SynthesisPloS one2015
Significance of Serum Pepsinogens as a Biomarker for Gastric Cancer and Atrophic Gastritis Screening: A Systematic Review and Meta-Analysis.
Synthesis in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 9 of them syntheses that pooled it.
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Who cites it
100 citing papers in PubMed, 9 syntheses or guidelines pooled it, 191 citations in OpenAlex.
- Serum markers and gastric cancer: an umbrella review.BMC gastroenterology · 2025Pooled it
- Chronic atrophic gastritis and risk of incident upper gastrointestinal cancers: a systematic review and meta-analysis.Journal of translational medicine · 2024Pooled it
- Association of Serum Pepsinogens With Esophageal Squamous Cell Carcinoma Risk: A Systematic Review and Meta-Analysis.Frontiers in oncology · 2022Pooled it
- Volatile organic compounds as a potential screening tool for neoplasm of the digestive system: a meta-analysis.Scientific reports · 2021Pooled it
- Identifying Novel Biomarkers Ready for Evaluation in Low-Prevalence Populations for the Early Detection of Upper Gastrointestinal Cancers: A Systematic Review.Advances in therapy · 2021Pooled it
- AGA Clinical Practice Guidelines on Management of Gastric Intestinal Metaplasia.Gastroenterology · 2020Guideline
- AGA Technical Review on Gastric Intestinal Metaplasia-Epidemiology and Risk Factors.Gastroenterology · 2020Pooled it
- Guideline
- MicroRNAs as non-invasive diagnostic biomarkers for gastric cancer: Current insights and future perspectives.World journal of gastroenterology · 2018Pooled it
- Screening, Monitoring, and Treatment of Precancerous Atrophic Gastritis in the Prospective Study for Seven Years.Asian Pacific journal of cancer prevention : APJCP · 2020Trial
- Multicentric randomised study ofBMJ open · 2017Trial
- Screening strategies for the early detection of non-cardia gastric cancer in low- to moderate-prevalence regions: Asia-Pacific gastroesophageal cancer congress consensus 2026.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026Review
- Hepatic origin of increased serum TFF3 in gastric cancer bearing subjects.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026Article
- Gastric Mucosa Cancer Risk: The Operative Link on Gastritis Assessment Staging System.The Korean journal of helicobacter and upper gastrointestinal research · 2026Review
- Machine learning models using serum gastric biomarkers for the non-invasive prediction of atrophic gastritis: a comparative study.Frontiers in medicine · 2026Article
- A Non-Endoscopic Dynamic Nomogram for Atrophic Gastritis Risk Stratification Based on Serum Indicators and Clinical Factors.Journal of inflammation research · 2026Article
- Characteristics of Gastric Endoscopic and Histopathological Findings in the South and Southeast Asian Populations.JGH open : an open access journal of gastroenterology and hepatology · 2025Article
- Saliva-derived transcriptomic signature for gastric cancer detection using machine learning and leveraging publicly available datasets.Scientific reports · 2025Article
- Gastric Cancer Screening in the United States: A Review of Current Evidence, Challenges, and Future Perspectives.The American journal of gastroenterology · 2025Review
- Elevated serum pepsinogen level predicts postoperative nausea and vomiting and pain in females with obesity following laparoscopic sleeve gastrectomy.International journal of obesity (2005) · 2025Article
40 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHuman pepsinogens are considered promising serological biomarkers for the screening of atrophic gastritis (AG) and gastric cancer (GC). However, there has been controversy in the literature with respect to the validity of serum pepsinogen (SPG) for the detection of GC and AG. Consequently, we conducted a systematic review and meta-analysis to assess the diagnostic accuracy of SPG in GC and AG detection.
methodsWe searched PubMed, Embase, and the Chinese National Knowledge Infrastructure (CNKI) for correlative original studies published up to September 30, 2014. The summary sensitivity, specificity, positive diagnostic likelihood ratio (DLR+), negative diagnostic likelihood ratio (DLR-), area under the summary receiver operating characteristic curve (AUC) and diagnostic odds ratio (DOR) were used to evaluate SPG in GC and AG screening based on bivariate random effects models. The inter-study heterogeneity was evaluated by the I2 statistics and publication bias was assessed using Begg and Mazumdar's test. Meta-regression and subgroup analyses were performed to explore study heterogeneity.
resultsIn total, 31 studies involving 1,520 GC patients and 2,265 AG patients were included in the meta-analysis. The summary sensitivity, specificity, DLR+, DLR-, AUC and DOR for GC screening using SPG were 0.69 (95% CI: 0.60-0.76), 0.73 (95% CI: 0.62-0.82), 2.57 (95% CI: 1.82-3.62), and 0.43 (95% CI: 0.34-0.54), 0.76 (95% CI: 0.72-0.80) and 6.01 (95% CI: 3.69-9.79), respectively. For AG screening, the summary sensitivity, specificity, DLR+, DLR-, AUC and DOR were 0.69 (95% CI: 0.55-0.80), 0.88 (95% CI: 0.77-0.94), 5.80 (95% CI: 3.06-10.99), and 0.35 (95% CI: 0.24-0.51), 0.85 (95% CI: 0.82-0.88) and 16.50 (95% CI: 8.18-33.28), respectively. In subgroup analysis, the use of combination of concentration of PGI and the ratio of PGI:PGII as measurement of SPG for GC screening yielded sensitivity of 0.70 (95% CI: 0.66-0.75), specificity of 0.79 (95% CI: 0.79-0.80), DOR of 6.92 (95% CI: 4.36-11.00), and AUC of 0.78 (95% CI: 0.72-0.81), while the use of concentration of PGI yielded sensitivity of 0.55 (95% CI: 0.51-0.60), specificity of 0.79 (95% CI: 0.76-0.82), DOR of 6.88 (95% CI: 2.30-20.60), and AUC of 0.77 (95% CI: 0.73-0.92). For AG screening, the use of ratio of PGI:PGII as measurement of SPG yielded sensitivity of 0.69 (95% CI: 0.52-0.83), specificity of 0.84 (95% CI: 0.68-0.93), DOR of 11.51 (95% CI: 6.14-21.56), and AUC of 0.83 (95% CI: 0.80-0.86), the use of combination of concentration of PGI and the ratio of PGI:PGII yield sensitivity of 0.79 (95% CI: 0.72-0.85), specificity of 0.89 (95% CI: 0.85-0.93), DOR of 24.64 (95% CI: 6.95-87.37), and AUC of 0.87 (95% CI: 0.81-0.92), concurrently, the use of concentration of PGI yield sensitivity of 0.46 (95% CI: 0.38-0.54), specificity of 0.93 (95% CI: 0.91-0.95), DOR of 19.86 (95% CI: 0.86-456.91), and AUC of 0.86 (95% CI: 0.52-1.00).
conclusionSPG has great potential as a noninvasive, population-based screening tool in GC and AG screening. In addition, given the potential publication bias and high heterogeneity of the included studies, further high quality studies are required in the future.
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