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A Prediction Model Based on the Risk Factors Associated with Pathological Upgrading in Patients with Early-Stage Gastric Neoplasms Diagnosed by Endoscopic Forceps Biopsy

Yu Han Zhao1 , Yu Zheng2 , Jie Sha3 , Hong Jin Hua4 , Ke Dong Li4 , Yu Lu1 , Yi Ni Dang1 , Guo Xin Zhang1

Departments of 1Gastroenterology and 2Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 3Department of Gastroenterology, Jingjiang People's Hospital, Jingjiang, and 4Department of Pathology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China

Correspondence to: Guo Xin Zhang
ORCID https://orcid.org/0000-0002-7103-3630
E-mail guoxinz@njmu.edu.cn

Yi Ni Dang
ORCID https://orcid.org/0000-0001-6449-516X
E-mail yeani_hi@126.com

Yu Han Zhao and Yu Zheng contributed equally to this work as first authors.

Received: February 12, 2022; Revised: April 25, 2022; Accepted: May 13, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Gut Liver

Published online September 2, 2022

Copyright © Gut and Liver.

Background/Aims: The discrepancies between the diagnosis of preoperative endoscopic forceps biopsy (EFB) and endoscopic submucosal dissection (ESD) in patients with early gastric neoplasm (EGN) exist objectively. Among them, pathological upgrading directly influences the accuracy and appropriateness of clinical decisions. The aims of this study were to investigate the risk factors for the discrepancies, with a particular focus on pathological upgrading and to establish a prediction model for estimating the risk of pathological upgrading after EFB.
Methods: We retrospectively collected the records of 978 patients who underwent ESD from December 1, 2017 to July 31, 2021 and who had a final histopathology determination of EGN. A nomogram to predict the risk of pathological upgrading was constructed after analyzing subgroup differences among the 901 lesions enrolled.
Results: The ratio of pathological upgrading was 510 of 953 (53.5%). Clinical, laboratorial and endoscopic characteristics were analyzed using univariable and binary multivariable logistic regression analyses. A nomogram was constructed by including age, history of chronic atrophic gastritis, symptoms of digestive system, blood high density lipoprotein concentration, macroscopic type, pathological diagnosis of EFB, uneven surface, remarkable redness, and lesion size. The C-statistics were 0.804 (95% confidence interval, 0.774 to 0.834) and 0.748 (95% confidence interval, 0.664 to 0.832) in the training and validation set, respectively. We also built an online webserver based on the proposed nomogram for convenient clinical use.
Conclusions: The clinical value of identifying the preoperative diagnosis of EGN lesions is limited when using EFB separately. We have developed a nomogram that can predict the probability of pathological upgrading with good calibration and discrimination value.

Keywords: Early gastric neoplasm, Pathological upgrading, Prediction model, Endoscopic forceps biopsy, Endoscopic submucosal dissection

Early gastric neoplasm (EGN) is a group including low grade intraepithelial neoplasia (LGIN), high grade intraepithelial neoplasia (HGIN), and early gastric carcinoma (EGC).1-4 LGIN and HGIN, for which the differences lie in the degree of cellular or structural heterogeneity, are ascribed as dysplasia and classified as precursor lesions. In current guidelines, endoscopic submucosal dissection (ESD) is preferred for EGN to prevent the deterioration of EGC to progressive gastric cancer, which has the following advantages: minimally invasive, faster recovery, higher curative ratio, and preservation of gastric function.5-8 Advanced endoscopic instruments, such as chromoendoscopy, high-definition white-light endoscopy, narrow-band imaging, are not yet widely applied and not easily mastered, and conventional white-light endoscopy in combination with endoscopic forceps biopsy (EFB) is under routine practice in the clinical context.

EFB is an important tool for the histopathological diagnosis of EGN. With multiple EFB, the diagnostic efficiency would be improved to some extent based on literature review and our clinical experience.9,10 However, further biopsies were not able to increase positive diagnosis cumulative rates, and may increase workload and medical cost, and may lead to trauma, bleeding, or perforation.11,12 On the other hand, the pathological outcomes of EFB and ESD are often inconsistent. These discrepancies could be divided into downgrading and upgrading. It has been reported that the overall rate of discrepancy between EFB and ESD ranges from 20.1% to 76.3%,10,11 with 16.3% to 44.9% pathological upgrading ultimately.7-9,12-16 In addition, the pathological upgrading group showed a significant tendency of submucosal invasion and lymphovascular/perineural invasion, which would lead to endoscopic noncurative resection and suboptimal prognostic results.17,18 Therefore, the question in front of us is how to classify patients with increased risk of pathological upgrading upon EFB. Indeed, it may be attributed to the experience of the endoscopist, but also highly associated with morphological features or biological characteristics of the lesion itself. Hitherto the risk factors associated with pathological upgrading remain unclear and the lack of a visual assessment model in clinical practice has led to insignificant improvements in diagnostic compliance.16

Considering the above concerns, this retrospective study was designed: (1) to investigate the risk factors of histological discrepancies between EFB and ESD, with a particular focus in pathological upgrading, and (2) to establish a prediction model in estimating the risk of pathological upgrading upon EFB.

1. Study design and settings

This is a retrospective single-center cohort study to explore the risk factors for pathological upgrading between EFB and ESD in patients with EGN. The secondary outcome was to construct a nomogram to show the predictive efficacy of detected risk factors on pathological upgrading. This clinical study consisted of two stages. The first stage (training set) retrospectively identified patients diagnosed with EGN according to EFB or ESD in the First Affiliated Hospital of Nanjing Medical University from December 2017 to December 2020. The second stage (validation set) included patients from January 2021 to July 2021. The detailed procedure of the study is shown in Fig. 1. This study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board of the First Affiliated Hospital of Nanjing Medical University (IRB number: 2021-SR-227). It has been previously registered in Chinese Clinical Trial Registry (ChiCTR2100048088). Informed consent was waived due to the nature of the study design.

Figure 1.Flowchart of the study. The “n” in parentheses represents lesions.
ESD, endoscopic submucosal dissection; EFB, endoscopic forceps biopsy.

2. Study population

From December 2017 to July 2021, a total of 1,863 patients underwent gastric ESD. Indications followed the Japanese gastric cancer treatment guidelines 2018 (5th edition).6 Endoscopic refinement is recommended for suspected lesions, with endoscopic interventions if necessary.19,20 The target population were diagnosed with EGN according to EFB or ESD. Initially, 774 patients were excluded because of pathological diagnosis of ESD was inconsistent with the purpose of this study. After further data collection, patients were excluded if: (1) with a history of gastrectomy or gastric tube reconstruction; (2) did not undergo EFB for target lesions; or (3) with no clinical or endoscopic data. After excluding lesions of which pathological diagnosis with EFB were carcinoma, the lesions were divided into two groups (training set and validation set). Training set was analyzed to develop the nomogram model to predict the risk of pathological upgrading. The validation set was used to further external validate the predictive model. Lesions that presented as pathological consistency or pathological downgrading were assigned into the non-pathological upgrading group.

3. Pathological diagnostic criteria

Collection of biopsies before ESD were conducted in our center and the pathological diagnosis was confirmed by at least two experienced pathologists. However, according to the routine clinical practice, part of EFB may be conducted prior to the patients’ admission to our center, therefore repeating endoscopic procedures would be performed for non-neoplastic pathology or questionable discrepancies between the pathologic results obtained at our institution and at the referring hospital.14 The gastroenterologist would evaluate lesions for the indication of ESD based on pathological and endoscopic records. The ESD consent form was signed on the patient’s own wishes. In fact, even though additional surgeries may be required due to exceeding ESD indications, the majority of target patients in our institution chose to undergo ESD first, based on the advantages of ESD, even though additional surgeries may be required due to exceeding ESD indications,17,18,21 which ensured us screening up sufficient study population.

In this study, we followed the World Health Organization pathological diagnostic criteria in digestive system.1 We enrolled patients with different pathological outcomes (e.g., acute inflammation, chronic gastric atrophy, gastric intestinal metaplasia, LGIN, HGIN, and intramucosal carcinoma) and prespecified principles to define pathological upgrading and non-upgrading according to EFB and ESD examinations. For instance, if one patient showed LGIN during EFB while the pathological grade was reported as HGIN or carcinoma following ESD, this was identified as pathological upgrading. On the other hand, if one patient showed lower or consistent pathological grade after ESD as compared to that from EFB, they were finally assigned as non-pathological upgrading.14,22

4. Data collection

Demographic (e.g., age, sex, and body mass index) and clinical data (e.g., Helicobacter pylori infection status, medical history, and comorbidity), and EFB information were collected during patients’ admission before ESD according to their medical records. Endoscopic data (e.g., location, macroscopic type, and lesion size) were collected during ESD and pathological information of ESD specimens were collected according to pathological reports. In case of multiple lesions, one patient was treated as two cases and distinguished with their pathological characteristics.

Individual medical history and digestive comorbidity was defined positive as written down in medical records or outpatient documents. Symptoms of digestive system were considered as existing if the following words appeared in the records: abdominal pain, nausea, vomiting, dyspepsia, eructation, heartburn, loss of appetite, weight loss.

Ulceration or ulcer scar was considered positive after excluding those caused by the biopsy.23 Remarkable redness was defined as discoloration on the mucosal surface of the lesion compared to the surrounding mucosa, and uneven surface was defined as the presence of irregularly raised or nodular mucosa.24,25 Fig. 2 shows the following endoscopic features in sequence: remarkable redness, ulceration or scar and uneven surface.

Figure 2.Illustrations of the endoscopic features. (A-C) Lesions with remarkable redness. (D-F) Lesions with ulceration or scaring. (G-I) Lesions with an uneven surface.

