Gastric cancer (GC) is the second most common malignant tumor in China. A total of 679,100 Chinese patients were diagnosed with GC in 2015, and 498,000 died as a result. The incidence and death of GC in China accounted for approximately half of the world’s total [
In China, the current national guidelines for early cancer screening suggest screening high-risk groups (refer to materials and methods) from the age of 40. Gastroscopy combined with gastric mucosa biopsy is the gold standard for diagnosing GC. However, gastroscopy and biopsy are invasive operations that may cause some discomfort and complications. Patients do not accept them well. If gastroscopy is performed on the entire high-risk group, it is estimated that only 1-3% of the population would be diagnosed with GC. The efficiency is relatively low, and the examination cost is relatively high, so it is not feasible to conduct gastroscopy surveys in large-scale populations in China [
Anti-Helicobacter pylori IgG antibody (anti-Hp IgG) combined with serum pepsinogen (PG) has been used in large-scale GC screening with satisfactory results in countries such as Japan and Finland. This method is called the “ABC method” [
Gastrin 17 (G-17) can reflect the atrophy and pathological changes of gastric antrum mucosa. Some scholars proposed using G-17 combined with pepsin as a serological screening indicator [
The study was conducted on subjects who underwent serological tests and gastroscopy from January 2016 to January 2018 in Hangzhou, Zhejiang Province. All the subjects were aware of the risks and benefits and signed an informed consent form. A total of 834 patients were included in the study. We designed a questionnaire to collect relevant clinical information. The inclusion criteria were as follows: (1)
Five milliliters of venous whole blood was collected from the cubital vein of subjects who fasted for more than 8 hours in the morning. The concentrations of G-17, pepsinogen I (PGI), and pepsinogen (PGII) in serum (E-plate EIKEN H. pylori, Eiken Chemical Co. Ltd, Tokyo, Japan) were quantitatively determined by the enzyme-linked immunosorbent assay (ELISA) method, and the PGI/PGII ratio (PGR) was calculated.
Gastroscopy was performed by skilled endoscopists (who perform over 1000 endoscopies each year). The gastric mucosa was observed according to standard gastroscopy. Endoscopic diagnosis was based on the Chinese consensus on chronic gastritis (2012, Shanghai) as well as records of other findings. The general analysis of superficial tumors was based on the Paris Classification. All subjects underwent standard biopsies in the antrum and gastric body during gastroscopy, and the biopsy tissue was large and deep enough to reach the muscularis mucosa. If suspicious lesions were found, the biopsy samples were increased according to the size of the lesions. After formalin fixation, dehydration, clearing, paraffin wax immersion, and embedding, sectioning, and staining, the gastric mucosal biopsy tissues were diagnosed by experienced pathologists who did not know the level of the serological markers of the patients in advance. According to the endoscopic and pathological diagnosis, the patients were divided into chronic nonatrophic gastritis (NAG)/CAG/IN/GC/gastric ulcer (GU) groups.
The statistical analysis was carried out by using SPSS statistical software (Version 22.0, SPSS Inc., Chicago, USA). Continuous variables are presented as the mean and standard deviation (
Baseline data and disease composition.
Variable | Value |
---|---|
No. of patients | 834 |
Sex | |
Male | 357 (42.8%) |
Female | 477 (57.2%) |
| |
Disease | |
Chronic nonatrophic gastritis (NAG) | 346 (41.5%) |
Chronic atrophic gastritis (CAG) | 332 (39.8%) |
Gastric ulcer (GU) | 54 (6.5%) |
Intraepithelial neoplasia (IN) | 48 (5.8%) |
Gastric cancer (GC) | 54 (6.5%) |
Early gastric cancer (EGC) | 27 (50%)a |
Advanced gastric cancer | 27 (50%)b |
SD: standard deviation. aAccounts for the proportion of all gastric cancer. bAccounts for the proportion of all gastric cancer.
A total of 834 subjects were included in the study. The mean age of the patients was
The diagnoses were as follows: NAG, 346 cases (41.5%); CAG, 332 cases (39.8%); IN, 48 cases (5.8%); GU, 54 cases (6.5%); and GC, 54 cases (6.5%), including 27 cases of early GC (EGC) (3.25%) and 27 cases of advanced GC (3.25%), with the proportion of EGC accounting for 50%.
Laboratory examination results of different disease states.
