaffin-like (ECL) cell hyperplasia and an increased incidence of gNENs[21-23]. Although, hypergastrinemia is frequently observed in patients with AIG and those using long-term PPIs, definitive data linking AIG to GPs, are limited, with most studies focusing on adenocarcinoma and gNENs[24]. The main objective of this study was to evaluate the frequency of GPs in patients with AIG and to investigate the biochemical, clinical, and histological factors that may predict GP occurrence in this group.
MATERIALS AND METHODS
This double center retrospective study retrospectively enrolled patients diagnosed with AIG at the Renji Hospital Affiliated with Shanghai Jiao Tong University School of Medicine, Department of Gastroenterology, and the Sichuan Armed Police Corps Hospital, Department of Gastroenterology, from June 2019 to June 2023. The exclusion criteria comprised the absence of histologic data, inadequate biopsy samples, discordant laboratory or pathological findings, presence of active tumors, or severe organ failure. This study received approval from the Institutional Ethics Committee of Renji Hospital, Shanghai Jiao Tong University, School of Medicine, with a waiver for informed consent.
Clinical data were obtained from medical records and outpatient consultation systems. To ensure confidentiality, all patient data were anonymized following collection, recording, assessment, and analysis. AIG diagnosis was based on pathological features observed in endoscopic biopsy tissue, such as parietal cell destruction, chronic lymphocytic infiltration, and the presence or absence of pseudopyloric gland metaplasia and neuroendocrine cell hyperplasia. Endoscopic findings of characteristic atrophy, positive PCA or IFA, and elevated circulating gastrin-17 levels were used to support the diagnosis of AIG[18,25,26]. Baseline evaluations for all enrolled patients, included demographic data (sex, and age at AIG diagnosis), clinical data (comorbidities and previous treatments), serologic examination, and upper gastrointestinal endoscopic biopsy with histopathology.
Upper gastrointestinal endoscopy
All diagnostic and surveillance esophagogastroduodenoscopy (EGD) procedures were performed using standard gastroscopy techniques. Patients who had previously undergone PPI therapy were examined at least 2 weeks after discontinuation. According to the updated Sydney classification[27], each patients with AIG undergoing monitored EGD, patients with five gastric biopsies: Four from the antrum, corpus and fundus, one from the incisura angularis. The biopsy specimens were directly sent to the pathology laboratory for examination. All patients with suspected H. pylori infection underwent a rapid urease test.
For macroscopic polypoid mucosal lesions, the following data were recorded: Histologic features (e.g., hyperplastic, fundic glandular, adenomatous, neuroendocrine, adenocarcinoma, or other neoplasm), and year of occurrence, location (antrum, body, or fundus), size, treatment modality. Lesions were biopsied, with the largest lesions removed if multiple polyps were present. Lesions less than or equal to 5 mm in diameter were removed using forceps as a “cold biopsy”, while larger lesions required endoscopic mucosal resection. For lesions greater than 1 cm, narrow band imaging or endoscopic ultrasonography was performed to assess the extent of the lesion and invasion depth. Endoscopic mucosal dissection was planned if necessary.
For patients with uncomplicated AIG, endoscopic monitoring was scheduled every 1-3 years, based on the degree of atrophy and the presence of intestinal metaplasia. Patients with gNENs underwent annual endoscopic follow-up[18,28]. For those diagnosed with gastric adenocarcinoma, individualized evaluations were carried out to establish the most suitable intervention and follow-up plan.
Histopathological examination
The diagnosis of AIG was made based on histopathological findings, including the destruction of parietal cells, chronic lymphocytic infiltration, with or without pseudopyloric gland metaplasia and neuroendocrine cell hyperplasia[18]. Biopsies sample were collected during EGD according to the updated Sydney classification[27]. Each patient was evaluated for H. pylori infection. The severity of mucosal atrophy and the associated gastric cancer risk were staged using the Operative Link on Gastritis Assessment (OLGA) score (stages I-IV), while intestinal metaplasia was assessed using the Operative Link on Gastric Intestinal Metaplasia (OLGIM) score (stages I-IV)[29,31].