5. Statistical analysis

All of the following statistical analyses were performed with SPSS 23.0 (IBM Corp., Armonk, NY, USA). Continuous variables were presented as means and standard deviations or medians with interquartile ranges. Categorical variables were demonstrated as numbers and percentages. Differences between groups were assessed using the chi-square test, the Student t-test, or the Mann-Whitney test in the univariate analysis, as appropriate. Variables detected with p<0.05 in the univariate logistic regression were further included in the multivariate logistic regression analysis to determine the variables that were independent influencing factors of pathological upgrading.

A predictive nomogram was constructed, based on the variables selected with the multivariate logistic regression analysis and by using the package of rms in R software (rms in R version 4.0.4, R Foundation for Statistical Computing, Vienna, Austria; https://www.r-project.org/). The model was validated internally in the training set and externally in the validation set. A calibration plot with bootstrapping (1,000 replications) was used to illustrate the association between the actual probability and the predicted probability. In addition, five training models were constructed to compare the robustness of each model. The performance of the prediction model was evaluated using the area under the curve (AUC) in receiver operating characteristic analysis. Decision curve analysis was used to explain the utility of benefits in clinical use.

1. Clinical characteristics

We retrospectively collected data for 1,053 lesions from 978 patients who underwent ESD for EGN. The comparison of diagnosis between the original EFB and the final ESD is summarized in Table 1. The predominant pathological upgrading involved upgrading from LGIN to HGIN or carcinoma (n=178) and upgrading from HGIN to carcinoma (n=270). After excluding lesions of which pathological diagnosis with EFB were carcinoma, 822 lesions were enrolled into the training and 131 were enrolled into validation sets. Clinical and endoscopic characteristics are summarized in Tables 2 and 3. Lesions (54.0%, 444/822) showed higher-grade disease after ESD in the training set (LGIN from non-neoplasia, HGIN or carcinoma from LGIN or non-neoplasia, or carcinoma from HGIN).

Table 1. Comparison of Pathological Diagnosis by Initial Biopsy and Final Endoscopic Resection

Pathologic diagnosis
with EFB
Pathologic diagnosis with ESD
Non-neoplasiaLGINHGINCarcinomaTotal No. (%)
Non-neoplasia1542*11*10*78 (7.4)
LGIN11293108*70*482 (45.8)
HGIN12993270*393 (37.3)
Carcinoma05491100 (9.5)
Total No. (%)27 (2.6)369 (35.0)216 (20.5)441 (41.9)1,053

EFB, endoscopic forceps biopsy; ESD, endoscopic submucosal dissection; LGIN, low grade intraepithelial neoplasia; HGIN, high grade intraepithelial neoplasia.

*Pathological upgrading; †Non-pathological upgrading.



Table 2. Clinical Characteristics of the Training and Validation Sets

CharacteristicsTraining set
(n=822)
Validation set
(n=131)
Age, yr63 (55–69)63 (57–70)
Male sex592 (72.0)103 (78.6)
Body mass index, kg/m223.8±3.324.1±2.9
Helicobacter pylori infection
Negative289 (35.1)45 (36.4)
Previous eradicated or infected533 (64.9)86 (65.6)
Symptoms of digestive system599 (72.9)56 (42.7)
Smoking198 (24.1)44 (33.6)
Drinking78 (20.6)24 (18.3)
Comorbidity
History of CAG466 (56.7)61 (46.6)
History of peptic ulcer137 (16.7)13 (9.9)
Medical history
Hypertension258 (31.4)58 (44.3)
Diabetes74 (9.0)14 (10.7)
Coronary heart disease33 (4.0)3 (2.3)
History of cholecystectomy58 (7.1)19 (14.5)
History of malignancy80 (9.7)4 (3.1)
Family history of malignancy133 (16.2)12 (9.2)
Laboratory examination
CEA, ng/mL3.4±4.62.8±4.4
CA19-9, U/mL12.7±28.212.8±8.0
CA724, U/mL3.9± 8.34.0±5.0
HDL, mmol/L1.2±0.31.1±0.3
LDL, mmol/L2.9±0.72.8±0.6
Albumin, g/L39.9±3.939.0±3.0
Calcium, mmol/L2.3±0.12.3±0.1

Data are presented as median (range), number (%), or mean±SD.

CAG, chronic atrophic gastritis; CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; CA724, carbohydrate antigen 724; HDL, high density lipoprotein; LDL, low density lipoprotein.



Table 3. Endoscopic Characteristics of the Training and Validation Sets

CharacteristicsTraining
set (n=822)
Validation
set (n=131)
Locations of lesions
Upper third241 (29.3)40 (30.5)
Middle third93 (11.3)21 (16.0)
Lower third488 (59.4)70 (53.4)
Macroscopic type of lesions
Elevated405 (49.3)55 (42.0)
Flat197 (24.0)26 (19.8)
Depressed220 (26.8)50 (38.2)
Pathologic diagnosis of EFB
Non-neoplasia74 (9.0)4 (3.1)
LGIN413 (50.2)69 (52.7)
HGIN335 (40.8)58 (44.3)
Pathologic diagnosis of ESD
Non-neoplasia27 (3.3)
LGIN314 (38.2)50 (38.2)
HGIN179 (21.8)33 (252)
Carcinoma302 (36.7)48 (36.8)
Pathologic upgrading
Yes444 (54.0)66 (50.4)
No378 (46.0)65 (49.6)
Multiple lesions52 (13.8)24 (18.3)
Endoscopic features
Ulceration or scar167 (20.3)39 (29.8)
Uneven surface364 (44.3)64 (48.9)
Remarkable redness531 (64.6)88 (67.2)
Lesion size
≤2 cm581 (70.7)78 (59.5)
>2 cm241 (29.3)53 (40.5)
Procedure time, min60 (45–90)60 (45–90)
Depth of invasion
M763 (92.8)126 (96.2)
SM129 (3.5)1 (0.8)
SM230 (3.6)4 (3.1)

Data are presented as number (%) or median (range).

EFB, endoscopic forceps biopsy; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm; ESD, endoscopic submucosal dissection; M, intraepithelial and/or the deepest infiltration depth is within the mucosal lamina propria; SM1, the infiltration depth >500 μm from the muscularis mucosae; SM2, the infiltration depth >500 μm from the muscularis mucosae.



2. Baseline characteristics

As shown in Table 4, statistical differences were detected in those with history of smoking, drinking, chronic atrophic gastritis (CAG), and symptoms of digestive system. History of CAG was less commonly detected in the pathological upgrading group than in the non-pathological upgrading group (50.2% vs 60.9%, p<0.001). The rate of H. pylori infection was more than 60% in both groups.

Table 4. Clinical Characteristics of Lesions with or without Pathological Upgrading

CharacteristicsNon-pathological upgrading group (n=378)Pathological upgrading group (n=444)p-value*
Age, yr63 (55–69)65 (58–70)<0.001
Male sex250 (66.1)342 (77.0)0.001
Body mass index, kg/m223.6±3.123.9±3.40.082
Helicobacter pylori infection0.680
Negative131 (34.7)160 (36.0)
Previous eradicated or infected247 (65.3)284 (64.0)
Symptoms of digestive system260 (68.8)339 (76.4)0.015
Smoking105 (27.8)159 (35.8)0.014
Drinking78 (20.6)120 (27.0)0.033
Comorbidity
History of CAG243 (64.3)223 (50.2)<0.001
History of peptic ulcer71 (15.4)82 (18.5)0.224
Medical history
Hypertension104 (27.5)154 (34.7)0.073
Diabetes30 (7.9)44 (9.9)0.270
Coronary heart disease11 (2.9)22 (5.0)0.269
History of cholecystectomy22 (5.8)36 (8.1)0.236
History of malignancy35 (9.3)45 (10.1)0.531
Family history of malignancy61 (16.1)72 (16.2)0.700
Laboratory examination
CEA, ng/mL3.3±4.53.5±4.40.398
CA19-9, U/mL12.4±30.513.1±26.20.734
CA724, U/mL4.0±9.73.8±6.90.682
HDL, mmol/L1.2±0.31.1±0.20.015
LDL, mmol/L2.9±0.72.9±0.70.099
Albumin, g/L40.2±3.639.7±4.20.056
Calcium, mmol/L2.3±0.12.2±0.10.004

Data are presented as median (range), number (%), or mean±SD.

CAG, chronic atrophic gastritis; CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; CA724, carbohydrate antigen 724; HDL, high density lipoprotein; LDL, low density lipoprotein.

*p-value was derived from the chi-square test, Student t-test, or Mann-Whitney test.



The contradistinction of endoscopic characteristics was presented in Table 5. Pathological upgrading more frequently occurred in lower third (51.1%), followed by upper third (36.5%) and middle third (12.4%) in the upgrading group. The predominant macroscopic type in both groups was elevated pattern, with a gradual tendency of depressed pattern in the pathological upgrading group. The endoscopic ulceration, uneven surface, remarkable redness was found to account for 26.8%, 56.1%, and 75.4% in cases of pathological upgrading, accordingly.

Table 5. Endoscopic Characteristics and Posttreatment Evaluation of the Lesions with or without Pathological Upgrading

CharacteristicsNon-pathological upgrading group (n=378)Pathological upgrading group (n=444)p-value*
Locations of lesions<0.001
Upper third79 (20.9)162 (36.5)
Middle third38 (10.1)55 (12.4)
Lower third261 (69.0)227 (51.1)
Macroscopic type of lesions<0.001
Elevated206 (54.5)199 (44.8)
Flat106 (28.0)91 (20.5)
Depressed66 (17.5)154 (34.7)
Pathologic diagnosis of EFB<0.001
Non-neoplasia16 (3.5)58 (13.1)
LGIN261 (56.7)152 (34.2)
HGIN101 (22.0)234 (52.7)
Multiple lesions52 (13.8)68 (15.3)0.528
Endoscopic features
Ulceration or scar48 (12.7)119 (26.8)<0.001
Uneven surface115 (30.4)249 (56.1)<0.001
Remarkable redness197 (52.1)334 (75.4)<0.001
Lesion size<0.001
≤2 cm306 (81.0)275 (61.9)
>2 cm72 (19.0)169 (38.1)
Procedure time, min60 (45–90)60 (45–100)<0.001
Depth of invasion<0.001
M378 (95.0)385 (86.7)
SM1-29 (6.5)
SM2-27 (6.8)

Data are presented as number (%) or median (range).