NAG | CAG | IN | GC | P | NAG vs. CAG | CG vs. IN | CG vs. GC | |
---|---|---|---|---|---|---|---|---|
G-17 | ≤0.001 | 0.002 | ≤.0.001 | ≤.0.001 | ||||
PGI | 0.377 | 0.883 | 0.139 | 0.279 | ||||
PGII | ≤0.001 | 0.170 | ≤.0.001 | ≤.0.001 | ||||
PGR | ≤.0.001 | ≤.0.001 | ≤.0.001 | ≤.0.001 |
The laboratory examination results according to different disease states are shown in Table
Determination of the cutoff values of G-17, PGII, and PGR and diagnostic value. (a) ROC curve of NAG and CAG. G-17: AUC is 0.555 (CI 0.512-0.598), YI is 0.101, and cutoff value is 9.25; PGII: AUC is 0.561 (CI 0.518-0.604), YI is 0.120, and cutoff value is 7.06; PGR: AUC is 0.571 (CI 0.528-0.614), YI is 0.135, and cutoff value is 12.07. (b) ROC curve of CG and IN. G-17 : AUC is 0.722 (CI 0.642-0.801), YI is 0.379, and cutoff value is 3.86; PGII: AUC is 0.697 (CI 0.611-0.783), YI is 0.362, and cutoff value is 11.92; PGR: AUC is 0.687 (CI 0.604-0.771), YI is 0.328, and cutoff value is 8.26. (c) ROC curve of CG and GC. G-17: AUC is 0.753 (CI 0.684-0.821), YI is 0.403, and cutoff value is 3.89; PGII: AUC is 0.717 (CI 0.642-0.793), YI is 0.342, and cutoff value is 9.16; PGR: AUC is 0.729 (CI 0.650-0.807), YI is 0.357, and cutoff value is 14.14. AUC: area under the receiver operating characteristic curve; YI: Youden index; CI: confidence interval.
Because there was no difference in the levels of PGI among the groups, we chose G-17, PGII, and PGR as the variables to determine appropriate cutoff values.
When distinguishing NAG from CAG, the best cutoff value of G-17 was 9.25 pmol/L, while that of PGII was 7.06
The AUC of G-17 for the diagnosis of GC was 0.753 (95% CI: 0.684-0.821), the maximum value of the YI was 0.403, and the corresponding cutoff value was 3.89 pmol/L. When the diagnostic cutoff value of 3.89 pmol/L was used, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of G-17 in the diagnosis of GC were 83.3% (45/54), 51.8% (404/780), 53.8% (449/834), 10.7% (45/421), and 97.8% (404/413), respectively (Table
Comparison between the diagnostic value of G-17, PGII, and PGR in gastric cancer and pathological.
Pathological diagnosis. Total: 834 | Sensitivity | Specificity | Accuracy | Positive predictive value | Negative predictive value | ||
---|---|---|---|---|---|---|---|
Gastric cancer | Nongastric cancer | ||||||
G-17 | |||||||
Gastric cancer | 45 | 376 | 83.3% | 51.8% | 53.8% | 10.7% | 97.8% |
Nongastric cancer | 9 | 404 | |||||
PGII | |||||||
Gastric cancer | 38 | 341 | 70.4 | 56.3% | 57.2% | 10.0% | 96.5% |
Nongastric cancer | 16 | 439 | |||||
PGR | |||||||
Gastric cancer | 43 | 407 | 79.6% | 47.8% | 49.9% | 9.6% | 97.1% |
Nongastric cancer | 11 | 373 | |||||
G-17 combined with PGII | |||||||
Gastric cancer | 34 | 230 | 63.0% | 70.5% | 70.0% | 12.9% | 96.5% |
Nongastric cancer | 20 | 550 | |||||
G-17 combined with PGR | |||||||
Gastric cancer | 38 | 233 | 70.4% | 70.1% | 70.1% | 14.0% | 97.2% |
Nongastric cancer | 16 | 547 | |||||
PGII combined with PGR | |||||||
Gastric cancer | 35 | 309 | 64.8% | 60.4% | 60.7% | 10.2% | 96.1% |
Nongastric cancer | 19 | 471 |
The AUC of PGII for the diagnosis of GC was 0.717 (95% CI: 0.642-0.793), the maximum value of the YI was 0.342, and the corresponding cutoff value was 9.16
The AUC of PGR for the diagnosis of GC was 0.729 (95% CI: 0.650-0.807), the maximum value of the YI was 0.357, and the corresponding cutoff value was 14.14. When 14.14 was used as the diagnostic cutoff value, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of PGR in the diagnosis of GC were 79.6% (43/54), 47.8% (373/780), 49.9% (416/834), 9.6% (43/450), and 97.1% (373/384), respectively (Table
The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of G-17 combined with PGII (
The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of G-17 combined with PGR (
The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of PGII combined with PGR (
This study used the so-called new ABC method (based on G-17, PG, and PGR) to screen GC and initially determined the effectiveness of this method and its appropriate threshold in eastern China. According to our results, the use of G-17 combined with PG is effective for screening GC. This combination is also valuable for distinguishing between gastritis and IN.