Additionally, pseudopyloric metaplasia was assessed. ECL cell proliferation was detected using chromogranin A staining following Solcia et al’s criteria[32,33], categorized as simple, linear, micronodular, or macronodular and defined as hyperplasia with a diameter greater than 150 μm. The specimens were preserved in formalin and processed through standard laboratory protocols. Gastric mucosa sections, with a thickness of 5 μm, were stained with hematoxylin and assessed for intestinal metaplasia using Alcian blue-PAS staining. Immunohistochemical analyses were conducted on gNEN sections for chromogranin A, synaptophysin, and the Ki-67 proliferation index, utilizing the MIB-I antibody. All gastric neuroendocrine tumors (gNETs) were classified according to the 2019 World Health Organization classification system[34] and staged in accordance with the tumor node metastasis staging system as per ENETS guidelines[35].
Laboratory serological testing
Fasting blood samples for biochemical testing were obtained at 8 am. Serum samples were collected using standard blood collection tubes, while plasma samples were collected using ethylenediaminetetraacetic acid (1 mg/mL) or heparin tubes. Anemia was defined as a hemoglobin level of less than 12 g/dL in women and less than 13 g/dL in men. Macrocytic anemia was identified when the mean corpuscular volume exceeded 100 fL, while microcytic anemia was defined when the mean corpuscular volume was less than 80 fL. The reference ranges for white blood cells were (4-11) × 109/L, for platelets were (100-300) × 109/L, for thyroid-stimulating hormone were 0.4-4.91 mIU/mL, for vitamin B12 were 180-914 pg/mL, and for iron were 7.8-32.2 μmol/L. PCA and IFA antibodies were detected using dilution and direct enzyme-linked immunosorbent assay, with positivity defined as a value ≥ 1:20. The PG-I, PG-II and gastrin-17 level in peripheral blood were measured by enzyme-linked immunosorbent assay, with normal ranges being 70-165 μg/L, 3-15 μg/L and less than 7 pmol/mL, respectively. For patients on PPI therapy, blood tests should were to repeated at least 15 days after discontinuation of the medication.
Construction and validation of a clinical nomogram
A multivariate logistic regression analysis was conducted using several clinical parameters: Age, sex, PCA, IFA, previous H. pylori infection, OLGA score, OLGIM score, presence or absence of anemia, ECL hyperplasia, PG ratio, and levels of PG-I, PG-II, and gastrin-17. Backward stepwise regression, optimal subset selection, and likelihood ratio tests were applied, with the Akaike Information Criterion (AIC) as the stopping criterion. The AIC was used to evaluate the model’s goodness of fit. To assist clinicians in predicting the likelihood of developing GPs in AIG patients, a clinical nomogram was developed based on multivariate logistic analysis of the main cohort. The model’s discrimination was evaluated using receiver operating characteristic (ROC) curve analysis, with performance measured by the area under the curve. Odds ratios with 95% confidence intervals (CIs) for the final predictors were calculated. Calibration curves were used to compare predicted and observed probabilities, thereby assessing the model’s accuracy.
Statistical analysis
The Kolmogorov-Smirnov test was employed to assess the normality of continuous variables. For variables with a normal distribution, data were presented as mean ± SD. For non-normally distributed variables, the median and interquartile range (IQR) were reported. Categorical variables were described using counts and percentages. To compare groups, the Mann-Whitney U test and Kruskal-Wallis test were utilized for non-parametric data, while proportions were compared using the χ2 test or Fisher’s exact test. Correlations between variables, such as sex, age, PPI usage, H. pylori infection status, PCA and/or IFA positivity, OLGA and OLGIM stages, PG ratio, types of GPs, and serum levels of gastrin-17, PG-I, PG-II, and vitamin B12, were analyzed using Pearson’s or Spearman’s correlation coefficients. Binary logistic regression was conducted to identify potential risk factors for GP development in AIG patients and to create a predictive model. A P value of less than 0.05 (two-tailed) was deemed statistically significant. All analyses were performed using R software (version 4.2.1; R Foundation for Statistical Computing, Vienna, Austria).