EFB, endoscopic forceps biopsy; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm; M, intraepithelial and/or the deepest infiltration depth is within the mucosal lamina propria; SM1, the infiltration depth >500 μm from the muscularis mucosae; SM2, the infiltration depth >500 μm from the muscularis mucosae.

*p-value was derived from chi-square test or Mann-Whitney test.



3. Analysis of risk predictors

Multivariate analysis (logistic regression analysis) was further performed to analyze the variables that were statistically significant in univariate analysis. Ultimately, a total of nine variables which pertained to clinical, laboratorial, endoscopic characteristics separately were enrolled to build the clinical prediction model. As revealed in Table 6, history of CAG (odds ratio [OR], 0.59; 95% confidence interval [CI], 0.42 to 0.84; p=0.003), blood high density lipoprotein (HDL) concentration (OR, 0.46; 95% CI, 0.24 to 0.86; p<0.016) were protective predictors. Age, symptoms of digestive system, macroscopic type of lesions, pathologic diagnosis of EFB, remarkable redness were risk factors, while uneven surface (OR, 2.35; 95% CI, 1.66 to 3.32; p<0.001), lesion size >2 cm (OR, 2.20; 95% CI, 1.50 to 3.22; p<0.001) were independent risk predictors.

Table 6. Univariate and Multivariate Regression Analyses of the Predictors Associated with Pathological Upgrading According to the Analyzed Variables

FactorUnivariate logistic analysisMultivariate logistic analysis
OR (95% CI)p-valueOR (95% CI)p-value
Age1.05 (1.03–1.06)<0.0011.04 (1.03–1.06)<0.001
Sex (ref. male)0.60 (0.44–0.82)0.001
Smoking (ref. no)1.38 (1.02–1.87)0.036
Drinking (ref. no)1.39 (1.03–1.89)0.034
Comorbidity: CAG (ref. no)0.47 (0.35–0.63)<0.0010.47 (0.33–0.68)<0.001
Symptoms of digestive system (ref. no)1.44 (1.05–1.97)0.0251.60 (1.08–2.36)0.019
Laboratory examination: HDL0.34 (0.20–0.58)<0.0010.44 (0.24–0.81)0.008
Laboratory examination: calcium0.09 (0.02–0.37)0.001
Locations of lesions (ref. upper third)1.00
Middle third0.71 (0.43–1.18)0.187
Lower third0.40 (0.29–0.56)0.001
Macroscopic type of lesions (ref. elevated)1.001.00
Flat0.84 (0.60–1.19)0.3310.74 (0.48–1.13)0.164
Depressed2.25 (1.68–3.20)<0.0011.63 (1.13–2.32)0.045
Pathological diagnosis of EFB (ref. non-neoplasia)1.001.00
LGIN0.01 (0.01–0.08)<0.0010.01 (0.01–0.06)<0.001
HGIN0.04 (0.01–0.30)0.0020.02 (0.01–0.13)<0.001
Endoscopic features: ulceration or scar (ref. no)2.63 (1.79–3.84)<0.001
Endoscopic features: uneven surface (ref. no)2.69 (2.01–3.60)<0.0012.24 (1.58–3.19)<0.001
Endoscopic features: remarkable redness (ref. no)2.95 (2.19–3.99)<0.0012.26 (1.57–3.27)<0.001
Lesion size (ref. ≤2 cm)2.47 (1.78–3.41)<0.0012.20 (1.49–3.24)<0.001

OR, odds ratio; CI, confidence interval; ref., reference group; CAG, chronic atrophic gastritis; HDL, high density lipoprotein; EFB, endoscopic forceps biopsy; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm.



4. Dynamic nomogram construction and validation

We developed a nomogram to predict the risk of pathological upgrading in patients with EGN (Fig. 3). For instance, a 65-year-old patient, with a previous history of CAG, without symptoms of digestive system, and blood HDL concentration of 1.0 mmol/L, was found to have an elevated lesion with remarkable redness and uneven surface, and less than 2 cm in diameter at endoscopy. If the EFB pathology was HGIN, the incidence of pathological upgrading would be 65.1% (95% CI, 0.522 to 0.761). The online version of our nomogram software is accessible at https://zyh-njmu.shinyapps.io/Dynamic_nomogram/.

Figure 3.Illustration of the prediction nomogram model based on clinical, laboratorial, endoscopic characteristics.
CAG, chronic atrophic gastritis; HDL, high density lipoprotein; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm; EFB, endoscopic forceps biopsy.

We performed validation by using the bootstrap method with 1,000 repetitions to display the calibration of the nomogram (Fig. 4A and B). Accuracy of the nomogram was examined with AUC. The C-statistics for our nomogram model was 0.804 (95% CI, 0.774 to 0.834) and 0.748 (95% CI, 0.664 to 0.832) in the training and validation set, respectively (Fig. 4C and D).

Figure 4.Calibration and diagnostic ability of the nomogram. Calibration curves by using bootstrapping (1,000 repetitions) in the training set (A) and validation set (B). The receiver operating characteristic curve in the training set (C) and validation set (D).
AUC, area under the curve; CI, confidence interval.

To assess the predictive ability of our nomogram, several training schemes (namely training models 1 to 5) were constructed (Fig. 5). Afterwards, we performed internal validation and AUC computation for training models 1 to 5 and EFB, and the calibration plot and C-statistics for each model were shown in Figs 6 and 7, respectively.

Figure 5.Training models 1 to 5. (A) Training model 1 was constructed with clinical and endoscopic factors without endoscopic forceps biopsy (EFB) diagnosis. (B) Training model 2 was constructed with clinical factors and EFB diagnosis without endoscopic factors. (C) Training model 3 was constructed with endoscopic factors and EFB diagnosis without clinical factors. (D) Training model 4 was constructed with clinical factors only. (E) Training model 5 was constructed with endoscopic factors only.
CAG, chronic atrophic gastritis; HDL, high density lipoprotein; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm.

Figure 6.Calibration curves for training model 1 to 5. Validation of the training models 1 to 5 based on calibration curves by using bootstrapping (1,000 repetitions).

Figure 7.Decision curve analysis for the nomogram, training models 1 to 5, and endoscopic forceps biopsy (EFB).

EFB and ESD are used for diagnosis of EGN. However, EFB is not able to show histology of the entire lesion, which may lead to discrepancy between histological diagnosis of EFB and resected specimen. Therefore, it is urgently needed to establish a clinical predictive tool to identify the risk of pathological upgrading. Nomogram is a visualization prediction tool that can incorporate different variables affecting outcomes.26 We developed a nomogram for pathological upgrading in patients received EFB before ESD which showed a steady accuracy in evaluating the risk of pathological upgrading.

In the current study, rate of pathological upgrading was 44.9%. It was similar to the results of previous studies.15,27-31 Sixty-nine point nine percent of HGIN in EFB were diagnosed as EGC in our study, which was comparable to reported results.30,32,33 It has been found that pathological upgrading was positively correlated with longer operation time and deeper submucosal invasion. In addition, the depth of invasion was verified in predicting the risk of nodal metastasis in EGCs.17,34,35

In agreement with reported data, our study demonstrated that the depressed pattern, nodular surface, surface redness, lesion size >2 cm, and location in the upper third of the stomach were risk factors in pathological upgrading.23,36,37 EGCs located in the lower third of the stomach, especially in the antrum, might be detected easily, but for those in the upper third, detection may be difficult due to denser mucosal folds, thinner stomach, and limited endoscopic visual fields.36

Ideally, one would incline to have a validated noninvasive biomarker to predict cancer risk. However, no positive values of traditional tumor markers in predicting pathological upgrading have been observed in our study. We found that associations between pathological upgrading and metabolic features such as body mass index, hypertension, and dyslipidemia were not significant except for HDL. A 2015 meta-analysis, which summarized studies associating apolipoprotein E gene and cancer, demonstrated that reduced circulating HDL might be a potentially causal risk factor for the development of overall cancer in Asians.38 As studies from several other centers have shown, the decreased HDL level was related to increased risk of gastric cancer and advanced disease stage.39-42 One possible explanation is that HDL may promote cancer development by generating reactive oxygen species, increasing hormone production and availability (e.g., insulin-like growth factor, insulin, and adipokines), and forming an energy rich environment. This imbalance of hormones, the redox system, and energy availability plays a role in epithelium transition.43,44

It was interesting to note that our study showed significant statistical differences in both univariate and multivariate analyses for history of CAG and symptoms of digestive system between groups. The intestinal type of gastric cancer typically follows the Correa precancerous cascade of changes initiated by a non-self-limiting inflammation, of which CAG represents the relatively early stage.45 With the upgrading of gastric carcinogenesis, non-specific conditions such as gastritis and ulceration may appear.46,47 Poor prognosis from gastric cancer is mainly due to late presentation. Alarm symptoms of EGN include abdominal or epigastric pain or discomfort, nausea and vomiting, etc.48,49 EGN is usually asymptomatic. Therefore, referral guidelines have been developed to encourage early detection.50,51 Normally, endoscopists would be more careful with symptomatic patients during endoscopy.52,53 We assumed that patients who had CAG or suffered from digestive symptoms may be concerned about their digestive system health and would go through endoscopic checks.52,54 Therefore, the history of CAG and symptoms of digestive system seem to be protective factors.