The serological screening of GC has gradually become increasingly widely used, and there are many different schemes for the serological screening of GC (several of the five markers (PGI, PGII, PGR, G-17, and anti-Hp IgG) have been selected as screening indicators) [
Correa’s cascade theory of intestinal-type GC has been widely accepted: GC develops from chronic atrophicgastritis, intestinal metaplasia, and atypical hyperplasia into intestinal-type adenocarcinoma as a multistep and sequential process [
Gastrin is a gastrointestinal hormone synthesized and released by G cells in the gastric antrum and duodenum. There are many kinds of gastrin molecules in the body; the most important of which are G-17 and gastrin-34 (G-34); G-17 accounts for 80%-90%, and G-34 accounts for 5%-10%. The main function of gastrin is to stimulate parietal cells to secrete hydrochloric acid while regulating the function of the digestive tract to maintain its structural integrity. With the gastric antral mucosa atrophies, the number of G cells decreases, which leads to a decrease in G-17 secretion. With the gastric mucosa atrophies, the number of parietal cells secreting gastric acid decreases, which leads to a decrease in gastric acid secretion. Hypergastrinemia can stimulate cell proliferation and lead to more mutations, which may eventually lead to tumorigenesis. Gastrin receptors are located in both gastric neuroendocrine tumors (NETs) and adenocarcinomas [
PGs (PGI and PGII) are inactive precursors of pepsin. PGI is secreted by the chief cells and mucous neck cells of the fundus and body. PGII is secreted not only by the chief cells and mucous neck cells of the fundus and body but also by cells in the pyloric gland and Brunner gland. PGI and PGII are secreted into the gastric cavity, with only 1% leaking into circulating blood [
Some studies have shown that the diagnostic efficacy of a single serological marker is not good, and the combination of different markers can improve the diagnostic efficiency [
In addition, it should be noted that there were some patients with GC in this study with no significant changes in the levels of G-17 and PG in their serum. The exclusion of gastric mucosal lesions by serological detection alone may easily cause missed diagnoses in the clinic, so it is necessary to make comprehensive use of all kinds of clinical data in order to obtain the best diagnosis and select the best treatment plan for patients.
To summarize the above research results, although there are many limitations in this study, we found that the levels of PGII and G-17 in patients with gastric IN and GC were significantly increased, while the level of serum PGR was significantly decreased. Serological detection is effective for screening GC, and combining different markers can improve the diagnostic efficiency, of which G-17 combined with PGR had the highest diagnostic accuracy. The optimal cutoff values are
Of course, due to the different conditions in many regions, more centers and larger populations are still needed to obtain more data.
The data used to support the findings of this study are available from the corresponding author upon request.
All patients were aware of the study and signed an informed consent form. All patients were aware that the relevant data would be published. A copy of the written informed consent form can be reviewed by the editor of this journal.
The funders had no role in study design, data collection, and interpretation, or the decision to submit the work for publication.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
HS conceived the study, performed some of the gastroscopies, drafted and revised the manuscript, and approved the final manuscript. KX conceived the study, completed most of the data collection, performed statistical analysis, drafted the manuscript, and approved the final manuscript. SC performed some of the gastroscopies, counted some data, drafted and revised the manuscript, and approved the final manuscript. QL recorded and collected most of the data, performed statistical analysis, and approved the final manuscript. HJ conceived the study, performed some of the gastroscopies, revised the manuscript, and reviewed and approved the final manuscript. XZ conceived the study, performed some of the gastroscopies, revised the manuscript, and reviewed and approved the final manuscript. Hongzhang Shen, Kangwei Xiong, and Xiangyu Wu contributed equally to this work.
This work was supported by grants from the Zhejiang Medical and Health Science and Technology Plan (Grant nos. WKJ-ZJ-2136 and 2019RC068) and the Hangzhou Medical and Health Science and Technology Plan (Grant nos. 2016ZD01, OO20190610, and A20200174).