RESULTS
Clinical characteristics
The study flow chart is depicted in Figure 1. A total of 530 patients with AIG were initially enrolled; of these, 114 patients were excluded, from the analysis, leaving 166 patients with GPs and 364 patients without GPs. Continuous data was tested for normality. Table 1 summarizes the demographic, characteristics, clinical, biochemical, and histological baseline characteristics of the enrolled patient. The median age of the study population was 59 (IQR: 48-67) years, with a predominance of females (68.3%). Among the subjects, 17.2% had a history of H. pylori infection. The positive rates for PCA and IFA antibodies were 78.3% and 24.7%, respectively. Anemia was present in 40.0% of the patients, with iron deficiency anemia accounting for 30.8% and pernicious anemia for 12.5%. The median gastrin-17 level was 70.44 (IQR: 18.30-112.97). ECL hyperplasia was observed in 27.0% of the patients with AIG.
Figure 1 Flow chart depicting the study population and study design.
AIG: Autoimmune gastritis.
Table 1 Baseline data showing the demographic data, clinical, biochemical, and histological characteristics of autoimmune gastritis patients.
Characteristics
Patients (N)
530
Age (year), median (IQR)
59 (48-67)
Sex (female), n (%)
362 (68.30)
PCA positivity, n (%)
415 (78.3)
IFA positivity, n (%)
131 (24.7)
HP infection positivity, n (%)
91 (17.2)
Anemia, n (%)
212 (40.0)
Iron deficiency anemia, n (%), mild/moderate/severe
163 (30.8), 135/22/6
Pernicious anemia, n (%), mild/moderate/severe
66 (12.5), 48/11/7
Gastrin-17 (pmol/L), median (IQR)
70.44 (18.30-112.97)
PG-I (μg/L), median (IQR)
30.67 (20.08-48.61)
PG-II (μg/L), median (IQR)
8.07 (6.40-11.00)
PG-I/PG-II, median (IQR)
3.74 (2.05-6.20)
Vitamin B12 (pg/mL), median (IQR)
239.00 (136.20-355.50)
Norm, n (%)
331 (62.5)
Low level, n (%)
199 (37.6)
OLGA, n (%)
0
44 (8.3)
I
120 (22.6)
II
179 (33.8)
III
146 (27.6)
IV
41 (7.7)
OLGIM, n (%)
0
134 (25.3)
I
240 (45.3)
II
98 (18.5)
III
45 (8.5)
IV
13 (2.5)
ECL hyperplasia, n (%)
143 (27.0)
Absent
387 (73.0)
Linear
62 (11.7)
Micronodular
46 (8.7)
Macronodular
18 (3.4)
gNET
17 (3.2)
Characteristics and differences between patients with AIG with and without GPs
Patients with AIG were categorized two groups: Those with GPs (GP group) and those without GPs (NGP group). We compared the characteristics and differences between these two groups. Continuous data of non-normal distribution, were analyzed using the Wilcoxon rank-sum test, and differences in categorical data were assessed using the χ2 test, with pairwise comparisons adjusted by the Bonferroni correction method. The results are summarized in Table 2. The median age of patients with GPs was significantly higher than that of patients without GPs [61 (IQR: 52.25-69) years vs 58 (IQR: 47-66) years, P = 0.006]. The gastrin-17 levels were also elevated in the GP group compared with the NGP group [91.9 (IQR: 34.2-138.9) pmol/mL vs 60.9 (IQR: 12.6-98.4) pmol/mL, P < 0.001]. The positive rate of PCA antibodies was also significantly higher in the GP group (88.6% vs 73.6%, P < 0.001).
Table 2 Differences between patients with and without polyps.