Here, we reported predictors for pathological upgrading, also we established a nomogram in a visualized pattern. Another strength of our study was that our predictors included clinical, laboratorial and endoscopic features, and its performance was verified in the comparison with other training models (Figs 7 and 8). The nomogram yielded the highest AUC demonstrating the best discrimination in estimating the risk of pathological upgrading in patients with EGN. The final decision curve analysis showed that as long as setting the threshold probability of patients or clinicians beyond 10% (i.e., if no intervention was provided for patient with pathological upgrading was considered probably inappropriate), screening strategies based on our nomogram’s pathological upgrading risk estimates resulted in superior net benefit than screen-none or screen-all strategies (Fig. 7). When we set the threshold up to 40% or higher, the predictive effect of nomogram was still better than that of any training model. For practical application, we recommended explaining the upgrading risk predicted by nomogram to patients based on EFB findings. For EFB diagnosis of HGIN, intervention of ESD is necessary regardless of upgrading.6,55 For LGIN or non-neoplasia, a predicting value >50% indicates a greater risk of misdiagnosis, and secondary examination or immediate endoscopic intervention would be recommended.

Figure 8.Receiver operating characteristic analysis for the nomogram, training model 1 to 5, and EFB.
AUC, area under the curve; CI, confidence interval; EFB, endoscopic forceps biopsy.

This study has some limitations. First of all, this was a retrospective cohort study, in which data were mainly obtained by reviewing medical records or endoscopic results from a single center. Thus, it may restrict application to a wider population. Second, the operational differences between primary examiner at the local clinic and the procedural endoscopic resection operator, as well as the impact of random/guided biopsies, number of biopsies, could not be evaluated.4,56 Several studies have reported that white-light endoscopy combined with narrow-band imaging is superior to white-light endoscopy alone in identifying patients with gastric intestinal metaplasia and dysplasia.57,58 In fact, there were still many medical institutions in which virtual chromoendoscopy and high-definition processors and screens were not routinely available. Here, we enrolled no endoscopic features other than from white-light endoscopy.

In conclusion, pathological upgrading in EGN is common with specific clinical, laboratorial and endoscopic characteristics. Based on the above identified risk factors, a nomogram was developed to objectively and accurately predict individualized pathological upgrading risk of patients with EGN before ESD.

This study was supported by the Jiangsu Municipal Science and Technology Bureau (No. BE2020784), the National Natural Science Foundation of China (No. 82000529), and the Natural Science Foundation of Jiangsu Province (No. SBK 2020042595). The funding body had no role in the study design, data collection, analysis, and interpretation of data.

The authors appreciate the study participants and the inestimable support from the research center. The authors are grateful for support of the medical and research staff of this study.

No potential conflict of interest relevant to this article was reported.

Study concept and design: Y.H.Z., Y.N.D., G.X.Z. Data acquisition: Y.H.Z., Y.L., J.S. Pathological support: H.J.H., K.D.L. Data analysis and interpretation: Y.H.Z. Drafting of the manuscript: Y.H.Z., J.S. Critical revision of the manuscript for important intellectual content: Y.Z. Statistical analysis: Y.H.Z., Y.Z. Obtained funding: Y.N.D., G.X.Z. Study supervision: Y.N.D., G.X.Z. Approval of final manuscript: all authors.

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Article

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Gut and Liver

Published online September 2, 2022

Copyright © Gut and Liver.

A Prediction Model Based on the Risk Factors Associated with Pathological Upgrading in Patients with Early-Stage Gastric Neoplasms Diagnosed by Endoscopic Forceps Biopsy

Yu Han Zhao1 , Yu Zheng2 , Jie Sha3 , Hong Jin Hua4 , Ke Dong Li4 , Yu Lu1 , Yi Ni Dang1 , Guo Xin Zhang1

Departments of 1Gastroenterology and 2Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 3Department of Gastroenterology, Jingjiang People's Hospital, Jingjiang, and 4Department of Pathology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China

Correspondence to:Guo Xin Zhang
ORCID https://orcid.org/0000-0002-7103-3630
E-mail guoxinz@njmu.edu.cn

Yi Ni Dang
ORCID https://orcid.org/0000-0001-6449-516X
E-mail yeani_hi@126.com

Yu Han Zhao and Yu Zheng contributed equally to this work as first authors.

Received: February 12, 2022; Revised: April 25, 2022; Accepted: May 13, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background/Aims: The discrepancies between the diagnosis of preoperative endoscopic forceps biopsy (EFB) and endoscopic submucosal dissection (ESD) in patients with early gastric neoplasm (EGN) exist objectively. Among them, pathological upgrading directly influences the accuracy and appropriateness of clinical decisions. The aims of this study were to investigate the risk factors for the discrepancies, with a particular focus on pathological upgrading and to establish a prediction model for estimating the risk of pathological upgrading after EFB.
Methods: We retrospectively collected the records of 978 patients who underwent ESD from December 1, 2017 to July 31, 2021 and who had a final histopathology determination of EGN. A nomogram to predict the risk of pathological upgrading was constructed after analyzing subgroup differences among the 901 lesions enrolled.
Results: The ratio of pathological upgrading was 510 of 953 (53.5%). Clinical, laboratorial and endoscopic characteristics were analyzed using univariable and binary multivariable logistic regression analyses. A nomogram was constructed by including age, history of chronic atrophic gastritis, symptoms of digestive system, blood high density lipoprotein concentration, macroscopic type, pathological diagnosis of EFB, uneven surface, remarkable redness, and lesion size. The C-statistics were 0.804 (95% confidence interval, 0.774 to 0.834) and 0.748 (95% confidence interval, 0.664 to 0.832) in the training and validation set, respectively. We also built an online webserver based on the proposed nomogram for convenient clinical use.
Conclusions: The clinical value of identifying the preoperative diagnosis of EGN lesions is limited when using EFB separately. We have developed a nomogram that can predict the probability of pathological upgrading with good calibration and discrimination value.

Keywords: Early gastric neoplasm, Pathological upgrading, Prediction model, Endoscopic forceps biopsy, Endoscopic submucosal dissection

INTRODUCTION

Early gastric neoplasm (EGN) is a group including low grade intraepithelial neoplasia (LGIN), high grade intraepithelial neoplasia (HGIN), and early gastric carcinoma (EGC).1-4 LGIN and HGIN, for which the differences lie in the degree of cellular or structural heterogeneity, are ascribed as dysplasia and classified as precursor lesions. In current guidelines, endoscopic submucosal dissection (ESD) is preferred for EGN to prevent the deterioration of EGC to progressive gastric cancer, which has the following advantages: minimally invasive, faster recovery, higher curative ratio, and preservation of gastric function.5-8 Advanced endoscopic instruments, such as chromoendoscopy, high-definition white-light endoscopy, narrow-band imaging, are not yet widely applied and not easily mastered, and conventional white-light endoscopy in combination with endoscopic forceps biopsy (EFB) is under routine practice in the clinical context.

EFB is an important tool for the histopathological diagnosis of EGN. With multiple EFB, the diagnostic efficiency would be improved to some extent based on literature review and our clinical experience.9,10 However, further biopsies were not able to increase positive diagnosis cumulative rates, and may increase workload and medical cost, and may lead to trauma, bleeding, or perforation.11,12 On the other hand, the pathological outcomes of EFB and ESD are often inconsistent. These discrepancies could be divided into downgrading and upgrading. It has been reported that the overall rate of discrepancy between EFB and ESD ranges from 20.1% to 76.3%,10,11 with 16.3% to 44.9% pathological upgrading ultimately.7-9,12-16 In addition, the pathological upgrading group showed a significant tendency of submucosal invasion and lymphovascular/perineural invasion, which would lead to endoscopic noncurative resection and suboptimal prognostic results.17,18 Therefore, the question in front of us is how to classify patients with increased risk of pathological upgrading upon EFB. Indeed, it may be attributed to the experience of the endoscopist, but also highly associated with morphological features or biological characteristics of the lesion itself. Hitherto the risk factors associated with pathological upgrading remain unclear and the lack of a visual assessment model in clinical practice has led to insignificant improvements in diagnostic compliance.16

Considering the above concerns, this retrospective study was designed: (1) to investigate the risk factors of histological discrepancies between EFB and ESD, with a particular focus in pathological upgrading, and (2) to establish a prediction model in estimating the risk of pathological upgrading upon EFB.

MATERIALS AND METHODS

1. Study design and settings

This is a retrospective single-center cohort study to explore the risk factors for pathological upgrading between EFB and ESD in patients with EGN. The secondary outcome was to construct a nomogram to show the predictive efficacy of detected risk factors on pathological upgrading. This clinical study consisted of two stages. The first stage (training set) retrospectively identified patients diagnosed with EGN according to EFB or ESD in the First Affiliated Hospital of Nanjing Medical University from December 2017 to December 2020. The second stage (validation set) included patients from January 2021 to July 2021. The detailed procedure of the study is shown in Fig. 1. This study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board of the First Affiliated Hospital of Nanjing Medical University (IRB number: 2021-SR-227). It has been previously registered in Chinese Clinical Trial Registry (ChiCTR2100048088). Informed consent was waived due to the nature of the study design.

Figure 1. Flowchart of the study. The “n” in parentheses represents lesions.
ESD, endoscopic submucosal dissection; EFB, endoscopic forceps biopsy.

2. Study population

From December 2017 to July 2021, a total of 1,863 patients underwent gastric ESD. Indications followed the Japanese gastric cancer treatment guidelines 2018 (5th edition).6 Endoscopic refinement is recommended for suspected lesions, with endoscopic interventions if necessary.19,20 The target population were diagnosed with EGN according to EFB or ESD. Initially, 774 patients were excluded because of pathological diagnosis of ESD was inconsistent with the purpose of this study. After further data collection, patients were excluded if: (1) with a history of gastrectomy or gastric tube reconstruction; (2) did not undergo EFB for target lesions; or (3) with no clinical or endoscopic data. After excluding lesions of which pathological diagnosis with EFB were carcinoma, the lesions were divided into two groups (training set and validation set). Training set was analyzed to develop the nomogram model to predict the risk of pathological upgrading. The validation set was used to further external validate the predictive model. Lesions that presented as pathological consistency or pathological downgrading were assigned into the non-pathological upgrading group.

3. Pathological diagnostic criteria

Collection of biopsies before ESD were conducted in our center and the pathological diagnosis was confirmed by at least two experienced pathologists. However, according to the routine clinical practice, part of EFB may be conducted prior to the patients’ admission to our center, therefore repeating endoscopic procedures would be performed for non-neoplastic pathology or questionable discrepancies between the pathologic results obtained at our institution and at the referring hospital.14 The gastroenterologist would evaluate lesions for the indication of ESD based on pathological and endoscopic records. The ESD consent form was signed on the patient’s own wishes. In fact, even though additional surgeries may be required due to exceeding ESD indications, the majority of target patients in our institution chose to undergo ESD first, based on the advantages of ESD, even though additional surgeries may be required due to exceeding ESD indications,17,18,21 which ensured us screening up sufficient study population.

In this study, we followed the World Health Organization pathological diagnostic criteria in digestive system.1 We enrolled patients with different pathological outcomes (e.g., acute inflammation, chronic gastric atrophy, gastric intestinal metaplasia, LGIN, HGIN, and intramucosal carcinoma) and prespecified principles to define pathological upgrading and non-upgrading according to EFB and ESD examinations. For instance, if one patient showed LGIN during EFB while the pathological grade was reported as HGIN or carcinoma following ESD, this was identified as pathological upgrading. On the other hand, if one patient showed lower or consistent pathological grade after ESD as compared to that from EFB, they were finally assigned as non-pathological upgrading.14,22

4. Data collection

Demographic (e.g., age, sex, and body mass index) and clinical data (e.g., Helicobacter pylori infection status, medical history, and comorbidity), and EFB information were collected during patients’ admission before ESD according to their medical records. Endoscopic data (e.g., location, macroscopic type, and lesion size) were collected during ESD and pathological information of ESD specimens were collected according to pathological reports. In case of multiple lesions, one patient was treated as two cases and distinguished with their pathological characteristics.

Individual medical history and digestive comorbidity was defined positive as written down in medical records or outpatient documents. Symptoms of digestive system were considered as existing if the following words appeared in the records: abdominal pain, nausea, vomiting, dyspepsia, eructation, heartburn, loss of appetite, weight loss.

Ulceration or ulcer scar was considered positive after excluding those caused by the biopsy.23 Remarkable redness was defined as discoloration on the mucosal surface of the lesion compared to the surrounding mucosa, and uneven surface was defined as the presence of irregularly raised or nodular mucosa.24,25 Fig. 2 shows the following endoscopic features in sequence: remarkable redness, ulceration or scar and uneven surface.

Figure 2. Illustrations of the endoscopic features. (A-C) Lesions with remarkable redness. (D-F) Lesions with ulceration or scaring. (G-I) Lesions with an uneven surface.

5. Statistical analysis

All of the following statistical analyses were performed with SPSS 23.0 (IBM Corp., Armonk, NY, USA). Continuous variables were presented as means and standard deviations or medians with interquartile ranges. Categorical variables were demonstrated as numbers and percentages. Differences between groups were assessed using the chi-square test, the Student t-test, or the Mann-Whitney test in the univariate analysis, as appropriate. Variables detected with p<0.05 in the univariate logistic regression were further included in the multivariate logistic regression analysis to determine the variables that were independent influencing factors of pathological upgrading.

A predictive nomogram was constructed, based on the variables selected with the multivariate logistic regression analysis and by using the package of rms in R software (rms in R version 4.0.4, R Foundation for Statistical Computing, Vienna, Austria; https://www.r-project.org/). The model was validated internally in the training set and externally in the validation set. A calibration plot with bootstrapping (1,000 replications) was used to illustrate the association between the actual probability and the predicted probability. In addition, five training models were constructed to compare the robustness of each model. The performance of the prediction model was evaluated using the area under the curve (AUC) in receiver operating characteristic analysis. Decision curve analysis was used to explain the utility of benefits in clinical use.

RESULTS

1. Clinical characteristics

We retrospectively collected data for 1,053 lesions from 978 patients who underwent ESD for EGN. The comparison of diagnosis between the original EFB and the final ESD is summarized in Table 1. The predominant pathological upgrading involved upgrading from LGIN to HGIN or carcinoma (n=178) and upgrading from HGIN to carcinoma (n=270). After excluding lesions of which pathological diagnosis with EFB were carcinoma, 822 lesions were enrolled into the training and 131 were enrolled into validation sets. Clinical and endoscopic characteristics are summarized in Tables 2 and 3. Lesions (54.0%, 444/822) showed higher-grade disease after ESD in the training set (LGIN from non-neoplasia, HGIN or carcinoma from LGIN or non-neoplasia, or carcinoma from HGIN).

Table 1 . Comparison of Pathological Diagnosis by Initial Biopsy and Final Endoscopic Resection.

Pathologic diagnosis
with EFB
Pathologic diagnosis with ESD
Non-neoplasiaLGINHGINCarcinomaTotal No. (%)
Non-neoplasia1542*11*10*78 (7.4)
LGIN11293108*70*482 (45.8)
HGIN12993270*393 (37.3)
Carcinoma05491100 (9.5)
Total No. (%)27 (2.6)369 (35.0)216 (20.5)441 (41.9)1,053

EFB, endoscopic forceps biopsy; ESD, endoscopic submucosal dissection; LGIN, low grade intraepithelial neoplasia; HGIN, high grade intraepithelial neoplasia..

*Pathological upgrading; †Non-pathological upgrading..



Table 2 . Clinical Characteristics of the Training and Validation Sets.

CharacteristicsTraining set
(n=822)
Validation set
(n=131)
Age, yr63 (55–69)63 (57–70)
Male sex592 (72.0)103 (78.6)
Body mass index, kg/m223.8±3.324.1±2.9
Helicobacter pylori infection
Negative289 (35.1)45 (36.4)
Previous eradicated or infected533 (64.9)86 (65.6)
Symptoms of digestive system599 (72.9)56 (42.7)
Smoking198 (24.1)44 (33.6)
Drinking78 (20.6)24 (18.3)
Comorbidity
History of CAG466 (56.7)61 (46.6)
History of peptic ulcer137 (16.7)13 (9.9)
Medical history
Hypertension258 (31.4)58 (44.3)
Diabetes74 (9.0)14 (10.7)
Coronary heart disease33 (4.0)3 (2.3)
History of cholecystectomy58 (7.1)19 (14.5)
History of malignancy80 (9.7)4 (3.1)
Family history of malignancy133 (16.2)12 (9.2)
Laboratory examination
CEA, ng/mL3.4±4.62.8±4.4
CA19-9, U/mL12.7±28.212.8±8.0
CA724, U/mL3.9± 8.34.0±5.0
HDL, mmol/L1.2±0.31.1±0.3
LDL, mmol/L2.9±0.72.8±0.6
Albumin, g/L39.9±3.939.0±3.0
Calcium, mmol/L2.3±0.12.3±0.1

Data are presented as median (range), number (%), or mean±SD..

CAG, chronic atrophic gastritis; CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; CA724, carbohydrate antigen 724; HDL, high density lipoprotein; LDL, low density lipoprotein..



Table 3 . Endoscopic Characteristics of the Training and Validation Sets.

CharacteristicsTraining
set (n=822)
Validation
set (n=131)
Locations of lesions
Upper third241 (29.3)40 (30.5)
Middle third93 (11.3)21 (16.0)
Lower third488 (59.4)70 (53.4)
Macroscopic type of lesions
Elevated405 (49.3)55 (42.0)
Flat197 (24.0)26 (19.8)
Depressed220 (26.8)50 (38.2)
Pathologic diagnosis of EFB
Non-neoplasia74 (9.0)4 (3.1)
LGIN413 (50.2)69 (52.7)
HGIN335 (40.8)58 (44.3)
Pathologic diagnosis of ESD
Non-neoplasia27 (3.3)
LGIN314 (38.2)50 (38.2)
HGIN179 (21.8)33 (252)
Carcinoma302 (36.7)48 (36.8)
Pathologic upgrading
Yes444 (54.0)66 (50.4)
No378 (46.0)65 (49.6)
Multiple lesions52 (13.8)24 (18.3)
Endoscopic features
Ulceration or scar167 (20.3)39 (29.8)
Uneven surface364 (44.3)64 (48.9)
Remarkable redness531 (64.6)88 (67.2)
Lesion size
≤2 cm581 (70.7)78 (59.5)
>2 cm241 (29.3)53 (40.5)
Procedure time, min60 (45–90)60 (45–90)
Depth of invasion
M763 (92.8)126 (96.2)
SM129 (3.5)1 (0.8)
SM230 (3.6)4 (3.1)

Data are presented as number (%) or median (range)..

EFB, endoscopic forceps biopsy; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm; ESD, endoscopic submucosal dissection; M, intraepithelial and/or the deepest infiltration depth is within the mucosal lamina propria; SM1, the infiltration depth >500 μm from the muscularis mucosae; SM2, the infiltration depth >500 μm from the muscularis mucosae..



2. Baseline characteristics

As shown in Table 4, statistical differences were detected in those with history of smoking, drinking, chronic atrophic gastritis (CAG), and symptoms of digestive system. History of CAG was less commonly detected in the pathological upgrading group than in the non-pathological upgrading group (50.2% vs 60.9%, p<0.001). The rate of H. pylori infection was more than 60% in both groups.