Group, n (%)
Gastric polyp, 166 (31.3)
Non-gastric polyp, 364 (68.7)
P value
Age (year), median (IQR)
61 (52.25-69)
58 (47-66)
0.006
Sex, n (%)
112 (67.5)
250 (68.7)
0.859
PCA positivity, n (%)
147 (88.6)
268 (73.6)
< 0.001
IFA positivity, n (%)
42 (25.3)
89 (24.5)
0.833
HP infection positivity, n (%)
24 (14.5)
67 (18.4)
0.264
Anemia, n (%)
70 (42.17)
159 (43.68)
0.302
Iron deficiency anemia, n (%), mild/moderate/severe
Furthermore, there were significant differences in OLGA (P < 0.001), OLGIM (P = 0.018) staging, and ECL hyperplasia (P < 0.001) between the GP and NGP groups (Figure 2). Specifically, the proportion of OLGA stage II was lower in the GP group than in the NGP group, while the proportions of OLGA stages III and IV were higher. There was no significant difference in the proportion of OLGA stages 0/I between the two groups. For OLGIM staging the GP group had a lower proportion of stages 0, I, and II and a higher proportion of stages III and IV than the NGP group. The degree of ECL hyperplasia, including linear, micronodular, and macronodular types, was more pronounced in the GP group than in the NGP group.
Figure 2 Group differences between the gastric polyp and without gastric polyp groups.
A: Heat map of age and blood biochemical difference between gastric polyp group and without gastric polyp group; B: Heat map of histopathological differences between gastric polyp group and without gastric polyp group. GP: Gastric polyp; NGP: Without gastric polyp; FDR: False discovery rate; PG: Pepsinogen; ECL: Enterochromaffin-like; OLGA: Operative Link on Gastritis Assessment; OLGIM: Operative Link on Gastric Intestinal Metaplasia; PCA: Parietal cell antibody.
Characteristics of the GP group differences
Table 3 presents the pathological types and distribution of GPs, as well as the associated degrees of atrophy intestinal metaplasia, and ECL hyperplasia. Among the 166 patients with AIG with GPs, a total of 433 polyps were identified. Hyperplastic polyps were the most prevalent, accounting for 295 (68.1%) of the polyps in 109 (65.7%) patients (Figure 3). Other types included FGPs (12.5%), gNETs (11.6%), gastric adenocarcinoma (5.3%), and gastric adenoma (2.5%). The characteristics of patients across different polyp categories are detailed in Table 4, which presents the pathological features and distribution of GPs. Significant differences were observed in terms of age, sex, H. pylori infection, PG-I levels, and gastrin-17 levels. Patients with gNET exhibited the highest mean gastrin-17 levels, while those with gastric adenocarcinomas were the oldest on average (Figure 4A and B). Additionally, the highest mean OLGA stage was noted in patients with GHPs and gNET (Figure 4C and D).
Univariate and multivariate binary logistic regression analyses were conducted to identify risk factors for the development of GPs in patients with AIG (Table 5). The univariate analysis indicated that age, PCA positivity, gastrin-17 level, PG-II level, and advanced OLGA and OLGIM stages (III and IV) were associated with an increased risk factors of GPs. Conversely, PG-I level, PG ratio, and ECL hyperplasia were identified as protective factors. Multivariate analysis showed that PCA positivity, PG-II, and ECL hyperplasia were independent risk factors, while PG-I served as a protective factor (Figure 5).
Figure 5 Forestplot depicting the results of univariate and multivariate analyses.
A: Forest plots for univariate analysis; B: Forest plots for multivariate analysis. OR: Odds ratio; CI: Confidence interval; ECL: Enterochromaffin-like; HP: Helicobacter pylori; PG: Pepsinogen; IFA: Intrinsic factor antibody; OLGA: Operative Link on Gastritis Assessment; OLGIM: Operative Link on Gastric Intestinal Metaplasia; PCA: Parietal cell antibody.
Table 5 Univariate and multivariate analysis of the characteristics most associated with the development of gastric polyps in patients with autoimmune gastritis.