Table 4 . Clinical Characteristics of Lesions with or without Pathological Upgrading.

CharacteristicsNon-pathological upgrading group (n=378)Pathological upgrading group (n=444)p-value*
Age, yr63 (55–69)65 (58–70)<0.001
Male sex250 (66.1)342 (77.0)0.001
Body mass index, kg/m223.6±3.123.9±3.40.082
Helicobacter pylori infection0.680
Negative131 (34.7)160 (36.0)
Previous eradicated or infected247 (65.3)284 (64.0)
Symptoms of digestive system260 (68.8)339 (76.4)0.015
Smoking105 (27.8)159 (35.8)0.014
Drinking78 (20.6)120 (27.0)0.033
Comorbidity
History of CAG243 (64.3)223 (50.2)<0.001
History of peptic ulcer71 (15.4)82 (18.5)0.224
Medical history
Hypertension104 (27.5)154 (34.7)0.073
Diabetes30 (7.9)44 (9.9)0.270
Coronary heart disease11 (2.9)22 (5.0)0.269
History of cholecystectomy22 (5.8)36 (8.1)0.236
History of malignancy35 (9.3)45 (10.1)0.531
Family history of malignancy61 (16.1)72 (16.2)0.700
Laboratory examination
CEA, ng/mL3.3±4.53.5±4.40.398
CA19-9, U/mL12.4±30.513.1±26.20.734
CA724, U/mL4.0±9.73.8±6.90.682
HDL, mmol/L1.2±0.31.1±0.20.015
LDL, mmol/L2.9±0.72.9±0.70.099
Albumin, g/L40.2±3.639.7±4.20.056
Calcium, mmol/L2.3±0.12.2±0.10.004

Data are presented as median (range), number (%), or mean±SD..

CAG, chronic atrophic gastritis; CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; CA724, carbohydrate antigen 724; HDL, high density lipoprotein; LDL, low density lipoprotein..

*p-value was derived from the chi-square test, Student t-test, or Mann-Whitney test..



The contradistinction of endoscopic characteristics was presented in Table 5. Pathological upgrading more frequently occurred in lower third (51.1%), followed by upper third (36.5%) and middle third (12.4%) in the upgrading group. The predominant macroscopic type in both groups was elevated pattern, with a gradual tendency of depressed pattern in the pathological upgrading group. The endoscopic ulceration, uneven surface, remarkable redness was found to account for 26.8%, 56.1%, and 75.4% in cases of pathological upgrading, accordingly.

Table 5 . Endoscopic Characteristics and Posttreatment Evaluation of the Lesions with or without Pathological Upgrading.

CharacteristicsNon-pathological upgrading group (n=378)Pathological upgrading group (n=444)p-value*
Locations of lesions<0.001
Upper third79 (20.9)162 (36.5)
Middle third38 (10.1)55 (12.4)
Lower third261 (69.0)227 (51.1)
Macroscopic type of lesions<0.001
Elevated206 (54.5)199 (44.8)
Flat106 (28.0)91 (20.5)
Depressed66 (17.5)154 (34.7)
Pathologic diagnosis of EFB<0.001
Non-neoplasia16 (3.5)58 (13.1)
LGIN261 (56.7)152 (34.2)
HGIN101 (22.0)234 (52.7)
Multiple lesions52 (13.8)68 (15.3)0.528
Endoscopic features
Ulceration or scar48 (12.7)119 (26.8)<0.001
Uneven surface115 (30.4)249 (56.1)<0.001
Remarkable redness197 (52.1)334 (75.4)<0.001
Lesion size<0.001
≤2 cm306 (81.0)275 (61.9)
>2 cm72 (19.0)169 (38.1)
Procedure time, min60 (45–90)60 (45–100)<0.001
Depth of invasion<0.001
M378 (95.0)385 (86.7)
SM1-29 (6.5)
SM2-27 (6.8)

Data are presented as number (%) or median (range)..

EFB, endoscopic forceps biopsy; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm; M, intraepithelial and/or the deepest infiltration depth is within the mucosal lamina propria; SM1, the infiltration depth >500 μm from the muscularis mucosae; SM2, the infiltration depth >500 μm from the muscularis mucosae..

*p-value was derived from chi-square test or Mann-Whitney test..



3. Analysis of risk predictors

Multivariate analysis (logistic regression analysis) was further performed to analyze the variables that were statistically significant in univariate analysis. Ultimately, a total of nine variables which pertained to clinical, laboratorial, endoscopic characteristics separately were enrolled to build the clinical prediction model. As revealed in Table 6, history of CAG (odds ratio [OR], 0.59; 95% confidence interval [CI], 0.42 to 0.84; p=0.003), blood high density lipoprotein (HDL) concentration (OR, 0.46; 95% CI, 0.24 to 0.86; p<0.016) were protective predictors. Age, symptoms of digestive system, macroscopic type of lesions, pathologic diagnosis of EFB, remarkable redness were risk factors, while uneven surface (OR, 2.35; 95% CI, 1.66 to 3.32; p<0.001), lesion size >2 cm (OR, 2.20; 95% CI, 1.50 to 3.22; p<0.001) were independent risk predictors.

Table 6 . Univariate and Multivariate Regression Analyses of the Predictors Associated with Pathological Upgrading According to the Analyzed Variables.

FactorUnivariate logistic analysisMultivariate logistic analysis
OR (95% CI)p-valueOR (95% CI)p-value
Age1.05 (1.03–1.06)<0.0011.04 (1.03–1.06)<0.001
Sex (ref. male)0.60 (0.44–0.82)0.001
Smoking (ref. no)1.38 (1.02–1.87)0.036
Drinking (ref. no)1.39 (1.03–1.89)0.034
Comorbidity: CAG (ref. no)0.47 (0.35–0.63)<0.0010.47 (0.33–0.68)<0.001
Symptoms of digestive system (ref. no)1.44 (1.05–1.97)0.0251.60 (1.08–2.36)0.019
Laboratory examination: HDL0.34 (0.20–0.58)<0.0010.44 (0.24–0.81)0.008
Laboratory examination: calcium0.09 (0.02–0.37)0.001
Locations of lesions (ref. upper third)1.00
Middle third0.71 (0.43–1.18)0.187
Lower third0.40 (0.29–0.56)0.001
Macroscopic type of lesions (ref. elevated)1.001.00
Flat0.84 (0.60–1.19)0.3310.74 (0.48–1.13)0.164
Depressed2.25 (1.68–3.20)<0.0011.63 (1.13–2.32)0.045
Pathological diagnosis of EFB (ref. non-neoplasia)1.001.00
LGIN0.01 (0.01–0.08)<0.0010.01 (0.01–0.06)<0.001
HGIN0.04 (0.01–0.30)0.0020.02 (0.01–0.13)<0.001
Endoscopic features: ulceration or scar (ref. no)2.63 (1.79–3.84)<0.001
Endoscopic features: uneven surface (ref. no)2.69 (2.01–3.60)<0.0012.24 (1.58–3.19)<0.001
Endoscopic features: remarkable redness (ref. no)2.95 (2.19–3.99)<0.0012.26 (1.57–3.27)<0.001
Lesion size (ref. ≤2 cm)2.47 (1.78–3.41)<0.0012.20 (1.49–3.24)<0.001

OR, odds ratio; CI, confidence interval; ref., reference group; CAG, chronic atrophic gastritis; HDL, high density lipoprotein; EFB, endoscopic forceps biopsy; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm..



4. Dynamic nomogram construction and validation

We developed a nomogram to predict the risk of pathological upgrading in patients with EGN (Fig. 3). For instance, a 65-year-old patient, with a previous history of CAG, without symptoms of digestive system, and blood HDL concentration of 1.0 mmol/L, was found to have an elevated lesion with remarkable redness and uneven surface, and less than 2 cm in diameter at endoscopy. If the EFB pathology was HGIN, the incidence of pathological upgrading would be 65.1% (95% CI, 0.522 to 0.761). The online version of our nomogram software is accessible at https://zyh-njmu.shinyapps.io/Dynamic_nomogram/.

Figure 3. Illustration of the prediction nomogram model based on clinical, laboratorial, endoscopic characteristics.
CAG, chronic atrophic gastritis; HDL, high density lipoprotein; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm; EFB, endoscopic forceps biopsy.

We performed validation by using the bootstrap method with 1,000 repetitions to display the calibration of the nomogram (Fig. 4A and B). Accuracy of the nomogram was examined with AUC. The C-statistics for our nomogram model was 0.804 (95% CI, 0.774 to 0.834) and 0.748 (95% CI, 0.664 to 0.832) in the training and validation set, respectively (Fig. 4C and D).

Figure 4. Calibration and diagnostic ability of the nomogram. Calibration curves by using bootstrapping (1,000 repetitions) in the training set (A) and validation set (B). The receiver operating characteristic curve in the training set (C) and validation set (D).
AUC, area under the curve; CI, confidence interval.

To assess the predictive ability of our nomogram, several training schemes (namely training models 1 to 5) were constructed (Fig. 5). Afterwards, we performed internal validation and AUC computation for training models 1 to 5 and EFB, and the calibration plot and C-statistics for each model were shown in Figs 6 and 7, respectively.

Figure 5. Training models 1 to 5. (A) Training model 1 was constructed with clinical and endoscopic factors without endoscopic forceps biopsy (EFB) diagnosis. (B) Training model 2 was constructed with clinical factors and EFB diagnosis without endoscopic factors. (C) Training model 3 was constructed with endoscopic factors and EFB diagnosis without clinical factors. (D) Training model 4 was constructed with clinical factors only. (E) Training model 5 was constructed with endoscopic factors only.
CAG, chronic atrophic gastritis; HDL, high density lipoprotein; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm.

Figure 6. Calibration curves for training model 1 to 5. Validation of the training models 1 to 5 based on calibration curves by using bootstrapping (1,000 repetitions).

Figure 7. Decision curve analysis for the nomogram, training models 1 to 5, and endoscopic forceps biopsy (EFB).

DISCUSSION

EFB and ESD are used for diagnosis of EGN. However, EFB is not able to show histology of the entire lesion, which may lead to discrepancy between histological diagnosis of EFB and resected specimen. Therefore, it is urgently needed to establish a clinical predictive tool to identify the risk of pathological upgrading. Nomogram is a visualization prediction tool that can incorporate different variables affecting outcomes.26 We developed a nomogram for pathological upgrading in patients received EFB before ESD which showed a steady accuracy in evaluating the risk of pathological upgrading.

In the current study, rate of pathological upgrading was 44.9%. It was similar to the results of previous studies.15,27-31 Sixty-nine point nine percent of HGIN in EFB were diagnosed as EGC in our study, which was comparable to reported results.30,32,33 It has been found that pathological upgrading was positively correlated with longer operation time and deeper submucosal invasion. In addition, the depth of invasion was verified in predicting the risk of nodal metastasis in EGCs.17,34,35

In agreement with reported data, our study demonstrated that the depressed pattern, nodular surface, surface redness, lesion size >2 cm, and location in the upper third of the stomach were risk factors in pathological upgrading.23,36,37 EGCs located in the lower third of the stomach, especially in the antrum, might be detected easily, but for those in the upper third, detection may be difficult due to denser mucosal folds, thinner stomach, and limited endoscopic visual fields.36

Ideally, one would incline to have a validated noninvasive biomarker to predict cancer risk. However, no positive values of traditional tumor markers in predicting pathological upgrading have been observed in our study. We found that associations between pathological upgrading and metabolic features such as body mass index, hypertension, and dyslipidemia were not significant except for HDL. A 2015 meta-analysis, which summarized studies associating apolipoprotein E gene and cancer, demonstrated that reduced circulating HDL might be a potentially causal risk factor for the development of overall cancer in Asians.38 As studies from several other centers have shown, the decreased HDL level was related to increased risk of gastric cancer and advanced disease stage.39-42 One possible explanation is that HDL may promote cancer development by generating reactive oxygen species, increasing hormone production and availability (e.g., insulin-like growth factor, insulin, and adipokines), and forming an energy rich environment. This imbalance of hormones, the redox system, and energy availability plays a role in epithelium transition.43,44

It was interesting to note that our study showed significant statistical differences in both univariate and multivariate analyses for history of CAG and symptoms of digestive system between groups. The intestinal type of gastric cancer typically follows the Correa precancerous cascade of changes initiated by a non-self-limiting inflammation, of which CAG represents the relatively early stage.45 With the upgrading of gastric carcinogenesis, non-specific conditions such as gastritis and ulceration may appear.46,47 Poor prognosis from gastric cancer is mainly due to late presentation. Alarm symptoms of EGN include abdominal or epigastric pain or discomfort, nausea and vomiting, etc.48,49 EGN is usually asymptomatic. Therefore, referral guidelines have been developed to encourage early detection.50,51 Normally, endoscopists would be more careful with symptomatic patients during endoscopy.52,53 We assumed that patients who had CAG or suffered from digestive symptoms may be concerned about their digestive system health and would go through endoscopic checks.52,54 Therefore, the history of CAG and symptoms of digestive system seem to be protective factors.

Here, we reported predictors for pathological upgrading, also we established a nomogram in a visualized pattern. Another strength of our study was that our predictors included clinical, laboratorial and endoscopic features, and its performance was verified in the comparison with other training models (Figs 7 and 8). The nomogram yielded the highest AUC demonstrating the best discrimination in estimating the risk of pathological upgrading in patients with EGN. The final decision curve analysis showed that as long as setting the threshold probability of patients or clinicians beyond 10% (i.e., if no intervention was provided for patient with pathological upgrading was considered probably inappropriate), screening strategies based on our nomogram’s pathological upgrading risk estimates resulted in superior net benefit than screen-none or screen-all strategies (Fig. 7). When we set the threshold up to 40% or higher, the predictive effect of nomogram was still better than that of any training model. For practical application, we recommended explaining the upgrading risk predicted by nomogram to patients based on EFB findings. For EFB diagnosis of HGIN, intervention of ESD is necessary regardless of upgrading.6,55 For LGIN or non-neoplasia, a predicting value >50% indicates a greater risk of misdiagnosis, and secondary examination or immediate endoscopic intervention would be recommended.

Figure 8. Receiver operating characteristic analysis for the nomogram, training model 1 to 5, and EFB.
AUC, area under the curve; CI, confidence interval; EFB, endoscopic forceps biopsy.

This study has some limitations. First of all, this was a retrospective cohort study, in which data were mainly obtained by reviewing medical records or endoscopic results from a single center. Thus, it may restrict application to a wider population. Second, the operational differences between primary examiner at the local clinic and the procedural endoscopic resection operator, as well as the impact of random/guided biopsies, number of biopsies, could not be evaluated.4,56 Several studies have reported that white-light endoscopy combined with narrow-band imaging is superior to white-light endoscopy alone in identifying patients with gastric intestinal metaplasia and dysplasia.57,58 In fact, there were still many medical institutions in which virtual chromoendoscopy and high-definition processors and screens were not routinely available. Here, we enrolled no endoscopic features other than from white-light endoscopy.

In conclusion, pathological upgrading in EGN is common with specific clinical, laboratorial and endoscopic characteristics. Based on the above identified risk factors, a nomogram was developed to objectively and accurately predict individualized pathological upgrading risk of patients with EGN before ESD.

ACKNOWLEDGEMENTS

This study was supported by the Jiangsu Municipal Science and Technology Bureau (No. BE2020784), the National Natural Science Foundation of China (No. 82000529), and the Natural Science Foundation of Jiangsu Province (No. SBK 2020042595). The funding body had no role in the study design, data collection, analysis, and interpretation of data.

The authors appreciate the study participants and the inestimable support from the research center. The authors are grateful for support of the medical and research staff of this study.

CONFLICTS OF INTEREST

No potential conflict of interest relevant to this article was reported.

AUTHOR CONTRIBUTIONS

Study concept and design: Y.H.Z., Y.N.D., G.X.Z. Data acquisition: Y.H.Z., Y.L., J.S. Pathological support: H.J.H., K.D.L. Data analysis and interpretation: Y.H.Z. Drafting of the manuscript: Y.H.Z., J.S. Critical revision of the manuscript for important intellectual content: Y.Z. Statistical analysis: Y.H.Z., Y.Z. Obtained funding: Y.N.D., G.X.Z. Study supervision: Y.N.D., G.X.Z. Approval of final manuscript: all authors.

Fig 1.

Figure 1.Flowchart of the study. The “n” in parentheses represents lesions.
ESD, endoscopic submucosal dissection; EFB, endoscopic forceps biopsy.
Gut and Liver 2022; :

Fig 2.

Figure 2.Illustrations of the endoscopic features. (A-C) Lesions with remarkable redness. (D-F) Lesions with ulceration or scaring. (G-I) Lesions with an uneven surface.
Gut and Liver 2022; :

Fig 3.

Figure 3.Illustration of the prediction nomogram model based on clinical, laboratorial, endoscopic characteristics.
CAG, chronic atrophic gastritis; HDL, high density lipoprotein; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm; EFB, endoscopic forceps biopsy.
Gut and Liver 2022; :

Fig 4.

Figure 4.Calibration and diagnostic ability of the nomogram. Calibration curves by using bootstrapping (1,000 repetitions) in the training set (A) and validation set (B). The receiver operating characteristic curve in the training set (C) and validation set (D).
AUC, area under the curve; CI, confidence interval.
Gut and Liver 2022; :

Fig 5.

Figure 5.Training models 1 to 5. (A) Training model 1 was constructed with clinical and endoscopic factors without endoscopic forceps biopsy (EFB) diagnosis. (B) Training model 2 was constructed with clinical factors and EFB diagnosis without endoscopic factors. (C) Training model 3 was constructed with endoscopic factors and EFB diagnosis without clinical factors. (D) Training model 4 was constructed with clinical factors only. (E) Training model 5 was constructed with endoscopic factors only.
CAG, chronic atrophic gastritis; HDL, high density lipoprotein; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm.
Gut and Liver 2022; :

Fig 6.

Figure 6.Calibration curves for training model 1 to 5. Validation of the training models 1 to 5 based on calibration curves by using bootstrapping (1,000 repetitions).
Gut and Liver 2022; :

Fig 7.

Figure 7.Decision curve analysis for the nomogram, training models 1 to 5, and endoscopic forceps biopsy (EFB).
Gut and Liver 2022; :

Fig 8.

Figure 8.Receiver operating characteristic analysis for the nomogram, training model 1 to 5, and EFB.
AUC, area under the curve; CI, confidence interval; EFB, endoscopic forceps biopsy.
Gut and Liver 2022; :

Table 1 Comparison of Pathological Diagnosis by Initial Biopsy and Final Endoscopic Resection

Pathologic diagnosis
with EFB
Pathologic diagnosis with ESD
Non-neoplasiaLGINHGINCarcinomaTotal No. (%)
Non-neoplasia1542*11*10*78 (7.4)
LGIN11293108*70*482 (45.8)
HGIN12993270*393 (37.3)
Carcinoma05491100 (9.5)
Total No. (%)27 (2.6)369 (35.0)216 (20.5)441 (41.9)1,053

EFB, endoscopic forceps biopsy; ESD, endoscopic submucosal dissection; LGIN, low grade intraepithelial neoplasia; HGIN, high grade intraepithelial neoplasia.

*Pathological upgrading; †Non-pathological upgrading.