Variable
Univariate analysis (95%CI)
P value
Multivariate analysis (95%CI)
P value
Age
1.023 (1.007-1.038)
0.003
1.015 (0.998-1.033)
0.084
Sex
Male
1.057 (0.714-1.566)
0.781
1.019 (0.656-1.582)
0.933
Female
PCA
Positive
2.771 (1.629-4.716)
< 0.001
2.003 (1.130-3.549)
0.017
Negative
IFA
Positive
1.047 (0.685-1.599)
0.833
0.866 (0.538-1.394)
0.553
Negative
HP infection
Positive
0.749 (0.451-1.244)
0.265
0.897 (0.512-1.571)
0.704
Negative
Anemia
Yes
0.819 (0.561-1.196)
0.302
0.811 (0.533-1.233)
0.326
No
Gastrin-17
1.007 (1.004-1.010)
< 0.001
1.002 (0.998-1.005)
0.306
PG-I
0.992 (0.985-0.998)
0.008
0.992 (0.985-0.999)
0.031
PG-II
1.037 (1.001-1.074)
0.044
1.053 (1.010-1.097)
0.015
PG-I/PG-II
0.927 (0.884-0.971)
0.002
OLGA
0-II
III-IV
2.408 (1.648-3.519)
< 0.001
1.541 (0.963-2.464)
0.071
OLGIM
0-II
III-IV
1.927 (1.107-3.353)
0.020
0.954 (0.487-1.869)
0.891
ECL hyperplasia
Absent
Exist
0.225 (0.150-0.338)
< 0.001
3.116 (1.868-5.197)
< 0.001
Construction and validation of the nomogram
To develop a predictive model, the optimal subset method was employed for variable selection, with AIC was used as the stopping criterion (Table 6). The final nomogram included age, OLGA stage, PCA positivity, PG ratio, and ECL hyperplasia (Figure 6A). An example of the nomogram score for a patient is illustrated in Figure 6B. ROC analysis revealed an area under the curve of 0.729 (95%CI: 0.683-0.775), indicating good diagnostic performance. The calibration curve demonstrated a good fit of the model with minimal error was small (Figure 6C and D).
Figure 6 Nomogram, receiver operating characteristic curve, and forest plot depictions.
A: Nomogram; B: An example of the nomogram; C: Calibration curve; D: Receiver operating characteristic curve. OLGA: Operative Link on Gastritis Assessment; ECL: Enterochromaffin-like; PCA: Parietal cell antibody; PG: Pepsinogen; AUC: Area under the receiver operating characteristic curve.
Table 6 Multivariate logistics regression analysis of the optimal subset method model.
Variable
Coefficient
OR (95%CI)
P value
Age
0.015
1.015 (0.999-1.032)
0.071
PCA
Positive
0.778
2.178 (1.243-3.818)
0.007
Negative
PG-I/PG-II
-0.069
0.927 (0.884-0.971)
0.008
OLGA
0-II
III-IV
0.375
1.455 (0.945-2.239)
0.088
ECL hyperplasia
Absent
Exist
1.247
3.479 (2.242-5.399)
< 0.001
Intercept
-1.711
-
-
DISCUSSION
AIG is a chronic atrophic gastritis with an immune-mediated etiology. Its onset is often insidious, and early stages may present without specific symptoms. As the disease progresses, patients may develop a range of symptoms including digestive, hematological, and neurological manifestations. In some cases, anemia becomes the predominant symptom, leading to a significant delays in diagnosis[36]. Progressive destruction of gastric parietal cells, mediated by PCA or IFA, results in gastric atrophy and/or intestinal or pseudopyloric metaplasia, creating an abnormal mucosal environment conducive to the formation of GPs. Furthermore, AIG is closely linked to gNETs[17]. Atrophy of the gastric body mucosa and decreased gastric acid secretion lead to the stimulation of gastric antral G cells, resulting in increased gastrin secretion. This, in turn, stimulates the proliferation of ECL cells, potentially culminating in gNET formation[37].
In our multicenter retrospective study, we aimed to investigate the pathological types of GPs and clinical and associated biochemical factors in patients with AIG. Among the 530 patients with AIG studied, 166 (31.3%) were found to have a total of 433 polypoid lesions. The study cohort was representative of the broader AIG patient population, with 68.3% being female and a median age of 59 years at diagnosis. Our findings align with previous studies, showing a significant incidence of gNETs in patients with AIG compared with the general population. Additionally, 16 patients with AIG (3.02%) were diagnosed with gastric adenocarcinoma. Of these, nine had a history of H. pylori infection, suggesting a potential link between past H. pylori infection and the development of gastric adenocarcinoma in patients with AIG.
Our study revealed no significant differences in sex between patients with AIG with GPs and those without. Additionally, previous H. pylori infection rates were similar across both groups, suggesting that H. pylori infection may not significantly impact abnormal epithelial cell proliferation in the context of AIG. The occurrence of GPs in patients with AIG was associated with PCA positivity and ECL hyperplasia, though the specific pathophysiological and molecular mechanisms remain unclear and warrant further investigation through basic research.
We observed that GPs were positively correlated with age, gastrin levels, and OLGA and OLGIM stages. However, OLGA and OLGIM staging scores may not be entirely reliable in predicting polyp formation in patients with AIG, as the histological lesions in AIG predominantly affect the fundus and body of the stomach rather than the antrum. Consequently, active endoscopic surveillance should be performed for all patients with AIG, irrespective of OLGA stage. Our study findings indicate that gastrin-17 levels were significantly higher in the GP group; this supports its role in ECL cell proliferation and the development of neuroendocrine lesions, while also maintaining its trophic effects on other epithelial components of the gastric mucosa. We speculate that elevated gastrin-17 levels contribute to abnormal mucosal proliferation, thereby facilitating to the growth of polyps in patients with AIG. Notably, PG-II levels were significantly was lower in the GP group, suggesting that atrophy of the antral mucosa might influence the occurrence of GPs. Histologically, a higher proportion of patients in the GP group, exhibited OLGA stages III-IV and more pronounced ECL hyperplasia than those in the NGP group. However, no significant differences were found in OLGA and ECL hyperplasia between benign and malignant polyps, potentially due to the low number of malignant polyps in our study sample. Additionally, anemia and vitamin B12 levels were not significantly associated with the presence of GPs.
This study represents the largest analysis to date of AIG and its relationship with GPs, featuring a substantial sample size of 530 patients. By using univariate and multivariate logistic regression analyses, we identified PCA positivity and ECL hyperplasia as significant risk factors for GPs in patients with AIG, while PG-I was found to be a protective factor. Although age and gastrin-17 did not achieve statistical significance in the regression models, they remain relevant variables in the context of AIG. The prediction model we developed, based on these logistic regression results, demonstrated good performance with an area under the ROC curve was of 0.729 (95%CI: 0.683-0.775). The use of fold cross-validation ensured robust consistency and extensibility, of the model, offering valuable insights for clinical practice. However, the model requires validation across diverse cohorts to enhance its clinical applicability and reliability.
Our study sheds light on the previously underexplored relationship between AIG GPs, leveraging a large and demographically diverse sample (68.3% women, median age: 59 years). Identified key risk factors, such as PCA positivity and ECL hyperplasia, provide useful tools for clinicians assessing the risk of GPs in patients with AIG. Despite the promising results, the study’s cross-sectional design limits causal inference, and highlights the need for further research into the molecular mechanisms driving polyp development.
CONCLUSION
In conclusion, our study not only confirms the relationship between AIG and the occurrence of GPs, but also highlights the predominance of benign, particularly hyperplastic polyps. Nonetheless, the potential risk of malignant transformation should not be overlooked. Comprehensive endoscopic surveillance and follow-up, as recommended by the Sydney protocol are essential for patients undergoing polyp resection. While our findings elucidate the roles of PCA and ECL hyperplasia in predicting GPs, they do not fully explain the roles of PCA, ECL hyperplasia, and gastrin-17 in the development and malignant potential of these polyps. Future research, particularly longitudinal studies, is crucial to further elucidate these relationships and improve noninvasive monitoring strategies for gastric mucosa and epithelial hyperplasia in patients with AIG.
ACKNOWLEDGEMENTS
We are grateful to all the individuals who participated in the study.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Gastroenterology and hepatology
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade C
Novelty: Grade B
Creativity or Innovation: Grade B
Scientific Significance: Grade B
P-Reviewer: Soldera J S-Editor: Wang JJ L-Editor: A P-Editor: Cai YX
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