Table 2 Clinical Characteristics of the Training and Validation Sets

CharacteristicsTraining set
(n=822)
Validation set
(n=131)
Age, yr63 (55–69)63 (57–70)
Male sex592 (72.0)103 (78.6)
Body mass index, kg/m223.8±3.324.1±2.9
Helicobacter pylori infection
Negative289 (35.1)45 (36.4)
Previous eradicated or infected533 (64.9)86 (65.6)
Symptoms of digestive system599 (72.9)56 (42.7)
Smoking198 (24.1)44 (33.6)
Drinking78 (20.6)24 (18.3)
Comorbidity
History of CAG466 (56.7)61 (46.6)
History of peptic ulcer137 (16.7)13 (9.9)
Medical history
Hypertension258 (31.4)58 (44.3)
Diabetes74 (9.0)14 (10.7)
Coronary heart disease33 (4.0)3 (2.3)
History of cholecystectomy58 (7.1)19 (14.5)
History of malignancy80 (9.7)4 (3.1)
Family history of malignancy133 (16.2)12 (9.2)
Laboratory examination
CEA, ng/mL3.4±4.62.8±4.4
CA19-9, U/mL12.7±28.212.8±8.0
CA724, U/mL3.9± 8.34.0±5.0
HDL, mmol/L1.2±0.31.1±0.3
LDL, mmol/L2.9±0.72.8±0.6
Albumin, g/L39.9±3.939.0±3.0
Calcium, mmol/L2.3±0.12.3±0.1

Data are presented as median (range), number (%), or mean±SD.

CAG, chronic atrophic gastritis; CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; CA724, carbohydrate antigen 724; HDL, high density lipoprotein; LDL, low density lipoprotein.


Table 3 Endoscopic Characteristics of the Training and Validation Sets

CharacteristicsTraining
set (n=822)
Validation
set (n=131)
Locations of lesions
Upper third241 (29.3)40 (30.5)
Middle third93 (11.3)21 (16.0)
Lower third488 (59.4)70 (53.4)
Macroscopic type of lesions
Elevated405 (49.3)55 (42.0)
Flat197 (24.0)26 (19.8)
Depressed220 (26.8)50 (38.2)
Pathologic diagnosis of EFB
Non-neoplasia74 (9.0)4 (3.1)
LGIN413 (50.2)69 (52.7)
HGIN335 (40.8)58 (44.3)
Pathologic diagnosis of ESD
Non-neoplasia27 (3.3)
LGIN314 (38.2)50 (38.2)
HGIN179 (21.8)33 (252)
Carcinoma302 (36.7)48 (36.8)
Pathologic upgrading
Yes444 (54.0)66 (50.4)
No378 (46.0)65 (49.6)
Multiple lesions52 (13.8)24 (18.3)
Endoscopic features
Ulceration or scar167 (20.3)39 (29.8)
Uneven surface364 (44.3)64 (48.9)
Remarkable redness531 (64.6)88 (67.2)
Lesion size
≤2 cm581 (70.7)78 (59.5)
>2 cm241 (29.3)53 (40.5)
Procedure time, min60 (45–90)60 (45–90)
Depth of invasion
M763 (92.8)126 (96.2)
SM129 (3.5)1 (0.8)
SM230 (3.6)4 (3.1)

Data are presented as number (%) or median (range).

EFB, endoscopic forceps biopsy; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm; ESD, endoscopic submucosal dissection; M, intraepithelial and/or the deepest infiltration depth is within the mucosal lamina propria; SM1, the infiltration depth >500 μm from the muscularis mucosae; SM2, the infiltration depth >500 μm from the muscularis mucosae.


Table 4 Clinical Characteristics of Lesions with or without Pathological Upgrading

CharacteristicsNon-pathological upgrading group (n=378)Pathological upgrading group (n=444)p-value*
Age, yr63 (55–69)65 (58–70)<0.001
Male sex250 (66.1)342 (77.0)0.001
Body mass index, kg/m223.6±3.123.9±3.40.082
Helicobacter pylori infection0.680
Negative131 (34.7)160 (36.0)
Previous eradicated or infected247 (65.3)284 (64.0)
Symptoms of digestive system260 (68.8)339 (76.4)0.015
Smoking105 (27.8)159 (35.8)0.014
Drinking78 (20.6)120 (27.0)0.033
Comorbidity
History of CAG243 (64.3)223 (50.2)<0.001
History of peptic ulcer71 (15.4)82 (18.5)0.224
Medical history
Hypertension104 (27.5)154 (34.7)0.073
Diabetes30 (7.9)44 (9.9)0.270
Coronary heart disease11 (2.9)22 (5.0)0.269
History of cholecystectomy22 (5.8)36 (8.1)0.236
History of malignancy35 (9.3)45 (10.1)0.531
Family history of malignancy61 (16.1)72 (16.2)0.700
Laboratory examination
CEA, ng/mL3.3±4.53.5±4.40.398
CA19-9, U/mL12.4±30.513.1±26.20.734
CA724, U/mL4.0±9.73.8±6.90.682
HDL, mmol/L1.2±0.31.1±0.20.015
LDL, mmol/L2.9±0.72.9±0.70.099
Albumin, g/L40.2±3.639.7±4.20.056
Calcium, mmol/L2.3±0.12.2±0.10.004

Data are presented as median (range), number (%), or mean±SD.

CAG, chronic atrophic gastritis; CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; CA724, carbohydrate antigen 724; HDL, high density lipoprotein; LDL, low density lipoprotein.

*p-value was derived from the chi-square test, Student t-test, or Mann-Whitney test.


Table 5 Endoscopic Characteristics and Posttreatment Evaluation of the Lesions with or without Pathological Upgrading

CharacteristicsNon-pathological upgrading group (n=378)Pathological upgrading group (n=444)p-value*
Locations of lesions<0.001
Upper third79 (20.9)162 (36.5)
Middle third38 (10.1)55 (12.4)
Lower third261 (69.0)227 (51.1)
Macroscopic type of lesions<0.001
Elevated206 (54.5)199 (44.8)
Flat106 (28.0)91 (20.5)
Depressed66 (17.5)154 (34.7)
Pathologic diagnosis of EFB<0.001
Non-neoplasia16 (3.5)58 (13.1)
LGIN261 (56.7)152 (34.2)
HGIN101 (22.0)234 (52.7)
Multiple lesions52 (13.8)68 (15.3)0.528
Endoscopic features
Ulceration or scar48 (12.7)119 (26.8)<0.001
Uneven surface115 (30.4)249 (56.1)<0.001
Remarkable redness197 (52.1)334 (75.4)<0.001
Lesion size<0.001
≤2 cm306 (81.0)275 (61.9)
>2 cm72 (19.0)169 (38.1)
Procedure time, min60 (45–90)60 (45–100)<0.001
Depth of invasion<0.001
M378 (95.0)385 (86.7)
SM1-29 (6.5)
SM2-27 (6.8)

Data are presented as number (%) or median (range).

EFB, endoscopic forceps biopsy; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm; M, intraepithelial and/or the deepest infiltration depth is within the mucosal lamina propria; SM1, the infiltration depth >500 μm from the muscularis mucosae; SM2, the infiltration depth >500 μm from the muscularis mucosae.

*p-value was derived from chi-square test or Mann-Whitney test.


Table 6 Univariate and Multivariate Regression Analyses of the Predictors Associated with Pathological Upgrading According to the Analyzed Variables

FactorUnivariate logistic analysisMultivariate logistic analysis
OR (95% CI)p-valueOR (95% CI)p-value
Age1.05 (1.03–1.06)<0.0011.04 (1.03–1.06)<0.001
Sex (ref. male)0.60 (0.44–0.82)0.001
Smoking (ref. no)1.38 (1.02–1.87)0.036
Drinking (ref. no)1.39 (1.03–1.89)0.034
Comorbidity: CAG (ref. no)0.47 (0.35–0.63)<0.0010.47 (0.33–0.68)<0.001
Symptoms of digestive system (ref. no)1.44 (1.05–1.97)0.0251.60 (1.08–2.36)0.019
Laboratory examination: HDL0.34 (0.20–0.58)<0.0010.44 (0.24–0.81)0.008
Laboratory examination: calcium0.09 (0.02–0.37)0.001
Locations of lesions (ref. upper third)1.00
Middle third0.71 (0.43–1.18)0.187
Lower third0.40 (0.29–0.56)0.001
Macroscopic type of lesions (ref. elevated)1.001.00
Flat0.84 (0.60–1.19)0.3310.74 (0.48–1.13)0.164
Depressed2.25 (1.68–3.20)<0.0011.63 (1.13–2.32)0.045
Pathological diagnosis of EFB (ref. non-neoplasia)1.001.00
LGIN0.01 (0.01–0.08)<0.0010.01 (0.01–0.06)<0.001
HGIN0.04 (0.01–0.30)0.0020.02 (0.01–0.13)<0.001
Endoscopic features: ulceration or scar (ref. no)2.63 (1.79–3.84)<0.001
Endoscopic features: uneven surface (ref. no)2.69 (2.01–3.60)<0.0012.24 (1.58–3.19)<0.001
Endoscopic features: remarkable redness (ref. no)2.95 (2.19–3.99)<0.0012.26 (1.57–3.27)<0.001
Lesion size (ref. ≤2 cm)2.47 (1.78–3.41)<0.0012.20 (1.49–3.24)<0.001

OR, odds ratio; CI, confidence interval; ref., reference group; CAG, chronic atrophic gastritis; HDL, high density lipoprotein; EFB, endoscopic forceps biopsy; LGIN, low grade intraepithelial neoplasm; HGIN, high grade intraepithelial neoplasm.


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Gut and Liver

Vol.16 No.5
September, 2022

pISSN 1976-2283
eISSN 2005-1212

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